VERSION 2000 S.L. NEITSCH, J.G. ARNOLD, J.R. WILLIAMS DRAFT-SEPTEMBER, 2000

Transcription

1 VERSION 2000 S.L. NEITSCH, J.G. ARNOLD, J.R. WILLIAMS DRAFT-SEPTEMBER, 2000 GRASSLAND, SOIL AND WATER RESEARCH LABORATORY AGRICULTURAL RESEARCH SERVICE 808 EAST BLACKLAND ROAD TEMPLE, TEXAS BLACKLAND RESEARCH CENTER TEXAS AGRICULTURAL EXPERIMENT STATION 808 EAST BLACKLAND ROAD TEMPLE, TEXAS 76502

2 SOIL AND WATER ASSESSMENT TOOL

3 CONTENTS CHAPTER 1 INTRODUCTION DEVELOPMENT OF SWAT OVERVIEW OF SWAT 6 LAND PHASE OF THE HYDROLOGIC CYCLE 8 ROUTING PHASE OF THE HYDROLOGIC CYCLE REFERENCES 24 PART 1: MODEL DESCRIPTION SECTION 1: CLIMATE CHAPTER 2 EQUATIONS: ENERGY SUN-EARTH RELATIONSHIPS 32 DISTANCE BETWEEN EARTH AND SUN 32 SOLAR DECLINATION 32 SOLAR NOON, SUNRISE, SUNSET, AND DAYLENGTH 33

4 2.2 SOLAR RADIATION 34 EXTRATERRESTRIAL RADIATION 34 SOLAR RADIATION UNDER CLOUDLESS SKIES 35 DAILY SOLAR RADIATION 36 HOURLY SOLAR RADIATION 37 DAILY NET RADIATION TEMPERATURE 41 DAILY AIR TEMPERATURE 41 HOURLY AIR TEMPERATURE 42 SOIL TEMPERATURE 42 WATER TEMPERATURE WIND SPEED NOMENCLATURE REFERENCES 51 CHAPTER 3 EQUATIONS: ATMOSPHERIC WATER PRECIPITATION MAXIMUM HALF-HOUR RAINFALL WATER VAPOR SNOW COVER SNOW MELT 61 SNOW PACK TEMPERATURE 61 SNOW MELT EQUATION NOMENCLATURE REFERENCES 64 CHAPTER 4 EQUATIONS: WEATHER GENERATOR PRECIPITATION 68 OCCURRENCE OF WET OR DRY DAY 68 AMOUNT OF PRECIPITATION SOLAR RADIATION & TEMPERATURE 70 DAILY RESIDUALS 70 GENERATED VALUES 72 ADJUSTMENT FOR CLEAR/OVERCAST CONDITIONS RELATIVE HUMIDITY 75 MEAN MONTHLY RELATIVE HUMIDITY 75 GENERATED DAILY VALUE 76 ADJUSTMENT FOR CLEAR/OVERCAST CONDITIONS MAXIMUM HALF-HOUR RAINFALL 78

5 MONTHLY MAXIMUM HALF-HOUR RAIN 79 GENERATED DAILY VALUE WIND SPEED NOMENCLATURE REFERENCES 83 CHAPTER 5 EQUATIONS: CLIMATE CUSTOMIZATION ELEVATION BANDS CLIMATE CHANGE NOMENCLATURE 90 SECTION 2: HYDROLOGY CHAPTER 6 EQUATIONS: SURFACE RUNOFF RUNOFF VOLUME: SCS CURVE NUMBER PROCEDURE 94 SCS CURVE NUMBER RUNOFF VOLUME: GREEN & AMPT INFILTRATION METHOD PEAK RUNOFF RATE 103 TIME OF CONCENTRATION 104 RUNOFF COEFFICIENT 106 RAINFALL INTENSITY 107 MODIFIED RATIONAL FORMULA TRANSMISSION LOSSES NOMENCLATURE REFERENCES 112 CHAPTER 7 EQUATIONS: EVAPOTRANSPIRATION CANOPY STORAGE 7.2 EVAPOTRANSPIRATION 7.3 REFERENCES CHAPTER 8 EQUATIONS: SUB-SURFACE WATER 8.1 CRACK FLOW

6 8.2 PERCOLATION 8.3 LATERAL FLOW 8.4 REFERENCES CHAPTER 9 EQUATIONS: GROUNDWATER 9.1 SHALLOW AQUIFER 9.2 DEEP AQUIFER 9.3 REFERENCES SECTION 3: NUTRIENTS/PESTICIDES CHAPTER 10 EQUATIONS: NITROGEN 10.1 NITROGEN CYCLE 10.2 MINERALIZATION 10.3 FIXATION 10.4 IMMOBILIZATION 10.5 NITRIFICATION 10.6 DENITRIFICATION 10.7 LEACHING 10.8 NITROGEN IN FERTILIZER 10.9 NITROGEN IN RAINFALL REFERENCES CHAPTER 11 EQUATIONS: PHOSPHORUS 11.1 PHOSPHORUS CYCLE 11.2 MINERALIZATION 11.3 IMMOBILIZATION 11.4 LEACHING 11.5 PHOSPHORUS IN FERTILIZER 11.6 REFERENCES

7 CHAPTER 12 EQUATIONS: PESTICIDES 12.1 DEGRADATION 12.2 VOLATILIZATION 12.3 LEACHING 12.4 APPLICATION 12.5 REFERENCES SECTION 4: EROSION CHAPTER 13 EQUATIONS: SEDIMENT 13.1 MUSLE 13.2 REFERENCES CHAPTER 14 EQUATIONS: NUTRIENTS 14.1 NO 3 REMOVAL IN SURFACE RUNOFF 14.2 NO 3 REMOVAL IN LATERAL FLOW 14.3 ORGANIC N IN SURFACE RUNOFF 14.4 SOLUBLE P IN SURFACE RUNOFF 14.5 ORGANIC P/MINERAL P ATTACHED TO SEDIMENT IN SURFACE RUNOFF 14.6 REFERENCES CHAPTER 15 EQUATIONS: PESTICIDES 15.1 SOLUBLE PESTICIDES IN SURFACE RUNOFF 15.2 PESTICIDE SORBED TO SEDIMENT IN SURFACE RUNOFF 15.3 REFERENCES

8 CHAPTER 16 EQUATIONS: WATER QUALITY PARAMETERS 16.1 DISSOLVED OXYGEN 16.2 CARBONACEOUS BIOLOGICAL OXYGEN DEMAND 16.3 CHLOROPHYLL-A 16.4 REFERENCES SECTION 5: LAND COVER/PLANT CHAPTER 17 EQUATIONS: GROWTH CYCLE 17.1 HEAT UNITS 17.2 PLANTING/BEGINNING OF GROWING SEASON 17.3 HARVEST OPERATION 17.4 GRAZING OPERATION 17.5 HARVEST & KILL OPERATION 17.6 KILL/END OF GROWING SEASON 17.7 DORMANCY 17.8 PLANT TYPES 17.9 REFERENCES CHAPTER 18 EQUATIONS: OPTIMAL GROWTH 18.1 POTENTIAL GROWTH 18.2 WATER UPTAKE BY PLANTS 18.3 NUTRIENT UPTAKE BY PLANTS 18.4 CROP YIELD 18.5 REFERENCES CHAPTER 19 EQUATIONS: ACTUAL GROWTH 19.1 GROWTH CONSTRAINTS 19.2 AUTO-APPLICATION OF WATER 19.3 AUTO-APPLICATION OF FERTILIZER 19.4 REFERENCES

9 SECTION 6: MANAGEMENT PRACTICES CHAPTER 20 EQUATIONS: WATER MANAGEMENT 20.1 IRRIGATION 20.2 POTHOLE/MANAGED IMPOUNDED AREAS 20.3 TILE DRAINAGE 20.4 CONSUMPTIVE WATER USE 20.5 WATER TRANSFER 20.6 REFERENCES CHAPTER 21 EQUATIONS: TILLAGE 21.1 RESIDUE 21.2 NUTRIENTS 21.3 REFERENCES CHAPTER 22 EQUATIONS: URBAN AREAS 22.1 USGS REGRESSION EQUATIONS 22.2 BUILD UP/WASH OFF 22.3 REFERENCES SECTION 7: MAIN CHANNEL PROCESSES CHAPTER 23 EQUATIONS: WATER ROUTING 23.1 CHANNEL CHARACTERISTICS 23.2 FLOW RATE AND VELOCITY 23.3 VARIABLE STORAGE ROUTING METHOD 23.4 MUSKINGUM ROUTING METHOD 23.5 TRANSMISSION LOSSES 23.6 EVAPORATION LOSSES 23.7 CHANNEL WATER BALANCE

10 23.8 NOMENCLATURE 23.9 REFERENCES CHAPTER 24 EQUATIONS: SEDIMENT ROUTING 24.1 JIMMY'S NEW METHOD 24.2 CHANNEL DEGRADATION 24.3 REFERENCES CHAPTER 25 EQUATIONS: STREAM WATER QUALITY 25.1 CHLOROPHYLL A (PHYTOPLANKTONIC ALGAE) 25.2 NITROGEN 25.3 PHOSPHORUS 25.4 CARBONACEOUS BIOLOGICAL OXYGEN DEMAND 25.5 DISSOLVED OXYGEN 25.6 TEMPERATURE 25.7 REFERENCES CHAPTER 26 EQUATIONS: PESTICIDE 26.1 DEGRADATION 26.2 VOLATILIZATION 26.3 DEPOSITION 26.4 RESUSPENSION 26.5 BURIAL 26.6 REFERENCES SECTION 8: WATER BODIES CHAPTER 27 EQUATIONS: WATER BODIES OFF CHANNEL NETWORK 27.1 PONDS

11 27.2 WETLANDS 27.3 DEPRESSIONAL AREAS/IMPOUNDED AREAS 27.4 REFERENCES CHAPTER 28 EQUATIONS: WATER BODIES ON CHANNEL NETWORK 28.1 RESERVOIRS 28.2 REFERENCES CHAPTER 29 EQUATIONS: NUTRIENTS IN WATER BODIES 29.1 PONDS, WETLANDS, AND RESERVOIRS NUTRIENT TRANSFORMATIONS TOTAL BALANCE EUTROPHICATION 29.2 DEPRESSIONAL/IMPOUNDED AREAS 29.3 NOMENCLATURE 29.4 REFERENCES CHAPTER 30 EQUATIONS: PESTICIDES 30.1 RESERVOIRS 30.2 REFERENCES

12 PART 2: MODEL OPERATION CHAPTER 31 SWAT INPUT: WATERSHED CONFIGURATION 31.1 DISCRETIZATION SCHEMES 31.2 WATERSHED CONFIGURATION FILE (.FIG) INCORPORATION OF COMMENTS COMMAND LINES 31.3 REFERENCES CHAPTER 32 SWAT INPUT: SIMULATION MANAGEMENT 32.1 CONTROL INPUT/OUTPUT FILE (FILE.CIO) 32.2 INPUT CONTROL CODE FILE (.COD) CHAPTER 33 SWAT INPUT: GENERAL WATERSHED ATTRIBUTES 33.1 BASIN INPUT FILE (.BSN) CHAPTER 34 SWAT INPUT: CLIMATE 34.1 WEATHER GENERATOR INPUT FILE (.WGN) 34.2 PRECIPITATION INPUT FILE (.PCP) 34.3 TEMPERATURE INPUT FILE (.TMP) 34.4 SOLAR RADIATION INPUT FILE (.SLR) 34.5 RELATIVE HUMIDITY INPUT FILE (.HMD) 34.6 WIND SPEED INPUT FILE (.WND) 34.7 POTENTIAL EVAPOTRANSPIRATION INPUT FILE (.PET) 34.8 MULTIPLE RECORDS IN PRECIP/TEMP FILES

13 CHAPTER 35 SWAT INPUT: GENERAL HRU/SUBBASIN ATTRIBUTES 35.1 SUBBASIN GENERAL INPUT FILE (.SUB) 35.2 HRU GENERAL INPUT FILE (.HRU) CHAPTER 36 SWAT INPUT: SOIL 36.1 SOIL INPUT FILE (.SOL) 36.2 SOIL CHEMICAL INPUT FILE (.CHM) CHAPTER 37 SWAT INPUT: LAND/WATER MANAGEMENT 37.1 MANAGEMENT INPUT FILE (.MGT) GENERAL MANAGEMENT VARIABLES SCHEDULED MANAGEMENT OPERATIONS 37.2 WATER USE INPUT FILE (.WUS) CHAPTER 38 SWAT INPUT: GROUNDWATER 38.1 GROUNDWATER INPUT FILE (.GW) CHAPTER 39 SWAT INPUT: MAIN CHANNEL 39.1 MAIN CHANNEL INPUT FILE (.RTE) CHAPTER 40 SWAT INPUT: RESERVOIRS/PONDS 40.1 RESERVOIR INPUT FILE (.RES) 40.2 DAILY RESERVOIR OUTFLOW FILE 40.3 MONTHLY RESERVOIR OUTFLOW FILE 40.4 POND INPUT FILE (.PND)

14 CHAPTER 41 SWAT INPUT: WATER QUALITY 41.1 GENERAL WATER QUALITY INPUT FILE (.WWQ) 41.2 STREAM WATER QUALITY INPUT FILE (.SWQ) 41.3 RESERVOIR WATER QUALITY INPUT FILE (.LWQ) CHAPTER 42 SWAT INPUT: DATABASES 42.1 LAND COVER/PLANT GROWTH DATABASE FILE (CROP.DAT) 42.2 TILLAGE DATABASE FILE (TILL.DAT) 42.3 PESTICIDE/TOXIN DATABASE FILE (PEST.DAT) 42.4 FERTILIZER DATABASE FILE (FERT.DAT) 42.5 URBAN DATABASE FILE (URBAN.DAT) CHAPTER 43 SWAT INPUT: MEASURED 43.1 DAILY RECORDS (RECDAY) DATA FILE 43.2 MONTHLY RECORDS (RECMON) DATA FILE 43.3 ANNUAL RECORDS (RECYEAR) DATA FILE 43.4 AVERAGE ANNUAL RECORDS (RECCNST) DATA FILE CHAPTER 44 SWAT OUTPUT FILES 44.1 INPUT SUMMARY FILE (INPUT.STD) 44.2 STANDARD OUTPUT FILE (OUTPUT.STD) 44.3 HRU OUTPUT FILE (.SBS) 44.4 SUBBASIN OUTPUT FILE (.BSB) 44.5 MAIN CHANNEL OUTPUT FILE (.RCH) 44.6 HRU IMPOUNDMENT OUTPUT FILE (.WTR) 44.7 RESERVOIR OUTPUT FILE (.RSV) 44.8 RESERVOIR WATER QUALITY OUTPUT FILE (.LWO) 44.9 PESTICIDE OUTPUT FILE (.PSO) EVENT OUTPUT FILE (.EVE)

15 CHAPTER 45 SWAT OUTPUT ANALYSIS 45.1 STREAM FLOW CALIBRATION 45.2 SEDIMENT CALIBRATION 45.3 NUTRIENT CALIBRATION 45.4 PESTICIDE CALIBRATION PART 3: APPENDICES APPENDIX A MODEL DATABASES A.1 LAND COVER/PLANT GROWTH DATABASE A.2 TILLAGE DATABASE A.3 PESTICIDE DATABASE A.4 FERTILIZER DATABASE A.5 URBAN LAND TYPE DATABASE A.6 REFERENCES APPENDIX B EXAMPLE WATERSHED CONFIGURATIONS B.1 SUBWATERSHED DISCRETIZATION SUBWATERSHED DISCRETIZATION: 3 SUBBASINS SUBWATERSHED DISCRETIZATION: SAVING RESULTS FOR DOWNSTREAM RUNS SUBWATERSHED DISCRETIZATION: INCORPORATING POINT SOURCE/UPSTREAM SIMULATION DATA SUBWATERSHED DISCRETIZATION: INCORPORATING RESERVOIRS SUBWATERSHED DISCRETIZATION: SAVING SIMULATION RESULTS FOR ONE LOCATION B.2 HILLSLOPE DISCRETIZATION HILLSLOPE DISCRETIZATION: MODELING A DAIRY OPERATION

16 HILLSLOPE DISCRETIZATION: COMBINING WITH SUBWATERSHED DISCRETIZATION B.3 GRID CELL DISCRETIZATION GRID CELL DISCRETIZATION: 9 CELLS APPENDIX C EXAMPLE MANAGEMENT SCENARIOS C.1 LAND COVER/PLANT GROWTH DATABASE APPENDIX D HYDROLOGIC GROUPS FOR U.S. SOILS

17 CHAPTER 1 INTRODUCTION SWAT is the acronym for Soil and Water Assessment Tool, a river basin, or watershed, scale model developed by Dr. Jeff Arnold for the USDA Agricultural Research Service (ARS). SWAT was developed to predict the impact of land management practices on water, sediment and agricultural chemical yields in large complex watersheds with varying soils, land use and management conditions over long periods of time. To satisfy this objective, the model is physically based. Rather than incorporating regression equations to describe the relationship between input and output variables, SWAT requires specific information about weather, soil properties, topography, vegetation, and land management practices occurring in the watershed. The physical processes associated with water 1

18 2 SWAT USER S MANUAL, VERSION 2000 movement, sediment movement, crop growth, nutrient cycling, etc. are directly modeled by SWAT using this input data. Benefits of this approach are watersheds with no monitoring data (e.g. stream gage data) can be modeled the relative impact of alternative input data (e.g. changes in management practices, climate, vegetation, etc.) on water quality or other variables of interest can be quantified uses readily available inputs. While SWAT can be used to study more specialized processes such as bacteria transport, the minimum data required to make a run are commonly available from government agencies. is computationally efficient. Simulation of very large basins or a variety of management strategies can be performed without excessive investment of time or money. enables users to study long-term impacts. Many of the problems currently addressed by users involve the gradual buildup of pollutants and the impact on downstream water bodies. To study these types of problems, results are needed from runs with output spanning several decades. SWAT is a continuous time model, i.e. a long-term yield model. The model is not designed to simulate detailed, single-event flood routing.

19 1.1 DEVELOPMENT OF SWAT CHAPTER 1: INTRODUCTION 3 SWAT incorporates features of several ARS models and is a direct outgrowth of the SWRRB 1 model (Simulator for Water Resources in Rural Basins) (Williams et al., 1985; Arnold et al., 1990). Specific models that contributed significantly to the development of SWAT were CREAMS 2 (Chemicals, Runoff, and Erosion from Agricultural Management Systems) (Knisel, 1980), GLEAMS 3 (Groundwater Loading Effects on Agricultural Management Systems) (Leonard et al., 1987), and EPIC 4 (Erosion-Productivity Impact Calculator) (Williams et al., 1984). Development of SWRRB began with modification of the daily rainfall hydrology model from CREAMS. The major changes made to the CREAMS hydrology model were: a) the model was expanded to allow simultaneous computations on several subbasins to predict basin water yield; b) a groundwater or return flow component was added; c) a reservoir storage component was added to calculate the effect of farm ponds and reservoirs on water and sediment yield; d) a weather simulation model incorporating data for rainfall, solar radiation, and temperature was added to facilitate long-term simulations and provide temporally and spatially representative weather; e) the method for predicting the peak runoff rates was improved; f) the EPIC crop growth model was added to account for annual variation in growth; g) a simple flood routing component was added; h) sediment transport components were added to simulate sediment movement 1 SWRRB is a continuous time step model that was developed to simulate nonpoint source loadings from watersheds. 2 In response to the Clean Water Act, ARS assembled a team of interdisciplinary scientists from across the U.S. to develop a process-based, nonpoint source simulation model in the early 1970s. From that effort CREAMS was developed. CREAMS is a field scale model designed to simulate the impact of land management on water, sediment, nutrients and pesticides leaving the edge of the field. A number of other ARS models such as GLEAMS, EPIC, SWRRB and AGNPS trace their origins to the CREAMS model. 3 GLEAMS is a nonpoint source model which focuses on pesticide and nutrient groundwater loadings. 4 EPIC was originally developed to simulate the impact of erosion on crop productivity and has now evolved into a comprehensive agricultural management, field scale, nonpoint source loading model.

20 4 SWAT USER S MANUAL, VERSION 2000 through ponds, reservoirs, streams and valleys; and i) calculations of transmission losses were incorporated. The primary focus of model use in the late 1980s was water quality assessment and development of SWRRB reflected this emphasis. Notable modifications of SWRRB at this time included: a) incorporation of the GLEAMS pesticide fate component; b) optional SCS technology for estimating peak runoff rates; and c) newly developed sediment yield equations. These modifications extended the model s capability to deal with a wide variety of watershed management problems. In the late 1980s, the Bureau of Indian Affairs needed a model to estimate the downstream impact of water management within Indian reservation lands in Arizona and New Mexico. While SWRRB was easily utilized for watersheds up to a few hundred square kilometers in size, the Bureau also wanted to simulate stream flow for basins extending over several thousand square kilometers. For an area this extensive, the watershed under study needed to be divided into several hundred subbasins. Watershed division in SWRRB was limited to ten subbasins and the model routed water and sediment transported out of the subbasins directly to the watershed outlet. These limitations led to the development of a model called ROTO (Routing Outputs to Outlet) (Arnold et al., 1995), which took output from multiple SWRRB runs and routed the flows through channels and reservoirs. ROTO provided a reach routing approach and overcame the SWRRB subbasin limitation by linking multiple SWRRB runs together. Although this approach was effective, the input and output of multiple SWRRB files was cumbersome and required considerable computer storage. In addition, all SWRRB runs had to be made independently and then input to ROTO for the channel and reservoir routing. To overcome the awkwardness of this arrangement, SWRRB and ROTO were merged into a single model, SWAT. While allowing simulations of very extensive areas, SWAT retained all the features which made SWRRB such a valuable simulation model.

21 CHAPTER 1: INTRODUCTION 5 Since SWAT was created in the early 90s, it has undergone continued review and expansion of capabilities. The most significant improvements of the model between releases include: SWAT94.2: Multiple hydrologic response units (HRUs) incorporated. SWAT96.2: Auto-fertilization and auto-irrigation added as management options; canopy storage of water incorporated; a CO 2 component added to crop growth model for climatic change studies; Penman-Monteith potential evapotranspiration equation added; lateral flow of water in the soil based on kinematic storage model incorporated; in-stream nutrient water quality equations from QUAL2E added; in-stream pesticide routing. SWAT98.1: Begin FORTRAN90 recode; snow melt routines improved; in-stream water quality improved; nutrient cycling routines expanded; grazing, manure applications, and tile flow drainage added as management options; model modified for use in Southern Hemisphere; urban build up/wash off equations from SWMM added along with regression equations from USGS. SWAT99.2: Nutrient cycling routines improved, rice/wetland routines improved, reservoir/pond/wetland nutrient removal by settling added; bank storage of water in reach added; routing of metals through reach added; all year references in model changed from last 2 digits of year to 4-digit year. SWAT2000: FORTRAN90 recode completed; bacteria transport routines added; Green & Ampt infiltration added; weather generator improved; allow daily solar radiation, relative humidity, and wind speed to be read in or generated; allow potential ET values for watershed to be read in or calculated; all potential ET methods reviewed and modified.

22 6 SWAT USER S MANUAL, VERSION 2000 In addition to the changes listed above, interfaces for the model have been developed in Windows (Visual Basic), GRASS, and ArcView. SWAT has also undergone extensive validation. 1.2 OVERVIEW OF SWAT SWAT allows a number of different physical processes to be simulated in a watershed. These processes will be briefly summarized in this section. For more detailed discussions of the various procedures, please consult the chapters covering model theory in Part 1 of the manual.. Figure 1.1: Map of the Lake Fork Watershed in Northeast Texas showing the land use distribution and stream network For modeling purposes, a watershed may be partitioned into a number of subwatersheds or subbasins. The use of subbasins in a simulation is particularly beneficial when different areas of the watershed are dominated by land uses or soils different enough in properties to impact hydrology. By partitioning the

23 CHAPTER 1: INTRODUCTION 7 watershed into subbasins, the user is able to relate different areas of the watershed to one another spatially. Figure 1.2 shows a subbasin delineation for the watershed shown in Figure 1.1. Figure 1.2: Subbasin delineation of the Lake Fork Watershed. Input information for each subbasin is grouped or organized into the following categories: climate; land cover/soil/management combinations within the subbasin (hydrologic response units or HRUs); ponds/reservoirs; groundwater; and the main channel, or reach, draining the subbasin. No matter what type of problem studied with SWAT, water balance is the driving force behind everything that happens in the watershed. To accurately predict the movement of pesticides, sediments or nutrients, the hydrologic cycle as simulated by the model must conform to what is happening in the watershed. Simulation of the hydrology of a watershed can be separated into two major

24 8 SWAT USER S MANUAL, VERSION 2000 divisions. The first division is the land phase of the hydrologic cycle, depicted in Figure 1.3. The land phase of the hydrologic cycle controls the amount of water, sediment, nutrient and pesticide loadings to the main channel in each subbasin. The second division is the water or routing phase of the hydrologic cycle which can be defined as the movement of water, sediments, etc. through the channel network of the watershed to the outlet. Figure 1.3: Schematic representation of the hydrologic cycle LAND PHASE OF THE HYDROLOGIC CYCLE equation: The hydrologic cycle as simulated by SWAT is based on the water balance SW t = SW + ( R t i= 1 day Q i E a P QR ) where SW t is the final soil water content (mm), i i (1)

25 CHAPTER 1: INTRODUCTION 9 SW t R day Q i E a P i QR i is the soil water content available for plant uptake, defined as the initial soil water content minus the permanent wilting point water content (mm), is the time (days), is the amount of precipitation (mm), is the amount of surface runoff (mm), is the amount of evapotranspiration (mm), is the amount of percolation (mm), and is the amount of return flow (mm). The subdivision of the watershed enables the model to reflect differences in evapotranspiration for various crops and soils. Runoff is predicted separately for each HRU and routed to obtain the total runoff for the watershed. This increases accuracy and gives a much better physical description of the water balance. Figure 1.4: HRU/Subbasin command loop

26 10 SWAT USER S MANUAL, VERSION 2000 Figure 1.4 shows the general sequence of processes used by SWAT to model the land phase of the hydrologic cycle. The different inputs and processes involved in this phase of the hydrologic cycle are summarized in the following sections CLIMATE The climate of a watershed provides the moisture and energy inputs that control the water balance and determine the relative importance of the different components of the hydrologic cycle. The climatic variables required by SWAT consist of daily precipitation, maximum/minimum air temperature, solar radiation, wind speed and relative humidity. The model allows values for daily precipitation, maximum/minimum air temperatures, solar radiation, wind speed and relative humidity to be input from records of observed data or generated during the simulation. WEATHER GENERATOR. Daily values for weather are generated from average monthly values. The model generates a set of weather data for each subbasin. The values for any one subbasin will be generated independently and there will be no spatial correlation of generated values between the different subbasins. GENERATED PRECIPITATION. SWAT uses a model developed by Nicks (1974) to generate daily precipitation for simulations which do not read in measured data. This precipitation model is also used to fill in missing data in the measured records. The precipitation generator uses a first-order Markov chain model to define a day as wet or dry by comparing a random number ( ) generated by the model to monthly wet-dry probabilities input by the user. If the day is classified as wet, the amount of precipitation is generated from a skewed distribution or a modified exponential distribution. GENERATED AIR TEMPERATURE AND SOLAR RADIATION. Maximum and minimum air temperatures and solar radiation are generated from a normal distribution. A continuity equation is incorporated into the generator to account for temperature and radiation variations caused by dry vs. rainy conditions. Maximum air temperature and solar radiation are adjusted downward when simulating rainy conditions and upwards when simulating dry conditions. The adjustments are made so that the long-term generated values for the average monthly maximum temperature and monthly solar radiation agree with the input averages.

27 CHAPTER 1: INTRODUCTION 11 GENERATED WIND SPEED. A modified exponential equation is used to generate daily mean wind speed given the mean monthly wind speed. GENERATED RELATIVE HUMIDITY. The relative humidity model uses a triangular distribution to simulate the daily average relative humidity from the monthly average. As with temperature and radiation, the mean daily relative humidity is adjusted to account for wet- and dry-day effects. SNOW. SWAT classifies precipitation as rain or freezing rain/snow using the average daily temperature. SNOW COVER. The snow cover component of SWAT has been updated from a simple, uniform snow cover model to a more complex model which allows non-uniform cover due to shading, drifting, topography and land cover. The user defines a threshold snow depth above which snow coverage will always extend over 100% of the area. As the snow depth in a subbasin decreases below this value, the snow coverage is allowed to decline non-linearly based on an areal depletion curve. SNOW MELT. Snow melt is controlled by the air and snow pack temperature, the melting rate, and the areal coverage of snow. If snow is present, it is melted on days when the maximum temperature exceeds 0 C using a linear function of the difference between the average snow packmaximum air temperature and the base or threshold temperature for snow melt. Melted snow is treated the same as rainfall for estimating runoff and percolation. For snow melt, rainfall energy is set to zero and the peak runoff rate is estimated assuming uniformly melted snow for a 24 hour duration. ELEVATION BANDS. The model allows the subbasin to be split into a maximum of ten elevation bands. Snow cover and snow melt are simulated separately for each elevation band. By dividing the subbasin into elevation bands, the model is able to assess the differences in snow cover and snow melt caused by orographic variation in precipitation and temperature. SOIL TEMPERATURE. Soil temperature impacts water movement and the decay rate of residue in the soil. Daily average soil temperature is calculated at the soil surface and the center of each soil layer. The temperature of the soil surface is a function of snow cover, plant cover and residue cover, the bare soil surface temperature, and the previous day s soil surface temperature. The temperature of the soil layers is a function of the surface temperature, mean annual air temperature and the depth in the soil at which variation in temperature due to changes in climatic conditions no longer occurs. This depth, referred to as the damping depth, is dependent upon the bulk density and the soil water content.

28 12 SWAT USER S MANUAL, VERSION HYDROLOGY As precipitation descends, it may be intercepted and held in the vegetation canopy or fall to the soil surface. Water on the soil surface will infiltrate into the soil profile or flow overland as runoff. Runoff moves relatively quickly toward a stream channel and contributes to short-term stream response. Infiltrated water may be held in the soil and later evapotranspired or it may slowly make its way to the surface-water system via underground paths. The potential pathways of water movement simulated by SWAT in the HRU are illustrated in Figure 1.5. CANOPY STORAGE. Canopy storage is the water intercepted by vegetative surfaces (the canopy) where it is held and made available for evaporation. When using the curve number method to compute surface runoff, canopy storage is taken into account in the surface runoff calculations. However, if methods such as Green & Ampt are used to model infiltration and runoff, canopy storage must be modeled separately. SWAT allows the user to input the maximum amount of water that can be stored in the canopy at the maximum leaf area index for the land cover. This value and the leaf area index are used by the model to compute the maximum storage at any time in the growth cycle of the land cover/crop. When evaporation is computed, water is first removed from canopy storage. INFILTRATION. Infiltration refers to the entry of water into a soil profile from the soil surface. As infiltration continues, the soil becomes increasingly wet, causing the rate of infiltration to decrease with time until it reaches a steady value. The initial rate of infiltration depends on the moisture content of the soil prior to the introduction of water at the soil surface. The final rate of infiltration is equivalent to the saturated hydraulic conductivity of the soil. Because SWAT operates on a daily time-step, it is unable to directly model infiltration. The amount of water entering the soil profile is calculated as the difference between the amount of rainfall and the amount of surface runoff. The Green & Ampt infiltration model is currently being incorporated into SWAT and should be available for use before the end of the year. REDISTRIBUTION. Redistribution refers to the continued movement of water through a soil profile after input of water (via precipitation or irrigation) has ceased at the soil surface. Redistribution is caused by differences in water content in the profile. Once the water content throughout the entire profile is uniform,

29 CHAPTER 1: INTRODUCTION 13

30 14 SWAT USER S MANUAL, VERSION 98.1 redistribution will cease. The redistribution component of SWAT uses a storage routing technique to predict flow through each soil layer in the root zone. Downward flow, or percolation, occurs when field capacity of a soil layer is exceeded and the layer below is not saturated. The flow rate is governed by the saturated conductivity of the soil layer. Movement of water from a subsurface layer to an adjoining upper layer may occur when the water content of the lower layer exceeds field capacity. The upward movement of water is regulated by the soil water to field capacity ratios of the two layers. Redistribution is also affected by soil temperature. If the temperature in a particular layer is 0 C or below, no redistribution is allowed from that layer. EVAPOTRANSPIRATION. Evapotranspiration is a collective term for all processes by which water in the liquid or solid phase at or near the earth's surface becomes atmospheric water vapor. Evapotranspiration includes evaporation from rivers and lakes, bare soil, and vegetative surfaces; evaporation from within the leaves of plants (transpiration); and sublimation from ice and snow surfaces. The model computes evaporation from soils and plants separately as described by Ritchie (1972). Potential soil water evaporation is estimated as a function of potential evapotranspiration and leaf area index (area of plant leaves relative to the area of the HRU). Actual soil water evaporation is estimated by using exponential functions of soil depth and water content. Plant transpiration is simulated as a linear function of potential evapotranspiration and leaf area index. POTENTIAL EVAPOTRANSPIRATION. Potential evapotranspiration is the rate at which evapotranspiration would occur from a large area completely and uniformly covered with growing vegetation which has access to an unlimited supply of soil water. This rate is assumed to be unaffected by micro-climatic processes such as advection or heat-storage effects. The model offers three options for estimating potential evapotranspiration: Hargreaves (Hargreaves et al., 1985), Priestley-Taylor (Priestley and Taylor, 1972), and Penman-Monteith (Monteith, 1965). LATERAL SUBSURFACE FLOW. Lateral subsurface flow, or interflow, is streamflow contribution which originates below the surface but above the zone where rocks are saturated with water. Lateral subsurface flow in the soil profile (0-2m) is calculated simultaneously with redistribution. A kinematic storage model is used to predict lateral flow in each soil layer. The model accounts for variation in conductivity, slope and soil water content. It also allows for flow upward to an adjacent layer or to the surface. SURFACE RUNOFF. Surface runoff, or overland flow, is flow that occurs along a sloping surface. Using daily rainfall amounts, SWAT simulates surface runoff volumes and peak runoff rates for each HRU. SURFACE RUNOFF VOLUME is computed using a modification of the SCS curve number method (USDA Soil Conservation Service, 1972). The curve number varies non-linearly with the moisture content of the soil. The curve number drops as the soil approaches the wilting point and increases

31 CHAPTER 1: INTRODUCTION 15 to near 100 as the soil approaches saturation. SWAT includes a provision for estimating runoff from frozen soil where a soil is defined as frozen if the temperature in the second soil layer is less than 0 C. The model increases runoff for frozen soils but still allows significant infiltration when the frozen soils are dry. PEAK RUNOFF RATE predictions are made with a modification of the rational method. In brief, the rational method is based on the idea that if a rainfall of intensity i begins instantaneously and continues indefinitely, the rate of runoff will increase until the time of concentration, t c, when all of the subbasin is contributing to flow at the outlet. In the modified Rational Formula, the peak runoff rate is a function of the proportion of daily precipitation that falls during the subbasin t c, the daily surface runoff volume, and the subbasin time of concentration. The proportion of rainfall occurring during the subbasin t c is estimated as a function of total daily rainfall using a stochastic technique. The subbasin time of concentration is estimated using Manning s Formula considering both overland and channel flow. PONDS. Ponds are water storage structures located within a subbasin which intercept surface runoff. The catchment area of a pond is defined as a fraction of the total area of the subbasin. When the catchment area fraction is equal to 1.00, the pond is assumed to be located at the outlet of the subbasin on the main channel. If the catchment area fraction is less than 1.00, the pond is assumed to be located on a minor tributary within the subbasin. Pond water storage is a function of pond capacity, daily inflows and outflows, seepage and evaporation. Ponds are assumed to have only emergency spillways. Required inputs are the storage capacity and surface area of the pond when filled to capacity. Surface area below capacity is estimated as a non-linear function of storage. TRIBUTARY CHANNELS. Two types of channels are defined within a subbasin: the main channel and tributary channels. Tributary channels are minor or lower order channels branching off the main channel within the subbasin. Each tributary channel within a subbasin drains only a portion of the subbasin and does not receive groundwater contribution to its flow. All flow in the tributary channels is released and routed through the main channel of the subbasin. SWAT uses the attributes of tributary channels to determine the time of concentration for the subbasin. TRANSMISSION LOSSES. Transmission losses are losses of surface flow via leaching through the streambed. This type of loss occurs in ephemeral or intermittent streams where groundwater contribution occurs only at certain times of the year, or not at all. SWAT uses Lane s method described in Chapter 19 of the SCS Hydrology Handbook (USDA Soil Conservation Service, 1983) to estimate transmission losses. Water losses from the channel are a function of channel width and length and flow duration. Both runoff volume and peak rate are adjusted when transmission losses occur in tributary channels.

32 16 SWAT USER S MANUAL, VERSION 98.1 RETURN FLOW. Return flow, or base flow, is the volume of streamflow originating from groundwater. SWAT partitions groundwater into two aquifer systems: a shallow, unconfined aquifer which contributes return flow to streams within the watershed and a deep, confined aquifer which contributes return flow to streams outside the watershed (Arnold et al., 1993). Water percolating past the bottom of the root zone is partitioned into two fractions each fraction becomes recharge for one of the aquifers. In addition to return flow, water stored in the shallow aquifer may replenish moisture in the soil profile in very dry conditions or be directly removed by plant uptake (only trees may uptake water from the shallow aquifer). Water in the shallow aquifer may also seep into the deep aquifer or be removed by pumping. Water in the deep aquifer may be removed by pumping LAND COVER/PLANT GROWTH SWAT utilizes a single plant growth model to simulate all types of land covers. The model is able to differentiate between annual and perennial plants. Annual plants grow from the planting date to the harvest date or until the accumulated heat units equal the potential heat units for the plant. Perennial plants maintain their root systems throughout the year, becoming dormant after frost. They resume growth when the average daily air temperature exceeds the minimum, or base, temperature required. The plant growth model is used to assess removal of water and nutrients from the root zone, transpiration, and biomass/yield production. POTENTIAL GROWTH. The potential increase in plant biomass on a given day is defined as the increase in biomass under ideal growing conditions. The potential increase in biomass for a day is a function of intercepted energy and the plant's efficiency in converting energy to biomass. Energy interception is estimated as a function of solar radiation and the plant s leaf area index. POTENTIAL AND ACTUAL TRANSPIRATION. The process used to calculate potential plant transpiration is described in the section on evapotranspiration. Actual transpiration is a function of potential transpiration and the soil water content. NUTRIENT UPTAKE. Plant use of nitrogen and phosphorus are estimated with a supply and demand approach where the daily plant nitrogen and phosphorus demands are calculated as the difference between the actual concentration of the element in the plant and the optimal concentration. The

33 CHAPTER 1: INTRODUCTION 17 optimal concentration of the elements varies with growth stage as described by Jones (1983). GROWTH CONTRAINTS. Potential plant growth and yield are usually not achieved due to constraints imposed by the environment. The model estimates stresses caused by water, nutrients and temperature EROSION Erosion and sediment yield are estimated for each HRU with the Modified Universal Soil Loss Equation (MUSLE) (Williams, 1975). While the USLE uses rainfall as an indicator of erosive energy, MUSLE uses the amount of runoff to simulate erosion and sediment yield. The substitution results in a number of benefits: the prediction accuracy of the model is increased, the need for a delivery ratio is eliminated, and single storm estimates of sediment yields can be calculated. The hydrology model supplies estimates of runoff volume and peak runoff rate which, with the subbasin area, are used to calculate the runoff erosive energy variable. The crop management factor is recalculated every day that runoff occurs. It is a function of above-ground biomass, residue on the soil surface, and the minimum C factor for the plant. Other factors of the erosion equation are evaluated as described by Wischmeier and Smith (1978) NUTRIENTS SWAT tracks the movement and transformation of several forms of nitrogen and phosphorus in the watershed. In the soil, transformation of nitrogen from one form to another is governed by the nitrogen cycle as depicted in Figure 1.6. The transformation of phosphorus in the soil is controlled by the phosphorus cycle shown in Figure 1.7. Nutrients may be introduced to the main channel and transported downstream through surface runoff and lateral subsurface flow. NITROGEN. The different processes modeled by SWAT in the HRUs and the various pools of nitrogen in the soil are depicted in Figure 1.6. Plant use of nitrogen is estimated using the supply and demand approach described in the section on plant growth. In addition to plant use, nitrate and organic N may be

34 18 SWAT USER S MANUAL, VERSION 98.1 removed from the soil via mass flow of water. Amounts of NO 3 -N contained in runoff, lateral flow and percolation are estimated as products of the volume of water and the average concentration of nitrate in the layer. Organic N transport with sediment is calculated with a loading function developed by McElroy et al. (1976) and modified by Williams and Hann (1978) for application to individual runoff events. The loading function estimates the daily organic N runoff loss based on the concentration of organic N in the top soil layer, the sediment yield, and the enrichment ratio. The enrichment ratio is the concentration of organic N in the sediment divided by that in the soil. Figure 1.6: Partitioning of Nitrogen in SWAT PHOSPHORUS. The different processes modeled by SWAT in the HRUs and the various pools of phosphorus in the soil are depicted in Figure 1.7. Plant use of phosphorus is estimated using the supply and demand approach described in the section on plant growth. In addition to plant use, soluble phosphorus and organic P may be removed from the soil via mass flow of water. Because phosphorus is not very soluble, the loss of phosphorus dissolved in surface runoff is based on the concept of partitioning pesticides into the solution and sediment phases as described by Leonard and Wauchope (1980). The amount of soluble P removed in runoff is predicted using labile P concentration in the top 10 mm of soil, the runoff volume and a partitioning factor. Sediment transport of P is simulated with a loading function as described in organic N transport.

35 CHAPTER 1: INTRODUCTION 19 Figure 1.7: Partitioning of Phosphorus in SWAT PESTICIDES Although SWAT does not simulate stress on the growth of a plant due to the presence of weeds, damaging insects, and other pests, pesticides may be applied to an HRU to study the movement of the chemical in the watershed. SWAT simulates pesticide movement into the stream network via surface runoff (in solution and sorbed to sediment transported by the runoff), into the soil profile and aquifer by percolation (in solution), and into the atmosphere through volatilization. The equations used to model the movement of pesticide in the land phase of the hydrologic cycle were adopted from GLEAMS (Leonard et al., 1987). The movement of the pesticide is controlled by its solubility, degradation half-life, and soil organic carbon adsorption coefficient. Pesticide on plant foliage and in the soil degrade exponentially according to the appropriate half-life. Pesticide transport by water and sediment is calculated for each runoff event and pesticide leaching is estimated for each soil layer when percolation occurs.

36 20 SWAT USER S MANUAL, VERSION 98.1 Figure 1.8 Pesticide fate and transport in SWAT MANAGEMENT SWAT allows the user to define management practices taking place in every HRU. The user may define the beginning and the ending of the growing season, specify timing and amounts of fertilizer, pesticide and irrigation applications as well as timing of tillage operations. At the end of the growing season, the biomass may be removed from the HRU as yield or placed on the surface as residue. In addition to these basic management practices, operations such as grazing, automated fertilizer and water applications, and incorporation of every conceivable management option for water use are available. The latest improvement to land management is the incorporation of routines to calculate sediment and nutrient loadings from urban areas.

37 CHAPTER 1: INTRODUCTION 21 ROTATIONS. The dictionary defines a rotation as the growing of different crops in succession in one field, usually in a regular sequence. A rotation in SWAT refers to a change in management practices from one year to the next. There is no limit to the number of years of different management operations specified in a rotation. SWAT also does not limit the number of land cover/crops grown within one year in the HRU. However, only one land cover can be growing at any one time. WATER USE. The two most typical uses of water are for application to agricultural lands or use as a town's water supply. SWAT allows water to be applied on an HRU from any water source within or outside the watershed. Water may also be transferred between reservoirs, reaches and subbasins as well as exported from the watershed ROUTING PHASE OF THE HYDROLOGIC CYCLE Once SWAT determines the loadings of water, sediment, nutrients and pesticides to the main channel, the loadings are routed through the stream network of the watershed using a command structure similar to that of HYMO (Williams and Hann, 1972). In addition to keeping track of mass flow in the channel, SWAT models the transformation of chemicals in the stream and streambed. Figure 1.9 illustrates the different in-stream processes modeled by SWAT. Figure 1.9: In-stream processes modeled by SWAT

38 22 SWAT USER S MANUAL, VERSION ROUTING IN THE MAIN CHANNEL OR REACH Routing in the main channel can be divided into four components: water, sediment, nutrients and organic chemicals. FLOOD ROUTING. As water flows downstream, a portion may be lost due to evaporation and transmission through the bed of the channel. Another potential loss is removal of water from the channel for agricultural or human use. Flow may be supplemented by the fall of rain directly on the channel and/or addition of water from point source discharges. Flow is routed through the channel using a variable storage coefficient method developed by Williams (1969) or the Muskingum routing method. SEDIMENT ROUTING. The transport of sediment in the channel is controlled by the simultaneous operation of two processes, deposition and degradation. Deposition in the channel is based on sediment particle fall velocity calculated with Stoke s Law. Stream power is used to predict degradation in the routing reaches. Bagnold (1977) defined stream power as the product of water density, flow rate and water surface slope. Williams (1980) modified Bagnold s equation to place more weight on high values of stream power stream power raised to 1.5. Prior to incorporation into SWAT, the stream power equation was further simplified to make stream power no longer a function of water surface slope. Available stream power is used to reentrain loose and deposited material until all of the material is removed. Excess stream power causes bed degradation. Bed degradation is adjusted for stream bed erodibility and cover. NUTRIENT ROUTING. Nutrient transformations in the stream are controlled by the in-stream water quality component of the model. The in-stream kinetics used in SWAT for nutrient routing are adapted from QUAL2E (Brown and Barnwell, 1987). The model tracks nutrients dissolved in the stream and nutrients adsorbed to the sediment. Dissolved nutrients are transported with the water while those sorbed to sediments are allowed to be deposited with the sediment on the bed of the channel. CHANNEL PESTICIDE ROUTING. While an unlimited number of pesticides may be applied to the HRUs, only one pesticide may be routed through the channel network of the watershed due to the complexity of the processes simulated. As with the nutrients, the total pesticide load in the channel is partitioned into dissolved and sediment-attached components. While the dissolved pesticide is transported with water, the pesticide attached to sediment undergoes sediment transport and deposition processes. Pesticide transformations in the dissolved and sorbed phases are governed by first-order decay relationships. The

39 CHAPTER 1: INTRODUCTION 23 major in-stream processes simulated by the model are settling, burial, resuspension, volatilization, diffusion and transformation ROUTING IN THE RESERVOIR The water balance for reservoirs includes inflow, outflow, rainfall on the surface, evaporation, seepage from the reservoir bottom and diversions. RESERVOIR OUTFLOW. The model offers three alternatives for estimating outflow from the reservoir. The first option allows the user to input measured outflow. The second option, designed for small, uncontrolled reservoirs, requires the users to specify a water release rate. When the reservoir volume exceeds the principle storage, the extra water is released at the specified rate. Volume exceeding the emergency spillway is released within one day. The third option, designed for larger, managed reservoirs, has the user specify monthly target volumes for the reservoir. SEDIMENT ROUTING. Sediment inflow may originate from transport through the upstream reaches or from surface runoff within the subbasin. The concentration of sediment in the reservoir is estimated using a simple continuity equation based on volume and concentration of inflow, outflow, and water retained in the reservoir. Settling of sediment in the reservoir is governed by Stoke's Law. The amount of sediment in the reservoir outflow is the product of the volume of water flowing out of the reservoir and the suspended sediment concentration in the reservoir at the time of release. RESERVOIR NUTRIENTS. A simple model for nitrogen and phosphorus mass balance was taken from Chapra (1997). The model assumes: 1) the lake is completely mixed; 2) phosphorus is the limiting nutrient; and, 3) total phosphorus is a measure of the lake trophic status. The first assumption ignores lake stratification and intensification of phytoplankton in the epilimnon. The second assumption is generally valid when non-point sources dominate and the third assumption implies that a relationship exists between total phosphorus and biomass. The phosphorus mass balance equation includes the concentration in the lake, inflow, outflow and overall loss rate. RESERVOIR PESTICIDES. The lake pesticide balance model is taken from Chapra (1989) and assumes well mixed conditions. The system is partitioned into a well mixed surface water layer underlain by a well mixed sediment layer. The pesticide is partitioned into dissolved and particulate phases in both the water and sediment layers. The major processes simulated by the model are loading, outflow, transformation, volatilization, settling, diffusion, resuspension and burial.

40 24 SWAT USER S MANUAL, VERSION REFERENCES Arnold, J.G., P.M. Allen, and G. Bernhardt A comprehensive surfacegroundwater flow model. J. Hydrol. 142: Arnold, J.G., J.R. Williams, A.D. Nicks, and N.B. Sammons SWRRB: A basin scale simulation model for soil and water resources management. Texas A&M Univ. Press, College Station, TX. Arnold, J.G., J.R. Williams and D.R. Maidment Continuous-time water and sediment-routing model for large basins. Journal of Hydraulic Engineering 121(2): Bagnold, R.A Bedload transport in natural rivers. Water Resources Res. 13(2): Brown, L.C. and T.O. Barnwell, Jr The enhanced water quality models QUAL2E and QUAL2E-UNCAS documentation and user manual. EPA document EPA/600/3-87/007. USEPA, Athens, GA. Chapra, S.C Surface water-quality modeling. McGraw-Hill, Boston. Chapra, S.C Water quality modeling of toxic organics in lakes. CADSWES Working Paper No. 4. Univ. Colorado, Boulder, CO. Hargreaves, G.L., G.H. Hargreaves, and J.P. Riley Agricultural benefits for Senegal River Basin. J. Irrig. and Drain. Engr. 111(2): Jones, C.A A survey of the variability in tissue nitrogen and phosphorus concentrations in maize and grain sorghum. Field Crops Res. 6: Knisel, W.G CREAMS, a field scale model for chemicals, runoff and erosion from agricultural management systems. USDA Conservation Research Rept. No. 26. Leonard, R.A. and R.D. Wauchope Chapter 5: The pesticide submodel. p In Knisel, W.G. (ed). CREAMS: A field-scale model for chemicals, runoff, and erosion from agricultural management systems. U.S. Department of Agriculture, Conservation research report no. 26.

41 CHAPTER 1: INTRODUCTION 25 Leonard, R.A., W.G. Knisel, and D.A. Still GLEAMS: Groundwater loading effects on agricultural management systems. Trans. ASAE 30(5): McElroy, A.D., S.Y. Chiu, J.W. Nebgen, and others Loading functions for assessment of water pollution from nonpoint sources. EPA document EPA 600/ USEPA, Athens, GA. Monteith, J.L Evaporation and the environment. p In The state and movement of water in living organisms. 19 th Symposia of the Society for Experimental Biology. Cambridge Univ. Press, London, U.K. Nicks, A.D Stochastic generation of the occurrence, pattern and location of maximum amount of daily rainfall. p In Proc. Symp. Statistical Hydrology, Tucson, AZ. Aug.-Sept USDA Misc. Publ U.S. Gov. Print. Office, Washington, DC. Priestley, C.H.B. and R.J. Taylor On the assessment of surface heat flux and evaporation using large-scale parameters. Mon. Weather Rev. 100: Ritchie, J.T A model for predicting evaporation from a row crop with incomplete cover. Water Resour. Res. 8: USDA Soil Conservation Service National Engineering Handbook Section 4 Hydrology, Chapter 19. USDA Soil Conservation Service National Engineering Handbook Section 4 Hydrology, Chapters Williams, J.R SPNM, a model for predicting sediment, phosphorus, and nitrogen yields from agricultural basins. Water Resour. Bull. 16(5): Williams, J.R Sediment routing for agricultural watersheds. Water Resour. Bull. 11(5): Williams, J.R Flood routing with variable travel time or variable storage coefficients. Trans. ASAE 12(1):

42 26 SWAT USER S MANUAL, VERSION 98.1 Williams, J.R., A.D. Nicks, and J.G. Arnold Simulator for water resources in rural basins. Journal of Hydraulic Engineering 111(6): Williams, J.R. and R.W. Hann Optimal operation of large agricultural watersheds with water quality constraints. Texas Water Resources Institute, Texas A&M Univ., Tech. Rept. No. 96. Williams, J.R. and R.W. Hann HYMO, a problem-oriented computer language for building hydrologic models. Water Resour. Res. 8(1): Williams, J.R., C.A. Jones and P.T. Dyke A modeling approach to determining the relationship between erosion and soil productivity. Trans. ASAE 27(1): Wischmeier, W.H., and D.D. Smith Predicting rainfall losses: A guide to conservation planning. USDA Agricultural Handbook No U.S. Gov. Print. Office, Washington, D. C.

43 PART 1 MODEL DESCRIPTION

44 CLIMATE The climatic inputs to the model are reviewed first because it is these inputs that provide the moisture and energy that drive all other processes simulated in the watershed. The climatic processes modeled in SWAT consist of precipitation, air temperature, soil temperature and solar radiation. Depending on the method used to calculate potential evapotranspiration, wind speed and relative humidity may also be modeled.

45 CHAPTER 2 EQUATIONS: ENERGY Once water is introduced to the system as precipitation, the available energy, specifically solar radiation, exerts a major control on the movement of water in the land phase of the hydrologic cycle. Processes that are greatly affected by temperature and solar radiation include snow fall, snow melt and evaporation. Since evaporation is the primary water removal mechanism in the watershed, the energy inputs become very important in reproducing or simulating an accurate water balance. 31

46 32 SWAT USER'S MANUAL, VERSION SUN-EARTH RELATIONSHIPS A number of basic concepts related to the earth's orbit around the sun are required by the model to make solar radiation calculations. This section summarizes these concepts. Iqbal (1983) provides a detailed discussion of these and other topics related to solar radiation for users who require more information DISTANCE BETWEEN EARTH AND SUN The mean distance between the earth and the sun is x 10 8 km and is called one astronomical unit (AU). The earth revolves around the sun in an elliptical orbit and the distance from the earth to the sun on a given day will vary from a maximum of AU to a minimum of AU. An accurate value of the earth-sun distance is important because the solar radiation reaching the earth is inversely proportional to the square of its distance from the sun. The distance is traditionally expressed in mathematical form as a Fourier series type of expansion with a number of coefficients. For most engineering applications a simple expression used by Duffie and Beckman (1980) is adequate for calculating the reciprocal of the square of the radius vector of the earth, also called the eccentricity correction factor, E 0, of the earth's orbit: E 2 ( r r) = cos[ ( 2πd 365) ] = n where r 0 is the mean earth-sun distance (1 AU), r is the earth-sun distance for any given day of the year (AU), and d n is the day number of the year, ranging from 1 on January 1 to 365 on December 31. February is always assumed to have 28 days, making the accuracy of the equation vary due to the leap year cycle SOLAR DECLINATION The solar declination is the earth's latitude at which incoming solar rays are normal to the earth's surface. The solar declination is zero at the spring and fall equinoxes, approximately +23½ at the summer solstice and approximately -23½ at the winter solstice. A simple formula to calculate solar declination from Perrin de Brichambaut (1975) is:

47 CHAPTER 2: EQUATIONS ENERGY 33 ( ) 2π δ = sin sin d n where δ is the solar declination reported in radians, and d n is the day number of the year SOLAR NOON, SUNRISE, SUNSET AND DAYLENGTH The angle between the line from an observer on the earth to the sun and a vertical line extending upward from the observer is called the zenith angle, θ z (Figure 2-1). Solar noon occurs when this angle is at its minimum value for the day. Figure 2-1: Diagram illustrating zenith angle For a given geographical position, the relationship between the sun and a horizontal surface on the earth's surface is: cos θ z = sinδ sinφ + cosδ cosφ cosωt where δ is the solar declination in radians, φ is the geographic latitude in radians, ω is the angular velocity of the earth's rotation ( rad h -1 or 15û h -1 ), and t is the solar hour. t equals zero at solar noon, is a positive value in the morning and is a negative value in the evening. The combined term ωt is referred to as the hour angle. Sunrise, T SR, and sunset, T SS, occur at equal times before and after solar noon. These times can be determined by rearranging the above equation as:

48 34 SWAT USER'S MANUAL, VERSION 2000 [ ] cos 1 tanδ tanφ T SR = ω and [ ] cos 1 tanδ tanφ TSS = ω Total daylength, T DL, is calculated: [ tanδ tanφ] 2 cos 1 TDL = ω At latitudes above 66.5 or below -66.5, the absolute value of [-tanδ tanφ] can exceed 1 and the above equation cannot be used. When this happens, there is either no sunrise (winter) or no sunset (summer) and T DL must be assigned a value of 0 or 24 hours, respectively. To determine the minimum daylength that will occur during the year, equation is solved with the solar declination set to ( radians) for the northern hemisphere or 23.5 ( radians) for the southern hemisphere. The only SWAT input variable used in the calculations reviewed in Section 2.1 is given in Table 2-1. Table 2-1: SWAT input variables that used in earth-sun relationship calculations. Variable name Definition File Name LATITUDE Latitude of the subbasin (degrees)..sub 2.2 SOLAR RADIATION EXTRATERRESTRIAL RADIATION The radiant energy from the sun is practically the only source of energy that impacts climatic processes on earth. The solar constant, I SC, is the rate of total solar energy at all wavelengths incident on a unit area exposed normally to rays of the sun at a distance of 1 AU from the sun. Quantifying this value has been the object of numerous studies through the years. The value officially adopted by the Commission for Instruments and Methods of Observation in October 1981 is

49 CHAPTER 2: EQUATIONS ENERGY 35 I SC = 1367 W m -2 = MJ m -2 h -1 On any given day, the extraterrestrial irradiance (rate of energy) on a surface normal to the rays of the sun, I 0n, is: I 0n = I SC E where E 0 is the eccentricity correction factor of the earth's orbit, and I 0n has the same units as the solar constant, I SC. To calculate the irradiance on a horizontal surface, I 0, I 0 I 0n θ z = = cos I E0 cosθ SC z where cos θ z is defined in equation The amount of energy falling on a horizontal surface during a day is given by ss ss H 0 = I 0dt = 2 I 0dt sr 0 where H 0 is the extraterrestrial daily irradiation (MJ m -2 d -1 ), sr is sunrise, and ss is sunset. Assuming that E 0 remains constant during one day and converting the time dt to the hour angle, the equation can be written or 24 ωt SR H 0 = I SC E0 + cos H π 0 0 I SC E0 SR + ( sinδ sinφ cosδ cosφ ωt) dωt = [ ωt ( sinδ sinφ ) ( cosδ cosφ sin( ωtsr ))] π where I SC is the solar constant (4.921 MJ m -2 h -1 ), E 0 is the eccentricity correction factor of the earth's orbit, ω is the angular velocity of the earth's rotation ( rad h -1 ), the hour of sunrise, T SR, is defined by equation 2.1.4, δ is the solar declination in radians, and φ is the geographic latitude in radians. Multiplying all the constants together gives H [ ω sinδ sinφ cosδ cosφ sin( ω )] = 37.59E0 T SR T SR SOLAR RADIATION UNDER CLOUDLESS SKIES When solar radiation enters the earth's atmosphere, a portion of the energy is removed by scattering and adsorption. The amount of energy lost is a function of the transmittance of the atmosphere, the composition and concentration of the

50 36 SWAT USER'S MANUAL, VERSION 2000 constituents of air at the location, the path length the radiation travels through the air column, and the radiation wavelength. Due to the complexity of the process and the detail of the information required to accurately predict the amount of radiant energy lost while passing through the atmosphere, SWAT makes a broad assumption that roughly 20% of the extraterrestrial radiation is lost while passing through the atmosphere under cloudless skies. Using this assumption, the maximum possible solar radiation, H MX, at a particular location on the earth's surface is calculated as: H MX [ ωt sinδ sinφ cosδ cosφ sin( ωt )] = 30.0E SR where the maximum possible solar radiation is the amount of radiation reaching the earth's surface under a clear sky DAILY SOLAR RADIATION The solar radiation reaching the earth's surface on a given day, H day, may be less than H MX due to the presence of cloud cover. The daily solar radiation data required by SWAT may be read from an input file or generated by the model. The variable SLRSIM in the input control code (.cod) file identifies the method used to obtain solar radiation data. To read in daily solar radiation data, the variable is set to 1 and the name of the solar radiation data file and the number of solar radiation records stored in the file are set in the control input/output (file.cio) file. To generate daily solar radiation values, SLRSIM is set to 2. The equations used to generate solar radiation data in SWAT are reviewed in Chapter 4. SWAT input variables that pertain to solar radiation are summarized in Table 2-2. Table 2-2: SWAT input variables used in solar radiation calculations. Variable name Definition File Name LATITUDE Latitude of the subbasin (degrees)..sub SLRSIM Solar radiation input code: 1-measured, 2-generated.cod NSTOT Number of solar radiation records within the.slr file (required if SLRSIM = 1) file.cio SLRFILE Name of measured solar radiation input file (.slr) (required if SLRSIM = 1) file.cio ISGAGE Number of solar radiation record used within the subbasin (required if SLRSIM = 1) SR file.cio see description of.slr file in Chapter 34 for input and format requirements if measured daily solar radiation data is being used

51 CHAPTER 2: EQUATIONS ENERGY HOURLY SOLAR RADIATION The extraterrestrial radiation falling on a horizontal surface during one hour is given by the equation: ( sinδ sinφ cosδ cosφ cos t) I = I SC E ω where I 0 is the extraterrestrial radiation for 1 hour centered around the hour angle ωt. An accurate calculation of the radiation for each hour of the day requires a knowledge of the difference between standard time and solar time for the location. SWAT simplifies the hourly solar radiation calculation by assuming that solar noon occurs at 12:00pm local standard time. When the values of I 0 calculated for every hour between sunrise and sunset are summed, they will equal the value of H 0. Because of the relationship between I 0 and H 0, it is possible to calculate the hourly radiation values by multiplying H 0 by the fraction of radiation that falls within the different hours of the day. The benefit of this alternative method is that assumptions used to estimate the difference between maximum and actual solar radiation reaching the earth s surface can be automatically incorporated in calculations of hourly solar radiation at the earth s surface. SWAT calculates hourly solar radiation at the earth s surface with the equation: I hr = I H frac day where I hr is the solar radiation reaching the earth s surface during a specific hour of the day (MJ m -2 hr -1 ), I frac is the fraction of total daily radiation falling during that hour, and H day is the total solar radiation reaching the earth s surface on that day. The fraction of total daily radiation falling during an hour is calculated I frac = SS ( sinδ sinφ + cosδ cosφ cosωt ) ( sinδ sinφ + cosδ cosφ cosωt) t= SR where t i is the solar time at the midpoint of the hour i. i

52 38 SWAT USER'S MANUAL, VERSION DAILY NET RADIATION Net radiation requires the determination of both incoming and reflected short-wave radiation and net long-wave or thermal radiation. Expressing net radiation in terms of the net short-wave and long-wave components gives: H H α H + H H net = day day L L or net ( ) H day H b H = 1 α where H net is the net radiation (MJ m -2 d -1 ), H day is the short-wave solar radiation reaching the ground (MJ m -2 d -1 ), α is the short-wave reflectance or albedo, H L is the long-wave radiation (MJ m -2 d -1 ), H b is the net long-wave radiation (MJ m -2 d -1 ) and the arrows indicate the direction of the radiation flux NET SHORT-WAVE RADIATION Net short-wave radiation is defined as ( α ) H day 1. SWAT calculates a daily value for albedo as a function of the soil type, plant cover, and snow cover. When the snow water equivalent is greater than 0.5 mm, α = When the snow water equivalent is less than 0.5 mm and no plants are growing in the HRU, α = α soil where α soil is the soil albedo. When plants are growing and the snow water equivalent is less than 0.5 mm, plant ( covsol ) + soil covsol α = α 1 α where α plant is the plant albedo (set at 0.23), and cov sol is the soil cover index. The soil cover index is calculated cov sol 5 ( CV ) = exp where CV is the aboveground biomass and residue (kg ha -1 ).

53 CHAPTER 2: EQUATIONS ENERGY NET LONG-WAVE RADIATION Long-wave radiation is emitted from an object according to the radiation law: H 4 R = σ T K ε where H R is the radiant energy (MJ m -2 d -1 ), ε is the emissivity, σ is the Stefan-Boltzmann constant ( MJ m -2 K -4 d -1 ), and T K is the mean air temperature in Kelvin ( C). Net long-wave radiation is calculated using a modified form of equation (Jensen et al., 1990): H b cld 4 ( ε ) T = f ε σ a vs K where H b is the net long-wave radiation (MJ m -2 d -1 ), f cld is a factor to adjust for cloud cover, ε a is the atmospheric emittance, and ε vs is the vegetative or soil emittance. Wright and Jensen (1972) developed the following expression for the cloud cover adjustment factor, f cld : f cld H day = a b H MX where a and b are constants, H day is the solar radiation reaching the ground surface on a given day (MJ m -2 d -1 ), and H MX is the maximum possible solar radiation to reach the ground surface on a given day (MJ m -2 d -1 ). The two emittances in equation may be combined into a single term, the net emittance ε. The net emittance is calculated using an equation developed by Brunt (1932): ( a + b e ) = ε a ε vs = 1 1 ε where a 1 and b 1 are constants and e is the vapor pressure on a given day (kpa). The calculation of e is given in Chapter 3. Combining equations , , and results in a general equation for net long-wave radiation: H b 4 [ a + b e] T H day = a b 1 1 K H σ MX

54 40 SWAT USER'S MANUAL, VERSION 2000 Experimental values for the coefficients a, b, a 1 and b 1 are presented in Table 2.3. The default equation in SWAT uses coefficent values proposed by Doorenbos and Pruitt (1977): 4 [ e] T H day H b = K H σ MX The model will allow users to override these defaults with other values, but this should be done only when local values are available. These coefficients are not calibration parameters!! Table 2-3: Experimental coefficients for net long-wave radiation equations (from Jensen et al., 1990) Region (a, b) (a 1, b 1 ) Davis, California (1.35, -0.35) (0.35, ) Southern Idaho (1.22, -0.18) (0.325, ) England not available (0.47, ) England not available (0.44, ) Australia not available (0.35, ) General (1.2, -0.2) (0.39, ) General-humid areas (1.0, 0.0) General-semihumid areas (1.1, -0.1) Table 2-4: SWAT input variables used in net radiation calculations. Variable name Definition File Name SOL_ALB α soil : moist soil albedo.sol RBO_A a: Constant a in equation used to estimate the cloud cover factor.bsn RBO_B b: Constant b in equation used to estimate the cloud cover factor.bsn RBO_A1 a 1 : Constant in equation used to estimate net emissivity.bsn RBA_B1 b 1 : Constant in equation used to estimate net emissivity.bsn MAX TEMP T mx : Daily maximum temperature ( C).tmp MIN TEMP T mn : Daily minimum temperature ( C).tmp SOL_RAD H day : Daily solar radiation reaching the earth s surface (MJ m -2 d -1 ).slr

55 CHAPTER 2: EQUATIONS ENERGY TEMPERATURE Temperature influences a number of physical, chemical and biological processes. Plant production is strongly temperature dependent, as are organic matter decomposition and mineralization. Daily air temperature may be input to the model or generated from average monthly values. Soil and water temperatures are derived from air temperature DAILY AIR TEMPERATURE SWAT requires daily maximum and minimum air temperature. This data may be read from an input file or generated by the model. The user is strongly recommended to obtain measured daily temperature records from gages in or near the watershed if at all possible. The accuracy of model results is significantly improved by the use of measured temperature data. The variable TMPSIM in the input control code (.cod) file identifies the method used to obtain air temperature data. To read in daily maximum and minimum air temperature data, the variable is set to 1 and the name of the temperature data file(s) and the number of temperature records stored in the file are set in the control input/output (file.cio) file. To generate daily air temperature values, TMPSIM is set to 2. The equations used to generate air temperature data in SWAT are reviewed in Chapter 4. SWAT input variables that pertain to air temperature are summarized in Table 2-5. Table 2-5: SWAT input variables that pertain to daily air temperature. Variable name Definition File Name TMPSIM Air temperature input code: 1-measured, 2-generated.cod NTGAGE Number of temperature gage (.tmp) files used in simulation file (required if file.cio TMPSIM = 1) NTTOT Number of temperature records used in simulation (required if TMPSIM = 1) file.cio NTFIL Number of temperature records within each.tmp file file (required if file.cio TMPSIM = 1) TFILE Name of measured temperature input file (.tmp) Up to 18 files may be file.cio used. (required if TMPSIM = 1) ITGAGE Number of temperature record used within the subbasin (required if TMPSIM = 1) file.cio see description of.tmp file in Chapter 34 for input and format requirements if measured temperature data is being used

56 42 SWAT USER'S MANUAL, VERSION HOURLY AIR TEMPERATURE Air temperature data are usually provided in the form of daily maximum and minimum temperature. A reasonable approximation for converting these to hourly temperatures is to assume a sinusoidal interpolation function between the minimum and maximum daily temperatures. The maximum daily temperature is assumed to occur at 1500 hours and the minimum daily temperature at 300 hours (Campbell, 1985). The temperature for the hour is then calculated with the equation: ( T T ) ( ( 15) ) mx mn Thr = T av + cos hr where T hr is the air temperature during hour hr of the day ( C), T av is the average temperature on the day ( C), T mx is the daily maximum temperature ( C), and T mn is the daily minimum temperature ( C). Table 2-6: SWAT input variables that pertain to hourly air temperature. Variable name Definition File Name MAX TEMP T mx : Daily maximum temperature ( C).tmp MIN TEMP T mn : Daily minimum temperature ( C).tmp SOIL TEMPERATURE Soil temperature will fluctuate due to seasonal and diurnal variations in temperature at the surface. Figure 2-2 plots air temperature and soil temperature at 5 cm and 300 cm below bare soil at College Station, Texas. Figure 2-2: Four-year average air and soil temperature at College Station, Texas.

57 CHAPTER 2: EQUATIONS ENERGY 43 This figure illustrates several important attributes of temperature variation in the soil. First, the annual variation in soil temperature follows a sinusoidal function. Second, the fluctuation in temperature during the year (the amplitude of the sine wave) decreases with depth until, at some depth in the soil, the temperature remains constant throughout the year. Finally, the timing of maximum and minimum temperatures varies with depth. Note in the above graph that there is a three month difference between the recording of the minimum temperature at the surface (January) and the minimum temperature at 300 cm (March). Carslaw and Jaeger (1959) developed an equation to quantify the seasonal variation in temperature: T ( z, d ) T AA + A exp( z / dd ) sin( d z dd ) = ω soil n surf tmp n / where T soil (z,d n ) is the soil temperature ( C) at depth z (mm) and day of the year d n, T AA is the average annual soil temperature ( C), A surf is the amplitude of the surface fluctuations ( C), dd is the damping depth (mm), and ω tmp is the angular frequency. When z = 0 (soil surface), equation reduces to T soil soil ( 0, d ) T AA + A sin( ω d ) n ( d ) T AA T, =. n =. As z, equation becomes surf tmp n In order to calculate values for some of the variables in this equation, the heat capacity and thermal conductivity of the soil must be known. These are properties not commonly measured in soils and attempts at estimating values from other soil properties have not proven very effective. Consequently, an equation has been adopted in SWAT that calculates the temperature in the soil as a function of the previous day s soil temperature, the average annual air temperature, the current day s soil surface temperature, and the depth in the profile. The equation used to calculate daily average soil temperature at the center of each layer is: soil ( z,d ) = T ( z,d ) + [ 1. 0 ] [ df [ T AAair T ] T ] T n soil n ssurf ssurf

58 44 SWAT USER'S MANUAL, VERSION 2000 where T soil (z,d n ) is the soil temperature ( C) at depth z (mm) and day of the year d n, is the lag coefficient (ranging from 0.0 to 1.0) that controls the influence of the previous day s temperature on the current day s temperature, T soil (z,d n -1) is the soil temperature ( C) in the layer from the previous day, df is the depth factor that quantifies the influence of depth below surface on soil temperature, T AAair is the average annual air temperature ( C), and T ssurf is the soil surface temperature on the day. SWAT sets the lag coefficient,, to The soil temperature from the previous day is known and the average annual air temperature is calculated from the long-term monthly maximum and minimum temperatures reported in the weather generator input (.wgn) file. This leaves the depth factor, df, and the soil surface temperature, T ssurf, to be defined. The depth factor is calculated using the equation: zd df = zd + exp( zd ) where zd is the ratio of the depth at the center of the soil layer to the damping depth: z zd = dd where z is the depth at the center of the soil layer (mm) and dd is the damping depth (mm). From the previous three equations (2.3.3, and 2.3.5) one can see that at depths close to the soil surface, the soil temperature is a function of the soil surface temperature. As the depth increases, soil temperature is increasingly influenced by the average annual air temperature, until at the damping depth, the soil temperature is within 5% of T AAair. The damping depth, dd, is calculated daily and is a function of the maximum damping depth, bulk density and soil water. The maximum damping depth, dd max, is calculated: dd 2500ρ b max = ρb exp( 5.63ρb )

59 CHAPTER 2: EQUATIONS ENERGY 45 where dd max is the maximum damping depth (mm), and ρ b is the soil bulk density (Mg/m 3 ). The impact of soil water content on the damping depth is incorporated via a scaling factor,ϕ, that is calculated with the equation: ϕ = SW ( ρb ) ztot where SW is the amount of water in the soil profile expressed as depth of water in the profile (mm H 2 O), ρ b is the soil bulk density (Mg/m 3 ), and z tot is the depth from the soil surface to the bottom of the soil profile (mm). The daily value for the damping depth, dd, is calculated: ϕ dd = dd max exp ln dd max 1+ ϕ where dd max is the maximum damping depth (mm), and ϕ is the scaling factor for soil water. The soil surface temperature is a function of the previous day s temperature, the amount of ground cover and the temperature of the surface when no cover is present. The temperature of a bare soil surface is calculated with the equation: T bare ( T T ) mx mn = T av + ε sr where T bare is the temperature of the soil surface with no cover ( C), T av is the average temperature on the day ( C), T mx is the daily maximum temperature ( C), T mn is the daily minimum temperature ( C), and ε sr is a radiation term. The radiation term is calculated with the equation: ( α ) H day 1 14 ε sr = where H day is the solar radiation reaching the ground on the current day (MJ m -2 d -1 ), and α is the albedo for the day.

60 46 SWAT USER'S MANUAL, VERSION 2000 Any cover present will significantly impact the soil surface temperature. The influence of plant canopy or snow cover on soil temperature is incorporated with a weighting factor, bcv, calculated as: CV + exp bcv = max SNO + exp CV 4 ( CV ) SNO ( SNO) where CV is the total aboveground biomass and residue present on the current day (kg ha -1 ) and SNO is the water content of the snow cover on the current day (mm H 2 O). The weighting factor, bcv, is 0.0 for a bare soil and approaches 1.0 as cover increases. The equation used to calculate the soil surface temperature is: T ssurf soil (, d n 1) + ( bcv) Tbare = bcv T where T ssurf is the soil surface temperature for the current day ( C), bcv is the weighting factor for soil cover impacts, T soil (2,d n -1) is the soil temperature of the 2 nd soil layer on the previous day ( C), and T bare is the temperature of the bare soil surface ( C). The influence of ground cover is to place more emphasis on the previous day s temperature near the surface. Remember that SWAT creates an artificial 1 st soil layer that is 10mm deep for calculating surface runoff interactions. The first soil layer listed in the.sol input file becomes layer #2 in the simulation. SWAT input variables that directly impact soil temperature calculations are listed in Table 2-7. There are several other variables that initialize residue and snow cover in the subbasins or HRUs (SNO_SUB and SNOEB in.sub; RSDIN in.hru). The influence of these variables will be limited to the first few months of simulation. Finally, the timing of management operations in the.mgt file will affect ground cover and consequently soil temperature.

61 Table 2-7: SWAT input variables that pertain to soil temperature. CHAPTER 2: EQUATIONS ENERGY 47 Variable name Definition File Name TMPMX Average maximum air temperature for month ( C).wgn TMPMN Average minimum air temperature for month ( C).wgn SOL_Z z: Depth from soil surface to bottom of layer (mm).sol SOL_BD ρ b : Moist bulk density (Mg m -3 or g cm -3 ).sol SOL_ALB Moist soil albedo..sol MAX TEMP T mx : Daily maximum temperature ( C).tmp MIN TEMP T mn : Daily minimum temperature ( C).tmp WATER TEMPERATURE Water temperature is required to model in-stream biological and water quality processes. SWAT uses an equation developed by Stefan and Preud homme (1993) to calculate average daily water temperature for a well-mixed stream: T = water T av where T water is the water temperature for the day ( C), and temperature on the day ( C). T av is the average Due to thermal inertia of the water, the response of water temperature to a change in air temperature is dampened and delayed. When water and air temperature are plotted for a stream or river, the peaks in the water temperature plots usually lag 3-7 hours behind the peaks in air temperature. As the depth of the river increases, the lag time can increase beyond this typical interval. For very large rivers, the lag time can extend up to a week. Equation assumes that the lag time between air and water temperatures is less than 1 day. In addition to air temperature, water temperature is influenced by solar radiation, relative humidity, wind speed, water depth, ground water inflow, artificial heat inputs, thermal conductivity of the sediments and the presence of impoundments along the stream network. SWAT assumes that the impact of these other variables on water temperature is not significant. Table 2-8: SWAT input variables that pertain to water temperature. Variable name Definition File Name MAX TEMP T mx : Daily maximum temperature ( C).tmp MIN TEMP T mn : Daily minimum temperature ( C).tmp

62 48 SWAT USER'S MANUAL, VERSION WIND SPEED Wind speed is required by SWAT if the Penman-Monteith equation is used to estimate potential evapotranspiration and transpiration. SWAT assumes wind speed information is collected from gages positioned 1.7 meters above the ground surface. When using the Penman-Monteith equation to estimate transpiration, the wind measurement used in the equation must be above the canopy. In SWAT, a minimum difference of 1 meter is specified for canopy height and wind speed measurements. When the canopy height exceeds 1 meter, the original wind measurements is adjusted to: z h w = c where z w is the height of the wind speed measurement (cm), and h c is the canopy height (cm). The variation of wind speed with elevation near the ground surface is estimated with the equation (Haltiner and Martin, 1957): aa z2 uz2 = uz1 z where u z1 is the wind speed (m s -1 ) at height z 1 (cm), u z2 is the wind speed (m s -1 ) at height z 2 (cm), and aa is an exponent between 0 and 1 that varies with atmospheric stability and surface roughness. Jensen (1974) recommended a value of 0.2 for aa and this is the value used in SWAT. The daily wind speed data required by SWAT may be read from an input file or generated by the model. The variable WNDSIM in the input control code (.cod) file identifies the method used to obtain wind speed data. To read in daily wind speed data, the variable is set to 1 and the name of the wind speed data file and the number of different records stored in the file are set in the control input/output (file.cio) file. To generate daily wind speed values, WNDSIM is set to 2. The equations used to generate wind speed data in SWAT are reviewed in Chapter 4.

63 CHAPTER 2: EQUATIONS ENERGY 49 Table 2-9: SWAT input variables used in wind speed calculations. Variable name Definition File Name WNDSIM Wind speed input code: 1-measured, 2-generated.cod NWTOT Number of wind speed records within the.wnd file (required if WNDSIM = 1) file.cio WNDFILE Name of measured wind speed input file (.wnd) (required if WNDSIM = 1) file.cio IWGAGE Number of wind speed record used within the subbasin (required if WNDSIM = 1) file.cio see description of.wnd file in Chapter 34 for input and format requirements if measured daily wind speed data is being used 2.5 NOMENCLATURE A surf Amplitude of the surface fluctuations in soil temperature ( C) AU Astronomical unit (1 AU = x 10 8 km) CV Total aboveground biomass and residue present on current day (kg ha -1 ) E 0 Eccentricity correction factor of earth (r 0 /r) 2 H 0 Extraterrestrial daily irradiation (MJ m -2 d -1 ) H b Net outgoing long-wave radiation (MJ m -2 d -1 ) H day Solar radiation reaching ground on current day of simulation (MJ m -2 d -1 ) H L Long-wave radiation (MJ m -2 d -1 ) H MX Maximum possible solar radiation (MJ m -2 d -1 ) H net Net radiation on day (MJ m -2 d -1 ) H R Radiant energy (MJ m -2 d -1 ) I frac Fraction of daily solar radiation falling during specific hour on current day of simulation I hr Solar radiation reaching ground during specific hour on current day of simulation (MJ m -2 h -1 ) I SC Solar constant (4.921 MJ m -2 h -1 ) I 0 Extraterrestrial daily irradiance incident on a horizontal surface (MJ m -2 h -1 ) I 0n Extraterrestrial daily irradiance incident on a normal surface (MJ m -2 h -1 ) SNO Water content of snow cover on current day (mm H 2 O) SW Amount of water in soil profile (mm H 2 O) T bare Temperature of soil surface with no cover ( C) T DL Daylength (h) T hr Air temperature during hour ( C) T K Mean air temperature in Kelvin ( C) T mn Minimum air temperature for day ( C) T mx Maximum air temperature for day ( C) T soil Soil temperature ( C) T ssurf Soil surface temperature ( C) T SR Time of sunrise in solar day (h) T SS Time of sunset in solar day (h) T water Average daily water temperature ( C) T AA Average annual soil temperature ( C)

64 50 SWAT USER'S MANUAL, VERSION 2000 T T av AAair Average annual air temperature ( C) Average air temperature for day ( C) a Constant in equation used to calculate the cloud cover adjustment factor a 1 Constant in equation used to calculate net emissivity aa Exponent between 0 and 1 that varies with atmospheric stability and surface roughness that is used in calculating wind speed at different heights b Constant in equation used to calculate the cloud cover adjustment factor b 1 Constant in equation used to calculate net emissivity bcv weighting factor for impact of ground cover on soil surface temperature cov sol Soil cover index for albedo determination d n Day number of year, 1 on January 1 and 365 on December 31 dd Damping depth (mm) dd max Maximum damping depth (mm) df Depth factor used in soil temperature calculations e Vapor pressure (actual) on a given day (kpa) f cld Factor to adjust for cloud cover in net long-wave radiation calculation h c Canopy height (cm) hr Hour of day (1-24) r Actual earth-sun distance (AU) r 0 Mean earth-sun distance, 1 AU t Number of hours before (+) or after (-) solar noon t i Solar time at the midpoint of the hour i u z1 Wind speed (m s -1 ) at height z 1 (cm) u z2 Wind speed (m s -1 ) at height z 2 (cm) z Depth below soil surface (mm) z 1 Height of wind speed measurement (cm) z 2 Height of wind speed measurement (cm) z tot Depth to bottom of soil profile (mm) z w Height of the wind speed measurement (cm) zd Ratio of depth in soil to damping depth α Short-wave reflectance or albedo α plant Plant albedo (set at 0.23) α soil Soil albedo δ Solar declination (radians) ε Emissivity ε Net emittance ε a Atmospheric emittance ε sr Radiation term for bare soil surface temperature calculation ε vs Vegetative or soil emittance Lag coefficient that controls influence of previous day s temperature on current days temperature σ Stefan-Boltzmann constant ( MJ m -2 K -4 d -1 ) θ z Zenith angle (radians)

65 φ Latitude in radians ρ b Soil bulk density (Mg m -3 ) ϕ Scaling factor for impact of soil water on damping depth ω Angular velocity of the earth's rotation ( radians h -1 ) ω tmp Angular frequency in soil temperature variation CHAPTER 2: EQUATIONS ENERGY REFERENCES Brunt, D Notes on radiation in the atmosphere. Quart. J. Roy. Meteorol. Soc. 58: Campbell, G.S Soil physics with BASIC: transport models for soil-plant systems. Elsevier, Amsterdam. Carslaw, H.S. and J.C. Jaeger Conduction of heat in solids. Oxford University Press, London. Doorenbos, J. and W.O. Pruitt Guidelines for predicting crop water requirements. FAO Irrig. and Drain. Paper No. 24, 2 nd ed. FAO, Rome. Duffie, J.A. and W.A. Beckman Solar engineering of thermal processes. Wiley, N.Y. Haltiner, G.J. and F.L. Martin Dynamical and physical meteorology. McGraw-Hill, New York. Iqbal, M An introduction to solar radiation. Academic Press, N.Y. Jensen, M.E. (ed.) Consumptive use of water and irrigation water requirements. Rep. Tech. Com. on Irrig. Water Requirements, Irrig. and Drain. Div., ASCE. Jensen, M.E., R.D. Burman, and R.G. Allen (ed) Evapotranspiration and irrigation water requirements. ASCE Manuals and Reports on Engineering Practice No. 70, ASCE, N.Y. Perrin de Brichambaut, Chr Cahiers A.F.E.D.E.S., supplément au no 1. Editions Européennes Thermique et Industrie, Paris. Stefan, H.G. and E.B. Preud homme Stream temperature estimation from air temperature. Water Resources Bulletin 29(1):

66 52 SWAT USER'S MANUAL, VERSION 2000 Wright, J.L. and M.E. Jensen Peak water requirements of crops in Southern Idaho. J. Irrig. and Drain. Div., ASCE, 96(IR1):

67 CHAPTER 3 EQUATIONS: ATMOSPHERIC WATER Precipitation is the mechanism by which water enters the land phase of the hydrologic cycle. Because precipitation controls the water balance, it is critical that the amount and distribution of precipitation in space and time is accurately simulated by the model. 53

68 54 SWAT USER S MANUAL, VERSION PRECIPITATION The precipitation reaching the earth's surface on a given day, R day, may be read from an input file or generated by the model. Users are strongly recommended to incorporate measured precipitation into their simulations any time the data is available. The ability of SWAT to reproduce observed stream hydrographs is greatly improved by the use of measured precipitation data. Unfortunately, even with the use of measured precipitation the model user can expect some error due to inaccuracy in precipitation data. Measurement of precipitation at individual gages is subject to error from a number of causes and additional error is introduced when regional precipitation is estimated from point values. Typically, total or average areal precipitation estimates for periods of a year or longer have relative uncertainties of 10% (Winter, 1981). Point measurements of precipitation generally capture only a fraction of the true precipitation. The inability of a gage to capture a true reading is primarily caused by wind eddies created by the gage. These wind eddies reduce the catch of the smaller raindrops and snowflakes. Larson and Peck (1974) found that deficiencies of 10% for rain and 30% for snow are common for gages projecting above the ground surface that are not designed to shield wind effects. Even when the gage is designed to shield for wind effects, this source of error will not be eliminated. For an in-depth discussion of this and other sources of error as well as methods for dealing with the error, please refer to Dingman (1994). The variable PCPSIM in the input control code (.cod) file identifies the method used to obtain precipitation data. To read in daily precipitation data, the variable is set to 1 and the names of the precipitation data files and the number of precipitation records stored in the files are defined in the control input/output (file.cio) file. To generate daily precipitation values, PCPSIM is set to 2. The equations used to generate precipitation data in SWAT are reviewed in Chapter 4. SWAT input variables that pertain to precipitation are summarized in Table 3-1.

69 CHAPTER 3: EQUATIONS ATMOSPHERIC WATER 55 Table 3-1: SWAT input variables used in precipitation calculations. Variable name Definition File Name PCPSIM Precipitation input code: 1-measured, 2-generated.cod NRGAGE Number of precipitation gage files (.pcp) used (required if PCPSIM = 1) file.cio NRTOT Total number of precipitation records used in simulation (required if PCPSIM file.cio = 1) NRGFIL Number of precipitation records in each.pcp file (required if PCPSIM = 1) file.cio RFILE Name of measured precipitation input file(s) (.pcp) (required if PCPSIM = 1) file.cio IRGAGE Number of precipitation record used within the subbasin (required if PCPSIM = 1) file.cio see description of.pcp file in Chapter 34 for input and format requirements if measured daily precipitation data is being used 3.2 MAXIMUM HALF-HOUR RAINFALL The maximum half-hour rainfall is required by SWAT to calculate the pear runoff rate. The maximum half-hour rainfall is reported as a fraction of the total daily rainfall, α 0.5. If sub-daily precipitation data is used in the model, SWAT will calculate the maximum half-hour rainfall fraction directly from the precipitation data. If daily precipitation data is used, SWAT generates a value for α 0.5 using the equations summarized in Chapter WATER VAPOR Relative humidity is required by SWAT if the Penman-Monteith or Priestley-Taylor equation is used to estimate potential evapotranspiration. The Penman-Monteith equation includes terms that quantify the effect of the amount of water vapor in the air near the evaporative surface on evaporation. Both Penman-Monteith and Priestley-Taylor require the actual vapor pressure, which is calculated from the relative humidity. Relative humidity is the ratio of an air volume s actual vapor pressure to its saturation vapor pressure: e R h = o e where R h is the relative humidity on a given day, e is the actual vapor pressure on a given day (kpa), and o e is the saturation vapor pressure on a given day (kpa).

70 56 SWAT USER S MANUAL, VERSION 2000 The saturation vapor pressure is the maximum vapor pressure that is thermodynamically stable and is a function of the air temperature. SWAT calculates saturation vapor pressure using an equation presented by Tetens (1930) and Murray (1967): where o T av e = exp T av o e is the saturation vapor pressure on a given day (kpa) and T av is the mean daily air temperature ( C). When relative humidity is known, the actual vapor pressure can be calculated by rearranging equation 3.3.1: e o = R h e The saturation vapor pressure curve is obtained by plotting equation The slope of the saturation vapor pressure curve can be calculated by differentiating equation 3.3.2: = 4098 e o ( T ) 2 av where is the slope of the saturation vapor pressure curve (kpa C -1 ), saturation vapor pressure on a given day (kpa) and temperature ( C) o e is the T av is the mean daily air The rate of evaporation is proportional to the difference between the vapor pressure of the surface layer and the vapor pressure of the overlying air. This difference is termed the vapor pressure deficit: vpd = e o e where vpd is the vapor pressure deficit (kpa), e o is the saturation vapor pressure on a given day (kpa), and e is the actual vapor pressure on a given day (kpa). The greater the value of vpd the higher the rate of evaporation. The latent heat of vaporization, λ, is the quantity of heat energy that must be absorbed to break the hydrogen bonds between water molecules in the liquid state to convert them to gas. The latent heat of vaporization is a function of temperature and can be calculated with the equation (Harrison, 1963):

71 CHAPTER 3: EQUATIONS ATMOSPHERIC WATER 57 3 λ = T av where λ is the latent heat of vaporization (MJ kg -1 ) and temperature ( C). T av is the mean daily air Evaporation involves the exchange of both latent heat and sensible heat between the evaporating body and the air. The psychrometric constant, γ, represents a balance between the sensible heat gained from air flowing past a wet bulb thermometer and the sensible heat converted to latent heat (Brunt, 1952) and is calculated: c γ = p P λ where γ is the psychrometric constant (kpa C -1 ), c p is the specific heat of moist air at constant pressure ( MJ kg -1 C -1 ), P is the atmospheric pressure (kpa), and λ is the latent heat of vaporization (MJ kg -1 ). Calculation of the psychrometric constant requires a value for atmospheric pressure. SWAT estimates atmospheric pressure using an equation developed by Doorenbos and Pruitt (1977) from mean barometric pressure data at a number of East African sites: P = EL EL where P is the atmospheric pressure (kpa) and EL is the elevation (m) The daily relative humidity data required by SWAT may be read from an input file or generated by the model. The variable RHSIM in the input control code (.cod) file identifies the method used to obtain relative humidity data. To read in daily relative humidity data, the variable is set to 1 and the name of the relative humidity data file and the number of different records stored in the file are set in the control input/output (file.cio) file. To generate daily relative humidity values, RHSIM is set to 2. The equations used to generate relative humidity data in SWAT are reviewed in Chapter 4.

72 58 SWAT USER S MANUAL, VERSION 2000 Table 3-2: SWAT input variables used in relative humidity calculations. Variable name Definition File Name RHD R h : daily average relative humidity.hmd TMP_MX T mx : maximum temperature for day ( C).tmp TMP_MN T mn : minimum temperature for day ( C).tmp ELEV EL: elevation (m).sub RHSIM Relative humidity input code: 1-measured, 2-generated.cod NHTOT Number of relative humidity records within the.hmd file (required if RHSIM = 1) file.cio RHFILE Name of measured relative humidity input file (.hmd) (required if RHSIM = 1) file.cio IHGAGE Number of relative humidity record used within the subbasin (required if file.cio RHSIM = 1) see description of.hmd file in Chapter 34 for input and format requirements if measured relative humidity data is being used 3.4 SNOW COVER SWAT classifies precipitation as rain or freezing rain/snow by the mean daily air temperature. The boundary temperature, T s-r, used to categorize precipitation as rain or snow is defined by the user. If the mean daily air temperature is less than the boundary temperature, then the precipitation within the HRU is classified as snow and the water equivalent of the snow precipitation is added to the snow pack. Snowfall is stored at the ground surface in the form of a snow pack. The amount of water stored in the snow pack is reported as a snow water equivalent. The snow pack will increase with additional snowfall or decrease with snow melt or sublimation. The mass balance for the snow pack is: SNO = SNO + R E SNO day sub mlt where SNO is the water content of the snow pack on a given day (mm H 2 O), R day is the amount of precipitation on a given day (added only if T av T s r ) (mm H 2 O), E sub is the amount of sublimation on a given day (mm H 2 O), and SNO mlt is the amount of snow melt on a given day (mm H 2 O). The amount of snow is expressed as depth over the total HRU area. Due to variables such as drifting, shading and topography, the snow pack in a subbasin will rarely be uniformly distributed over the total area. This results

73 CHAPTER 3: EQUATIONS ATMOSPHERIC WATER 59 in a fraction of the subbasin area that is bare of snow. This fraction must be quantified to accurately compute snow melt in the subbasin. The factors that contribute to variable snow coverage are usually similar from year to year, making it possible to correlate the areal coverage of snow with the amount of snow present in the subbasin at a given time. This correlation is expressed as an areal depletion curve, which is used to describe the seasonal growth and recession of the snow pack as a function of the amount of snow present in the subbasin (Anderson, 1976). The areal depletion curve requires a threshold depth of snow, SNO 100, to be defined above which there will always be 100 % cover. The threshold depth will depend on factors such as vegetation distribution, wind loading of snow, wind scouring of snow, interception and aspect, and will be unique to the watershed of interest. The areal depletion curve is based on a natural logarithm. The areal depletion curve equation is: SNO SNO SNO snocov = exp + cov1 cov SNO100 SNO100 SNO100 where sno cov is the fraction of the HRU area covered by snow, SNO is the water content of the snow pack on a given day (mm H 2 O), SNO 100 is the threshold depth of snow at 100% coverage (mm H 2 O), cov 1 and cov 2 are coefficients that define the shape of the curve. The values used for cov 1 and cov 2 are determined by solving equation using two known points: 95% coverage at 95% SNO 100 ; and 50% coverage at a user specified fraction of SNO 100. Example areal depletion curves for various fractions of SNO 100 at 50% coverage are shown in the following figures. 1

74 60 SWAT USER S MANUAL, VERSION Fraction areal coverage Fraction areal coverage Snow volume (fraction of SNO100 ) Snow volume (fraction of SNO100 ) Figure 3-1:10% SNO 100 = 50% coverage Figure 3-2: 30% SNO 100 = 50% coverage Fraction areal coverage Fraction areal coverage Snow volume (fraction of SNO100 ) Snow volume (fraction of SNO100) Figure 3-3: 50% SNO 100 = 50% coverage Figure 3-4: 70% SNO 100 = 50% coverage Fraction areal coverage Snow volume (fraction of SNO100) Figure 3-5: 90% SNO 100 = 50% coverage It is important to remember that once the volume of water held in the snow pack exceeds SNO 100 the depth of snow over the HRU is assumed to be uniform, i.e. sno cov = 1.0. The areal depletion curve affects snow melt only when the snow

75 CHAPTER 3: EQUATIONS ATMOSPHERIC WATER 61 pack water content is between 0.0 and SNO 100. Consequently if SNO 100 is set to a very small value, the impact of the areal depletion curve on snow melt will be minimal. As the value for SNO 100 increases, the influence of the areal depletion curve will assume more importance in snow melt processes. Table 3-3: SWAT input variables used in snow cover calculations. Variable name Definition File Name SFTMP T s-r : Mean air temperature at which precipitation is equally likely to be.bsn rain as snow/freezing rain ( C) SNOCOVMX SNO 100 : Threshold depth of snow, above which there is 100% cover.bsn SNO50COV Fraction of SNOCOVMX that provides 50% cover.bsn SNO_SUB Initial snow water content in subbasin (mm H 2 O).sub SNOEB Initial snow water content in subbasin elevation band (mm H 2 O).sub 3.5 SNOW MELT Snow melt is controlled by the air and snow pack temperature, the melting rate, and the areal coverage of snow. Snow melt is included with rainfall in the calculations of runoff and percolation. When SWAT calculates erosion, the rainfall energy of the snow melt fraction of the water is set to zero. The water released from snow melt is assumed to be evenly distributed over the 24 hours of the day SNOW PACK TEMPERATURE The snow pack temperature is a function of the mean daily temperature during the preceding days and varies as a dampened function of air temperature (Anderson, 1976). The influence of the previous day s snow pack temperature on the current day s snow pack temperature is controlled by a lagging factor, sno. The lagging factor inherently accounts for snow pack density, snow pack depth, exposure and other factors affecting snow pack temperature. The equation used to calculate the snow pack temperature is: T snow = T T ( d ) snow( d ) ( sno ) av sno n n

76 62 SWAT USER S MANUAL, VERSION 2000 where T snow( ) is the snow pack temperature on a given day ( C), T snow( d n 1) is the d n snow pack temperature on the previous day ( C), sno is the snow temperature lag factor, and T av is the mean air temperature on the current day ( C). As sno approaches 1.0, the mean air temperature on the current day exerts an increasingly greater influence on the snow pack temperature and the snow pack temperature from the previous day exerts less and less influence. The snow pack will not melt until the snow pack temperature exceeds a threshold value, T mlt. This threshold value is specified by the user SNOW MELT EQUATION The snow melt in SWAT is calculated as a linear function of the difference between the average snow pack-maximum air temperature and the base or threshold temperature for snow melt: Tsnow + Tmx SNOmlt = bmlt snocov Tmlt where SNO mlt is the amount of snow melt on a given day (mm H 2 O), b mlt is the melt factor for the day (mm H 2 O/day- C), sno cov is the fraction of the HRU area covered by snow, T snow is the snow pack temperature on a given day ( C), T mx is the maximum air temperature on a give day ( C), and T mlt is the base temperature above which snow melt is allowed ( C). The melt factor is allowed a seasonal variation with maximum and minimum values occurring on summer and winter solstices: ( b + b ) ( b b ) mlt6 mlt12 mlt6 mlt12 2π bmlt = + sin ( d n 81) where b mlt is the melt factor for the day (mm H 2 O/day- C), b mlt6 is the melt factor for June 21 (mm H 2 O/day- C), b mlt12 is the melt factor for December 21 (mm H 2 O/day- C), and d n is the day number of the year. In rural areas, the melt factor will vary from 1.4 to 6.9 mm H 2 O/day- C (Huber and Dickinson, 1988). In urban areas, values will fall in the higher end of the range due to compression of the snow pack by vehicles, pedestrians, etc.

77 CHAPTER 3: EQUATIONS ATMOSPHERIC WATER 63 Urban snow melt studies in Sweden (Bengston, 1981; Westerstrom, 1981) reported melt factors ranging from 3.0 to 8.0 mm H 2 O/day- C. Studies of snow melt on asphalt (Westerstrom, 1984) gave melt factors of 1.7 to 6.5 mm H 2 O/day- C. Table 3-4: SWAT input variables used in snow melt calculations. Variable name Definition File Name TIMP : Snow temperature lag factor.bsn sno SMTMP T mlt : Threshold temperature for snow melt ( C).bsn SMFMX b mlt6 : Melt factor on June 21 (mm H 2 O/day- C).bsn SMFMN b mlt12 : Melt factor on December 21 (mm H 2 O/day- C).bsn 3.6 NOMENCLATURE E sub Amount of sublimation on a given day (mm H 2 O) EL Elevation (m) P Atmospheric pressure (kpa) R day Amount of rainfall on a given day (mm H 2 O) R h Average relative humidity for the day SNO Water content of snow cover on current day (mm H 2 O) SNO 100 Amount of snow above which there is 100% cover (mm H 2 O) SNO mlt Amount of snow melt on a given day (mm H 2 O) T mlt Threshold temperature for snow melt ( C) T mx Maximum air temperature for day ( C) T s-r Rain/snow boundary temperature ( C) T Snow pack temperature on a given day ( C) snow T av Average air temperature for day ( C) b mlt Melt factor for the day (mm H 2 O/day- C) b mlt6 Melt factor for June 21 (mm H 2 O/day- C) b mlt12 Melt factor for December 21 (mm H 2 O/day- C) c p Specific heat of moist air at constant pressure ( MJ kg -1 C -1 ) cov 1 Snow cover areal depletion curve shape coefficient cov 2 Snow cover areal depletion curve shape coefficient d n Day number of year, 1 on January 1 and 365 on December 31 e Actual vapor pressure on a given day (kpa) o e Saturation vapor pressure on a given day (kpa) sno cov Fraction of the HRU area covered by snow vpd Vapor pressure deficit (kpa)

78 64 SWAT USER S MANUAL, VERSION 2000 α 0.5 Maximum half-hour rainfall expressed as a fraction of daily rainfall Slope of the saturation vapor pressure curve (kpa C -1 ) γ Psychrometric constant (kpa C -1 ) λ Latent heat of vaporization (MJ kg -1 ) Snow temperature lag factor sno 3.7 REFERENCES Anderson, E.A A point energy and mass balance model of snow cover. NOAA Technical Report NWS 19, U.S. Dept. of Commerce, National Weather Service. Bengston, L Snowmelt-generated runoff in urban areas. p In B.C. Yen (ed.) Urban stormwater hydraulics and hydrology: proceedings of the Second International Conference on Urban Storm Drainage, held at Urbana, Illinois, USA, June Water Resources Publications, Littleton, CO. Brunt, D Physical and dynamical meteorology, 2 nd ed. University Press, Cambridge. Dingman, S.L Physical hydrology. Prentice-Hall, Inc., Englewood Cliffs, NJ. Doorenos, J. and W.O. Pruitt Guidelines for predicting crop water requirements. FAO Irrig. and Drain. Paper No. 24, 2 nd ed. FAO, Rome. Harrison, L.P Fundamental concepts and definitions relating to humidity. In A. Wexler (ed.) Humidity and moisture, Vol. 3. Reinhold Publishing Company, N.Y. Huber, W.C. and R.E. Dickinson Storm water management model, version 4: user s manual. U.S. Environmental Protection Agency, Athens, GA. Larson, L.L., and E.L. Peck Accuracy of precipitation measurements for hydrologic modeling. Water Resources Research 10: Murray, F.W On the computation of saturation vapor pressure. J. Appl. Meteor. 6: Tetens, O Uber einige meteorologische Begriffe. Z. Geophys. 6: Westerstrom, G Snowmelt runoff from Porson residential area, Lulea, Sweden. p In Proceedings of the Third International Conference on Urban Storm Drainage held at Chalmers University, Goteborg, Sweden, June 1984.

79 CHAPTER 3: EQUATIONS ATMOSPHERIC WATER 65 Westerstrom, G Snowmelt runoff from urban plot. p In B.C. Yen (ed.) Urban stormwater hydraulics and hydrology: proceedings of the Second International Conference on Urban Storm Drainage, held at Urbana, Illinois, USA, June Water Resources Publications, Littleton, CO. Winter, T.C Uncertainties in estimating the water balance of lakes. Water Resources Bulletin 17:

80 66 SWAT USER S MANUAL, VERSION 2000

81 CHAPTER 4 EQUATIONS: WEATHER GENERATOR SWAT requires daily values of precipitation, maximum and minimum temperature, solar radiation, relative humidity and wind speed. The user may choose to read these inputs from a file or to generate the values using monthly average data summarized over a number of years. SWAT includes the WXGEN weather generator model (Sharpley, A.N. and J.R. Williams, 1990) to generate climatic data or to fill in gaps in measured records. This weather generator was developed for the contiguous U.S. If the user prefers a different weather generator, daily input values for the different weather parameters may be generated with an alternative model and formatted for input to SWAT. 67

82 68 SWAT USER'S MANUAL, VERSION 2000 The occurrence of rain on a given day has a major impact on relative humidity, temperature and solar radiation for the day. The weather generator first independently generates precipitation for the day. Maximum temperature, minimum temperature, solar radiation and relative humidity are then generated based on the presence or absence of rain for the day. Finally, wind speed is generated independently. 4.1 PRECIPITATION The precipitation generator is a Markov chain-skewed (Nicks, 1974) or Markov chain-exponential model (Williams, 1995). A first-order Markov chain is used to define the day as wet or dry. When a wet day is generated, a skewed distribution or exponential distribution is used to generate the precipitation amount. Table 4.1 lists SWAT input variables that are used in the precipitation generator OCCURRENCE OF WET OR DRY DAY With the first-order Markov-chain model, the probability of rain on a given day is conditioned on the wet or dry status of the previous day. A wet day is defined as a day with 0.1 mm of rain or more. The user is required to input the probability of a wet day on day i given a wet day on day i 1, P i (W/W), and the probability of a wet day on day i given a dry day on day i 1, P i (W/D), for each month of the year. From these inputs the remaining transition probabilities can be derived: P i P i ( D W ) P ( W W ) = ( D D) P ( W D) i i = where P i (D/W) is the probability of a dry day on day i given a wet day on day i 1 and P i (D/D) is the probability of a dry day on day i given a dry day on day i 1. To define a day as wet or dry, SWAT generates a random number between 0.0 and 1.0. This random number is compared to the appropriate wet-dry probability, P i (W/W) or P i (W/D). If the random number is equal to or less than the

83 CHAPTER 4: EQUATIONS WEATHER GENERATOR 69 wet-dry probability, the day is defined as wet. If the random number is greater than the wet-dry probability, the day is defined as dry AMOUNT OF PRECIPITATION Numerous probability distribution functions have been used to describe the distribution of rainfall amounts. SWAT provides the user with two options: a skewed distribution and an exponential distribution. The skewed distribution was proposed by Nicks (1974) and is based on a skewed distribution used by Fiering (1967) to generate representative streamflow. The equation used to calculate the amount of precipitation on a wet day is: R day 3 gmon gmon SNDday = µ mon + 2 σ mon gmon where R day is the amount of rainfall on a given day (mm H 2 O), µ mon is the mean daily rainfall (mm H 2 O) for the month, σ mon is the standard deviation of daily rainfall (mm H 2 O) for the month, SND day is the standard normal deviate calculated for the day, and g mon is the skew coefficient for daily precipitation in the month. The standard normal deviate for the day is calculated: SND day ( rnd ) 2 ( rnd ) = cos 2 ln where rnd 1 and rnd 2 are random numbers between 0.0 and 1.0. The exponential distribution is provided as an alternative to the skewed distribution. This distribution requires fewer inputs and is most commonly used in areas where limited data on precipitation events is available. Daily precipitation is calculated with the exponential distribution using the equation: R day mon r ( ln( rnd )) exp = µ where R day is the amount of rainfall on a given day (mm H 2 O), µ mon is the mean daily rainfall (mm H 2 O) for the month, rnd 1 is a random number between 0.0 and 1.0, and rexp is an exponent that should be set between 1.0 and 2.0. As the value of rexp is increased, the number of extreme rainfall events during the year will

84 70 SWAT USER'S MANUAL, VERSION 2000 increase. Testing of this equation at locations across the U.S. have shown that a value of 1.3 gives satisfactory results. Table 4-1: SWAT input variables that pertain to generation of precipitation. Variable name Definition File Name PCPSIM Precipitation input code: 1-measured, 2-generated.cod PR_W(1,mon) P i (W/D): probability of a wet day following a dry day in month.wgn PR_W(2,mon) P i (W/W): probability of a wet day following a wet day in month.wgn IDIST Rainfall distribution code: 0-skewed, 1-exponential.cod REXP rexp: value of exponent (required if IDIST = 1).cod PCPMM(mon) average amount of precipitation falling in month (mm H 2 O).wgn PCPD(mon) average number of days of precipitation in month.wgn (µ mon = PCPMM / PCPD) PCPSTD(mon) σ mon : standard deviation for daily precipitation in month (mm H 2 O).wgn PCPSKW(mon) g mon : skew coefficient for daily precipitation in month.wgn 4.2 SOLAR RADIATION & TEMPERATURE The procedure used to generate daily values for maximum temperature, minimum temperature and solar radiation (Richardson, 1981; Richardson and Wright, 1984) is based on the weakly stationary generating process presented by Matalas (1967) DAILY RESIDUALS Residuals for maximum temperature, minimum temperature and solar radiation are required for calculation of daily values. The residuals must be serially correlated and cross-correlated with the correlations being constant at all locations. The equation used to calculate residuals is: i ( j) Aχ ( j) Bε ( j) χ = i i where χ i (j) is a 3 1 matrix for day i whose elements are residuals of maximum temperature (j = 1), minimum temperature (j = 2) and solar radiation (j = 3), χ i-1 (j) is a 3 1 matrix of the previous day s residuals, ε i is a 3 1 matrix of independent random components, and A and B are 3 3 matrices whose elements are defined such that the new sequences have the desired serial-correlation and cross-correlation coefficients. The A and B matrices are given by A = M M 4.2.2

85 T 1 T B B = M 0 M 1 M 0 M 1 CHAPTER 4: EQUATIONS WEATHER GENERATOR where the superscript 1 denotes the inverse of the matrix and the superscript T denotes the transpose of the matrix. M 0 and M 1 are defined as 1 ρ0 ( 1,2) ρ0 ( 1,3) ( 1,2) 1 ρ0 ( 2,3) ( 1,3) ρ ( 2,3) 1 0 M 0 = ρ ρ0 ( 1,1 ) ρ1( 1,2) ρ1( 1,3) ( 2,1) ρ1( 2,2) ρ1( 2,3) ( 3,1 ) ρ ( 3,2) ( 3,3) 1 ρ1 ρ1 M = 1 ρ ρ1 ρ 0 (j,k) is the correlation coefficient between variables j and k on the same day where j and k may be set to 1 (maximum temperature), 2 (minimum temperature) or 3 (solar radiation) and ρ 1 (j,k) is the correlation coefficient between variable j and k with variable k lagged one day with respect to variable j. Correlation coefficients were determined for 31 locations in the United States using 20 years of temperature and solar radiation data (Richardson, 1982). Using the average values of these coefficients, the M 0 and M 1 matrices become M 0 = M 1 = Using equations and 4.2.3, the A and B matrices become A = B =

86 72 SWAT USER'S MANUAL, VERSION 2000 The A and B matrices defined in equations and are used in conjunction with equation to generate daily sequences of residuals of maximum temperature, minimum temperature and solar radiation GENERATED VALUES The daily generated values are determined by multiplying the residual elements generated with equation by the monthly standard deviation and adding the monthly average value. T mx mon i () σmxmon = µ mx + χ T mn mon i ( ) σmnmon = µ mn + χ H day mon i () σrad mon = µ rad + χ where T mx is the maximum temperature for the day ( C), µmx mon is the average daily maximum temperature for the month ( C), χ i (1) is the residual for maximum temperature on the given day, σmx mon is the standard deviation for daily maximum temperature during the month ( C), T mn is the minimum temperature for the day ( C), µmn mon is the average daily minimum temperature for the month ( C), χ i (2) is the residual for minimum temperature on the given day, σmn mon is the standard deviation for daily minimum temperature during the month ( C), H day is the solar radiation for the day (MJ m -2 ), µrad mon is the average daily solar radiation for the month (MJ m -2 ), χ i (3) is the residual for solar radiation on the given day, and σrad mon is the standard deviation for daily solar radiation during the month (MJ m -2 ). The user is required to input standard deviation for maximum and minimum temperature. For solar radiation the standard deviation is estimated as ¼ of the difference between the extreme and mean value for each month. σrad mon H mx µ rad mon = where σrad mon is the standard deviation for daily solar radiation during the month (MJ m -2 ), H mx is the maximum solar radiation that can reach the earth s surface on

87 CHAPTER 4: EQUATIONS WEATHER GENERATOR 73 a given day (MJ m -2 ), and µrad mon is the average daily solar radiation for the month (MJ m -2 ) ADJUSTMENT FOR CLEAR/OVERCAST CONDITIONS Maximum temperature and solar radiation will be lower on overcast days than on clear days. To incorporate the influence of wet/dry days on generated values of maximum temperature and solar radiation, the average daily maximum temperature, µmx mon, and average daily solar radiation, µrad mon, in equations and are adjusted for wet or dry conditions MAXIMUM TEMPERATURE The continuity equation relates average daily maximum temperature adjusted for wet or dry conditions to the average daily maximum temperature for the month: µ mx days = µ Wmx days + µ Dmx days mon tot mon where µmx mon is the average daily maximum temperature for the month ( C), days tot are the total number of days in the month, µwmx mon is the average daily maximum temperature of the month on wet days ( C), days wet are the number of wet days in the month, µdmx mon is the average daily maximum temperature of the month on dry days ( C), and days dry are the number of dry days in the month. The wet day average maximum temperature is assumed to be less than the dry day average maximum temperature by some fraction of (µmx mon - µmn mon ): mon mon T wet mon ( µ mx mn ) µ Wmx = µ Dmx b µ where µwmx mon is the average daily maximum temperature of the month on wet days ( C), µdmx mon is the average daily maximum temperature of the month on dry days ( C), b T is a scaling factor that controls the degree of deviation in temperature caused by the presence or absence of precipitation, µmx mon is the average daily maximum temperature for the mon mon dry

88 74 SWAT USER'S MANUAL, VERSION 2000 month ( C), and µmn mon is the average daily minimum temperature for the month ( C). The scaling factor, b T, is set to 0.5 in SWAT. To calculate the dry day average maximum temperature, equations and are combined and solved for µdmx mon : days µ = ( µ mx mn ) wet Dmx mon µ mxmon + bt mon µ daystot Incorporating the modified values into equation , SWAT calculates the maximum temperature for a wet day using the equation: T mx mon i () σmxmon = µ Wmx + χ and the maximum temperature for a dry day using the equation: T mx mon i () σmxmon = µ Dmx + χ SOLAR RADIATION The continuity equation relates average daily solar radiation adjusted for wet or dry conditions to the average daily solar radiation for the month: µ rad days = µ Wrad days + µ Drad days mon tot mon where µrad mon is the average daily solar radiation for the month (MJ m -2 ), days tot are the total number of days in the month, µwrad mon is the average daily solar radiation of the month on wet days (MJ m -2 ), days wet are the number of wet days in the month, µdrad mon is the average daily solar radiation of the month on dry days (MJ m -2 ), and days dry are the number of dry days in the month. The wet day average solar radiation is assumed to be less than the dry day average solar radiation by some fraction: µ Wrad = b µ Drad mon R mon where µwrad mon is the average daily solar radiation of the month on wet days (MJ m -2 ), µdrad mon is the average daily solar radiation of the month on dry days (MJ m -2 ), and b R is a scaling factor that controls the degree of wet mon mon dry

89 CHAPTER 4: EQUATIONS WEATHER GENERATOR 75 deviation in solar radiation caused by the presence or absence of precipitation. The scaling factor, b R, is set to 0.5 in SWAT. To calculate the dry day average solar radiation, equations and are combined and solved for µdrad mon : µ rad days mon tot µ Drad mon = br dayswet + daysdry Incorporating the modified values into equation , SWAT calculated the solar radiation on a wet day using the equation: H day mon i () σrad mon = µ Wrad + χ and the solar radiation on a dry day using the equation: H day mon i () σrad mon = µ Drad + χ Table 4-2: SWAT input variables that pertain to generation of temperature and solar radiation. Variable name Definition File Name TMPSIM Temperature input code: 1-measured, 2-generated.cod SLRSIM Solar radiation input code: 1-measured, 2-generated.cod TMPMX(mon) µmx mon : average maximum air temperature for month ( C).wgn TMPSTDMX(mon) σmx mon : standard deviation for maximum air temperature in month ( C).wgn TMPMN(mon) µmn mon : average minimum air temperature for month ( C).wgn TMPSTDMN(mon) σmn mon : standard deviation for minimum air temperature in month ( C).wgn SOLARAV(mon) µrad mon : average daily solar radiation for month (MJ m -2 ).wgn PCPD(mon) days wet : average number of days of precipitation in month.wgn 4.3 RELATIVE HUMIDITY Relative humidity is required by SWAT when the Penman-Monteith equation is used to calculate potential evapotranspiration. Daily average relative humidity values are calculated from a triangular distribution using average monthly relative humidity MEAN MONTHLY RELATIVE HUMIDITY Relative humidity is defined as the ratio of the actual vapor pressure to the saturation vapor pressure at a given temperature: e R hmon = e mon o mon

90 76 SWAT USER'S MANUAL, VERSION 2000 where R hmon is the average relative humidity for the month, e mon is the actual vapor pressure at the mean monthly temperature (kpa), and o e mon is the saturation vapor pressure at the mean monthly temperature (kpa). The saturation vapor pressure, o e mon, is related to the mean monthly air temperature with the equation: e o mon µ tmp = exp µ tmpmon + mon where o e mon is the saturation vapor pressure at the mean monthly temperature (kpa), and µtmp mon is the mean air temperature for the month ( C). The mean air temperature for the month is calculated by averaging the mean maximum monthly temperature, µmx mon, and the mean minimum monthly temperature, µmn mon. The dew point temperature is the temperature at which the actual vapor pressure present in the atmosphere is equal to the saturation vapor pressure. Therefore, by substituting the dew point temperature in place of the average monthly temperature in equation 4.3.2, the actual vapor pressure may be calculated: µ dew mon emon = exp µ dewmon where e mon is the actual vapor pressure at the mean month temperature (kpa), and µdew mon is the average dew point temperature for the month ( C) GENERATED DAILY VALUE The triangular distribution used to generate daily relative humidity values requires four inputs: mean monthly relative humidity, maximum relative humidity value allowed in month, minimum relative humidity value allowed in month, and a random number between 0.0 and 1.0. The maximum relative humidity value, or upper limit of the triangular distribution, is calculated from the mean monthly relative humidity with the equation: ( 1 R ) exp( R 1) RhUmon = Rhmon + hmon hmon 4.3.4

91 CHAPTER 4: EQUATIONS WEATHER GENERATOR 77 where R humon is the largest relative humidity value that can be generated on a given day in the month, and R hmon is the average relative humidity for the month. The minimum relative humidity value, or lower limit of the triangular distribution, is calculated from the mean monthly relative humidity with the equation: R hlmon hmon ( ( R )) = R 1 exp hmon where R hlmon is the smallest relative humidity value that can be generated on a given day in the month, and R hmon is the average relative humidity for the month. The triangular distribution uses one of two sets of equations to generate a Rhmon RhLmon relative humidity value for the day. If rnd 1 then RhUmon RhLmon R h hlmon [ rnd ( R R ) ( R R )] 0. 5 = R Rhmon RhLmon If rnd 1 > then RhUmon RhLmon 1 humon hlmon hmon hlmon ( 1 rnd ) R ( rnd ) 0.5 RhUmon 1 hlmon 1 1 Rh = RhUmon ( RhUmon Rhmon ) R humon Rhmon where R h is the average relative humidity calculated for the day, rnd 1 is a random number generated by the model each day, R hmon is the average relative humidity for the month, R hlmon is the smallest relative humidity value that can be generated on a given day in the month, and R humon is the largest relative humidity value that can be generated on a given day in the month ADJUSTMENT FOR CLEAR/OVERCAST CONDITIONS To incorporate the effect of clear and overcast weather on generated values of relative humidity, monthly average relative humidity values can be adjusted for wet or dry conditions. The continuity equation relates average relative humidity adjusted for wet or dry conditions to the average relative humidity for the month: R hmon days = R days + R days tot hwmon wet hdmon dry

92 78 SWAT USER'S MANUAL, VERSION 2000 where R hmon is the average relative humidity for the month, days tot are the total number of days in the month, R hwmon is the average relative humidity for the month on wet days, days wet are the number of wet days in the month, R hdmon is the average relative humidity of the month on dry days, and days dry are the number of dry days in the month. The wet day average relative humidity is assumed to be greater than the dry day average relative humidity by some fraction: R hwmon hdmon H ( R ) = R + b hdmon where R hwmon is the average relative humidity of the month on wet days, R hdmon is the average relative humidity of the month on dry days, and b H is a scaling factor that controls the degree of deviation in relative humidity caused by the presence or absence of precipitation. The scaling factor, b H, is set to 0.9 in SWAT. To calculate the dry day relative humidity, equations and are combined and solved for R hdmon : dayswet dayswet RhDmon = Rhmon bh 1.0 bh daystot daystot 1 To reflect the impact of wet or dry conditions, SWAT will replace R hmon with R hwmon on wet days or R hdmon on dry days in equations through Table 4-3: SWAT input variables that pertain to generation of relative humidity. Variable name Definition File Name RHSIM Relative humidity input code: 1-measured, 2-generated.cod TMPMN(mon) µmn mon : average minimum air temperature for month ( C).wgn TMPMX(mon) µmx mon : average maximum air temperature for month ( C).wgn DEWPT(mon) µdew mon : average dew point temperature for month ( C).wgn PCPD(mon) days wet : average number of days of precipitation in month.wgn 4.4 MAXIMUM HALF-HOUR RAINFALL Maximum half-hour rainfall is required by SWAT to calculate the peak flow rate for runoff. When daily precipitation data is used by the model, the maximum half-hour rainfall is calculated from a triangular distribution using monthly maximum half-hour rainfall data. The maximum half-hour rainfall is calculated only on days where surface runoff has been generated.

93 CHAPTER 4: EQUATIONS WEATHER GENERATOR MONTHLY MAXIMUM HALF-HOUR RAIN For each month, users provide the maximum half-hour rain observed over the entire period of record. These extreme values are used to calculate representative monthly maximum half-hour rainfall fractions. Prior to calculating the representative maximum half-hour rainfall fraction for each month, the extreme half-hour rainfall values are smoothed by calculating three month average values: R0.5 x( mon 1) + R0.5x( mon) + R0.5x( mon+ 1) R0.5sm( mon) = where R 0.5sm(mon) is the smoothed maximum half-hour rainfall for a given month (mm H 2 O) and R 0.5x is the extreme maximum half-hour rainfall for the specified month (mm H 2 O). Once the smoothed maximum half-hour rainfall is known, the representative half-hour rainfall fraction is calculated using the equation: R0.5sm( mon) α 0.5mon = adj0.5 α 1 exp µ mon ln yrs dayswet where α 0.5mon is the average half-hour rainfall fraction for the month, adj 0.5α is an adjustment factor, R 0.5sm is the smoothed half-hour rainfall amount for the month (mm H 2 O), µ mon is the mean daily rainfall (mm H 2 O) for the month, yrs is the number of years of rainfall data used to obtain values for monthly extreme halfhour rainfalls, and days wet are the number of wet days in the month. The adjustment factor is included to allow users to modify estimations of half-hour rainfall fractions and peak flow rates for runoff GENERATED DAILY VALUE The triangular distribution used to generate the maximum half-hour rainfall fraction requires four inputs: average monthly half-hour rainfall fraction, maximum value for half-hour rainfall fraction allowed in month, minimum value for half-hour rainfall fraction allowed in month, and a random number between 0.0 and 1.0.

94 80 SWAT USER'S MANUAL, VERSION 2000 The maximum half-hour rainfall fraction, or upper limit of the triangular distribution, is calculated from the daily amount of rainfall with the equation: 125 α 0.5U = 1 exp Rday + 5 where α 0.5U is the largest half-hour fraction that can be generated on a given day, and R day is the precipitation on a given day (mm H 2 O). The minimum half-hour fraction, or lower limit of the triangular distribution, α 0.5L, is set at The triangular distribution uses one of two sets of equations to generate a maximum half-hour rainfall fraction for the day. If If rnd 1 α rnd [ ( α α ) ( α )] U 0.5L 0.5mon 0.5L α0.5 > α 1 α0.5 α mon 0.5U α α 0.5L 0.5L then = α L + rnd α mon 0.5U α α 0.5L 0.5L then ( α α ) α ( 1 rnd ) α ( 1 rnd ) 0.5U 1 0.5L 1 α0.5 = α0.5 U 0.5U 0.5mon α0.5 U α0.5mon where α 0.5 is the maximum half-hour rainfall fraction for the day, α 0.5mon is the average maximum half-hour rainfall fraction for the month, rnd 1 is a random number generated by the model each day, α 0.5L is the smallest half-hour rainfall fraction that can be generated, and α 0.5U is the largest half-hour fraction that can be generated. Table 4-4: SWAT input variables that pertain to generation of maximum half-hour rainfall. Variable name Definition 0.5 File Name RAINHHMX(mon) R 0.5x : extreme half-hour rainfall for month (mm H 2 O).wgn APM adj 0.5α : peak rate adjustment factor.bsn PCPMM(mon) average amount of precipitation falling in month (mm H 2 O).wgn PCPD(mon) days wet : average number of days of precipitation in month.wgn (µ mon = PCPMM / PCPD) RAIN_YRS yrs: number of years of data used to obtain values for RAINHHMX.wgn PRECIPITATION R day : amount of rain falling on a given day (mm H 2 O).pcp

95 CHAPTER 4: EQUATIONS WEATHER GENERATOR WIND SPEED Wind speed is required by SWAT when the Penman-Monteith equation is used to calculate potential evapotranspiration. Mean daily wind speed is generated in SWAT using a modified exponential equation: ( ( )) 0. 3 µ 10 m = µ wnd mon ln rnd where µ 10m is the mean wind speed for the day (m s -1 ), µwnd mon is the average wind speed for the month (m s -1 ), and rnd 1 is a random number between 0.0 and 1.0. Table 4-5: SWAT input variables that pertain to generation of wind speed. Variable name Definition File Name WNDSIM Wind speed input code: 1-measured, 2-generated.cod WNDAV(mon) µwnd mon : Average wind speed in month (m/s).wgn 4.6 NOMENCLATURE A 3 3 matrix of elements defined to ensure serial and cross correlation of 1 generated temperature and radiation values A = M 1 M 0 B 3 3 matrix of elements defined to ensure serial and cross correlation of T 1 T generated temperature and radiation values B B = M 0 M 1 M 0 M 1 H day Solar radiation reaching ground on current day of simulation (MJ m -2 d -1 ) H MX Maximum possible solar radiation (MJ m -2 d -1 ) M matrix of correlation coefficients between maximum temperature, minimum temperature and solar radiation on same day M matrix of correlation coefficients between maximum temperature, minimum temperature and solar radiation on consecutive days P i (D/D) Probability of a dry day on day i given a dry day on day i 1 P i (D/W) Probability of a dry day on day i given a wet day on day i 1 P i (W/D) Probability of a wet day on day i given a dry day on day i 1 P i (W/W) Probability of a wet day on day i given a wet day on day i 1 R 0.5sm Smoothed maximum half-hour rainfall for a given month (mm H 2 O) R 0.5x Extreme maximum half-hour rainfall for the specified month (mm H 2 O) R day Amount of rainfall on a given day (mm H 2 O) R h Average relative humidity for the day R hdmon Average relative humidity of the month on dry days

96 82 SWAT USER'S MANUAL, VERSION 2000 R hlmon Smallest relative humidity value that can be generated on a given day in the month R humon Largest relative humidity value that can be generated on a given day in the month R hwmon Average relative humidity for the month on wet days R hmon Average relative humidity for the month SND day Standard normal deviate for the day T mn Minimum air temperature for day ( C) Maximum air temperature for day ( C) T mx adj 0.5α Peak rate adjustment factor b H Scaling factor that controls the degree of deviation in relative humidity caused by the presence or absence of precipitation b R Scaling factor that controls the degree of deviation in solar radiation caused by the presence or absence of precipitation b T Scaling factor that controls the degree of deviation in temperature caused by the presence or absence of precipitation days dry Number of dry days in the month days tot Total number of days in the month days wet Number of wet days in the month e mon Actual vapor pressure at the mean monthly temperature (kpa) o emon Saturation vapor pressure at the mean monthly temperature (kpa) g mon Skew coefficient for daily precipitation in the month rexp Exponent for exponential precipitation distribution rnd 1 Random number between 0.0 and 1.0 rnd 2 Random number between 0.0 and 1.0 yrs Number of years of rainfall data used to obtain values for monthly extreme halfhour rainfalls α 0.5 Maximum half-hour rainfall expressed as a fraction of daily rainfall α 0.5L Smallest half-hour rainfall fraction that can be generated on a given day α 0.5mon Average maximum half-hour rainfall fraction for the month α 0.5U Largest half-hour rainfall fraction that can be generated on a given day ε i 3 1 matrix of independent random components σ mon Standard deviation of daily rainfall (mm H 2 O) for the month σmn mon Standard deviation for daily minimum temperature during the month ( C) σmx mon Standard deviation for daily maximum temperature during the month ( C) σrad mon Standard deviation for daily solar radiation during the month (MJ m -2 ) ρ 0 (j,k) Correlation coefficient between variables j and k on the same day where j and k may be set to 1 (maximum temperature), 2 (minimum temperature) or 3 (solar radiation) ρ 1 (j,k) Correlation coefficient between variable j and k with variable k lagged one day with respect to variable j µ mon Mean daily rainfall (mm H 2 O) for the month µdmx mon Average daily maximum temperature of the month on dry days ( C) µdrad mon Average daily solar radiation of the month on dry days (MJ m -2 )

97 CHAPTER 4: EQUATIONS WEATHER GENERATOR 83 µwmx mon Average daily maximum temperature of the month on wet days ( C) µwrad mon Average daily solar radiation of the month on wet days (MJ m -2 ) µdew mon Average dew point temperature for the month ( C) µmn mon Average daily minimum temperature for the month ( C) µmx mon Average daily maximum temperature for the month ( C) µrad mon Average daily solar radiation for the month (MJ m -2 ) µtmp mon Mean air temperature for the month ( C) µwnd mon Average wind speed for the month (m s -1 ) µ 10m Mean wind speed for the day at height of 10 meters (m s -1 ) χ i (j) 3 1 matrix for day i whose elements are residuals of maximum temperature (j = 1), minimum temperature (j = 2) and solar radiation (j = 3), 4.7 REFERENCES Fiering, M.B Streamflow synthesis. Harvard University Press, Cambridge. Matalas, N.C Mathematical assessment of synthetic hydrology. Water Resources Res. 3(4): Nicks, A.D Stochastic generation of the occurrence, pattern, and location of maximum amount of daily rainfall. p In Proc. Symp. Statistical Hydrology, Aug.-Sept. 1971, Tuscon, AZ. U.S. Department of Agriculture, Misc. Publ. No Richardson, C.W Dependence structure of daily temperature and solar radiation. Trans. ASAE 25(3): Richardson, C.W Stochastic simulation of daily precipitation, temperature, and solar radiation. Water Resources Res. 17(1): Richardson, C.W. and D.A. Wright WGEN: a model for generating daily weather variables. U.S. Department of Agriculture, Agricultural Research Service, ARS-8. Sharpley, A.N. and J.R. Williams, eds EPIC-Erosion Productivity Impact Calculator, 1. model documentation. U.S. Department of Agriculture, Agricultural Research Service, Tech. Bull Williams, J.R Chapter 25. The EPIC Model. p In Computer Models of Watershed Hydrology. Water Resources Publications. Highlands Ranch, CO.

98 84 SWAT USER'S MANUAL, VERSION 2000

99 CHAPTER 5 EQUATIONS: CLIMATE CUSTOMIZATION SWAT is capable of simulating orographic impacts on temperature and precipitation for watersheds in mountainous regions. The model will also modify climate inputs for simulations that are looking at the impact of climatic change in a given watershed. 85

100 86 SWAT USER'S MANUAL, VERSION ELEVATION BANDS Orographic precipitation is a significant phenomenon in certain areas of the world. To account for orographic effects on both precipitation and temperature, SWAT allows up to 10 elevation bands to be defined in each subbasin. Precipitation and maximum and minimum temperatures are calculated for each band as a function of the respective lapse rate and the difference between the gage elevation and the average elevation specified for the band. For precipitation, R band ( ELband ELgage ) 1000 plaps = R + when R > day where R band is the precipitation falling in the elevation band (mm H 2 O), R day is the precipitation recorded at the gage or generated from gage data (mm H 2 O), EL band is the mean elevation in the elevation band (m), EL gage is the elevation at the recording gage (m), plaps is the precipitation lapse rate (mm H 2 O/km), and 1000 is a factor needed to convert meters to kilometers. For temperature, T mx, band tlaps ( ELband ELgage ) 1000 = T mx day T T mn, band av, band tlaps ( ELband ELgage ) 1000 = T mn tlaps ( ELband ELgage ) 1000 = T av where T mx,band is the maximum daily temperature in the elevation band ( C), T mn,band is the minimum daily temperature in the elevation band ( C), T av, band is the mean daily temperature in the elevation band ( C), T mx is the maximum daily temperature recorded at the gage or generated from gage data ( C), T mn is the minimum daily temperature recorded at the gage or generated from gage data ( C), T av is the mean daily temperature recorded at the gage or generated from gage data ( C), EL band is the mean elevation in the elevation band (m), EL gage is the elevation at the recording gage (m), tlaps is the temperature lapse rate ( C/km), and 1000 is a factor needed to convert meters to kilometers.

101 CHAPTER 5: EQUATIONS CLIMATE CUSTOMIZATION 87 Once the precipitation and temperature values have been calculated for each elevation band in the subbasin, new average subbasin precipitation and temperature values are calculated: R day = b R band bnd = 1 fr bnd T T mx mn = = b T bnd = 1 b T bnd = 1, fr mx band bnd, fr mn band bnd T av = b T bnd = 1 av, band fr bnd where R day is the daily average precipitation adjusted for orographic effects (mm H 2 O), T mx is the daily maximum temperature adjusted for orographic effects ( C), T mn is the daily minimum temperature adjusted for orographic effects ( C), T av is the daily mean temperature adjusted for orographic effects ( C), R band is the precipitation falling in elevation band bnd (mm H 2 O), T mx,band is the maximum daily temperature in elevation band bnd ( C), T mn,band is the minimum daily temperature in elevation band bnd ( C), T av, band is the mean daily temperature in elevation band bnd ( C), fr bnd is the fraction of subbasin area within the elevation band, and b is the total number of elevation bands in the subbasin. The only processes modeled separately for each individual elevation band are the accumulation, sublimation and melting of snow. As with the initial precipitation and temperature data, after amounts of sublimation and snow melt are determined for each elevation band, subbasin average values are calculated. These average values are the values that are used in the remainder of the simulation and reported in the output files.

102 88 SWAT USER'S MANUAL, VERSION 2000 Table 5-1: SWAT input variables that pertain to orographic effects. Variable Name Definition Input File ELEVB EL band : Elevation at center of the elevation band (m).sub ELEVB_FR fr bnd : Fraction of subbasin area within the elevation band..sub WELEV EL gage : Elevation of recording gage whose data is used to calculate.wgn values in.wgn file (m) ELEVATION EL gage : Elevation of precipitation recording gage (m).pcp ELEVATION EL gage : Elevation of temperature recording gage (m).tmp PLAPS plaps: Precipitation lapse rate (mm H 2 O/km).sub TLAPS tlaps: Temperature lapse rate ( C/km).sub PRECIPITATION R day : Daily precipitation (mm H 2 O).pcp MAX TEMP T mx : Daily maximum temperature ( C).tmp MIN TEMP T mn : Daily minimum temperature ( C).tmp 5.2 CLIMATE CHANGE The impact of global climate change on water supply is a major area of research. Climate change can be simulated with SWAT by manipulating the climatic input that is read into the model (precipitation, temperature, solar radiation, relative humidity, wind speed, potential evapotranspiration and weather generator parameters). A less time-consuming method is to set adjustment factors for the various climatic inputs. SWAT will allow users to adjust precipitation, temperature, solar radiation, relative humidity, and carbon dioxide levels in each subbasin. The alteration of precipitation, temperature, solar radiation and relative humidity are straightforward: adjpcp Rday = Rday where R day is the precipitation falling in the subbasin on a given day (mm H 2 O), and adj pcp is the % change in rainfall. T = T + adj mx mx tmp where T mx is the daily maximum temperature ( C), and adj tmp is the change in temperature ( C). T = T + adj mn mn tmp

103 CHAPTER 5: EQUATIONS CLIMATE CUSTOMIZATION 89 where T mn is the daily minimum temperature ( C), and adj tmp is the change in temperature ( C). where T av T av + = adj tmp T av is the daily mean temperature ( C), and adj tmp is the change in temperature ( C). H = H + adj day day rad where H day is the daily solar radiation reaching the earth s surface (MJ m -2 ), and adj rad is the change in radiation (MJ m -2 d -1 ). R = R + adj h h hmd where R h is the relative humidity for the day expressed as a fraction, and adj hmd is the change in relative humidity expressed as a fraction. SWAT allows the adjustment terms to vary from month to month so that the user is able to simulate seasonal changes in climatic conditions. Changes in carbon dioxide levels impact plant growth. As carbon dioxide levels increase, plant productivity increases and plant water requirements go down. The equations used to account for the impact of carbon dioxide levels on plant water requirements are reviewed in Chapters 7 and 18. When carbon dioxide climate change effects are being simulated, the Penman-Monteith equation must be used to calculate potential evapotranspiration. This method has been modified to account for CO 2 impacts on potential evapotranspiration levels. Table 5-2: SWAT input variables that pertain to climate change. Variable Name Definition Input File RFINC(mon) adj pcp : % change in rainfall for month.sub TMPINC(mon) adj tmp : increase or decrease in temperature for month ( C).sub RADINC(mon) adj rad : increase or decrease in solar radiation reaching earth s.sub surface for month (MJ m -2 ) HUMINC(mon) adj hmd : increase or decrease in relative humidity for month.sub CO2 CO 2 : carbon dioxide level in subbasin (ppmv).sub IPET Potential evapotranspiration method.cod

104 90 SWAT USER'S MANUAL, VERSION NOMENCLATURE CO 2 Concentration of carbon dioxide in the atmosphere (ppmv) EL band Mean elevation in the elevation band (m) EL gage Elevation at the precipitation, temperature, or weather generator data recording gage (m) H day Solar radiation reaching ground on current day of simulation (MJ m -2 d -1 ) R band Precipitation falling in the elevation band (mm H 2 O) R day Amount of rainfall on a given day (mm H 2 O) R h Average relative humidity for the day T mn Minimum air temperature for day ( C) T mn,band Minimum daily temperature in the elevation band ( C) T mx Maximum air temperature for day ( C) T mx,band Maximum daily temperature in the elevation band ( C) T av Mean air temperature for day ( C) T av, band Mean daily temperature in the elevation band ( C) adj hmd Change in relative humidity expressed as a fraction adj pcp % change in rainfall adj rad Change in radiation (MJ m -2 d -1 ) adj tmp Change in temperature ( C) fr bnd Fraction of subbasin area within the elevation band plaps Precipitation lapse rate (mm H 2 O/km) tlaps Temperature lapse rate ( C/km)

105 HYDROLOGY The land phase of the hydrologic cycle is based on the water balance equation: SW t = SW + ( R t i= 1 day Q surf E a P QR ) i where SW t is the final soil water content (mm H 2 O), SW is the initial soil water content (mm H 2 O), t is the time (days), R day is the amount of precipitation on day i (mm H 2 O), Q surf is the amount of surface runoff on day i (mm H 2 O), E a is the amount of evapotranspiration on day i (mm H 2 O), P i is the amount of percolation on day i (mm H 2 O), and QR i is the amount of return flow on day i (mm H 2 O). i

106 CHAPTER 6 EQUATIONS: SURFACE RUNOFF Surface runoff occurs whenever the rate of water application to the ground surface exceeds the rate of infiltration. When water is initially applied to a dry soil, the application rate and infiltration rates may be similar. However, the infiltration rate will decrease as the soil becomes wetter. When the application rate is higher than the infiltration rate, surface depressions begin to fill. If the application rate continues to be higher than the infiltration rate once all surface depressions have filled, surface runoff will commence. 93

107 94 SWAT USER'S MANUAL, VERSION 2000 SWAT provides two methods for estimating surface runoff: the SCS curve number procedure (SCS, 1972) and the Green & Ampt infiltration method (1911). 6.1 RUNOFF VOLUME: SCS CURVE NUMBER PROCEDURE The SCS runoff equation is an empirical model that came into common use in the 1950s. It was the product of more than 20 years of studies involving rainfall-runoff relationships from small rural watersheds across the U.S. The model was developed to provide a consistent basis for estimating the amounts of runoff under varying land use and soil types (Rallison and Miller, 1981). The SCS curve number equation is (SCS, 1972): Q surf = 2 ( Rday I a ) ( R I + S) day a where Q surf is the accumulated runoff or rainfall excess (mm H 2 O), R day is the rainfall depth for the day (mm H 2 O), I a is the initial abstractions which includes surface storage, interception and infiltration prior to runoff (mm H 2 O), and S is the retention parameter (mm H 2 O). The retention parameter varies spatially due to changes in soils, land use, management and slope and temporally due to changes in soil water content. The retention parameter is defined as: 1000 S = CN where CN is the curve number for the day. The initial abstractions, I a, is commonly approximated as 0.2S and equation becomes Q surf 2 ( Rday 0.2S) ( R + 0.8S) = day Runoff will only occur when R day > I a. A graphical solution of equation for different curve number values is presented in Figure 6-1.

108 CHAPTER 6: EQUATIONS SURFACE RUNOFF 95 Figure 6-1: Relationship of runoff to rainfall in SCS curve number method SCS CURVE NUMBER The SCS curve number is a function of the soil s permeability, land use and antecedent soil water conditions. Typical curve numbers for moisture condition II are listed in tables 6-1, 6-2 and 6-3 for various land covers and soil types (SCS Engineering Division, 1986). These values are appropriate for a 5% slope. Table 6-1: Runoff curve numbers for cultivated agricultural lands Cover Hydrologic Soil Group Land Use Treatment or practice Hydrologic condition A B C D Fallow Bare soil Crop residue cover Poor Good Row crops Straight row Poor Good Straight row w/ residue Poor Good Contoured Poor Good Contoured w/ residue Poor Good Contoured & terraced Poor Good Contoured & terraced w/ residue Poor Good Small grains Straight row Poor Good Straight row w/ residue Poor Crop residue cover applies only if residue is on at least 5% of the surface throughout the year.

109 96 SWAT USER'S MANUAL, VERSION 2000 Table 6-1, cont.: Runoff curve numbers for cultivated agricultural lands Cover Land Use Close-seeded or broadcast legumes or rotation Treatment or practice Hydrologic Soil Group Hydrologic condition A B C D Good Contoured Poor Good Contoured w/ residue Poor Good Contoured & terraced Poor Good Contoured & terraced w/ residue Poor Good Straight row Poor Good Contoured Poor Good Contoured & terraced Poor Good Table 6-2: Runoff curve numbers for other agricultural lands Cover Hydrologic Soil Group Cover Type Hydrologic condition A B C D Pasture, grassland, or range continuous forage for grazing 1 Poor Fair Good Meadow continuous grass, protected from grazing and generally mowed for hay Brush brush-weed-grass mixture with brush the major element 2 Poor Fair Good Woods grass combination (orchard or tree farm) Poor Fair Good Woods 3 Poor Fair Good Farmsteads buildings, lanes, driveways, and surrounding lots Table 6-3: Runoff curve numbers for urban areas Cover Hydrologic Soil Group Cover Type Hydrologic condition Average % impervious area A B C D Fully developed urban areas Open spaces (lawns, parks, golf courses, cemeteries, etc.) Poor Fair Good Impervious areas: Paved parking lots, roofs, driveways, etc. (excl. right-of-way) Paved streets and roads; open ditches (incl. right-of-way) Gravel streets and roads (including right-of-way) Dirt streets and roads (including right-of way) Poor: < 50% ground cover or heavily grazed with no mulch; Fair: 50 to 75% ground cover and not heavily grazed; Good: > 75% ground cover and lightly or only occasionally grazed 2 Poor: < 50% ground cover; Fair: 50 to 75% ground cover; Good: > 75% ground cover 3 Poor: Forest litter, small trees, and brush are destroyed by heavy grazing or regular burning; Fair: Woods are grazed but not burned, and some forest litter covers the soil; Good: Woods are protected from grazing, and litter and brush adequately cover the soil. SWAT will automatically adjust curve numbers for impervious areas when IURBAN and URBLU are defined in the.hru file. Curve numbers from Table 6-3 should not be used in this instance. Poor: grass cover < 50%; Fair: grass cover 50 to 75%; Good: grass cover > 75%

110 CHAPTER 6: EQUATIONS SURFACE RUNOFF 97 Table 6-3, continued: Runoff curve number for urban areas Cover Hydrologic Soil Group Cover Type Hydrologic condition Average % impervious area A B C D Urban districts: Commercial and business 85% Industrial 72% Residential Districts by average lot size: 1/8 acre (0.05 ha) or less (town houses) 65% /4 acre (0.10 ha) 38% /3 acre (0.13 ha) 30% /2 acre (0.20 ha) 25% acre (0.40 ha) 20% acres (0.81 ha) 12% Developing urban areas: Newly graded areas (pervious areas only, no vegetation) SOIL HYDROLOGIC GROUPS The U.S. Natural Resource Conservation Service (NRCS) classifies soils into four hydrologic groups based on infiltration characteristics of the soils. NRCS Soil Survey Staff (1996) defines a hydrologic group as a group of soils having similar runoff potential under similar storm and cover conditions. Soil properties that influence runoff potential are those that impact the minimum rate of infiltration for a bare soil after prolonged wetting and when not frozen. These properties are depth to seasonally high water table, saturated hydraulic conductivity, and depth to a very slowly permeable layer. Soil may be placed in one of four groups, A, B, C, and D, or three dual classes, A/D, B/D, and C/D. Definitions of the classes are: A: (Low runoff potential). The soils have a high infiltration rate even when thoroughly wetted. They chiefly consist of deep, well drained to excessively drained sands or gravels. They have a high rate of water transmission. B: The soils have a moderate infiltration rate when thoroughly wetted. They chiefly are moderately deep to deep, moderately well-drained to well-drained soils that have moderately fine to moderately coarse textures. They have a moderate rate of water transmission. C: The soils have a slow infiltration rate when thoroughly wetted. They chiefly have a layer that impedes downward movement of water or have moderately fine to fine texture. They have a slow rate of water transmission.

111 98 SWAT USER'S MANUAL, VERSION 2000 D. (High runoff potential). The soils have a very slow infiltration rate when thoroughly wetted. They chiefly consist of clay soils that have a high swelling potential, soils that have a permanent water table, soils that have a claypan or clay layer at or near the surface, and shallow soils over nearly impervious material. They have a very slow rate of water transmission. Dual hydrologic groups are given for certain wet soils that can be adequately drained. The first letter applies to the drained condition, the second to the undrained. Only soils that are rated D in their natural condition are assigned to dual classes. A summary of U.S. soils and their hydrologic group is given in Appendix D ANTECEDENT SOIL MOISTURE CONDITION SCS defines three antecedent moisture conditions: I dry (wilting point), II average moisture, and III wet (field capacity). The moisture condition I curve number is the lowest value the daily curve number can assume in dry conditions. The curve numbers for moisture conditions I and III are calculated with the equations: CN CN ( 100 CN 2 ) ( 100 CN + exp[ ( 100 CN )]) = CN [ ( CN )] 3 CN 2 exp 100 = where CN 1 is the moisture condition I curve number, CN 2 is the moisture condition II curve number, and CN 3 is the moisture condition III curve number. The retention parameter varies with soil profile water content according to the following equation: SW S = Smax 1 [ SW + ( w w SW )] exp 1 2 where S is the retention parameter for a given moisture content (mm), S max is the maximum value the retention parameter can achieve on any given day (mm), SW is the soil water content of the entire profile excluding the amount of water held in the profile at wilting point (mm H 2 O), and w 1 and 2

112 CHAPTER 6: EQUATIONS SURFACE RUNOFF 99 w 2 are shape coefficients. The maximum retention parameter value, S max, is calculated by solving equation using CN 1. The shape coefficients are determined by solving equation assuming that 1) the retention parameter for moisture condition I curve number corresponds to wilting point soil profile water content, 2) the retention parameter for moisture condition III curve number corresponds to field capacity soil profile water content, and 3) the soil has a curve number of 99 (S = 2.54) when completely saturated. w w FC ln FC + w FC S3 Smax 1 = 2 2 FC ln 1 S3 S = SAT FC ln S 1 1 max max ( SAT FC) SAT where w 1 is the first shape coefficient, w 2 is the second shape coefficient, FC is the amount of water in the soil profile at field capacity (mm H 2 O), S 3 is the retention parameter for the moisture condition III curve number, S max is the retention parameter for the moisture condition I curve number, SAT is the amount of water in the soil profile when completely saturated (mm H 2 O), and 2.54 is the retention parameter value for a curve number of 99. When the top layer of the soil is frozen, the retention parameter is modified using the following equation: S frz [ 1 exp( 0. S) ] = Smax where S frz is the retention parameter adjusted for frozen conditions (mm), S max is the maximum value the retention parameter can achieve on any given day (mm), and S is the retention parameter for a given moisture content calculated with equation (mm).

113 100 SWAT USER'S MANUAL, VERSION 2000 The daily curve number value adjusted for moisture content is calculated by rearranging equation and inserting the retention parameter calculated for that moisture content: CN = ( S + 254) where CN is the curve number on a given day and S is the retention parameter calculated for the moisture content of the soil on that day SLOPE ADJUSTMENTS The moisture condition II curve numbers provided in the tables are assumed to be appropriate for 5% slopes. Williams (1995) developed an equation to adjust the curve number to a different slope: ( CN CN ) [ 1 2 exp( 13. slp) ] CN CN 2 s = where CN 2s is the moisture condition II curve number adjusted for slope, CN 3 is the moisture condition III curve number for the default 5% slope, CN 2 is the moisture condition II curve number for the default 5% slope, and slp is the average percent slope of the subbasin. SWAT does not adjust curve numbers for slope. If the user wishes to adjust the curve numbers for slope effects, the adjustment must be done prior to entering the curve numbers in the management input file. Table 6-1: SWAT input variables that pertain to surface runoff calculated with the SCS curve number method. Input Variable Name Definition File IEVENT Rainfall, runoff, routing option..cod PRECIPITATION R day : Daily precipitation (mm H 2 O).pcp CN2 CN 2 : Moisture condition II curve number.mgt CNOP CN 2 : Moisture condition II curve number.mgt

114 CHAPTER 6: EQUATIONS SURFACE RUNOFF RUNOFF VOLUME: GREEN & AMPT INFILTRATION METHOD The Green & Ampt equation was developed to predict infiltration assuming excess water at the surface at all times (Green & Ampt, 1911). The equation assumes that the soil profile is homogenous and antecedent moisture is uniformly distributed in the profile. As water infiltrates into the soil, the model assumes the soil above the wetting front is completely saturated and there is a sharp break in moisture content at the wetting front. Figure 6-2 graphically illustrates the difference between the moisture distribution with depth modeled by the Green & Ampt equation and what occurs in reality. Figure 6-2: Comparison of moisture content distribution modeled by Green & Ampt and a typical observed distribution. Mein and Larson (1973) developed a methodology for determining ponding time with infiltration using the Green & Ampt equation. The Green- Ampt Mein-Larson excess rainfall method was incorporated into SWAT to provide an alternative option for determining surface runoff. This method requires sub-daily precipitation data supplied by the user. The Green-Ampt Mein-Larson infiltration rate is defined as: f inf () t = K e Ψwf θ v () Finf t

115 102 SWAT USER'S MANUAL, VERSION 2000 where f inf is the infiltration rate at time t (mm/hr), K e is the effective hydraulic conductivity (mm/hr), Ψ wf is the wetting front matric potential (mm), θ v is the change in volumetric moisture content across the wetting front (mm/mm) and F inf is the cumulative infiltration at time t (mm H 2 O). When the rainfall intensity is less than the infiltration rate, all the rainfall will infiltrate during the time period and the cumulative infiltration for that time period is calculated: F inf () t Finf ( t ) + R t = where and F inf (t) is the cumulative infiltration for a given time step (mm H 2 O), F inf (t-1) is the cumulative infiltration for the previous time step (mm H 2 O), and R t is the amount of rain falling during the time step (mm H 2 O). The infiltration rate defined by equation is a function of the infiltrated volume, which in turn is a function of the infiltration rates in previous time steps. To avoid numerical errors over long time steps, f inf is replaced by df inf dt in equation and integrated to obtain () t + Ψwf θ v ( ) t 1 + Ψwf θ v Finf Finf () t = Finf ( t 1) + Ke t + Ψwf θ v ln Finf Equation must be solved iteratively for F inf (t), the cumulative infiltration at the end of the time step. A successive substitution technique is used. The Green-Ampt effective hydraulic conductivity parameter, K e, is approximately equivalent to one-half the saturated hydraulic conductivity of the soil, K sat (Bouwer, 1969). Nearing et al. (1996) developed an equation to calculate the effective hydraulic conductivity as a function of saturated hydraulic conductivity and curve number. This equation incorporates land cover impacts into the calculated effective hydraulic conductivity. The equation for effective hydraulic conductivity is: K sat Ke = exp( CN ) where K e is the effective hydraulic conductivity (mm/hr), K sat is the saturated hydraulic conductivity (mm/hr), and CN is the curve number.

116 CHAPTER 6: EQUATIONS SURFACE RUNOFF 103 Wetting front matric potential, Ψ wf, is calculated as a function of porosity, percent sand and percent clay (Rawls and Brakensiek, 1985): 2 2 Ψwf = 10 exp[ φsoil mc φsoil ms mc ms φsoil ms φsoil m 2 c 2 s φ 2 soil soil ] m 2 s m c m m φ where φ soil is the porosity of the soil (mm/mm), m c is the percent clay content, and m s is the percent sand content. For each time step, SWAT calculates the amount of water entering the soil. The water that does not infiltrate into the soil becomes surface runoff. 2 2 c 2 φ + soil Table 6-2: SWAT input variables that pertain to Green & Ampt infiltration calculations. Variable Name Definition Input File IEVENT Rainfall, runoff, routing option..cod IDT Length of time step (min): t=idt/60.cod PRECIPITATION R t : Precipitation during time step (mm H 2 O).pcp SOL_K K sat : Saturated hydraulic conductivity of first layer (mm/hr).sol CN2 CN: Moisture condition II curve number.mgt CNOP CN: Moisture condition II curve number.mgt SOL_BD ρ b : Moist bulk density (Mg/m 3 ): φ soil =1 - ρ b / 2.65.sol CLAY m c : % clay content.sol SAND m s : % sand content.sol 6.3 PEAK RUNOFF RATE The peak runoff rate is the maximum runoff flow rate that occurs with a given rainfall event. The peak runoff rate is an indicator of the erosive power of a storm and is used to predict sediment loss. SWAT calculates the peak runoff rate with a modified rational method. The rational method is widely used in the design of ditches, channels and storm water control systems. The rational method is based on the assumption that if a rainfall of intensity i begins at time t = 0 and continues indefinitely, the rate of runoff will increase until the time of concentration, t = t conc, when the entire subbasin area is contributing to flow at the outlet. The rational formula is:

117 104 SWAT USER'S MANUAL, VERSION 2000 q peak C i Area = where q peak is the peak runoff rate (m 3 s -1 ), C is the runoff coefficient, i is the rainfall intensity (mm/hr), Area is the subbasin area (km 2 ) and 3.6 is a unit conversion factor TIME OF CONCENTRATION The time of concentration is the amount of time from the beginning of a rainfall event until the entire subbasin area is contributing to flow at the outlet. In other words, the time of concentration is the time for a drop of water to flow from the remotest point in the subbasin to the subbasin outlet. The time of concentration is calculated by summing the overland flow time (the time it takes for flow from the remotest point in the subbasin to reach the channel) and the channel flow time (the time it takes for flow in the upstream channels to reach the outlet): t = t + t conc ov ch where t conc is the time of concentration for a subbasin (hr), t ov is the time of concentration for overland flow (hr), and t ch is the time of concentration for channel flow (hr) OVERLAND FLOW TIME OF CONCENTRATION The overland flow time of concentration, t ov, can be computed using the equation L slp ov = vov t where L slp is the subbasin slope length (m), v ov is the overland flow velocity (m s -1 ) and 3600 is a unit conversion factor. The overland flow velocity can be estimated from Manning s equation by considering a strip 1 meter wide down the sloping surface: v ov 0.4 ov q slp = n

118 CHAPTER 6: EQUATIONS SURFACE RUNOFF 105 where q ov is the average overland flow rate (m 3 s -1 ), slp is the average slope in the subbasin (m m -1 ), and n is Manning s roughness coefficient for the subbasin. Assuming an average flow rate of 6.35 mm/hr and converting units v ov 0.4 slp L slp = n Substituting equation into equation gives t ov 0.6 slp 0.6 L n = slp CHANNEL FLOW TIME OF CONCENTRATION The channel flow time of concentration, t ch, can be computed using the equation: t ch L = 6 c vc where L c is the average flow channel length for the subbasin (km), v c is the average channel velocity (m s -1 ), and 3.6 is a unit conversion factor. The average channel flow length can be estimated using the equation L = L c L cen where L is the channel length from the most distant point to the subbasin outlet (km), and L cen is the distance along the channel to the subbasin centroid (km). Assuming L cen = 0. 5 L, the average channel flow length is L c = L The average velocity can be estimated from Manning s equation assuming a trapezoidal channel with 2:1 side slopes and a 10:1 bottom width-depth ratio. v c 0.25 ch ch q slp = n where v c is the average channel velocity (m s -1 ), q ch is the average channel flow rate (m 3 s -1 ), slp ch is the channel slope (m m -1 ), and n is Manning s

119 106 SWAT USER'S MANUAL, VERSION 2000 roughness coefficient for the channel. To express the average channel flow rate in units of mm/hr, the following expression is used * qch Area qch = * where q ch is the average channel flow rate (mm hr -1 ), Area is the subbasin area (km 2 ), and 3.6 is a unit conversion factor. The average channel flow rate is related to the unit source area flow rate (unit source area = 1 ha) where 0. 5 ( 100 ) * * q ch = q0 Area * q 0 is the unit source area flow rate (mm hr -1 ), Area is the subbasin area (km 2 ), and 100 is a unit conversion factor. Assuming the unit source area flow rate is 6.35 mm/hr and substituting equations and into gives ch Area slp vc = n Substituting equations and into gives t ch L n = Area slp ch where t ch is the time of concentration for channel flow (hr), L is the channel length from the most distant point to the subbasin outlet (km), n is Manning s roughness coefficient for the channel, Area is the subbasin area (km 2 ), and slp ch is the channel slope (m m -1 ). Although some of the assumptions used in developing equations and may appear liberal, the time of concentration values obtained generally give satisfactory results for homogeneous subbasins. Since equations and are based on hydraulic considerations, they are more reliable than purely empirical equations RUNOFF COEFFICIENT The runoff coefficient is the ratio of the inflow rate, i Area, to the peak discharge rate, q peak. The coefficient will vary from storm to storm and is calculated with the equation:

120 Q day CHAPTER 6: EQUATIONS SURFACE RUNOFF 107 surf C = R where Q surf is the surface runoff (mm H 2 O) and R day is the rainfall for the day (mm H 2 O) RAINFALL INTENSITY The rainfall intensity is the average rainfall rate during the time of concentration. Based on this definition, it can be calculated with the equation: R t tc i = conc where i is the rainfall intensity (mm/hr), R tc is the amount of rain falling during the time of concentration (mm H 2 O), and t conc is the time of concentration for the subbasin (hr). An analysis of rainfall data collected by Hershfield (1961) for different durations and frequencies showed that the amount of rain falling during the time of concentration was proportional to the amount of rain falling during the 24-hr period. R tc = α R tc day where R tc is the amount of rain falling during the time of concentration (mm H 2 O), α tc is the fraction of daily rainfall that occurs during the time of concentration, and R day is the amount of rain falling during the day. For short duration storms, all or most of the rain will fall during the time of concentration, causing α tc to approach its upper limit of 1.0. The minimum value of α tc would be seen in storms of uniform intensity (i 24 = i). This minimum value can be defined by substituting the products of time and rainfall intensity into equation Rtc i tconc tconc αtc,min = = = R i day Thus, α tc falls in the range t conc /24 α tc

121 108 SWAT USER'S MANUAL, VERSION 2000 SWAT estimates the fraction of rain falling in the time of concentration as a function of the fraction of daily rain falling in the half-hour of highest intensity rainfall. α [ 2 ln( 1 )] tc = 1 exp tconc α where α 0.5 is the fraction of daily rain falling in the half-hour highest intensity rainfall, and t conc is the time of concentration for the subbasin (hr). The determination of a value for α 0.5 is discussed in Chapters 3 and MODIFIED RATIONAL FORMULA The modified rational formula used to estimate peak flow rate is obtained by substituting equations , , and into equation q peak αtc = Q surf 3.6 t Area conc where q peak is the peak runoff rate (m 3 s -1 ), α tc is the fraction of daily rainfall that occurs during the time of concentration, Q surf is the surface runoff (mm H 2 O), Area is the subbasin area (km 2 ), t conc is the time of concentration for the subbasin (hr) and 3.6 is a unit conversion factor. Table 6-3: SWAT input variables that pertain to peak rate calculations. Variable Name Definition Input File DA_KM Area of the watershed (km 2 ).bsn HRU_FR Fraction of total watershed area contained in HRU.hru SLSUBBSN L slp : Average slope length (m).hru SLOPE slp: Average slope steepness (m/m).hru OV_N n: Manning s n value for overland flow.hru CH_L(1) L: Longest tributary channel length in subbasin (km).sub CH_S(1) slp ch : Average slope of tributary channels (m/m).sub CH_N(1) n: Manning s n value for tributary channels.sub 6.4 TRANSMISSION LOSSES Many semiarid and arid watersheds have ephemeral channels that abstract large quantities of streamflow (Lane, 1982). The abstractions, or transmission losses, reduce runoff volume as the flood wave travels downstream. Chapter 19 of the SCS Hydrology Handbook (Lane, 1983) describes a procedure for estimating transmission losses for ephemeral streams which has been incorporated into

122 CHAPTER 6: EQUATIONS SURFACE RUNOFF 109 SWAT. This method was developed to estimate transmission losses in the absence of observed inflow-outflow data and assumes no lateral inflow or out-of-bank flow contributions to runoff. The prediction equation for runoff volume after transmission losses is 0 volqsurf, i volthr volqsurf, f = ax + bx volqsurf, i volqsurf, i > volthr where vol Qsurf,f is the volume of runoff after transmission losses (m 3 ), a x is the regression intercept for a channel of length L and width W (m 3 ), b x is the regression slope for a channel of length L and width W, vol Qsurf,i is the volume of runoff prior to transmission losses (m 3 ), and vol thr is the threshold volume for a channel of length L and width W (m 3 ). The threshold volume is vol a x thr = bx The corresponding equation for peak runoff rate is [ ax ( bx ) volqsurf, i ] + bx q peak i 1 = q peak, f 1, ( 3600 durflw ) where q peak,f is the peak rate after transmission losses (m 3 /s), dur flw is the duration of flow (hr), a x is the regression intercept for a channel of length L and width W (m 3 ), b x is the regression slope for a channel of length L and width W, vol Qsurf,i is the volume of runoff prior to transmission losses (m 3 ), q peak,i is the peak rate before accounting for transmission losses (m 3 /s). The duration of flow is calculated with the equation: dur flw Qsurf Area = 3.6 q peak where dur flw is the duration of runoff flow (hr), Q surf is the surface runoff (mm H 2 O), Area is the area of the subbasin (km 2 ), q peak is the peak runoff rate (m 3 /s), and 3.6 is a conversion factor. In order to calculate the regression parameters for channels of differing lengths and widths, the parameters of a unit channel are needed. A unit channel is defined as a channel of length L = 1 km and width W = 1 m. The unit channel parameters are calculated with the equations:

123 110 SWAT USER'S MANUAL, VERSION 2000 k a b r r Kch dur = 2.22 ln volqsurf, i = K ch dur [ 0. ] = exp 4905 r k r flw where k r is the decay factor (m -1 km -1 ), a r is the unit channel regression intercept (m 3 ), b r is the unit channel regression slope, K ch is the effective hydraulic conductivity of the channel alluvium (mm/hr), dur flw is the duration of runoff flow (hr), and vol Qsurf,i is the initial volume of runoff (m 3 ). The regression parameters are b x = exp [ k L W ] r flw a x a = 1 r ( ) ( b ) x 1 b r where a x is the regression intercept for a channel of length L and width W (m 3 ), b x is the regression slope for a channel of length L and width W, k r is the decay factor (m -1 km -1 ), L is the channel length from the most distant point to the subbasin outlet (km), W is the average width of flow, i.e. channel width (m) a r is the unit channel regression intercept (m 3 ), and b r is the unit channel regression slope. Transmission losses from surface runoff are assumed to percolate into the shallow aquifer. Table 6-4: SWAT input variables that pertain to transmission loss calculations. Variable Name Definition Input File DA_KM Area of the watershed (km 2 ).bsn HRU_FR Fraction of total watershed area contained in HRU.hru CH_K(1) K ch : effective hydraulic conductivity (mm/hr).sub CH_W(1) W: average width of tributary channel (m).sub CH_L(1) L: Longest tributary channel length in subbasin (km).sub

124 CHAPTER 6: EQUATIONS SURFACE RUNOFF NOMENCLATURE Area Subbasin area (km 2 ) C Runoff coefficient in peak runoff rate calculation CN Curve number CN 1 Moisture condition I curve number CN 2 Moisture condition II curve number CN 2s Moisture condition II curve number adjusted for slope CN 3 Moisture condition III curve number F inf Cumulative infiltration at time t (mm H 2 O) FC Water content of soil profile at field capacity (mm H 2 O) I a Initial abstractions which includes surface storage, interception and infiltration prior to runoff (mm H 2 O) K ch Effective hydraulic conductivity of the channel alluvium (mm/hr) K e Effective hydraulic conductivity (mm/hr) K sat Saturated hydraulic conductivity (mm/hr) L Channel length from the most distant point to the subbasin outlet (km) L c Average flow channel length for the subbasin (km) L cen Distance along the channel to the subbasin centroid (km) L slp Subbasin slope length (m) Q surf Accumulated runoff or rainfall excess (mm H 2 O) R t Amount of rain falling during the time step (mm H 2 O) R day Amount of rainfall on a given day (mm H 2 O) R tc Amount of rain falling during the time of concentration (mm H 2 O) S Retention parameter in SCS curve number equation (mm) S 3 Retention parameter for the moisture condition III curve number S frz Retention parameter adjusted for frozen conditions (mm) S max Maximum value the retention parameter can achieve on any given day (mm) SAT Amount of water in the soil profile when completely saturated (mm H 2 O), SW Amount of water in soil profile (mm H 2 O) W Average width of flow, i.e. channel width (m) a r Unit channel regression intercept (m 3 ) a x Regression intercept for a channel of length L and width W (m 3 ) b r Unit channel regression slope b x Regression slope for a channel of length L and width W dur flw Duration of flow (hr) f inf Infiltration rate (mm/hr) i Rainfall intensity (mm/hr) k r Decay factor (m -1 km -1 ) m c Percent clay content m s Percent sand content n Manning s roughness coefficient for the subbasin or channel q Unit source area flow rate (mm hr -1 ) * 0

125 112 SWAT USER'S MANUAL, VERSION 2000 q ch Average channel flow rate (m 3 s -1 ) * qch Average channel flow rate (mm hr -1 ) q ov Average overland flow rate (m 3 s -1 ) q peak Peak runoff rate (m 3 /s) q peak,f Peak rate after transmission losses (m 3 /s) q peak,i Peak rate before accounting for transmission losses (m 3 /s) slp Average slope of the subbasin (% or m/m) slp ch Average channel slope (m m -1 ) t ch Time of concentration for channel flow (hr) t conc Time of concentration for a subbasin (hr) t ov Time of concentration for overland flow (hr) v c Average channel velocity (m s -1 ) v ov Overland flow velocity (m s -1 ) vol Qsurf,f Volume of runoff after transmission losses (m 3 ) vol Qsurf,i Volume of runoff prior to transmission losses (m 3 ) vol thr Threshold volume for a channel of length L and width W (m 3 ) w 1 Shape coefficient in retention parameter adjustments for soil moisture content Shape coefficient in retention parameter adjustments for soil moisture content w 2 α 0.5 α tc φ soil Ψ wf θ v Fraction of daily rain falling in the half-hour highest intensity rainfall, Fraction of daily rainfall that occurs during the time of concentration Porosity of the soil (mm/mm) Wetting front matric potential (mm) Volumetric moisture content (mm/mm) 6.6 REFERENCES Bouwer, H Infiltration of water into nonuniform soil. Journal Irrigation and Drainage Div., ASCE 95(IR4): Green, W.H. and G.A. Ampt Studies on soil physics, 1. The flow of air and water through soils. Journal of Agricultural Sciences 4: Hershfield, D.M Rainfall frequency atlas of the United States for durations from 30 minutes to 24 hours and return periods from 1 to 100 years. U.S. Dept. Commerce Tech. Paper No. 40. Lane, L.J Chapter 19: Transmission Losses. p In Soil Conservation Service. National engineering handbook, section 4: hydrology. U.S. Government Printing Office, Washington, D.C.

126 CHAPTER 6: EQUATIONS SURFACE RUNOFF 113 Lane, L.J Distributed model for small semi-arid watersheds. J. Hydraulic Eng., ASCE, 108(HY10): Mein, R.G. and C.L. Larson Modeling infiltration during a steady rain. Water Resources Research 9(2): Natural Resources Conservation Service Soil Survey Staff National soil survey handbook, title 430-VI. U.S. Government Printing Office, Washington, D.C. Nearing, M.A., B.Y. Liu, L.M. Risse, and X. Zhang Curve number and Green-Ampt effective hydraulic conductivities. Water Resources Bulletin 32: Rallison, R.E. and N. Miller Past, present and future SCS runoff procedure. p In V.P. Singh (ed.). Rainfall runoff relationship. Water Resources Publication, Littleton, CO. Rawls, W.J. and D.L. Brakensiek Prediction of soil water properties for hydrologic modeling. p In E.B. Jones and T.J. Ward (eds). Watershed management in the 80 s. ASCE, New York, N.Y. Soil Conservation Service Section 4: Hydrology In National Engineering Handbook. SCS. Soil Conservation Service Engineering Division Urban hydrology for small watersheds. U.S. Department of Agriculture, Technical Release 55. Williams, J.R Chapter 25: The EPIC model. p In V.P. Singh (ed). Computer models of watershed hydrology. Water Resources Publications, Highlands Ranch, CO.

127 114 SWAT USER'S MANUAL, VERSION 2000

128 CHAPTER 7 EQUATIONS: EVAPOTRANSPIRATION Evapotranspiration is a collective term that includes all processes by which water at the earth s surface is converted to water vapor. It includes evaporation from the plant canopy, transpiration, sublimation and evaporation from the soil. Evapotranspiration is the primary mechanism by which water is removed from a watershed. Roughly 62% of the precipitation that falls on the continents is evapotranspired. Evapotranspiration exceeds runoff in most river basins and on all continents except Antarctica (Dingman, 1994). The difference between precipitation and evapotranspiration is the water available for human use and management. An accurate estimation of 115

129 116 SWAT USER'S MANUAL, VERSION 2000 evapotranspiration is critical in the asssessment of water resources and the impact of climate and land use change on those resources. 7.1 POTENTIAL EVAPOTRANSPIRATION Potential evapotranspiration (PET) was a concept originally introduced by Thornthwaite (1948) as part of a climate classification scheme. He defined PET is the rate at which evapotranspiration would occur from a large area uniformly covered with growing vegetation that has access to an unlimited supply of soil water and that was not exposed to advection or heat storage effects. Because the evapotranspiration rate is strongly influenced by a number of vegetative surface characteristics, Penman (1956) redefined PET as the amount of water transpired... by a short green crop, completely shading the ground, of uniform height and never short of water. Penman used grass as his reference crop, but later researchers (Jensen, et al., 1990) have suggested that alfalfa at a height of 30 to 50 cm may be a more appropriate choice. Numerous methods have been developed to estimate PET. Three of these methods have been incorporated into SWAT: the Penman-Monteith method (Monteith, 1965; Allen, 1986; Allen et al., 1989), the Priestley-Taylor method (Priestley and Taylor, 1972) and the Hargreaves method (Hargreaves et al., 1985). The model will also read in daily PET values if the user prefers to apply a different potential evapotranspiration method. The three PET methods included in SWAT vary in the amount of required inputs. The Penman-Monteith method requires solar radiation, air temperature, relative humidity and wind speed. The Priestley-Taylor method requires solar radiation, air temperature and relative humidity. The Hargreaves method requires air temperature only PENMAN-MONTEITH METHOD The Penman-Monteith equation combines components that account for energy needed to sustain evaporation, the strength of the mechanism required to

130 CHAPTER 7: EQUATIONS EVAPOTRANSPIRATION 117 remove the water vapor and aerodynamic and surface resistance terms. The Penman-Monteith equation is: o ( H G) + ρ c [ e e ] net air p z z a λe = γ ( 1 + rc ra ) where λe is the latent heat flux density (MJ m -2 d -1 ), E is the depth rate evaporation (mm d -1 ), is the slope of the saturation vapor pressure-temperature curve, de/dt (kpa ûc -1 ), H net is the net radiation (MJ m -2 d -1 ), G is the heat flux density to the ground (MJ m -2 d -1 ), ρ air is the air density (kg m -3 ), c p is the specific heat at constant pressure (MJ kg -1 ûc -1 o ), e z is the saturation vapor pressure of air at height z (kpa), e z is the water vapor pressure of air at height z (kpa), γ is the psychrometric constant (kpa ûc -1 ), r c is the plant canopy resistance (s m -1 ), and r a is the diffusion resistance of the air layer (aerodynamic resistance) (s m -1 ). For well-watered plants under neutral atmospheric stability and assuming logarithmic wind profiles, the Penman-Monteith equation may be written (Jensen et al., 1990): o ( H G) + γ K ( λ ρ P) ( e e ) net 1 air z z a λet = γ ( 1 + rc ra ) where λ is the latent heat of vaporization (MJ kg -1 ), E t is the maximum transpiration rate (mm d -1 ), K 1 is a dimension coefficient needed to ensure the two terms in the numerator have the same units (for u z in m s -1, K 1 = 8.64 x 10 4 ), and P is the atmospheric pressure (kpa). The calculation of net radiation, H net, is reviewed in Chapter 2. The calculations for the latent heat of vaporization, λ, the slope of the saturation vapor pressure-temperature curve,, the psychrometric constant, γ, and the saturation and actual vapor pressure, e o z and e z, are reviewed in Chapter 3. The remaining undefined terms are the soil heat flux, G, the combined term K λρ/P, the aerodynamic resistance, r a, and the canopy resistance, r c. r r

131 118 SWAT USER'S MANUAL, VERSION SOIL HEAT FLUX Soil heat storage or release can be significant over a few hours, but is usually small from day to day because heat stored as the soil warms early in the day is lost when the soil cools late in the day or at night. Since the magnitude of daily soil heat flux over a 10- to 30-day period is small when the soil is under a crop cover, it can normally be ignored for most energy balance estimates. SWAT assumes the daily soil heat flux, G, is always equal to zero AERODYNAMIC RESISTANCE The aerodynamic resistance to sensible heat and vapor transfer, r a, is calculated: ln [ z ] [( z d ) z ] ln ( z d ) w om p ov ra = k uz where z w is the height of the wind speed measurement (cm), z p is the height of the humidity (psychrometer) and temperature measurements (cm), d is the zero plane displacement of the wind profile (cm), z om is the roughness length for momentum transfer (cm), z ov is the roughness length for vapor transfer (cm), k is the von Kármán constant, and u z is the wind speed at height z w (m s -1 ). The von Kármán constant is considered to be a universal constant in turbulent flow. Its value has been calculated to be near 0.4 with a range of 0.36 to 0.43 (Jensen et al., 1990). A value of 0.41 is used by SWAT for the von Kármán constant. Brutsaert (1975) determined that the surface roughness parameter, z o, is related to the mean height (h c ) of the plant canopy by the relationship h c /z o = 3e or 8.15 where e is the natural log base. Based on this relationship, the roughness length for momentum transfer is estimated as: z z om om = h 8.15 = h h c 200cm c ( h ) c = c h c > 200cm where mean height of the plant canopy (h c ) is reported in centimeters.

132 CHAPTER 7: EQUATIONS EVAPOTRANSPIRATION 119 The roughness length for momentum transfer includes the effects of bluff-body forces. These forces have no impact on heat and vapor transfer, and the roughness length for vapor transfer is only a fraction of that for momentum transfer. To estimate the roughness length for vapor transfer, Stricker and Brutsaert (1978) recommended using: z = ov z om The displacement height for a plant can be estimated using the following relationship (Monteith, 1981; Plate, 1971): d = 2 / h c The height of the wind speed measurement, z w, and the height of the humidity (psychrometer) and temperature measurements, z p, are always assumed to be 170 cm CANOPY RESISTANCE Studies in canopy resistance have shown that the canopy resistance for a well-watered reference crop can be estimated by dividing the minimum surface resistance for a single leaf by one-half of the canopy leaf area index (Jensen et. al, 1990): r c ( 0. LAI ) = r where r c is the canopy resistance (s m -1 ), r is the minimum effective stomatal resistance of a single leaf (s m -1 ), and LAI is the leaf area index of the canopy. The distribution of stomates on a plant leaf will vary between species. Typically, stomates are distributed unequally on the top and bottom of plant leaves. Plants with stomates located on only one side are classified as hypostomatous while plants with an equal number of stomates on both sides of the leaf are termed amphistomatous. The effective leaf stomatal resistance is determined by considering the stomatal resistance of the top (adaxial) and bottom (abaxial) sides to be connected in parallel (Rosenburg, et al., 1983). When there are unequal

133 120 SWAT USER'S MANUAL, VERSION 2000 numbers of stomates on the top and bottom, the effective stomatal resistance is calculated: r r r ad ab = r ab + r ad where r is the minimum effective stomatal resistance of a single leaf (s m -1 ), r ad is the minimum adaxial stomatal leaf resistance (s m -1 ), and r ab is the minimum abaxial stomatal leaf resistance (s m -1 ). For amphistomatous leaves, the effective stomatal resistance is: r ad r ab r = = For hypostomatous leaves the effective stomatal resistance is: where r = r ad = r ab Leaf conductance is defined as the inverse of the leaf resistance: g 1 = r g is the maximum effective leaf conductance (m s -1 ). When the canopy resistance is expressed as a function of leaf conductance instead of leaf resistance, equation becomes: ( 0.5 g ) 1 r c = LAI where r c is the canopy resistance (s m -1 ), g is the maximum conductance of a single leaf (m s -1 ), and LAI is the leaf area index of the canopy. For climate change simulations, the canopy resistance term can be modified to reflect the impact of change in CO 2 concentration on leaf conductance. The influence of increasing CO 2 concentrations on leaf conductance was reviewed by Morison (1987). Morison found that at CO 2 concentrations between 330 and 660 ppmv, a doubling in CO 2 concentration resulted in a 40% reduction in leaf conductance. Within the specified range, the reduction in conductance is linear (Morison and Gifford, 1983). Easterling et al. (1992) proposed the following

134 CHAPTER 7: EQUATIONS EVAPOTRANSPIRATION 121 modification to the leaf conductance term for simulating carbon dioxide concentration effects on evapotranspiration: [ ( 330) ] g, CO = g 1 CO where g,co is the leaf conductance modified to reflect CO 2 2 effects (m s -1 ) and CO 2 is the concentration of carbon dioxide in the atmosphere (ppmv). Incorporating this modification into equation gives 1 CO2 r c = r ( 0.5 LAI ) SWAT will default the value of CO 2 concentration to 330 ppmv if no CO2 value is entered by the user. With this default, the term reduces to 1.0 and the canopy resistance equation becomes equation When calculating actual evapotranspiration, the canopy resistance term is modified to reflect the impact of high vapor pressure deficit on leaf conductance. For a plant species, a threshold vapor pressure deficit is defined at which the plant s leaf conductance begins to drop in response to the vapor pressure deficit. The adjusted leaf conductance is calculated: [ 1 g ( vpd )] g dcl = g, mx vpd, thr if vpd thr g g, mx vpd > = if vpd vpd thr where g is the conductance of a single leaf (m s -1 ), g, mx is the maximum conductance of a single leaf (m s -1 ), is the rate of decline g, dcl in leaf conductance per unit increase in vapor pressure deficit (m s -1 kpa - 1 ), vpd is the vapor pressure deficit (kpa), and vpd thr is the threshold vapor pressure deficit above which a plant will exhibit reduced leaf conductance (kpa) COMBINED TERM For wind speed in m s -1, Jensen et al. (1990) provided the following relationship to calculate K λρ/P:

135 122 SWAT USER'S MANUAL, VERSION 2000 where K λ ρ P = T av T av is the mean air temperature for the day (ûc). To calculate potential evapotranspiration, the Penman-Monteith equation must be solved for a reference crop. SWAT uses alfalfa at a height of 40 cm with a minimum leaf resistance of 100 s m -1 for the reference crop. Using this canopy height, the equation for aerodynamic resistance (7.1.3) simplifies to: r a 114. = u z The equation for canopy resistance requires the leaf area index. The leaf area index for the reference crop is estimated using an equation developed by Allen et al. (1989) to calculate LAI as a function of canopy height. For nonclipped grass and alfalfa greater than 3 cm in height: ( h ) 1. 4 LAI 1.5 ln = c where LAI is the leaf area index and h c is the canopy height (cm). For alfalfa with a 40 cm canopy height, the leaf area index is 4.1. Using this value, the equation for canopy resistance simplifies to: CO2 r c = The most accurate estimates of evapotranspiration with the Penman- Monteith equation are made when evapotranspiration is calculated on an hourly basis and summed to obtain the daily values. Mean daily parameter values have been shown to provide reliable estimates of daily evapotranspiration values and this is the approach used in SWAT. However, the user should be aware that calculating evapotranspiration with the Penman-Monteith equation using mean daily values can potentially lead to significant errors. These errors result from diurnal distributions of wind speed, humidity, and net radiation that in combination create conditions which the daily averages do not replicate.

136 7.1.2 PRIESTLEY-TAYLOR METHOD CHAPTER 7: EQUATIONS EVAPOTRANSPIRATION 123 Priestley and Taylor (1972) developed a simplified version of the combination equation for use when surface areas are wet. The aerodynamic component was removed and the energy component was multiplied by a coefficient, α pet = 1.28, when the general surroundings are wet or under humid conditions λeo = α pet ( H net G) γ where λ is the latent heat of vaporization (MJ kg -1 ), E o is the potential evapotranspiration (mm d -1 ), α pet is a coefficient, is the slope of the saturation vapor pressure-temperature curve, de/dt (kpa ûc -1 ), γ is the psychrometric constant (kpa ûc -1 ), H net is the net radiation (MJ m -2 d -1 ), and G is the heat flux density to the ground (MJ m -2 d -1 ). The Priestley-Taylor equation provides potential evapotranspiration estimates for low advective conditions. In semiarid or arid areas where the advection component of the energy balance is significant, the Priestley-Taylor equation will underestimate potential evapotranspiration HARGREAVES METHOD The Hargreaves method was originally derived from eight years of coolseason Alta fescue grass lysimeter data from Davis, California (Hargreaves, 1975). Several improvements were made to the original equation (Hargreaves and Samani, 1982 and 1985) and the form used in SWAT was published in 1985 (Hargreaves et al., 1985): 0.5 ( T T ) ( T 17.8) λe = H av o 0 mx mn + where λ is the latent heat of vaporization (MJ kg -1 ), E o is the potential evapotranspiration (mm d -1 ), H 0 is the extraterrestrial radiation (MJ m -2 d -1 ), T mx is the maximum air temperature for a given day ( C), T mn is the minimum air temperature for a given day ( C), and ( C). T av is the mean air temperature for day

137 124 SWAT USER'S MANUAL, VERSION 2000 Table 7-1: SWAT input variables used in potential evapotranspiration calculations summarized in this section. Variable name Definition File Name IPET Potential evapotranspiration method.cod WND_SP u z : Daily wind speed (m/s).wnd CO2 CO 2 : Carbon dioxide concentration (ppmv).sub MAX TEMP T mx : Daily maximum temperature ( C).tmp MIN TEMP T mn : Daily minimum temperature ( C).tmp GSI : maximum leaf conductance (m s -1 ) crop.dat VPD2 g,mx g,dcl : Rate of decline in leaf conductance per unit increase in vapor crop.dat pressure deficit (m s -1 kpa -1 ) VPTH vpd thr : Threshold vapor pressure deficit above which a plant will exhibit crop.dat reduced leaf conductance (kpa) PET_ALPHA α pet : Coefficient in Priestley-Taylor equation.bsn

138 CHAPTER 7: EQUATIONS EVAPOTRANSPIRATION ACTUAL EVAPOTRANSPIRATION Once total potential evapotranspiration is determined, actual evaporation must be calculated. SWAT first evaporates any rainfall intercepted by the plant canopy. Next, SWAT calculates the maximum amount of transpiration and the maximum amount of sublimation/soil evaporation using an approach similar to that of Richtie (1972). The actual amount of sublimation and evaporation from the soil is then calculated. If snow is present in the HRU, sublimation will occur. Only when no snow is present will evaporation from the soil take place EVAPORATION OF INTERCEPTED RAINFALL Any free water present in the canopy is readily available for removal by evapotranspiration. The amount of actual evapotranspiration contributed by intercepted rainfall is especially significant in forests where in some instances evaporation of intercepted rainfall is greater than transpiration. SWAT removes as much water as possible from canopy storage when calculating actual evaporation. If potential evapotranspiration, E o, is less than the amount of free water held in the canopy, R INT, then E = E = E R a INT f ) can o ( E = RINT ( i) can where E a is the actual amount of evapotranspiration occurring in the watershed on a given day (mm H 2 O), E can is the amount of evaporation from free water in the canopy on a given day (mm H 2 O), E o is the potential evapotranspiration on a given day (mm H 2 O), R INT(i) is the initial amount of free water held in the canopy on a given day (mm H 2 O), and R INT(f) is the final amount of free water held in the canopy on a given day (mm H 2 O). If potential evapotranspiration, E o, is greater than the amount of free water held in the canopy, R INT, then E can = R INT (i) R INT ( f ) =

139 126 SWAT USER'S MANUAL, VERSION 2000 Once any free water in the canopy has been evaporated, the remaining evaporative water demand ( E = E E ) is partitioned between the vegetation o o can and snow/soil TRANSPIRATION If the Penman-Monteith equation is selected as the potential evapotranspiration method, transpiration is also calculated with the equations summarized in Section For the other potential evapotranspiration methods, transpiration is calculated as: E t E o LAI = 0 LAI E t = E o LAI > where E t is the transpiration on a given day (mm H 2 O), E o is the potential evapotranspiration adjusted for evaporation of free water in the canopy (mm H 2 O), and LAI is the leaf area index. The value for transpiration calculated by equations and is the amount of transpiration that will occur on a given day when the plant is growing under ideal conditions. The actual amount of transpiration may be less than this due to stress on the plant. The reduction in transpiration and plant growth due to stress is reviewed in Chapter SUBLIMATION AND EVAPORATION FROM THE SOIL The amount of sublimation and soil evaporation will be impacted by the degree of shading. The maximum amount of sublimation/soil evaporation on a given day is calculated as: E s = E cov o sol where E s is the maximum sublimation/soil evaporation on a given day (mm H 2 O), E o is the potential evapotranspiration adjusted for evaporation of free water in the canopy (mm H 2 O), and cov sol is the soil cover index. The soil cover index is calculated cov sol 5 ( CV ) = exp 7.2.8

140 CHAPTER 7: EQUATIONS EVAPOTRANSPIRATION 127 where CV is the aboveground biomass and residue (kg ha -1 ). If the snow water content is greater than 0.5 mm H 2 O, the soil cover index is set to 0.5. The maximum amount of sublimation/soil evaporation is reduced during periods of high plant water use with the relationship: where E s Eo E s = min Es, Es + Et E s is the maximum sublimation/soil evaporation adjusted for plant water use on a given day (mm H 2 O), E s is the maximum sublimation/soil evaporation on a given day (mm H 2 O), E o is the potential evapotranspiration adjusted for evaporation of free water in the canopy (mm H 2 O), and E t is the transpiration on a given day (mm H 2 O). When E t is low s Es. However, as E t approaches o E E, Es E s 1 + cov sol SUBLIMATION Once the maximum amount of sublimation/soil evaporation for the day is calculated, SWAT will first remove water from the snow pack to meet the evaporative demand. If the water content of the snow pack is greater than the maximum sublimation/soil evaporation demand, then E sub = E s SNO E ( f ) = SNO( i) s E = s where E sub is the amount of sublimation on a given day (mm H 2 O), E s is the maximum sublimation/soil evaporation adjusted for plant water use on a given day (mm H 2 O), SNO (i) is the amount of water in the snow pack on a given day prior to accounting for sublimation (mm H 2 O), SNO (f) is the amount of water in the snow pack on a given day after accounting for sublimation (mm H 2 O), and E s is the maximum soil water evaporation on

141 128 SWAT USER'S MANUAL, VERSION 2000 a given day (mm H 2 O). If the water content of the snow pack is less than the maximum sublimation/soil evaporation demand, then E sub = SNO (i) SNO s ( f ) = E = E E s sub SOIL WATER EVAPORATION When an evaporation demand for soil water exists, SWAT must first partition the evaporative demand between the different layers. The depth distribution used to determine the maximum amount of water allowed to be evaporated is: E soil z z = Es, z + exp ( z) where E soil,z is the evaporative demand at depth z (mm H 2 O), E s is the maximum soil water evaporation on a given day (mm H 2 O), and z is the depth below the surface. The coefficients in this equation were selected so that 50% of the evaporative demand is extracted from the top 10 mm of soil and 95% of the evaporative demand is extracted from the top 100 mm of soil. The amount of evaporative demand for a soil layer is determined by taking the difference between the evaporative demands calculated at the upper and lower boundaries of the soil layer: E soil, ly Esoil, zl Esoil, zu = where E soil,ly is the evaporative demand for layer ly (mm H 2 O), E soil,zl is the evaporative demand at the lower boundary of the soil layer (mm H 2 O), and E soil,zu is the evaporative demand at the upper boundary of the soil layer (mm H 2 O). Figure 7-1 graphs the depth distribution of the evaporative demand for a soil that has been partitioned into 1 mm layers assuming a total soil evaporation demand of 100 mm.

142 CHAPTER 7: EQUATIONS EVAPOTRANSPIRATION 129 Evaporation allowed with depth assuming 100 mm demand Maximum Evaporation (mm H2O) Depth (mm) Figure 7-1: Soil evaporative demand distribution with depth. As mentioned previously, the depth distribution assumes 50% of the evaporative demand is met by soil water stored in the top 10 mm of the soil profile. With our example of a 100 mm total evaporative demand, 50 mm of water is 50%. This is a demand that the top layer cannot satisfy. SWAT does not allow a different layer to compensate for the inability of another layer to meet its evaporative demand. The evaporative demand not met by a soil layer results in a reduction in actual evapotranspiration for the HRU. A coefficient has been incorporated into equation to allow the user to modify the depth distribution used to meet the soil evaporative demand. The modified equation is: E, = E, E, esco soil ly soil zl soil zu where E soil,ly is the evaporative demand for layer ly (mm H 2 O), E soil,zl is the evaporative demand at the lower boundary of the soil layer (mm H 2 O), E soil,zu is the evaporative demand at the upper boundary of the soil layer

143 130 SWAT USER'S MANUAL, VERSION 2000 (mm H 2 O), and esco is the soil evaporation compensation coefficient. Solutions to this equation for different values of esco are graphed in Figure 7-2. The plot for esco = 1.0 is that shown in Figure Evaporation allowed with depth assuming 100 mm demand Maximum Evaporation (mm H2O) Depth (mm) esco = 1.0 esco = 0.9 esco = 0.8 esco = 0.7 Figure 7-2: Soil evaporative demand distribution with depth As the value for esco is reduced, the model is able to extract more of the evaporative demand from lower levels. When the water content of a soil layer is below field capacity, the evaporative demand for the layer is reduced according to the following equations: E soil ( SW FC ) 2.5 ly ly, ly = Esoil, ly exp when SW ly < FCly FCly WPly when SWly FCly E soil, ly = Esoil, ly where is the evaporative demand for layer ly adjusted for water E soil, ly content (mm H 2 O), E soil,ly is the evaporative demand for layer ly (mm

144 CHAPTER 7: EQUATIONS EVAPOTRANSPIRATION 131 H 2 O), SW ly is the soil water content of layer ly (mm H 2 O), FC ly is the water content of layer ly at field capacity (mm H 2 O), and WP ly is the water content of layer ly at wilting point (mm H 2 O). In addition to limiting the amount of water removed by evaporation in dry conditions, SWAT defines a maximum value of water that can be removed at any time. This maximum value is 80% of the plant available water on a given day where the plant available water is defined as the total water content of the soil layer minus the water content of the soil layer at wilting point (-15 bar). ( E 0.8 ( SW WP )) E soil, ly = min soil, ly ly ly where is the amount of water removed from layer ly by evaporation E soil, ly (mm H 2 O), is the evaporative demand for layer ly adjusted for E soil, ly water content (mm H 2 O), SW ly is the soil water content of layer ly (mm H 2 O), and WP ly is the water content of layer ly at wilting point (mm H 2 O). Table 7-2: SWAT input variables used in soil evaporation calculations. Variable name Definition File Name ESCO esco: soil evaporation compensation coefficient.hru 7.3 NOMENCLATURE CO 2 Concentration of carbon dioxide in the atmosphere (ppmv) CV Total aboveground biomass and residue present on current day (kg ha -1 ) E Depth rate evaporation (mm d -1 ) E a Actual amount of evapotranspiration on a given day (mm H 2 O) E can Amount of evaporation from free water in the canopy on a given day (mm H 2 O) E o Potential evapotranspiration (mm d -1 ) E o Potential evapotranspiration adjusted for evaporation of free water in the canopy (mm H 2 O) E s Maximum sublimation/soil evaporation on a given day (mm H 2 O) E s Maximum sublimation/soil evaporation adjusted for plant water use on a given day (mm H 2 O) E s Maximum soil water evaporation on a given day (mm H 2 O) E soil,ly Evaporative demand for layer ly (mm H 2 O)

145 E soil, ly E soil, ly 132 SWAT USER'S MANUAL, VERSION 2000 Evaporative demand for layer ly adjusted for water content (mm H 2 O) Amount of water removed from layer ly by evaporation (mm H 2 O) E soil,z Evaporative demand at depth z (mm H 2 O) E sub Amount of sublimation on a given day (mm H 2 O) E t Transpiration rate (mm d -1 ) FC ly Water content of layer ly at field capacity (mm H 2 O) G Heat flux density to the ground (MJ m -2 d -1 ) H 0 Extraterrestrial daily irradiation (MJ m -2 d -1 ) H net Net radiation on day (MJ m -2 d -1 ) K 1 Dimension coefficient in Penman-Monteith equation LAI Leaf area index of the canopy P Atmospheric pressure (kpa) R INT Amount of free water held in the canopy on a given day (mm H 2 O) SNO Water content of snow cover on current day (mm H 2 O) SW ly Soil water content of layer ly (mm H 2 O) T mn Minimum air temperature for day ( C) T mx Maximum air temperature for day ( C) T av Mean air temperature for day ( C) Water content of layer ly at wilting point (mm H 2 O). WP ly c p Specific heat of moist air at constant pressure ( MJ kg -1 C -1 ) cov sol Soil cover index d Zero plane displacement of the wind profile (cm) e Actual vapor pressure on a given day (kpa) o e Saturation vapor pressure on a given day (kpa) esco Soil evaporation compensation coefficient g Leaf conductance (m s -1 ) g,mx Maximum conductance of a single leaf (m s -1 ) h c Canopy height (cm) k Von Kármán constant r a Diffusion resistance of the air layer (aerodynamic resistance) (s m -1 ) r c Plant canopy resistance (s m -1 ) r Minimum effective resistance of a single leaf (s m -1 ) r ab Minimum abaxial stomatal leaf resistance (s m -1 ) r ad Minimum adaxial stomatal leaf resistance (s m -1 ) u z Wind speed at height z w (m s -1 ) vpd Vapor pressure deficit (kpa) vpd thr Threshold vapor pressure deficit above which a plant will exhibit reduced leaf conductance (kpa) z Depth below soil surface (mm) z om Roughness length for momentum transfer (cm) z ov Roughness length for vapor transfer (cm) z p Height of the humidity (psychrometer) and temperature measurements (cm) Height of the wind speed measurement (cm) z w

146 CHAPTER 7: EQUATIONS EVAPOTRANSPIRATION 133 α pet Coefficient in Priestley-Taylor equation Slope of the saturation vapor pressure curve (kpa C -1 ) Rate of decline in leaf conductance per unit increase in vapor pressure deficit (m g,dcl s -1 kpa -1 ) ρ air Air density (kg m -3 ) γ Psychrometric constant (kpa C -1 ) λ Latent heat of vaporization (MJ kg -1 ) 7.4 REFERENCES Allen, R.G A Penman for all seasons. J. Irrig. and Drain Engng., ASCE, 112(4): Allen, R.G., M.E. Jensen, J.L. Wright, and R.D. Burman Operational estimates of evapotranspiration. Agron. J. 81: Brutsaert, W Comments on surface roughness parameters and the height of dense vegetation. J. Meterol. Soc. Japan 53: Dingman, S.L Physical hydrology. Prentice-Hall, Inc., Englewood Cliffs, NJ. Easterling, W.E., N.J. Rosenburg, M.S. McKenney, C.A. Jones, P.T. Dyke, and J.R. Williams Preparing the erosion productivity impact calculator (EPIC) model to simulate crop response to climate change and the direct effects of CO 2. Agricultural and Forest Meteorology 59: Hargreaves, G.H Moisture availability and crop production. Trans. ASAE 18: Hargreaves, G.H. and Z.A. Samani Reference crop evapotranspiration from temperature. Applied Engineering in Agriculture 1: Hargreaves, G.H. and Z.A. Samani Estimating potential evapotranspiration. Tech. Note, J. Irrig. and Drain. Engr. 108(3): Hargreaves, G.L., G.H. Hargreaves, and J.P. Riley Agricultural benefits for Senegal River Basin. J. Irrig. and Drain. Engr. 111(2):

147 134 SWAT USER'S MANUAL, VERSION 2000 Jensen, M.E., R.D. Burman, and R.G. Allen (ed) Evapotranspiration and irrigation water requirements. ASCE Manuals and Reports on Engineering Practice No. 70, ASCE, N.Y. 332 pp. Monteith, J.L Evaporation and the environment. p In The state and movement of water in living organisms, XIXth Symposium. Soc. for Exp. Biol., Swansea, Cambridge University Press. Monteith, J.L Evaporation and surface temperature. Quart. J. Roy. Meteorol. Soc. 107:1-27. Morison, J.I.L Intercellular CO 2 concentration and stomatal response to CO 2. p In E. Zeiger, G.D. Farquhar and I.R. Cowan (ed.) Stomatal function. Standford University Press, Palo Alto, CA. Morison, J.I.L. and R.M. Gifford Stomatal sensitivity tocarbon dioxide and humidity. Plant Physiol. 71: Penman, H.L Evaporation: An introductory survey. Netherlands Journal of Agricultural Science 4:7-29. Plate, E.J Aerodynamic characteristics of atmospheric boundary layers. U.S. Atomic Energy Comm., Critical Review Series, TID pp. Priestley, C.H.B. and R.J. Taylor On the assessment of surface heat flux and evaporation using large-scale parameters. Mon. Weather. Rev. 100: Ritchie, J.T Model for predicting evaporation from a row crop with incomplete cover. Water Resour. Res. 8: Rosenburg, N.J., B.L. Blad, and S.B. Verma Microclimate: the biological environment, 2 nd ed. John Wiley & Sons, New York. Stricker, H. and W. Brutsaert Actual evapotranspiration over summer period in the 'Hupsel Catchment.' J. Hydrol. 39: Thornthwaite, C.W An approach toward a rational classification of climate. Geographical Review 38:55-94.

148 CHAPTER 17 EQUATIONS: GROWTH CYCLE The growth cycle of a plant is controlled by plant attributes summarized in the plant growth database and by the timing of operations listed in the management file. This chapter focuses on the impact of user inputs in management operations on the growth and development of plants. 127

149 128 SWAT USER'S MANUAL, VERSION HEAT UNITS Temperature is one of the most important factors governing plant growth. Each plant has its own temperature range, i.e. its minimum, optimum, and maximum for growth. For any plant, a minimum or base temperature must be reached before any growth will take place. Above the base temperature, the higher the temperature the more rapid the growth rate of the plant. Once the optimum temperature is exceeded the growth rate will begin to slow until a maximum temperature is reached at which growth ceases. In the 1920s and 1930s, canning factories were searching for ways to time the planting of sweet peas so that there would be a steady flow of peas at the peak of perfection to the factory. Crops planted at weekly intervals in the early spring would sometimes come to maturity with only a 1- or 2-day differential while at other times there was a 6- to 8-day differential (Boswell, 1926; 1929). A heat unit theory was suggested (Boswell, 1926; Magoon and Culpepper, 1932) that was revised and successfully applied (Barnard, 1948; Phillips, 1950) by canning companies to determine when plantings should be made to ensure a steady harvest of peas with no bunching or breaks. The heat unit theory postulates that plants have heat requirements that can be quantified and linked to time to maturity. Because a plant will not grow when the mean temperature falls below its base temperature, the only portion of the mean daily temperature that contributes towards the plant s development is the amount that exceeds the base temperature. To measure the total heat requirements of a plant, the accumulation of daily mean air temperatures above the plant s base temperature is recorded over the period of the plant s growth and expressed in terms of heat units. For example, assume sweet peas are growing with a base temperature of 4.5 C. If the mean temperature on a given day is 20 C, the heat units accumulated on that day are = 15.5 heat units. Knowing the planting date, maturity date, base temperature and mean daily temperatures, the total number of heat units required to bring a crop to maturity can be calculated.

150 CHAPTER 17: SWAT EQUATIONS GROWTH CYCLE 129 The heat index used by SWAT is a direct summation index. Each degree of the daily mean temperature above the base temperature is one heat unit. This method assumes that the rate of growth is directly proportional to the increase in temperature. It is important to keep in mind that the heat unit theory ignores the impact of harmful high temperatures. It assumes that all heat above the base temperature contributes to crop growth Temperature (deg C) Mean daily temperature 1/1/92 1/15/92 1/29/92 2/12/92 2/26/92 3/11/92 3/25/92 4/8/92 4/22/92 5/6/92 5/20/92 6/3/92 6/17/92 7/1/92 7/15/92 Figure 17-1: Mean daily temperature recorded for Greenfield, Illinois The mean daily temperature during 1992 for Greenfield, Illinois is plotted in Figure 17-1 along with the base temperature for corn (8 C). Crop growth will only occur on those days where the mean daily temperature exceeds the base temperature. The heat unit accumulation for a given day is calculated with the equation: Date Base temperature, corn 7/29/92 8/12/92 8/26/92 9/9/92 9/23/92 10/7/92 10/21/92 11/4/92 11/18/92 12/2/92 12/16/92 12/30/92 HU = T av T base when T av > Tbase where HU is the number of heat units accumulated on a given day (heat units), T av is the mean daily temperature ( C), and T base is the plant s base or minimum temperature for growth ( C). The total number of heat units required for a plant to reach maturity is calculated:

151 130 SWAT USER'S MANUAL, VERSION 2000 PHU = m d = 1 HU where PHU is the total heat units required for plant maturity (heat units), HU is the number of heat units accumulated on day d where d = 1 on the day of planting and m is the number of days required for a plant to reach maturity. PHU is also referred to as potential heat units. When calculating the potential heat units for a plant, the number of days to reach maturity must be known. For most crops, these numbers have been quantified and are easily accessible. For other plants, such as forest or range, the time that the plants begin to develop buds should be used as the beginning of the growing season and the time that the plant seeds reach maturation is the end of the growing season. For the Greenfield Illinois example, a 120 day variety of corn was planted on May 15. Summing daily heat unit values, the total heat units required to bring the corn to maturity was HEAT UNIT SCHEDULING As the heat unit theory was proven to be a reliable predictor of harvest dates for all types of crops, it was adapted by researchers for prediction of the timing of other plant development stages such as flowering (Cross and Zuber, 1972). The successful adaptation of heat units to predict the timing of plant stages has subsequently led to the use of heat units to schedule management operations. SWAT allows management operations to be scheduled by day or by fraction of potential heat units. For each operation the model checks to see if a month and day has been specified for timing of the operation. If this information is provided, SWAT will perform the operation on that month and day. If the month and day are not specified, the model required a fraction of potential heat units to be specified. As a general rule, if exact dates are available for scheduling operations, these dates should be used. Scheduling by heat units allows the model to time operations as a function of temperature. This method of timing is useful for several situations. When very large watersheds are being simulated where the climate in one portion of the watershed is different enough from the climate in another section of the watershed

152 CHAPTER 17: SWAT EQUATIONS GROWTH CYCLE 131 to affect timing of operations, heat unit scheduling may be beneficial. By using heat unit scheduling, only one generic management file has to be made for a given land use. This generic set of operations can then be used wherever the land use is found in the watershed. Also, in areas where the climate can vary greatly from year to year, heat unit scheduling will allow the model to adjust the timing of operations to the weather conditions for each year. To schedule by heat units, the timing of the operations are expressed as fractions of the potential heat units for the plant or fraction of maturity. Let us use the following example for corn in Illinois. Date Operation Heat Units Accumulated Fraction of PHU April 24 Tandem disk April 30 Tandem disk May 7 Field cultivator May 15 Plant corn (PHU = 1456) 0.00 June 3 Row cultivator June 17 Row cultivator October 15 Harvest & Kill October 29 Tandem disk November 5 Chisel The number of heat units accumulated for the different operation timings is calculated by summing the heat units for every day starting with the planting date (May 15) and ending with the day the operation takes place. To calculate the fraction of PHU at which the operation takes place, the heat units accumulated is divided by the PHU for the crop (1456). Note that the fraction of PHU for the harvest operation is The fraction is greater than 1.0 because corn is allowed to dry down prior to harvesting. The model will simulate plant growth until the crop reaches maturity (where maturity is defined as PHU = 1456). From that point on, the plant will cease to transpire and uptake nutrients and water and will stand in the HRU until converted to residue or harvested. While the operations after planting have been scheduled by fraction of PHU, the operations that occur during periods when no crop is growing must still be scheduled. (This includes the planting operation.) To schedule these operations, SWAT keeps track of a second heat index where heat units are

153 132 SWAT USER'S MANUAL, VERSION 2000 summed over the entire year using T base = 0 C. This heat index is solely a function of the climate and is termed the base zero heat index. For the base zero index, the heat units accumulated on a given day are: HU 0 = T av when T av > 0 C where HU 0 is the number of base zero heat units accumulated on a given day (heat units), and units for the year is calculated: T av is the mean daily temperature ( C). The total number of heat 365 PHU = HU d = 1 0 where PHU 0 is the total base zero heat units (heat units), HU 0 is the number of base zero heat units accumulated on day d where d = 1 on January 1 and 365 on December 31. Unlike the plant PHU which must be provided by the user, PHU 0 is calculated by SWAT using long-term weather data provided in the.wgn file. For the example watershed in Illinois, PHU 0 = The remaining heat unit fractions in the example are calculated using this value for potential heat units. Date Operation Base Zero Heat Units Accumulated Plant Heat Units Accumulated Fraction of PHU 0 (PHU 0 = 4050) Fraction of PHU (PHU = 1456) April 24 Tandem disk April 30 Tandem disk May 7 Field cultivator May 15 Plant corn (PHU = 1456) June 3 Row cultivator June 17 Row cultivator October 15 Harvest & Kill October 29 Tandem disk November 5 Chisel As stated previously, SWAT always keeps track of base zero heat units. The base zero heat unit scheduling is used any time there are no plants growing in the HRU (before and including the plant operation and after the kill operation). Once plant growth is initiated, the model switches to plant heat unit scheduling until the plant is killed.

154 CHAPTER 17: SWAT EQUATIONS GROWTH CYCLE 133 The following heat unit fractions have been found to provide reasonable timings for the specified operations: 0.15 planting 1.0 harvest/kill for crops with no dry-down 1.2 harvest/kill for crops with dry-down 0.6 hay cutting operation Table 17-1: SWAT input variables that pertain to heat units. Variable Name Definition Input File PHU PHU: potential heat units for plant that is growing at the beginning of.mgt the simulation in an HRU HEAT UNITS PHU: potential heat units for plant whose growth is initiated with a.mgt planting operation. HUSC Fraction of potential heat units at which operation takes place..mgt T_BASE T base : Minimum temperature for plant growth ( C) crop.dat 17.2 PLANTING/BEGINNING OF GROWING SEASON The plant operation initiates plant growth. This operation can be used to designate the time of planting for agricultural crops or the initiation of plant growth in the spring for a land cover that require several years to reach maturity (forests, orchards, etc.). The plant operation will be performed by SWAT only when no land cover is growing in an HRU. Before planting a new land cover, the previous land cover must be removed with a kill operation or a harvest and kill operation. If two plant operations are placed in the management file and the first land cover is not killed prior to the second plant operation, the second plant operation is ignored by the model. This means that agricultural systems in which two crops are grown simultaneously cannot be modeled by SWAT. Information required in the plant operation includes the timing of the operation (month and day or fraction of base zero potential heat units), the total number of heat units required for the land cover to reach maturity, and the specific land cover to be simulated in the HRU. If the land cover is being transplanted, the leaf area index and biomass for the land cover at the time of transplanting must be provided. Also, for transplanted land covers, the total

155 134 SWAT USER'S MANUAL, VERSION 2000 number of heat units for the land cover to reach maturity should be from the period the land cover is transplanted to maturity (not from seed generation). The user has the option of varying the curve number in the HRU throughout the year. New curve number values may be entered in a plant operation, tillage operation and harvest and kill operation. The curve number entered for these operations are for moisture condition II. SWAT adjusts the entered value daily to reflect change in water content. For simulations where a certain amount of crop yield and biomass is required, the user can force the model to meet this amount by setting a harvest index target and a biomass target. These targets are effective only if a harvest and kill operation is used to harvest the crop HARVEST OPERATION The harvest operation will remove plant biomass without killing the plant. This operation is most commonly used to cut hay or grass. The only information required by the harvest operation is the date. However, the harvest index override is usually required for hay or grass cuttings. When no harvest index override is specified, SWAT uses the plant harvest index from the plant growth database to set the fraction of biomass removed. The plant harvest index in the plant growth database is usually set to the fraction of the plant biomass partitioned into seed. For grasses, this fraction is typically 1 to 2 % of the total biomass. If no harvest index override is provided in a harvest operation for one of these grasses, SWAT will remove only 1 or 2 % of the total biomass. A more realistic value would be 60-80% of the plant biomass. A harvest efficiency may also be defined for the operation. This value specifies the fraction of harvested plant biomass removed from the HRU. The remaining fraction is converted to residue in the HRU. If the harvest efficiency is left blank or set to zero, the model assumes this feature is not being used and removes 100% of the harvested biomass (no biomass is converted to residue). After biomass is removed in a harvest operation, the plant s leaf area index and accumulated heat units are set back by the fraction of biomass removed.

156 CHAPTER 17: SWAT EQUATIONS GROWTH CYCLE 135 Reducing the number of accumulated heat units shifts the plant s development to an earlier period in which growth is usually occurring at a faster rate GRAZING OPERATION The grazing operation simulates plant biomass removal and manure deposition over a specified period of time. This operation is used to simulate pasture or range grazed by animals. Information required in the grazing operation includes the time during the year at which grazing begins (month and day or fraction of plant potential heat units), the length of the grazing period, the amount of biomass removed daily, the amount of manure deposited daily, and the type of manure deposited. The amount of biomass trampled is an optional input. Biomass removal in the grazing operation is similar to that in the harvest operation. However, instead of a fraction of biomass being specified, an absolute amount to be removed every day is given. In some conditions, this can result in a reduction of the plant biomass to a very low level that will result in increased erosion in the HRU. To prevent this, a minimum plant biomass for grazing may be specified (BIO_MIN in the second line of the management file). When the plant biomass falls below the amount specified for BIO_MIN, the model will not graze, trample, or apply manure in the HRU on that day. If the user specifies an amount of biomass to be removed daily by trampling, this biomass is converted to residue. Removal of biomass by trampling was an option added at the request of a user. We have not performed any literature reviews to evaluate the significance of this process. Nutrient fractions of the manure applied during grazing must be stored in the fertilizer database. The manure nutrient loadings are added to the topmost 10 mm of soil. This is the portion of the soil with which surface runoff interacts. After biomass is removed by grazing and/or trampling, the plant s leaf area index and accumulated heat units are set back by the fraction of biomass removed.

157 136 SWAT USER'S MANUAL, VERSION HARVEST & KILL OPERATION The harvest and kill operation stops plant growth in the HRU. The fraction of biomass specified in the land cover s harvest index (in the plant growth database) is removed from the HRU as yield. The remaining fraction of plant biomass is converted to residue. The only information required by the harvest and kill operation is the timing of the operation (month and day or fraction of plant potential heat units). The user also has the option of updating the moisture condition II curve number in this operation KILL/END OF GROWING SEASON The kill operation stops plant growth in the HRU. All plant biomass is converted to residue. The only information required by the kill operation is the timing of the operation (month and day or fraction of plant potential heat units) DORMANCY Plant dormancy is controlled by daylength. When the daylength is within one hour of the minimum daylength, SWAT allows trees, perennials and cool season annuals to go dormant. During the dormant period, no plant growth occurs. The plants come out of dormancy once the daylength exceeds the minimum daylength by more than one hour. At the beginning of the dormant period for trees, leaf biomass is converted to residue and the leaf area index for the tree species is set to the minimum value allowed (defined in the plant growth database). At the beginning of the dormant period for perennials, 95% of the biomass is converted to residue and the leaf area index for the species is set to the minimum value allowed. For cool season annuals, none of the biomass is converted to residue.

158 17.8 PLANT TYPES CHAPTER 17: SWAT EQUATIONS GROWTH CYCLE 137 SWAT categorizes plants into seven different types: warm season annual legume, cold season annual legume, perennial legume, warm season annual, cold season annual, perennial and trees. The differences between the different plant types, as modeled by SWAT, are as follows: 1 warm season annual legume: simulate nitrogen fixation root depth varies during growing season due to root growth 2 cold season annual legume: simulate nitrogen fixation root depth varies during growing season due to root growth fall-planted land covers will go dormant during period where the daylength is within 1 hour of the minimum daylength for the HRU 3 perennial legume: simulate nitrogen fixation root depth always equal to the maximum allowed for the plant species and soil plant goes dormant at end of growing period 4 warm season annual: root depth varies during growing season due to root growth 5 cold season annual: root depth varies during growing season due to root growth fall-planted land covers will go dormant during period where the daylength is within 1 hour of the minimum daylength for the HRU 6 perennial: root depth always equal to the maximum allowed for the plant species and soil plant goes dormant at end of growing period 7 trees: root depth always equal to the maximum allowed for the plant species and soil partition new growth between leaves/needles (30%) and woody growth (70%). At the end of a growing season, only the biomass in the leaf fraction is converted to residue

159 138 SWAT USER'S MANUAL, VERSION NOMENCLATURE HU HU 0 PHU PHU 0 T base T av Number of heat units accumulated on a given day (heat units) Number of base zero heat units accumulated on a given day (heat units) Potential heat units or total heat units required for plant maturity (heat units) Total base zero heat units or potential base zero heat units (heat units) Plant s base or minimum temperature for growth ( C) Mean air temperature for day ( C) REFERENCES Barnard, J.D Heat units as a measure of canning crop maturity. The Canner 106:28. Boswell, V.G Factors influencing yield and quality of peas Biophysical and biochemical studies. Maryland Agr. Exp. Sta. Bul Boswell, V.G The influence of temperature upon the growth and yield of garden peas. Proc. Amer. Soc. Hort. Sci. 23: Cross, H.Z. and M.S. Zuber Prediction of flowering dates in maize based on different methods of estimating thermal units. Agronomy Journal 64: Magoon, C.A. and C.W. Culpepper Response of sweet corn to varying temperatures from time of planting to canning maturity. U.S.D.A. tech. Bull Phillips, E.E Heat summation theory as applied to canning crops. The Canner 27:13-15.

160 CHAPTER 22 EQUATIONS: URBAN AREAS Most large watersheds and river basins contain areas of urban land use. Estimates of the quantity and quality of runoff in urban areas are required for comprehensive management analysis. SWAT calculates runoff from urban areas with the SCS curve number method or the Green & Ampt equation. Loadings of sediment and nutrients are determined using one of two options. The first is a set of linear regression equations developed by the USGS (Driver and Tasker, 1988) for estimating storm runoff volumes and constituent loads. The other option is to simulate the buildup and washoff mechanisms, similar to SWMM - Storm Water Management Model (Huber and Dickinson, 1988). 127

161 128 SWAT USER'S MANUAL, VERSION CHARACTERISTICS OF URBAN AREAS Urban areas differ from rural areas in the fraction of total area that is impervious. Construction of buildings, parking lots and paved roads increases the impervious cover in a watershed and reduces infiltration. With development, the spatial flow pattern of water is altered and the hydraulic efficiency of flow is increased through artificial channels, curbing, and storm drainage and collection systems. The net effect of these changes is an increase in the volume and velocity of runoff and larger peak flood discharges. Impervious areas can be differentiated into two groups: the area that is hydraulically connected to the drainage system and the area that is not directly connected. As an example, assume there is a house surrounded by a yard where runoff from the roof flows into the yard and is able to infiltrate into the soil. The rooftop is impervious but it is not hydraulically connected to the drainage system. In contrast, a parking lot whose runoff enters a storm water drain is hydraulically connected. Table 22-1 lists typical values for impervious and directly connected impervious fractions in different urban land types. Table 22-1: Range and average impervious fractions for different urban land types. Average directly Urban Land Type Average total impervious Range total impervious connected impervious Range directly connected impervious Residential-High Density (> 8 unit/acre or unit/2.5 ha) Residential-Medium Density (1-4 unit/acre or unit/2.5 ha) Residential-Med/Low Density (> unit/acre or unit/2.5 ha) Residential-Low Density (< 0.5 unit/acre or unit/2.5 ha) Commercial Industrial Transportation Institutional During dry periods, dust, dirt and other pollutants build up on the impervious areas. When precipitation events occur and runoff from the impervious areas is generated, the runoff will carry the pollutants as it moves through the drainage system and enters the channel network of the watershed.

162 CHAPTER 22: SWAT EQUATIONS URBAN AREAS SURFACE RUNOFF FROM URBAN AREAS In urban areas, surface runoff is calculated separately for the directly connected impervious area and the disconnected impervious/pervious area. For directly connected impervious areas, a curve number of 98 is always used. For disconnected impervious/pervious areas, a composite curve number is calculated and used in the surface runoff calculations. The equations used to calculate the composite curve number for disconnected impervious/pervious areas are (Soil Conservation Service Engineering Division, 1986): CN CN c c CN = CN = p p 1 imp tot ( 1 imp ) imp imp con dcon con tot + 98 imp 1 imp imp dcon dcon if imp tot if imp > where CN c is the composite moisture condition II curve number, CN p is the pervious moisture condition II curve number, imp tot is the fraction of the HRU area that is impervious (both directly connected and disconnected), imp con is the fraction of the HRU area that is impervious and hydraulically connected to the drainage system, imp dcon is the fraction of the HRU area that is impervious but not hydraulically connected to the drainage system. tot Table 22-2: SWAT input variables that pertain to surface runoff calculations in urban areas. Input Variable Name Definition File CN2 CN p : SCS moisture condition II curve number for pervious areas.mgt CNOP CN p : SCS moisture condition II curve number for pervious areas.mgt specified in plant, harvest/kill and tillage operation FIMP imp tot : fraction of urban land type area that is impervious urban.dat FCIMP imp con : fraction of urban land type area that is connected impervious urban.dat 22.3 USGS REGRESSION EQUATIONS The linear regression models incorporated into SWAT are those described by Driver and Tasker (1988). The regression models were developed from a national urban water quality database that related storm runoff loads to urban

163 130 SWAT USER'S MANUAL, VERSION 2000 physical, land use, and climatic characteristics. USGS developed these equations to predict loadings in ungaged urban watersheds. The regression models calculate loadings as a function of total storm rainfall, drainage area and impervious area. The general equation is β β2 ( R.4) ( DA 2.59) ( ) 1 3 β0 day 25 imp β4 Y = tot where Y is the total constituent load (kg), R day is precipitation on a given day (mm H 2 O), DA is the HRU drainage area (km 2 ), imp tot is the fraction of the total area that is impervious, and the β variables are regression coefficients. The regression equations were developed in English units, so conversion factors were incorporated to adapt the equations to metric units: 25.4 mm/inch, 2.59 km 2 /mi 2, and lb/kg. USGS derived three different sets of regression coefficients that are based on annual precipitation. Category I coefficients are used in watersheds with less than 508 mm of annual precipitation. Category II coefficients are used in watersheds with annual precipitation between 508 and 1016 mm. Category III coefficients are used in watersheds with annual precipitation greater than 1016 mm. SWAT determines the annual precipitation category for each subbasin by summing the monthly precipitation totals provided in the weather generator input file. Regression coefficients were derived to estimate suspended solid load, total nitrogen load, total phosphorus load and carbonaceous oxygen demand (COD). SWAT calculates suspended solid, total nitrogen, and total phosphorus loadings (the carbonaceous oxygen demand is not currently calculated). Regression coefficients for these constituents are listed in Table Once total nitrogen and phosphorus loads are calculated, they are partitioned into organic and mineral forms using the following relationships from Northern Virginia Planning District Commission (1979). Total nitrogen loads consist of 70 percent organic nitrogen and 30 percent mineral (nitrate). Total phosphorus loads are divided into 75 percent organic phosphorus and 25 percent orthophosphate. β

164 CHAPTER 22: SWAT EQUATIONS URBAN AREAS 131 Table 22-3: Urban regression coefficients (from Driver and Tasker, 1988). Precipitation Loading Category β 0 β 1 β 2 β 3 β 4 suspended solids I II III total nitrogen I II III total phosphorus I II III COD I II III I = annual precipitation < 508 mm II = 508 mm < annual precipitation < 1,016 mm III = annual precipitation > 1,016 mm Table 22-4: SWAT input variables that pertain to urban modeling with regression equations. Input Variable Name Definition File IURBAN Urban simulation code.hru URBLU Urban land type identification number from urban database.hru FIMP Fraction of HRU that is impervious. imp tot = FIMP 100 urban.dat PRECIPITATION R day : Precipitation on a given day (mm H 2 O).pcp HRU_FR Fraction of total watershed area in HRU.hru DA_KM Area of watershed (km 2 ).bsn PCPMM(mon) Average amount of precipitation falling in month (mm H 2 O).wgn 22.4 BUILD UP/WASH OFF In an impervious area, dust, dirt and other constituents are built up on street surfaces in periods of dry weather preceding a storm. Build up may be a function of time, traffic flow, dry fallout and street sweeping. During a storm runoff event, the material is then washed off into the drainage system. Although the build up/wash off option is conceptually appealing, the reliability and credibility of the simulation may be difficult to establish without local data for calibration and validation (Huber and Dickinson, 1988). When the build up/wash off option is used in SWAT, the urban hydrologic response unit (HRU) is divided into pervious and impervious areas. Management operations other than sweep operations are performed in the pervious portion of

165 132 SWAT USER'S MANUAL, VERSION 2000 the HRU. Sweep operations impact build up of solids in the impervious portion of the HRU. For the pervious portion of the HRU, sediment and nutrient loadings are calculated using the methodology summarized in Chapters 13 and 14. The impervious portion of the HRU uses the build up/wash off algorithm to determine sediment and nutrient loadings. The build up/wash off algorithm calculates the build up and wash off of solids. The solids are assumed to possess a constant concentration of organic and mineral nitrogen and phosphorus where the concentrations are a function of the urban land type. Build up of solids is simulated on dry days with a Michaelis-Menton equation taken from Roesner (1982): SEDmx td SED = ( t + td ) half where SED is the solid build up (kg/curb km) td days after the last occurrence of SED = 0 kg/curb km, SED mx is the maximum accumulation of solids possible for the urban land type (kg/curb km), and t half is the length of time needed for solid build up to increase from 0 kg/curb km to ½ SED mx (days). A dry day is defined as a day with surface runoff less than 0.1 mm. An example build-up curve is shown in Figure As can be seen from the plot, the Michaelis-Menton function will initially rise steeply and then approach the asymptote slowly Figure 22-1: Build-up function for solids in urban areas.

166 CHAPTER 22: SWAT EQUATIONS URBAN AREAS 133 The two parameters that determine the shape of this curve are SED mx and t half. These parameters are a function of the urban land type. Wash off is the process of erosion or solution of constituents from an impervious surface during a runoff event. An exponential relationship is used to simulate the wash off process (Huber and Dickinson, 1988): t ( e kk ) Ysed = SED where Y sed is the cumulative amount of solids washed off at time t (kg/curb km), SED 0 is the amount of solids built up on the impervious area at the beginning of the precipitation event (kg/curb km), and kk is a coefficient. The coefficient, kk, may be estimated by assuming it is proportional to the peak runoff rate: kk = urb coef q peak where urb coef is the wash off coefficient (mm -1 ) and q peak is the peak runoff rate (mm/hr). The original default value for urb coef was calculated as 0.18 mm -1 by assuming that 13 mm of total runoff in one hour would wash off 90% of the initial surface load. Later estimates of urb coef gave values ranging from mm -1. Huber and Dickinson (1988) noted that values between and mm -1 for urb coef give sediment concentrations in the range of most observed values. They also recommended using this variable to calibrate the model to observed data. To convert the sediment loading from units of kg/curb km to kg/ha, the amount of sediment removed by wash off is multiplied by the curb length density. The curb length density is a function of the urban land type. Nitrogen and phosphorus loadings from the impervious portion of the urban land area are calculated by multiplying the concentration of nutrient by the sediment loading STREET CLEANING Street cleaning is performed in urban areas to control buildup of solids and trash. While it has long been thought that street cleaning has a beneficial effect on the quality of urban runoff, studies by EPA have found that street sweeping has

167 134 SWAT USER'S MANUAL, VERSION 2000 little impact on runoff quality unless it is performed every day (U.S. Environmental Protection Agency, 1983). SWAT performs street sweeping operations only when the build up/wash off algorithm is specified for urban loading calculations. Street sweeping is performed only on dry days, where a dry day is defined as a day with less than 0.1 mm of surface runoff. The sweeping removal equation (Huber and Dickinson, 1988) is: ( fr reff ) SED = SED0 1 av where SED is amount of solids remaining after sweeping (kg/curb km), SED 0 is the amount of solids present prior to sweeping (kg/curb km), fr av is the fraction of the curb length available for sweeping (the availability factor), and reff is the removal efficiency of the sweeping equipment. The availability factor and removal efficiency are specified by the user. Table 22-5: Removal efficiencies (fraction removed) from street cleaner path (from Pitt, 1979) Street Cleaning Program and Total BOD 5 COD KN PO 4 Pesticides Street Surface Loading Conditions Solids Vacuum Street Cleaner ( kg/curb km) 1 pass passes passes Vacuum Street Cleaner ( kg/curb km) Vacuum Street Cleaner ( kg/curb km) Mechanical Street Cleaner ( kg/curb km) 1 pass passes passes pass passes passes pass passes passes Flusher.30 a a a a a Mechanical Street Cleaner followed by a Flusher.80 b b b b b a: efficiency fraction estimated.15 to.40 b: efficiency fraction estimated.35 to 1.00

168 CHAPTER 22: SWAT EQUATIONS URBAN AREAS 135 The availability factor, fr av, is the fraction of the curb length that is sweepable. The entire curb length is often not available for sweeping due to the presence of cars and other obstacles. The removal efficiency of street sweeping is a function of the type of sweeper, whether flushing is a part of the street cleaning process, the quantity of total solids, the frequency of rainfall events and the constituents considered. Removal efficiency can vary depending on the constituent being considered, with efficiencies being greater for particulate constituents. The removal efficiencies for nitrogen and phosphorus are typically less than the solid removal efficiency (Pitt, 1979). Because SWAT assumes a set concentration of nutrient constituents in the solids, the same removal efficiency is in effect used for all constituents. Table 22-5 provides removal efficiencies for various street cleaning programs. Table 22-6: SWAT input variables that pertain to build up/wash off. Variable Name Definition Input File IURBAN Urban simulation code.hru URBLU Urban land type identification number from urban database.hru DIRTMX SED mx : maximum amount of solids allowed to build up on urban.dat impervious areas (kg/curb km) THALF t half : number of days for amount of solids on impervious area to urban.dat build up from 0 kg/curb km to ½ SED mx URBCOEF urb coef : wash off coefficient (mm -1 ) urban.dat CURBDEN curb length density in urban land type (km/ha) urban.dat TNCONC concentration of total nitrogen in suspended solid load (mg N/kg) urban.dat TPCONC concentration of total phosphorus in suspended solid load (mg urban.dat N/kg) TNO3CONC concentration of nitrate in suspended solid load (mg N/kg) urban.dat SWEEPEFF reff: removal efficiency of the sweeping equipment.mgt AVWSP fr av : fraction of the curb length that is sweepable..mgt 22.5 NOMENCLATURE CN Curve number DA HRU drainage area (km 2 ) R day Amount of rainfall on a given day (mm H 2 O) SED Solid build up (kg/curb km) SED mx Maximum accumulation of solids possible for the urban land type (kg/curb km) Y Total constituent load (kg) Cumulative amount of solids washed off at time t (kg/curb km) Y sed

169 fr av imp con 136 SWAT USER'S MANUAL, VERSION 2000 Fraction of the curb length available for sweeping (the availability factor) Fraction of the HRU area that is impervious and hydraulically connected to the drainage system imp dcon Fraction of the HRU area that is impervious but not hydraulically connected to the drainage system imp tot Fraction of the HRU area that is impervious (both connected and disconnected) kk Coefficient in urban wash off equation q peak Peak runoff rate (mm/hr) reff Removal efficiency of the sweeping equipment t half Length of time needed for solid build up to increase from 0 kg/curb km to ½ SED mx (days) urb coef Wash off coefficient (mm -1 ) β 0 β 1 β 2 β 3 β 4 Coefficient for USGS regression equations for urban loadings Coefficient for USGS regression equations for urban loadings Coefficient for USGS regression equations for urban loadings Coefficient for USGS regression equations for urban loadings Coefficient for USGS regression equations for urban loadings 22.6 REFERENCES Driver and Tasker Huber, W.C. and R.E. Dickinson Storm water management model, version 4: user s manual. U.S. Environmental Protection Agency, Athens, GA. Northern Virginia Planning District Commission Guidebook for screening urban nonpoint pollution management strategies: a final report prepared for Metropolitan Washington Council of Governments. Northern Virginia Planning District Commission, Falls Church, VA. Pitt, R Demonstration of non-point pollution abatement through improved street cleaning practices. EPA-600/ (NTIS PB ), U.S. Environmental Protection Agency, Cincinnati, OH. Roesner Soil Conservation Service Engineering Division Urban hydrology for small watersheds. U.S. Department of Agriculture, Technical Release 55. U.S. Environmental Protection Agency Results of the nationwide urban runoff program; Volume 1 final report. NTIS PB , U.S. Environmental Protection Agency, Washington, D.C.

170 MAIN CHANNEL PROCESSES Flow in a watershed is classified as overland or channelized. The primary difference between the two flow processes is that water storage and its influence on flow rates is considered in channelized flow. Main channel processes modeled by SWAT include the movement of water, sediment and other constituents (e.g. nutrients, pesticides) in the stream network, in-stream nutrient cycling, and in-stream pesticide transformations. Optional processes include the change in channel dimensions with time due to downcutting and widening.

171 CHAPTER 23 EQUATIONS: WATER ROUTING Open channel flow is defined as channel flow with a free surface, such as flow in a river or partially full pipe. SWAT uses Manning s equation to define the rate and velocity of flow. Water is routed through the channel network using the variable storage routing method or the Muskingum river routing method. Both the variable storage and Muskingum routing methods are variations of the kinematic wave model. A detailed discussion of the kinematic wave flood routing model can be found in Chow et al. (1988). 127

172 128 SWAT USER'S MANUAL, VERSION CHANNEL CHARACTERISTICS SWAT assumes the main channels, or reaches, have a trapezoidal shape (Figure 23-1). Figure 23-1: Trapezoidal channel dimensions Users are required to define the width and depth of the channel when filled to the top of the bank as well as the channel length, slope along the channel length and Manning s n value. SWAT assumes the channel sides have a 2:1 run to rise ratio (z ch = 2). The slope of the channel sides is then ½ or 0.5. The bottom width is calculated from the bankfull width and depth with the equation: W btm = W 2 z depth bnkfull ch bnkfull where W btm is the bottom width of the channel (m), W bnkfull is the top width of the channel when filled with water (m), z ch is the inverse of the channel side slope, and depth bnkfull is the depth of water in the channel when filled to the top of the bank (m). Because of the assumption that z ch = 2, it is possible for the bottom width calculated with equation to be less than or equal to zero. If this occurs, the model sets W btm = 0. 5 W and calculates a new value for the bnkfull channel side slope run by solving equation for z ch : z ( W W ) bnkfull btm ch = depthbnkfull For a given depth of water in the channel, the width of the channel at water level is:

173 CHAPTER 23: SWAT EQUATIONS WATER ROUTING 129 W = W + 2 z depth btm ch where W is the width of the channel at water level (m), W btm is the bottom width of the channel (m), z ch is the inverse of the channel slope, and depth is the depth of water in the channel (m). The cross-sectional area of flow is calculated: A ch ( W + z depth) depth = btm ch where A ch is the cross-sectional area of flow in the channel (m 2 ), W btm is the bottom width of the channel (m), z ch is the inverse of the channel slope, and depth is the depth of water in the channel (m). The wetted perimeter of the channel is defined as ch btm 2 2 depth 1 zch P = W where P ch is the wetted perimeter for a given depth of flow (m). The hydraulic radius of the channel is calculated A ch R ch = Pch where R ch is the hydraulic radius for a given depth of flow (m), A ch is the crosssectional area of flow in the channel (m 2 ), and P ch is the wetted perimeter for a given depth of flow (m). The volume of water held in the channel is V ch = 1000 L A ch ch where V ch is the volume of water stored in the channel (m 3 ), L ch is the channel length (km), and A ch is the cross-sectional area of flow in the channel for a given depth of water (m 2 ). When the volume of water in the reach exceeds the maximum amount that can be held by the channel, the excess water spreads across the flood plain. The flood plain dimensions used by SWAT are shown in Figure Figure 23-2: Illustration of flood plain dimensions.

174 130 SWAT USER'S MANUAL, VERSION 2000 The bottom width of the floodplain, W btm,fld, is W, = 5 W. SWAT btm fld bnkfull assumes the flood plain side slopes have a 4:1 run to rise ratio (z fld = 4). The slope of the flood plain sides is then ¼ or When flow is present in the flood plain, the calculation of the flow depth, cross-sectional flow area and wetting perimeter is a sum of the channel and floodplain components: depth = depth bnkfull + depth fld A ch ( Wbtm + zch depthbnkfull ) depthbnkfull + ( Wbtm fld + z fld depth fld ) depth fld =, ch btm depthbnkfull 1 + zch + 4 Wbnkfull + 2 depth fld 1 z fld P = W where depth is the total depth of water (m), depth bnkfull is the depth of water in the channel when filled to the top of the bank (m), depth fld is the depth of water in the flood plain (m), A ch is the cross-sectional area of flow for a given depth of water (m 2 ), W btm is the bottom width of the channel (m), z ch is the inverse of the channel side slope, W btm,fld is the bottom width of the flood plain (m), z fld is the inverse of the flood plain side slope, P ch is the wetted perimeter for a given depth of flow (m), and W bnkfull is the top width of the channel when filled with water (m). Table 23-1: SWAT input variables that pertain to channel dimension calculations. Variable name Definition File Name CH_W(2) W bnkfull : Width of channel at top of bank (m).rte CH_D depth bnkfull : Depth of water in channel when filled to bank (m).rte CH_L(2) L ch : Length of main channel (km).rte 23.2 FLOW RATE AND VELOCITY Manning s equation for uniform flow in a channel is used to calculate the rate and velocity of flow in a reach segment for a given time step: q ch Ach Rch slpch = n Rch slpch vc = n

175 CHAPTER 23: SWAT EQUATIONS WATER ROUTING 131 where q ch is the rate of flow in the channel (m 3 /s), A ch is the cross-sectional area of flow in the channel (m 2 ), R ch is the hydraulic radius for a given depth of flow (m), slp ch is the slope along the channel length (m/m), n is Manning s n coefficient for the channel, and v c is the flow velocity (m/s). SWAT routes water as a volume. The daily value for cross-sectional area of flow, A ch, is calculated by rearranging equation to solve for the area: A V ch ch = Lch where A ch is the cross-sectional area of flow in the channel for a given depth of water (m 2 ), V ch is the volume of water stored in the channel (m 3 ), and L ch is the channel length (km). Equation is rearranged to calculate the depth of flow for a given time step: depth = A z ch ch W + 2 z btm ch 2 W 2 z btm ch where depth is the depth of flow (m), A ch is the cross-sectional area of flow in the channel for a given depth of water (m 2 ), W btm is the bottom width of the channel (m), and z ch is the inverse of the channel side slope. Equation is valid only when all water is contained in the channel. If the volume of water in the reach segment has filled the channel and is in the flood plain, the depth is calculated: depth = depth bnkfull + ( A A ) ch z ch, bnkfull fld W + 2 z btm, fld fld 2 W 2 z btm, fld fld where depth is the depth of flow (m), depth bnkfull is the depth of water in the channel when filled to the top of the bank (m), A ch is the cross-sectional area of flow in the channel for a given depth of water (m 2 ), A ch,bnkfull is the cross-sectional area of flow in the channel when filled to the top of the bank (m 2 ), W btm,fld is the bottom width of the flood plain (m), and z fld is the inverse of the flood plain side slope. Once the depth is known, the wetting perimeter and hydraulic radius are calculated using equations (or ) and At this point, all values

176 132 SWAT USER'S MANUAL, VERSION 2000 required to calculate the flow rate and velocity are known and equations and can be solved. Table 23-2: SWAT input variables that pertain to channel flow calculations. Variable name Definition File Name CH_S(2) slp ch : Average channel slope along channel length (m m -1 ).rte CH_N(2) n: Manning s n value for the main channel.rte CH_L(2) L ch : Length of main channel (km).rte 23.3 VARIABLE STORAGE ROUTING METHOD The variable storage routing method was developed by Williams (1969) and used in the HYMO (Williams and Hann, 1973) and ROTO (Arnold et al., 1995) models. For a given reach segment, storage routing is based on the continuity equation: V in V = V out stored where V in is the volume of inflow during the time step (m 3 H 2 O), V out is the volume of outflow during the time step (m 3 H 2 O), and V stored is the change in volume of storage during the time step (m 3 H 2 O). This equation can be written as t q + q in,1 in,2 out,1 out,2 stored,2 stored, t q + q 2 = V where t is the length of the time step (s), q in,1 is the inflow rate at the beginning of the time step (m 3 /s), q in,2 is the inflow rate at the end of the time step (m 3 /s), q out,1 is the outflow rate at the beginning of the time step (m 3 /s), q out,2 is the outflow rate at the end of the time step (m 3 /s), V stored,1 is the storage volume at the beginning of the time step (m 3 H 2 O), and V stored,2 is the storage volume at the end of the time step (m 3 H 2 O). Rearranging equation so that all known variables are on the left side of the equation, Vstored,1 qout,1 Vstored,2 qout,2 q in, ave + = t 2 t 2 V where q in,ave is the average inflow rate during the time step: q in, ave qin,1 + qin,2 =. 2

177 CHAPTER 23: SWAT EQUATIONS WATER ROUTING 133 Travel time is computed by dividing the volume of water in the channel by the flow rate. V V V TT = stored stored,1 stored,2 = = qout qout,1 qout,2 where TT is the travel time (s), V stored is the storage volume (m 3 H 2 O), and q out is the discharge rate (m 3 /s). To obtain a relationship between travel time and the storage coefficient, equation is substituted into equation : Vstored,1 qout,1 Vstored,2 qout,2 q in, ave + = t V 2 2 stored,1 t Vstored,2 TT q out,1 TT q out,2 which simplifies to 2 t 2 t qout,2 = qin, ave + 1 qout, TT + t 2 TT + t This equation is similar to the coefficient method equation q ( SC) q, 1 = SC q out, 2 in, ave 1 out where SC is the storage coefficient. Equation is the basis for the SCS convex routing method (SCS, 1964) and the Muskingum method (Brakensiek, 1967; Overton, 1966). From equation , the storage coefficient in equation is defined as 2 t SC = TT + t It can be shown that Vstored ( 1 SC) qout = SC t Substituting this into equation gives Vstored,1 qout, 2 = SC qin, ave t To express all values in units of volume, both sides of the equation are multiplied by the time step ( V V ) V = SC out, 2 in stored,1

178 134 SWAT USER'S MANUAL, VERSION MUSKINGUM ROUTING METHOD The Muskingum routing method models the storage volume in a channel length as a combination of wedge and prism storages (Figure 23-3). Figure 23-3: Prism and wedge storages in a reach segment (from Chow et al., 1988) When a flood wave advances into a reach segment, inflow exceeds outflow and a wedge of storage is produced. As the flood wave recedes, outflow exceeds inflow in the reach segment and a negative wedge is produced. In addition to the wedge storage, the reach segment contains a prism of storage formed by a volume of constant cross-section along the reach length. As defined by Manning s equation (equation ), the cross-sectional area of flow is assumed to be directly proportional to the discharge for a given reach segment. Using this assumption, the volume of prism storage can be expressed as a function of the discharge, K qout, where K is the ratio of storage to discharge and has the dimension of time. In a similar manner, the volume of wedge storage can be expressed as K X ( ) q in q out, where X is a weighting factor that controls the relative importance of inflow and outflow in determining the storage in a reach. Summing these terms gives a value for total storage

179 V stored out CHAPTER 23: SWAT EQUATIONS WATER ROUTING 135 ( q q ) = K q + K X in out where V stored is the storage volume (m 3 H 2 O), q in is the inflow rate (m 3 /s), q out is the discharge rate (m 3 /s), K is the storage time constant for the reach (s), and X is the weighting factor. This equation can be rearranged to the form V stored ( X q + ( X ) q ) = K in out This format is similar to equation The weighting factor, X, has a lower limit of 0.0 and an upper limit of 0.5. This factor is a function of the wedge storage. For reservoir-type storage, there is no wedge and X = 0.0. For a full-wedge, X = 0.5. For rivers, X will fall between 0.0 and 0.3 with a mean value near 0.2. The definition for storage volume in equation can be incorporated into the continuity equation (equation ) and simplified to q = C q + C q + C q out, 2 1 in,2 2 in,1 3 out,1 where q in,1 is the inflow rate at the beginning of the time step (m 3 /s), q in,2 is the inflow rate at the end of the time step (m 3 /s), q out,1 is the outflow rate at the beginning of the time step (m 3 /s), q out,2 is the outflow rate at the end of the time step (m 3 /s), and t 2 K X C1 = K ( 1 X ) + t t + 2 K X C2 = K ( 1 X ) + t ( 1 X ) t ( 1 X ) + t 2 K C3 = K where C + C + C 1. To express all values in units of volume, both sides of = equation are multiplied by the time step V = C V + C V + C V out, 2 1 in,2 2 in,1 3 out,1 To maintain numerical stability and avoid the computation of negative outflows, the following condition must be met: ( X ) 2 K X < t < 2 K

180 136 SWAT USER'S MANUAL, VERSION 2000 The value for the weighting factor, X, is input by the user. The value for the storage time constant is estimated as: K coef1 Kbnkfull + coef 2 K0. 1bnkfull = where K is the storage time constant for the reach segment (s), coef 1 and coef 2 are weighting coefficients input by the user, K bnkfull is the storage time constant calculated for the reach segment with bankfull flows (s), and K 0.1bnkfull is the storage time constant calculated for the reach segment with one-tenth of the bankfull flows (s). To calculate K bnkfull and K 0.1bnkfull, an equation developed by Cunge (1969) is used: K L ch = ck where K is the storage time constant (s), L ch is the channel length (km), and c k is the celerity corresponding to the flow for a specified depth (m/s). Celerity is the velocity with which a variation in flow rate travels along the channel. It is defined as d c k = ( qch ) da ch where the flow rate, q ch, is defined by Manning s equation. Differentiating equation with respect to the cross-sectional area gives Rch slp ch 5 c k = = vc 3 n where c k is the celerity (m/s), R ch is the hydraulic radius for a given depth of flow (m), slp ch is the slope along the channel length (m/m), n is Manning s n coefficient for the channel, and v c is the flow velocity (m/s). Table 23-3: SWAT input variables that pertain to Muskingum routing. Variable name Definition File Name MSK_X X: weighting factor.bsn MSK_CO1 coef 1 : weighting factor for influence of normal flow on storage time.bsn constant value MSK_CO2 coef 2 : weighting factor for influence of low flow on storage time constant.bsn

181 23.5 TRANSMISSION LOSSES CHAPTER 23: SWAT EQUATIONS WATER ROUTING 137 The classification of a stream as ephemeral, intermittent or perennial is a function of the amount of groundwater contribution received by the stream. Ephemeral streams contain water during and immediately after a storm event and are dry the rest of the year. Intermittent streams are dry part of the year, but contain flow when the groundwater is high enough as well as during and after a storm event. Perennial streams receive continuous groundwater contributions and flow throughout the year. During periods when a stream receives no groundwater contributions, it is possible for water to be lost from the channel via transmission through the side and bottom of the channel. Transmission losses are estimated with the equation tloss = K TT P L ch ch ch where tloss are the channel transmission losses (m 3 H 2 O), K ch is the effective hydraulic conductivity of the channel alluvium (mm/hr), TT is the flow travel time (hr), P ch is the wetted perimeter (m), and L ch is the channel length (km). Transmission losses from the main channel are assumed to enter bank storage. Typical values for K ch for various alluvium materials are given in Table For perennial streams with continuous groundwater contribution, the effective conductivity will be zero. Table 23-4: Example hydraulic conductivity values for various bed materials (from Lane, 1983). Bed material group Bed material characteristics Hydraulic conductivity 1 Very high loss rate Very clean gravel and large sand > 127 mm/hr 2 High loss rate Clean sand and gravel, field conditions mm/hr 3 Moderately high Sand and gravel mixture with low silt-clay content mm/hr loss rate 4 Moderate loss rate Sand and gravel mixture with high silt-clay content 6-25 mm/hr 5 Consolidated bed material; high silt-clay content mm/hr Insignificant to low loss rate

182 138 SWAT USER'S MANUAL, VERSION 2000 Table 23-5: SWAT input variables that pertain to transmission losses. Variable name Definition File Name CH_K(2) K ch : Effective hydraulic conductivity of channel (mm/hr).rte CH_L(2) L ch : Length of main channel (km).rte 23.6 EVAPORATION LOSSES Evaporation losses from the reach are calculated: E ch = coef E L W fr ev o ch t where E ch is the evaporation from the reach for the day (m 3 H 2 O), coef ev is an evaporation coefficient, E o is potential evaporation (mm H 2 O), L ch is the channel length (km), W is the channel width at water level (m), and fr t is the fraction of the time step in which water is flowing in the channel. The evaporation coefficient is a calibration parameter for the user and is allowed to vary between 0.0 and 1.0. The fraction of the time step in which water is flowing in the channel is calculated by dividing the travel time by the length of the time step. Table 23-6: SWAT input variables that pertain to evaporation losses. Variable name Definition File Name EVRCH coef ev : Reach evaporation adjustment factor.bsn CH_L(2) L ch : Length of main channel (km).rte 23.7 CHANNEL WATER BALANCE Water storage in the reach at the end of the time step is calculated: V + stored, 2 = Vstored, 1 + Vin Vout tloss Ech + div Vbnk where V stored,2 is the volume of water in the reach at the end of the time step (m 3 H 2 O), V stored,1 is the volume of water in the reach at the beginning of the time step (m 3 H 2 O), V in is the volume of water flowing into the reach during the time step (m 3 H 2 O), V out is the volume of water flowing out of the reach during the time step (m 3 H 2 O), tloss is the volume of water lost from the reach via transmission through the bed (m 3 H 2 O), E ch is the evaporation from the reach for the day (m 3

183 CHAPTER 23: SWAT EQUATIONS WATER ROUTING 139 H 2 O), div is the volume of water added or removed from the reach for the day through diversions (m 3 H 2 O), and V bnk is the volume of water added to the reach via return flow from bank storage (m 3 H 2 O). SWAT treats the volume of outflow calculated with equation or as the net amount of water removed from the reach. As transmission losses, evaporation and other water losses for the reach segment are calculated, the amount of outflow to the next reach segment is reduced by the amount of the loss. When outflow and all losses are summed, the total amount will equal the value obtained from or NOMENCLATURE A ch Cross-sectional area of flow in the channel (m 2 ) A ch,bnkfull Cross-sectional area of flow in the channel when filled to the top of the bank (m 2 ) C 1 Coefficient in Muskingum flood routing equation C 2 Coefficient in Muskingum flood routing equation C 3 Coefficient in Muskingum flood routing equation E ch Evaporation from the reach for the day (m 3 H 2 O) E o Potential evapotranspiration (mm d -1 ) K Storage time constant for the reach (s) K 0.1bnkfull Storage time constant calculated for the reach segment with one-tenth of the bankfull flows (s) K bnkfull Storage time constant calculated for the reach segment with bankfull flows (s) K ch Effective hydraulic conductivity of the channel alluvium (mm/hr) L ch Length of main channel (km) P ch Wetted perimeter for a given depth of flow (m) R ch Hydraulic radius for a given depth of flow (m) SC Storage coefficient for variable storage flow routing TT Travel time (s) V bnk Volume of water added to the reach via return flow from bank storage (m 3 H 2 O) V ch Volume of water stored in the channel (m 3 ) V in Volume of inflow during the time step (m 3 H 2 O) V out Volume of outflow during the time step (m 3 H 2 O) V stored Volume of water stored in water body or channel (m 3 H 2 O) W Width of channel at water level (m) W bnkfull Top width of the channel when filled with water (m) W btm Bottom width of the channel (m) W btm,fld Bottom width of the flood plain (m) X Weighting factor in Muskingum routing

184 140 SWAT USER'S MANUAL, VERSION 2000 c k Celerity corresponding to the flow for a specified depth (m/s) coef 1 Weighting coefficient for storage time constant calculation coef 2 Weighting coefficient for storage time constant calculation coef ev Evaporation coefficient depth Depth of water in the channel (m) depth bnkfull Depth of water in the channel when filled to the top of the bank (m) depth fld Depth of water in the flood plain (m) div Volume of water added or removed from the reach for the day through diversions (m 3 H 2 O) fr t Fraction of the time step in which water is flowing in the channel n Manning s roughness coefficient for the subbasin or channel q ch Average channel flow rate (m 3 s -1 ) q in Inflow rate (m 3 /s) q out Outflow rate (m 3 /s) slp ch Average channel slope along channel length (m m -1 ) tloss Channel transmission losses (m 3 H 2 O) v c Average channel velocity (m s -1 ) Z ch Inverse of the channel side slope Inverse of the flood plain side slope Z fld t Length of the time step (s) 23.9 REFERENCES Arnold, J.G., J.R. Williams, and D.R. Maidment Continuous-time water and sediment routing model for large basins. Journal of Hydraulic Engineering 121(2): Brakensiek, D.L Kinematic flood routing. Transactions of the ASAE 10(3): Chow, V.T., D.R. Maidment, and L.W. Mays Applied hydrology. McGraw-Hill, Inc., New York, NY. Cunge, J.A On the subject of a flood propagation method (Muskingum method). J. Hydraulics Research 7(2): Lane, L.J Chapter 19: Transmission Losses. p In Soil Conservation Service. National engineering handbook, section 4: hydrology. U.S. Government Printing Office, Washington, D.C. Overton, D.E Muskingum flood routing of upland streamflow. Journal of Hydrology 4:

185 CHAPTER 23: SWAT EQUATIONS WATER ROUTING 141 Soil Conservation Service Chapter 17: Flood routing, Section 4, Hydrology, National engineering handbook. U.S. Department of Agriculture. U.S. Gov t Printing Office, Washington, D.C. Williams, J.R Flood routing with variable travel time or variable storage coefficients. Transactions of the ASAE 12(1): Williams, J.R. and R.W. Hann HYMO: Problem-oriented language for hydrologic modeling User s manual. USDA, ARS-S-9.

186 142 SWAT USER'S MANUAL, VERSION 2000

187 CHAPTER 29 EQUATIONS: NUTRIENTS IN WATER BODIES SWAT incorporates a simple empirical model to predict the trophic status of water bodies. For studies that require detailed modeling of lake water quality, SWAT has been linked to distributed lake water quality models such as WASP. SWAT defines four different types of water bodies: ponds, wetlands, reservoirs and depressional/impounded areas (potholes). Nutrient processes modeled in ponds, wetlands and reservoirs are identical and are covered in section Nutrient processes modeled in potholes are reviewed in section

188 128 SWAT USER'S MANUAL, VERSION PONDS, WETLANDS, AND RESERVOIRS Ponds, wetlands and reservoirs treat nutrients in the same manner. This section summarizes the processes modeled in these water bodies. When calculating nutrient transformations in a water body, SWAT assumes the system is completely mixed. In a completely mixed system, as nutrients enter the water body they are instantaneously distributed throughout the volume. The assumption of a completely mixed system ignores lake stratification and intensification of phytoplankton in the epilimnion. The initial amount of nitrogen and phosphorus in the water body on the given day is calculated by summing the mass of nutrient entering the water body on that day with the mass of nutrient already present in the water body. M = M + M initial stored flowin where M initial is the initial mass of nutrient in the water body for the given day (kg), M stored is the mass of nutrient in the water body at the end of the previous day (kg), and M flowin is the mass of nutrient added to the water body on the given day (kg). In a similar manner, the initial volume of water in the water body is calculated by summing the volume of water entering the water body on that day with the volume already present in the water body. V = V + V initial stored flowin where V initial is the initial volume of water in the water body for a given day (m 3 H 2 O), V stored is the volume of water in the water body at the end of the previous day (m 3 H 2 O), and V flowin is the volume of water entering the water body on the given day (m 3 H 2 O). The initial concentration of nutrients in the water body is calculated by dividing the initial mass of nutrient by the initial volume of water.

189 CHAPTER 29: SWAT EQUATIONS NUTRIENTS IN WATER BODIES NUTRIENT TRANSFORMATIONS Nutrient transformations simulated in ponds, wetlands and reservoirs are limited to the removal of nutrients by settling. Transformations between nutrient pools (e.g. NO 2 NO 3 NH 4 ) are ignored. Settling losses in the water body can be expressed as a flux of mass across the surface area of the sediment-water interface (Figure 29-1) (Chapra, 1997). Figure 29-1: Settling losses calculated as flux of mass across the sediment-water interface. The mass of nutrient lost via settling is calculated by multiplying the flux by the area of the sediment-water interface. M settling = ν c A dt s where M settling is the mass of nutrient lost via settling on a day (kg), ν is the apparent settling velocity (m/day), A s is the area of the sediment-water interface (m 2 ), c is the initial concentration of nutrient in the water (kg/m 3 H 2 O), and dt is the length of the time step (1 day). The settling velocity is labeled as apparent because it represents the net effect of the different processes that deliver nutrients to the water body s sediments. The water body is assumed to have a uniform depth of water and the area of the sediment-water interface is equivalent to the surface area of the water body. The apparent settling velocity is most commonly reported in units of m/year and this is how the values are input to the model. For natural lakes, measured phosphorus settling velocities most frequently fall in the range of 5 to

190 130 SWAT USER'S MANUAL, VERSION m/year although values less than 1 m/year to over 200 m/year have been reported (Chapra, 1997). Panuska and Robertson (1999) noted that the range in apparent settling velocity values for reservoirs tends to be significantly greater than for natural lakes. Higgins and Kim (1981) reported phosphorus apparent settling velocity values from 90 to 269 m/year for 18 reservoirs in Tennessee with a median value of 42.2 m/year. For 27 Midwestern reservoirs, Walker and Kiihner (1978) reported phosphorus apparent settling velocities ranging from 1 to 125 m/year with an average value of 12.7 m/year. A number of inflow and impoundment properties affect the apparent settling velocity for a water body. Factors of particular importance include the form of phosphorus in the inflow (dissolved or particulate) and the settling velocity of the particulate fraction. Within the impoundment, the mean depth, potential for sediment resuspension and phosphorus release from the sediment will affect the apparent settling velocity (Panuska and Robertson, 1999). Water bodies with high internal phosphorus release tend to possess lower phosphorus retention and lower phosphorus apparent settling velocities than water bodies with low internal phosphorus release (Nürnberg, 1984). Table 29-1 summarizes typical ranges in phosphorus settling velocity for different systems. Table 29-1: Recommended apparent settling velocity values for phosphorus (Panuska and Robertson, 1999) Range in settling velocity Nutrient Dynamics values (m/year) Shallow water bodies with high net internal phosphorus flux ν 0 Water bodies with moderate net internal phosphorus flux 1 < ν < 5 Water bodies with minimal net internal phosphorus flux 5 < ν < 16 Water bodies with high net internal phosphorus removal ν > 16 SWAT input variables that pertain to nutrient settling in ponds, wetlands and reservoirs are listed in Table The model allows the user to define two settling rates for each nutrient and the time of the year during which each settling rate is used. A variation in settling rates is allowed so that impact of temperature and other seasonal factors may be accounted for in the modeling of nutrient settling. To use only one settling rate for the entire year, both variables for the

191 CHAPTER 29: SWAT EQUATIONS NUTRIENTS IN WATER BODIES 131 nutrient may be set to the same value. Setting all variables to zero will cause the model to ignore settling of nutrients in the water body. Table 29-2: SWAT input variables that control settling in ponds, wetlands and reservoirs. Variable Name Definition Input File IPND1 Beginning month of mid-year nutrient settling period for pond and.pnd wetland modeled in subbasin IPND2 Ending month of mid-year nutrient settling period for pond and.pnd wetland modeled in subbasin PSETL1 Phosphorus settling rate in pond during mid-year nutrient settling.pnd period (IPND1 month IPND2) (m/year) PSETL2 Phosphorus settling rate in pond during time outside mid-year nutrient.pnd settling period ( month < IPND1 or month > IPND2) (m/year) NSETL1 Nitrogen settling rate in pond during mid-year nutrient settling period.pnd (IPND1 month IPND2) (m/year) NSETL2 Nitrogen settling rate in pond during time outside mid-year nutrient.pnd settling period ( month < IPND1 or month > IPND2) (m/year) PSETLW1 Phosphorus settling rate in wetland during mid-year nutrient settling.pnd period (IPND1 month IPND2) (m/year) PSETLW2 Phosphorus settling rate in wetland during time outside mid-year.pnd nutrient settling period ( month < IPND1 or month > IPND2) (m/year) NSETLW1 Nitrogen settling rate in wetland during mid-year nutrient settling.pnd period (IPND1 month IPND2) (m/year) NSETLW2 Nitrogen settling rate in wetland during time outside mid-year nutrient.pnd settling period ( month < IPND1 or month > IPND2) (m/year) IRES1 Beginning month of mid-year nutrient settling period for reservoir.lwq IRES2 Ending month of mid-year nutrient settling period for reservoir.lwq PSETLR1 Phosphorus settling rate in reservoir during mid-year nutrient settling.lwq period (IRES1 month IRES2) (m/year) PSETLR2 Phosphorus settling rate in reservoir during time outside mid-year.lwq nutrient settling period ( month < IRES1 or month > IRES2) (m/year) NSETLR1 Nitrogen settling rate in reservoir during mid-year nutrient settling.lwq period (IRES1 month IRES2) (m/year) NSETLR2 Nitrogen settling rate in reservoir during time outside mid-year nutrient settling period ( month < IRES1 or month > IRES2) (m/year).lwq After nutrient losses in the water body are determined, the final concentration of nutrients in the water body is calculated by dividing the final mass of nutrient by the initial volume of water. The concentration of nutrients in outflow from the water body is equivalent to the final concentration of the nutrients in the water body for the day. The mass of nutrient in the outflow is calculated by multiplying the concentration of nutrient in the outflow by the volume of water leaving the water body on that day.

192 132 SWAT USER'S MANUAL, VERSION TOTAL BALANCE Assuming that the volume of the water body remains constant over time, the processes described above (inflow, settling, outflow) can be combined into the following mass balance equation for a well-mixed water body: V dc dt () t Qc νcas = W where V is the volume of the system (m 3 H 2 O), c is the concentration of nutrient in the system (kg/m 3 H 2 O), dt is the length of the time step (1 day), W(t) is the amount of nutrient entering the water body during the day (kg/day), Q is the rate of water flow exiting the water body (m 3 H 2 O/day), ν is the apparent settling velocity (m/day), and A s is the area of the sediment-water interface (m 2 ) EUTROPHICATION Under favorable conditions of light and temperature, excess amounts of nutrients in water can increase the growth of algae and other plants. The result of this growth is an increase in the rate of eutrophication, which is a natural ecological process of change from a nutrient-poor to a nutrient-rich environment. Eutrophication is defined as the process by which a body of water becomes enriched in dissolved nutrients (as phosphates) that stimulate the growth of aquatic plant life, usually resulting in the depletion of dissolved oxygen (Merriam-Webster, Inc., 1996). Nutrient enrichment of moving waters and lakes is a normal result of soil weathering and erosion processes. The gradual evolution of Ice Age lakes into marshes and, eventually, organic soils is a result of eutrophication. However, this process can be accelerated by the discharge of wastes containing high levels of nutrients into lakes or rivers. One example of this is Lake Erie, which is estimated to have aged the equivalent of 150 natural years in a 15-year span of accelerated eutrophication. Excessive plant growth caused by accelerated eutrophication can lead to stagnation of the water. The stagnation is caused by an increased biological oxygen demand created by decaying plant remains. The result of this increased

193 CHAPTER 29: SWAT EQUATIONS NUTRIENTS IN WATER BODIES 133 oxygen demand is a tendency toward anaerobic conditions and the inability of the water body to support fish and other aerobic organisms. Nitrogen, carbon and phosphorus are essential to the growth of aquatic biota. Due to the difficulty of controlling the exchange of nitrogen and carbon between the atmosphere and water and fixation of atmospheric nitrogen by some blue-green algae, attempts to mitigate eutrophication have focused on phosphorus inputs. In fresh-water systems, phosphorus is often the limiting element. By controlling phosphorus loading, accelerated eutrophication of lake waters can be reduced. In systems where phosphorus is the primary, controllable limiting nutrient of water body eutrophication, the amount of phosphorus present in the water body can be used to estimate the amount of eutrophication present in the water body PHOSPHORUS/CHLOROPHYLL a CORRELATIONS A number of empirically derived equations have been developed to calculate chlorophyll a level as a function of total phosphorus concentration. SWAT uses an equation developed by Rast and Lee (1978) to calculate the chlorophyll a concentration in the water body Chla = 0.551p where Chla is the chlorophyll a concentration (µg/l) and p is the total phosphorus concentration (µg/l). The equation has been modified to include a user-defined coefficient: Chla 0.76 = Chlaco 0.551p The user-defined coefficient, Chla co, is included to allow the user to adjust the predicted chlorophyll a concentration for limitations of nutrients other than phosphorus. When Chla co is set to 1.00, equation is equivalent to equation For most water bodies, the original equation will be adequate. SWAT input variables that pertain to chlorophyll a calculations in ponds, wetlands and reservoirs are listed in Table 29-3.

194 134 SWAT USER'S MANUAL, VERSION 2000 Table 29-3: SWAT input variables that impact chlorophyll a calculations in ponds, wetlands and reservoirs. Variable Name Definition Input File CHLA Chla co variable for calculation of chlorophyll a.pnd concentration in a pond CHLAW Chla co variable for calculation of chlorophyll a.pnd concentration in a wetland CHLAR Chla co variable for calculation of chlorophyll a.lwq concentration in a reservoir CHLOROPHYLL a/secchi-disk DEPTH CORRELATIONS The secchi-disk depth is another measure of the trophic status of a water body. The secchi-disk depth quantifies the clarity of the water, an attribute easily perceived by the general public. The secchi-disk depth can be calculated from chlorophyll levels using the equation (Chapra, 1997): SD = 6.35Chla where SD is the secchi-disk depth (m) and Chla is the chlorophyll a concentration (µg/l). For incorporation into SWAT, equation was modified to include a user-defined coefficient: SD = SDco 6.35Chla The user-defined coefficient, SD co, is included to allow the user to adjust the predicted secchi-disk depth for impacts of suspended sediment and other particulate matter on water clarity that are ignored by the original equation. When SD co is set to 1.00, equation is equivalent to equation For most water bodies, the original equation will be adequate. SWAT input variables that pertain to secchi-disk depth calculations in ponds, wetlands and reservoirs are listed in Table Table 29-4: SWAT input variables that impact secchi-disk depth calculations in ponds, wetlands and reservoirs. Variable Name Definition Input File SECCI SD co variable for calculation of secchi-disk depth in a pond.pnd SECCIW SD co variable for calculation of secchi-disk depth in a.pnd wetland SECCIR SD co variable for calculation of secchi-disk depth in a reservoir.lwq

195 CHAPTER 29: SWAT EQUATIONS NUTRIENTS IN WATER BODIES 135 While evaluation of water quality by secchi-disk depth measurements is subjective, some general correlations between secchidisk depth and public perception of water quality have been made. One such correlation made for Annebessacook Lake in Maine (EPA, 1980) is given in Table Table 29-5: Relationship between secchi-disk depth and public perception of water quality. Secchi-disk depth (m) Public perception of water quality gross pollution; water body totally unsuitable for recreation algae blooms still evident; quality unacceptable for most uses some complaints of declining water quality; some impairment of water use satisfactory quality; no impairment of water use excellent water quality; a positive factor encouraging use of lake exceptional quality 29.2 DEPRESSIONAL/IMPOUNDED AREAS Potholes are a feature recently added to SWAT and development up to this point has focused on the water balance. No nutrient processes are modeled in depressional/impounded areas at this time. The nutrient balance in depressional/impounded areas will be incorporated into SWAT in the future NOMENCLATURE A s Area of sediment-water interface (m 2 ) Chla Chlorophyll a concentration (µg/l) Chla co User-defined coefficient to adjust predicted chlorophyll a concentration M flowin Mass of nutrient entering water body on the given day (kg) M initial Initial mass of nutrient in water body for the given day (kg) M settling Mass of nutrient lost via settling on a given day (kg) M stored Mass of nutrient in water body at end of previous day (kg) Q Volumetric flow rate for water exiting water body (m 3 H 2 O/day) SD Secchi-disk depth (m) User-defined coefficient to adjust predicted secchi-disk depth SD co

196 136 SWAT USER'S MANUAL, VERSION 2000 V Volume of water in water body (assumed constant) (m 3 H 2 O) V flowin Volume of water entering water body on given day (m 3 H 2 O) V initial Initial volume of water in water body on given day (m 3 H 2 O) V stored Volume of water in water body at end of previous day (m 3 H 2 O) W(t) Rate of nutrient loading (kg/day) c Concentration of nutrient in the water (kg/m 3 H 2 O) dt Length of time step (1 day) p Total phosphorus concentration (µg P/L) ν Apparent settling velocity (m/day) 29.4 REFERENCES Chapra, S.C Surface water-quality modeling. WCB/McGraw-Hill, Boston, MA. Higgins, J.M. and B.R. Kim Phosphorus retention models for the Tennessee Valley Authority reservoirs. Wat. Resour. Res. 17: Merriam-Webster, Inc Merriam-Webster s collegiate dictionary, 10 th edition. Merriam-Webster, Inc. Springfield, MA. Nürnberg, G.K The prediction of internal phosphorus load in lakes with anoxic hypolimnia. Limnol. Oceanogr. 29: Panuska, J.C. and D.M. Robertson Estimating phosphorus concentration following alum treatment using apparent settling velocity. Lake and Reserv. Manage. 15: Rast, W. and Lee, G.F Summary analysis of the North American project (US portion) OECD eutrophication project: nutrient loading-lake response relationships and trophic state indices. USEPA Corvallis Environmental Research Laboratory, Corvallis, OR. EPA-600/ USEPA Walker, W.W. and J. Kiihner An empirical analysis of factors controlling eutrophication in midwestern impoundments. Paper presented at the International Symposium on the Environmental Effects of Hydraulic Engineering Works, Univ. of Tenn., Knoxville.

197 PART 2 MODEL OPERATION

198 CHAPTER 31 SWAT INPUT DATA: WATERSHED CONFIGURATION The first step in setting up a watershed simulation is to define the relative arrangement of the parts or elements, i.e. the configuration, of the watershed. If the watershed has only one primary channel and there is very little variation in topography and climate across the watershed, there may not be a need to partition the watershed into smaller units. However, the majority of watersheds will exhibit enough complexity in the stream network, topography or climate to warrant subdivision for modeling purposes. There are several techniques used to discretize a watershed. In the past, models could only apply one type of discretization scheme to a watershed. This 29

199 30 SWAT USER S MANUAL, VERSION 2000 resulted in the development of several models that differ only in the watershed discretization scheme used DISCRETIZATION SCHEMES The three most common techniques used to discretize a watershed are: Grid cell. This configuration allows the user to incorporate significant spatial detail into a simulation. Models which use this technique include AGNPS (Young et al., 1987), ANSWERS (Beasley et al., 1980) and the WEPP grid version (Foster, 1987). Representative hillslope. This configuration is useful for modeling hillslope processes. This technique is used in APEX (Williams, et al., 1998) and the WEPP hillslope version (Lane and Nearing, 1989). Subwatershed. This configuration preserves the natural channels and flow paths of the watershed. This technique is used in the WEPP watershed version (Foster, 1987), HYMO (Williams and Hann, 1973) and SWRRB (Arnold et al., 1990). All of these schemes have strengths and weaknesses and applications for which they are most appropriate. SWAT uses the subwatershed configuration as the primary discretization scheme for a watershed. However, because of the routing command language utilized in SWAT, it is possible to use any of these three, alone or in combination, to model a watershed WATERSHED CONFIGURATION FILE (.FIG) The watershed configuration file contains information used by SWAT to simulate processes occurring within the HRU/subbasin and to route the stream

200 CHAPTER 31: SWAT INPUT WATERSHED CONFIGURATION 31 loadings through the channel network of the watershed. A reach routing command structure, similar to that developed for HYMO (Williams and Hann, 1973), is utilized to route and add flows through the watershed. The following sections review the different features of the watershed configuration file INCORPORATION OF COMMENTS To assist the user in interpreting the watershed configuration file, an unlimited number of comment lines are allowed. These comments can be used to isolate the routing commands for different reaches, etc. To included comments in the watershed configuration file, a line must have an asterisk (*) in the 1 st space on the line. When SWAT reads the asterisk, it will skip to the next line COMMAND LINES Thirteen different commands may be used in the watershed configuration file. The commands, along with their numeric codes, are: finish 0 subbasin 1 route 2 routres 3 transfer 4 add 5 recmon 7 recyear 8 save 9 recday 10 reccnst 11 structur 12 saveconc 14 The most commonly used commands are: subbasin, route, add, and finish. In brief, these commands simulated the land phase of the hydrologic cycle and determine the loadings to the reach (subbasin), model the movement and transformations occurring in the reach (route), allow the output from different

201 32 SWAT USER S MANUAL, VERSION 2000 subbasins to be summed together (add), and identify the end of the routing command sequence (finish). The remaining commands are utilized to model more unique configurations. This set of commands can be divided several subgroups: routing of water through a reservoir (routres), humanly contrived movement of water (transfer), aeration of water resulting from flow through structures along the channel (structur), incorporation of point source data (recday, recmon, recyear, reccnst), formatting of watershed outflow for input into a different SWAT simulation (save), and formatting of water quality simulation results at specified points in the reach network (saveconc) SUBBASIN COMMAND (1) The subbasin command simulates all processes involved in the land phase of the hydrologic cycle and computes runoff, sediment, and chemical loadings from each HRU within the subbasin. Variables required on the subbasin command line are: Variable name COMMAND HYD_STOR SUB_NUM GIS_CODE Definition The command code = 1 for the subbasin command. The hydrograph storage location number. After a command is executed, the results are stored in an array at the position defined by this number. It is crucial that all hydrograph storage location numbers are unique. If the same number is used twice, output from one command line will be overwritten by that from another and simulation results will be incorrect. Subbasin number. This number is assigned in file.cio. Every subbasin in the watershed has a different number. GIS code printed to output files (optional)

202 The format of the subbasin command line is: CHAPTER 31: SWAT INPUT WATERSHED CONFIGURATION 33 Variable name Position Format F90 Format COMMAND space digit integer i6 HYD_STOR space digit integer i6 SUB_NUM space digit integer i6 GIS_CODE space digit integer i ROUTE COMMAND (2) The route command routes the water, sediment, and chemical loadings through a main channel or reach. Variables required on the route command line are: Variable name COMMAND HYD_STOR RCH_NUM HYD_NUM Definition The command code = 2 for the route command. The hydrograph storage location number. After a command is executed, the results are stored in an array at the position defined by this number. It is crucial that all hydrograph storage location numbers are unique. If the same number is used twice, output from one command line will be overwritten by that from another and simulation results will be incorrect. Reach number. The reach number is the same as the subbasin number. Inflow hydrograph storage location number. The data that is to be routed through the reach.

203 34 SWAT USER S MANUAL, VERSION 2000 Variable name FLOW_OVN Definition Fraction of overland flow (0.000 to 1.000). If flow leaving a subbasin is completely channelized, FLOW_OVN = In cases where a hillslope is being simulated, overland flow from one subbasin to another occurs and the value of FLOW_OVN can be increased to account for the amount of non-channelized overland flow taking place between the subbasins. The overland flow to the next subbasin is added to the rainfall of the receiving subbasin and allowed to infiltrate or run off. The sediment and chemical loadings associated with the overland flow are assumed to be deposited on the upper soil layer of the receiving subbasin. The fraction of the flow in the channel is routed directly to the reach of the receiving subbasin. The format of the route command line is: Variable name Position Format F90 Format COMMAND space digit integer i6 HYD_STOR space digit integer i6 RCH_NUM space digit integer i6 HYD_NUM space digit integer i6 FLOW_OVN space decimal (xx.xxx) f ADD COMMAND (5) The add command is used to sum the water, sediment, and chemical loadings of any two flows. Variables required on the add command line are: Variable name COMMAND HYD_STOR HYD_NUM1 HYD_NUM2 Definition The command code = 5 for the add command. The hydrograph storage location number for the results. The hydrograph storage location number of the 1 st set of data to be added. The hydrograph storage location number of the 2 nd set of data to be added.

204 The format of the add command line is: CHAPTER 31: SWAT INPUT WATERSHED CONFIGURATION 35 Variable name Position Format F90 Format COMMAND space digit integer i6 HYD_STOR space digit integer i6 HYD_NUM1 space digit integer i6 HYD_NUM2 space digit integer i FINISH COMMAND (0) The last command line in the.fig file must be a finish command line. The finish command notifies the model that the end of the command lines in the watershed configuration file has been reached. Variables required on the finish command line are: Variable name COMMAND Definition The command code = 0 for the finish command The format of the finish command line is: Variable name Position Format F90 Format COMMAND space digit integer i ROUTRES COMMAND (3) The routres command routes water, sediment, and chemical loadings through a reservoir. The routres command requires two lines. Variables required on the routres command lines are: Variable name COMMAND HYD_STOR RES_NUM Definition The command code = 3 for the routres command. The hydrograph storage location number for results. Reservoir number. Every reservoir modeled in the watershed must be assigned a unique consecutive number (beginning with 1)

205 36 SWAT USER S MANUAL, VERSION 2000 Variable name HYD_NUM RESFILE LWQFILE Definition Inflow hydrograph storage location number. The data that is to be routed through the reservoir. Name of reservoir input file (.res) Name of reservoir water quality input file (optional) (.lwq) The format of the routres command lines is: Variable Line # Position Format F90 Format name COMMAND 1 space digit integer i6 HYD_STOR 1 space digit integer i6 RES_NUM 1 space digit integer i6 HYD_NUM 1 space digit integer i6 RESFILE 2 space character a13 LWQFILE 2 space character a TRANSFER COMMAND (4) Originally, the transfer command was the only method available to irrigate an HRU. While the irrigation scenarios are now handled primarily in the management files, the transfer command was retained for flexibility. The transfer command moves water from any reach or reservoir to any other reach or reservoir. Variables required on the transfer command line are: Variable name COMMAND DEP_TYPE Definition The command code = 4 for the transfer command. Water source type: 1 reach 2 reservoir

206 CHAPTER 31: SWAT INPUT WATERSHED CONFIGURATION 37 Variable name DEP_NUM DEST_TYPE DEST_NUM TRANS_AMT TRANS_CODE Definition Water source number. The number of the reach or reservoir from which the flow will be diverted. Destination type. Defines the receiving body. 1 reach 2 reservoir Destination number. Number of reach or reservoir receiving the water. The flow amount transferred. (defined by TRANS_CODE) The rule code governing the transfer of water: 1 A fraction of the flow or volume to be transferred out of the reach or reservoir is specified 2 A minimum flow (reach) or volume (reservoir) to leave in the reach or reservoir is specified (m 3 /day) 3 An exact amount of water to be transferred is specified (m 3 /day) The format of the transfer command line is: Variable name Position Format F90 Format COMMAND space digit integer i6 DEP_TYPE space digit integer i6 DEP_NUM space digit integer i6 DEST_TYPE space digit integer i6 DEST_NUM space digit integer i6 TRANS_AMT space decimal (xx.xxx) f6.3 TRANS_CODE space digit integer i STRUCTUR COMMAND (12) The structur command simulates aeration caused by the tumbling of water as it moves over weirs or other structures along the stream network. In highly polluted streams, the aeration of the stream by this method is a significant source of oxygen. The structur command alters the dissolved oxygen content based on the aeration coefficient input by the user. Variables required on the structur command line are:

207 38 SWAT USER S MANUAL, VERSION 2000 Variable name COMMAND HYD_STOR HYD_NUM AERATION_COEF Definition The command code = 12 for the structur command. The hydrograph storage location number for data. Inflow hydrograph storage location number. The data that is to be adjusted to reflect aeration. (Dissolved oxygen content is the only value that is altered with this command.) Aeration coefficient. The format of the structur command is: Variable name Position Format F90 Format COMMAND space digit integer i6 HYD_STOR space digit integer i6 HYD_NUM space digit integer i6 AERATION_COEF space decimal (xx.xxx) f RECMON COMMAND (7) The recmon command is one of four routing commands that reads in flow, sediment and chemical loading records from a file and routes the input through the watershed. The recmon command is used to read in data summarized by month. The recmon command requires two lines. Variables required on the recmon command lines are: Variable name COMMAND HYD_STOR FILEMON_NUM DRAINAGE_AREA FILE_MON Definition The command code = 7 for the recmon command. The hydrograph storage location number for data. The file number. Unique file numbers should be used for each recmon command. Drainage area associated with records (km 2 ) (optional) Name of the file containing the monthly records

208 The format of the recmon command lines is: CHAPTER 31: SWAT INPUT WATERSHED CONFIGURATION 39 Variable name Line # Position Format F90 Format COMMAND 1 space digit integer i6 HYD_STOR 1 space digit integer i6 FILEMON_NUM 1 space digit integer i6 DRAINAGE_AREA 1 space decimal (xx.xxx) f6.3 FILE_MON 2 space character a RECYEAR COMMAND (8) The recyear command is one of four routing commands that reads in flow, sediment and chemical loading records from a file and routes the input through the watershed. The recyear command is used to read in annual output. The recyear command requires two lines. Variables required on the recyear command lines are: Variable name COMMAND HYD_STOR FILEYR_NUM DRAINAGE_AREA FILE_YR Definition The command code = 8 for the recyear command. The hydrograph storage location number for data. The file number. Unique file numbers should be used for each recyear command. Drainage area associated with records (km 2 ) (optional) Name of file containing annual output. The format of the recyear command lines is: Variable name Line # Position Format F90 Format COMMAND 1 space digit integer i6 HYD_STOR 1 space digit integer i6 FILEYR_NUM 1 space digit integer i6 DRAINAGE_AREA 1 space decimal(xx.xxx) f6.3 FILE_YR 2 space character a13

209 40 SWAT USER S MANUAL, VERSION RECDAY COMMAND (10) The recday command is one of four routing commands that reads in flow, sediment and chemical loading records from a file and routes the input through the watershed. This command is useful for reading in point source data or data from simulations of upstream areas. The recday command is used to read in data summarized on a daily basis. The recday command requires two lines. Variables required on the recday command lines are: Variable name COMMAND HYD_STOR FILEDAY_NUM DRAINAGE_AREA FILE_DAY Definition The command code = 10 for the recday command. The hydrograph storage location number for data. The file number. Unique file numbers should be used for each recday command. Drainage area associated with records (km 2 ) (optional) Name of file containing daily records. The format of the recday command lines is: Variable name Line # Position Format F90 Format COMMAND 1 space digit integer i6 HYD_STOR 1 space digit integer i6 FILEDAY_NUM 1 space digit integer i6 DRAINAGE_AREA 1 space decimal (xx.xxx) f6.3 FILE_DAY 2 space character a RECCNST COMMAND (11) The reccnst command is one of four routing commands that reads in flow, sediment and chemical loading records from a file and routes the input through the watershed. This command is useful for reading in point source data. The reccnst command is used to read in average annual data. The reccnst command requires two lines. Variables required on the reccnst command lines are:

210 CHAPTER 31: SWAT INPUT WATERSHED CONFIGURATION 41 Variable name COMMAND HYD_STOR FILECNST_NUM DRAINAGE_AREA FILE_CNST Definition The command code = 11 for the reccnst command. The hydrograph storage location number for data. The file number. Unique file numbers should be used for each reccnst command. Drainage area associated with records (km 2 ) (optional) Name of file containing average annual records. The format of the reccnst command lines is: Variable name Line # Position Format F90 Format COMMAND 1 space digit integer i6 HYD_STOR 1 space digit integer i6 FILECNST_NUM 1 space digit integer i6 DRAINAGE_AREA 1 space decimal(xx.xxx) f6.3 FILE_CNST 2 space character a SAVE COMMAND (9) The save command allows the user to print daily SWAT output to the event output file specified in file.cio. This output file can then be read into another SWAT run using the recday command. Variables required on the save command line are: Variable name COMMAND HYD_NUM Definition The command code = 9 for save command. The hydrograph storage location number of the data to be printed to file. The format of the save command line is: Variable name Position Format F90 Format COMMAND space digit integer i6 HYD_NUM space digit integer i6

211 42 SWAT USER S MANUAL, VERSION SAVECONC COMMAND (14) The saveconc command saves flow, sediment and water quality indicator information from a specified point on the reach network to a file. The water quality information is reported as concentrations. This command is useful for isolating reach information at a particular point on the channel network. Up to 50 saveconc commands can be specified in the watershed configuration file. The saveconc command requires two lines. Variables required on the saveconc command lines are: Variable name COMMAND HYD_NUM FILECONC_NUM PRINT_FREQ FILE_CONC Definition The command code = 14 for the saveconc command. The hydrograph storage location number of the data to be printed to file. The file number. Unique file numbers should be used for each saveconc command. Printing frequency. For simulations using a sub-daily time step, water quality information may be summarized and printed for every hour or every day. Simulations using a daily time step will always print daily average values. 0 report daily averages 1 report hourly averages (currently not operational) If no printing frequency is specified, the model will print daily averages. Name of file to which the water quality information is written. The format of the saveconc command lines is: Variable name Line # Position Format F90 Format COMMAND 1 space digit integer i6 HYD_NUM 1 space digit integer i6 FILECONC_NUM 1 space digit integer i6 PRINT_FREQ 1 space digit integer i6 FILE_CONC 2 space character a13

212 CHAPTER 31: SWAT INPUT WATERSHED CONFIGURATION REFERENCES Arnold, J.G., J.R. Williams, A.D. Nicks, and N.B. Sammons SWRRB, a basin scale simulation model for soil and water resources management. Texas A&M University Press, College Station, TX. Beasley, D.B., L.F. Huggins, and E.J. Monke ANSWERS: A model for watershed planning. Trans. of the ASAE 23(4): Foster, G.R User requirements: USDA-Water erosion prediction project. Lane, L.J. and M.A. Nearing (ed.) USDA-Water erosion prediction project: hillslope profile model documentation. NSERL Report No. 2. National Soil Erosion Research Laboratory. USDA-Agricultural Research Service. W. Lafayette, IN. Williams, J.R. J.G. Arnold, R. Srinivasan, and T.S. Ramanarayanan Chapter 33. APEX: a new tool for predicting the effects of climate and CO 2 changes on erosion and water quality. p In J. Boardman and D. Favis-Mortlock (ed.) Modeling soil erosion by water. Springer-Verlag, Berlin. Williams, J.R. and R.W. Hann HYMO: Problem oriented computer language for hydrologic modeling. USDA ARS-S pp. Young, R.A. et al AGNPS, Agricultural non-point source pollution model: a watershed analysis tool. USDA Agricultural Research Service.

213 44 SWAT USER S MANUAL, VERSION 2000

214 CHAPTER 32 SWAT INPUT DATA: SIMULATION MANAGEMENT Two different files contain information used by SWAT to govern the processing of input data and the formatting and type of output data produced by the simulation. These files also include parameters that identify any specialized processes to be simulated. They are the control input/output file (file.cio) and the input control code file (.cod). 45

215 46 SWAT USER'S MANUAL, VERSION CONTROL INPUT/OUTPUT FILE (FILE.CIO) File management is performed with the control input/output file (file.cio). The control input/output file contains the name of files associated with the subbasins, database files, climate files and watershed-level input files accessed by SWAT during a simulation as well as the name of the files in which output will be stored. While the user may adopt any file naming scheme, we recommend that the file extensions listed in the manual are used to facilitate identification of the different file types. Files required by the model that are not listed in the control input/output file include HRU files listed in the subbasin general input (.sub) file, reservoir and point source input files listed in the watershed configuration (.fig) file and "unique" files which contain input for uncommon or specialized processes not typically simulated. The control input/output file can be divided into a number of different sections. Figure 32.1 illustrates the different groupings of files within file.cio. Figure 32.1: General organization of control input/output files

216 CHAPTER 32:SWAT INPUT SIMULATION MANAGEMENT 47 Following is a brief description of the variables in the control input/output file. They are listed in the order they appear within the file TITLE SECTION (FILE.CIO) Variable name TITLE Definition The first three lines of file.cio are reserved for a description of the simulation run. The description may take up to 80 spaces per line. The title given in file.cio is printed to every output file. (optional) GENERAL INPUT/OUTPUT SECTION (FILE.CIO) Variable name BIGSUB SBSOUT RCHOUT RSVOUT LWQOUT Definition Name of subbasin output file (.bsb). Loadings to the reach (water, sediment and nutrients) are summarized for each subbasin. Name of hydrologic response unit (HRU) output file (.sbs). Loadings to the reach (water, sediment and nutrients) and crop growth are summarized for each HRU. Name of main channel, or reach, output file (.rch). Summarizes the amount of water, sediment and pollutants entering and leaving the reach and provides data on in-steam processes (e.g. sediment deposition, evaporation occurring in the channel) Name of reservoir output file (.rsv). Summarizes the amount of water, sediment and pollutants entering and leaving the reservoir and quantifies processes occurring in the reservoir (e.g. sediment deposition). Name of lake water quality output file (.lqo). Summarizes the amounts and transformations affecting pesticides in the reservoir.

217 48 SWAT USER'S MANUAL, VERSION 2000 Variable name WTROUT PESTOUT EVENT ROUTIN CODEDAT BASNDAT WATQAL CROPDB TILLDAT PESTIDAT FERTDAT URBDAT Definition Name of HRU impoundment output file (.wtr). Summarizes the amount of water, sediment and pollutants entering and leaving ponds, wetlands and depressional areas (potholes) and quantifies processes occurring in the different impoundments. Name of pesticide output file (.pso). The movement and transformation of the different pesticides used in the simulation are summarized for each HRU. Name of event output file (.eve). When very large basins are being simulated, it is often easier to split them into several SWAT runs. This file writes daily output which can be read into a different SWAT run. Name of watershed configuration file (.fig). Contains the commands to add and route flows through the watershed. Name of input control code file (.cod). The input control code file summarizes information that affects the operation of SWAT (e.g. print codes, weather generator codes, number of years being simulated, number of subbasins being simulated) Name of basin input file (.bsn). Contains inputs for processes modeled at the watershed level. Name of watershed water quality input file (.wwq) Name of land cover/plant growth database file (crop.dat). This file contains growth parameters for the different land covers. Name of tillage database file (till.dat). This file contains mixing efficiencies for different tillage implements. Name of pesticide database file (pest.dat). This file contains parameters governing movement and degradation of pesticides. Name of fertilizer/manure database file (fert.dat). This file contains nutrient content data for fertilizers. Name of urban land type database file (urban.dat). This file contains data required to model build-up/wash-off in urban areas.

218 CHAPTER 32:SWAT INPUT SIMULATION MANAGEMENT CLIMATE INPUT SECTION (FILE.CIO) Variable name NRGAGE NTGAGE NRTOT NTTOT NRGFIL NTGFIL NSTOT NHTOT NWTOT RFILE(1) RFILE(2) RFILE(3) RFILE(4) RFILE(5) Definition Number of precipitation gage (.pcp) files used in the simulation. Up to 18 files may be used. Number of temperature gage (.tmp) files used in the simulation. Up to 18 files may be used. Total number of precipitation gage records used in the simulation. If each.pcp file contains only one precipitation gage record, NRTOT = NRGAGE. Otherwise, NRTOT > NRGAGE. A maximum of 5400 precipitation gage records may be used in a simulation. Total number of temperature gage records used in the simulation. If each.tmp file contains only one temperature gage record, NTTOT = NTGAGE. Otherwise, NTTOT > NTGAGE. A maximum of 2700 temperature gage records may be used in a simulation. Number of precipitation gage records within each.pcp file. A maximum of 300 precipitation gage records may be placed in each.pcp file. Number of temperature gage records within each.tmp file. a maximum of 150 temperature gage records may be placed in each.tmp file Number of solar radiation records within the.slr file. A maximum of 300 solar radiation records may be placed in the.slr file. Number of relative humidity records within the.hmd file. A maximum of 300 relative humidity records may be placed in the.hmd file. Number of wind speed records within the.wnd file. A maximum of 300 wind speed records may be placed in the.wnd file. Name of measured precipitation input file #1 (.pcp). Name of measured precipitation input file #2 (.pcp). Name of measured precipitation input file #3 (.pcp). Name of measured precipitation input file #4 (.pcp). Name of measured precipitation input file #5 (.pcp).

219 50 SWAT USER'S MANUAL, VERSION 2000 Variable name RFILE(6) RFILE(7) RFILE(8) RFILE(9) RFILE(10) RFILE(11) RFILE(12) RFILE(13) RFILE(14) RFILE(15) RFILE(16) RFILE(17) RFILE(18) TFILE(1) TFILE(2) TFILE(3) TFILE(4) TFILE(5) TFILE(6) TFILE(7) TFILE(8) TFILE(9) TFILE(10) TFILE(11) TFILE(12) TFILE(13) TFILE(14) TFILE(15) TFILE(16) TFILE(17) Definition Name of measured precipitation input file #6 (.pcp). Name of measured precipitation input file #7 (.pcp). Name of measured precipitation input file #8 (.pcp). Name of measured precipitation input file #9 (.pcp). Name of measured precipitation input file #10 (.pcp). Name of measured precipitation input file #11 (.pcp). Name of measured precipitation input file #12 (.pcp). Name of measured precipitation input file #13 (.pcp). Name of measured precipitation input file #14 (.pcp). Name of measured precipitation input file #15 (.pcp). Name of measured precipitation input file #16 (.pcp). Name of measured precipitation input file #17 (.pcp). Name of measured precipitation input file #18 (.pcp). Name of measured temperature input file #1 (.tmp). Name of measured temperature input file #2 (.tmp). Name of measured temperature input file #3 (.tmp). Name of measured temperature input file #4 (.tmp). Name of measured temperature input file #5 (.tmp). Name of measured temperature input file #6 (.tmp). Name of measured temperature input file #7 (.tmp). Name of measured temperature input file #8 (.tmp). Name of measured temperature input file #9 (.tmp). Name of measured temperature input file #10 (.tmp). Name of measured temperature input file #11 (.tmp). Name of measured temperature input file #12 (.tmp). Name of measured temperature input file #13 (.tmp). Name of measured temperature input file #14 (.tmp). Name of measured temperature input file #15 (.tmp). Name of measured temperature input file #16 (.tmp). Name of measured temperature input file #17 (.tmp).

220 CHAPTER 32:SWAT INPUT SIMULATION MANAGEMENT 51 Variable name TFILE(18) SLRFILE RHFILE WNDFILE PETFILE Definition Name of measured temperature input file #18 (.tmp). Name of measured solar radiation input file (.slr). Name of measured relative humidity input file (.hmd). Name of measured wind speed input file (.wnd). Name of potential evapotranspiration input file (.pet) SUBBASIN INPUT SECTION (FILE.CIO) Variable name ISB SUBDAT RTEDAT PNDDAT WUSDAT WGNDAT SWQDAT IRGAGE ITGAGE ISGAGE IHGAGE IWGAGE Definition Subbasin number. This number is present to assist the user the model ignores this number. Input files for the different subbasins must be listed consecutively in the subbasin input section. Name of subbasin general input data file (.sub). Name of subbasin routing input data file (.rte). This file contains parameters for the main channel. Name of subbasin pond input data file (.pnd). Name of subbasin water use management data file (.wus). Name of subbasin weather generator data file (.wgn). Name of subbasin stream water quality data file (.swq). Number of the measured precipitation record used within subbasin. Optional. Number of the measured temperature record used within the subbasin. Optional. Number of the solar radiation record used within the subbasin. Optional. Number of the relative humidity record used within the subbasin. Optional. Number of the wind speed record used within the subbasin. Optional.

221 52 SWAT USER'S MANUAL, VERSION FILE FORMAT (FILE.CIO) Variable name Line # Position Format F90 Format TITLE 1-3 space 1-80 character a80 BIGSUB 4 space 1-13 character a13 SBSOUT 4 space character a13 RCHOUT 4 space character a13 RSVOUT 4 space character a13 LWQOUT 4 space character a13 WTROUT 4 space character a13 PESTOUT 5 space 1-13 character a13 EVENT 5 space character a13 ROUTIN 5 space character a13 CODEDAT 5 space character a13 BASNDAT 5 space character a13 WATQAL 5 space character a13 CROPDB 6 space 1-13 character a13 TILLDAT 6 space character a13 PESTIDAT 6 space character a13 FERTDAT 6 space character a13 URBDAT 6 space character a13 NRGAGE 7 space 1-4 integer i4 NTGAGE 7 space 5-8 integer i4 NRTOT 7 space 9-12 integer i4 NTTOT 7 space integer i4 NRGFIL 7 space integer i4 NTGFIL 7 space integer i4 NSTOT 7 space integer i4 NHTOT 7 space integer i4 NWTOT 7 space integer i4 RFILE(1) 8 space 1-13 character a13 RFILE(2) 8 space character a13 RFILE(3) 8 space character a13 RFILE(4) 8 space character a13 RFILE(5) 8 space character a13

222 CHAPTER 32:SWAT INPUT SIMULATION MANAGEMENT 53 Variable name Line # Position Format F90 Format RFILE(6) 8 space character a13 RFILE(7) 9 space 1-13 character a13 RFILE(8) 9 space character a13 RFILE(9) 9 space character a13 RFILE(10) 9 space character a13 RFILE(11) 9 space character a13 RFILE(12) 9 space character a13 RFILE(13) 10 space 1-13 character a13 RFILE(14) 10 space character a13 RFILE(15) 10 space character a13 RFILE(16) 10 space character a13 RFILE(17) 10 space character a13 RFILE(18) 10 space character a13 TFILE(1) 11 space 1-13 character a13 TFILE(2) 11 space character a13 TFILE(3) 11 space character a13 TFILE(4) 11 space character a13 TFILE(5) 11 space character a13 TFILE(6) 11 space character a13 TFILE(7) 12 space 1-13 character a13 TFILE(8) 12 space character a13 TFILE(9) 12 space character a13 TFILE(10) 12 space character a13 TFILE(11) 12 space character a13 TFILE(12) 12 space character a13 TFILE(13) 13 space 1-13 character a13 TFILE(14) 13 space character a13 TFILE(15) 13 space character a13 TFILE(16) 13 space character a13 TFILE(17) 13 space character a13 TFILE(18) 13 space character a13 SLRFILE 14 space 1-13 character a13 RHFILE 14 space character a13 WNDFILE 14 space character a13 PETFILE 14 space character a13

223 54 SWAT USER'S MANUAL, VERSION 2000 Variable name Line # Position Format F90 Format The remaining lines provide input data for all of the subbasins. Two lines are devoted to each subbasin's input data. In the equation for the line number, i is the subbasin number. ISB i space 1-5 integer i5 SUBDAT i space 7-19 character a13 RTEDAT i space character a13 PNDDAT i space character a13 WUSDAT i space character a13 WGNDAT i space 7-19 character a13 SWQDAT i space character a13 IRGAGE i space integer i4 ITGAGE i space integer i4 ISGAGE i space integer i4 IHGAGE i space integer i4 IWGAGE i space integer i4

224 CHAPTER 32:SWAT INPUT SIMULATION MANAGEMENT INPUT CONTROL CODE FILE (.COD) The input control code file regulates the general operation of SWAT. In addition to setting output file formats, the input control code file defines which processes are/are not modeled in the SWAT simulation. Following is a brief description of the variables in the input control file. They are listed in the order they appear within the file. Variable name TITLE NBYR IYR IDAF IDAL Definition The first line of the.cod file is reserved for user comments. The comments may take up to 80 spaces. (optional) Number of calendar years simulated. The number of years simulated in a SWAT run can vary from 1 to 9,999 years. If a simulation is begun on August 1 st of the year 1995 and ends July 30 th of the year 1997, the model will be simulating 3 calendar years (1995, 1996 and 1997). Beginning year of simulation (for example, 1980). The value entered for this variable is not important unless measured data (e.g. weather) is used in the run. When measured data is used, the model uses this variable to locate the beginning year within the data file. Beginning julian day of simulation. With this variable, SWAT is able to begin a simulation at any time of the year. If the variable is left blank or set to zero, the model starts the simulation on January 1 st. Ending julian day of simulation. With this variable, SWAT will end the simulation on the date specified. If the variable is left blank or set to zero, the model ends the simulation on December 31 st.

225 56 SWAT USER'S MANUAL, VERSION 2000 Variable name IPD NYSKIP IPRN ILOG Definition Print code. This variable governs the frequency that model results are printed to output files. There are three options: 0 monthly 1 daily 2 annually If you choose to print results on a daily basis, the number of years simulated should be limited and/or the variables printed to the output file should be restricted. If these precautions are not taken, the output files will be too large to view. Number of years to not print output. The options are 0 print output for all years of the simulation 1 print output after the first year of simulation 2 print output after the second year of simulation $ nbyr no output will be printed If initial conditions are not well known, a warm-up or equilibration period may be needed to get the values of soil water, residue, etc. to representative amounts. NYSKIP defines the duration of the equilibration period. In addition to not writing data to the output files, annual averages are not computed for the skipped years. Averages for the entire simulation period will also exclude data from the skipped years. The default value for NYSKIP is 0. Print code for input.std file. There are two options: 0 entire input.std file is printed 1 condensed version of input.std file is printed Streamflow print code. This variable allows the user to take the log 10 of the flow prior to printing streamflow values to the.rch file. There are two options: 0 print streamflow in.rch file 1 print log of streamflow in.rch file In large basins (for example, the Mississippi River basin), streamflow values printed to the.rch file may exceed the range allowed by the file format statements. This variable will eliminate print errors caused by very large values.

226 CHAPTER 32:SWAT INPUT SIMULATION MANAGEMENT 57 Variable name IPRP IGN PCPSIM IDT IDIST Definition Print code for.pso file. There are two options: 0 do not print pesticide output (.pso file will be empty) 1 print pesticide output Random generator seed code. A set of random numbers is needed by SWAT to generate weather data. SWAT has a set of default random numbers embedded in the code. To use the default random numbers, the user should set IGN = 0. This is the default value for IGN. In some situations, a user may wish to vary the weather sequence between runs. This is done by setting IGN to a different number every time the model is run. This code will activate a random number generator, which will replace the default set of random numbers with a new set. The value to which IGN is set determines the number of times the random number generator is cycled before the simulation begins. The seeds produced by the random number generator are then utilized by the weather generator instead of the default values. Measured weather data read into the model is not affected by this variable. However, if the measured data contains missing values, the weather generator is activated to produce data to replace the missing values. The data produced to replace missing values will be affected by this variable. Rainfall input code. This variable identifies the method the model will use to process rainfall data. There are two options: 1 measured data read for each subbasin 2 rainfall generated for each subbasin Time step used to report measured rainfall data (minutes). Required if IEVENT = 2 or 3. One of the following should be chosen: 1 min, 2 min, 3 min, 4 min, 5 min, 6 min, 10 min, 12 min, 15 min, 20 min, 30 min. Rainfall distribution code. There are two options: 0 skewed distribution 1 mixed exponential distribution

227 58 SWAT USER'S MANUAL, VERSION 2000 Variable name REXP TMPSIM SLRSIM RHSIM WNDSIM IPET Definition Value of exponent for mixed exponential rainfall distribution. A value for REXP must be entered if IDIST = 1. The model will set REXP = 1.3 if no value is entered. Temperature input code. This variable identifies the method the model will use to process temperature data. There are two options: 1 measured date read for each subbasin 2 daily max/min generated for each subbasin Solar radiation input code. This variable identifies the method the model will use to process solar radiation data. There are two options: 1 measured data read for each subbasin 2 solar radiation generated for each subbasin Relative humidity input code. This variable identifies the method the model will use to process relative humidity data. There are two options: 1 measured data read for each subbasin 2 relative humidity generated for each subbasin Wind speed input code. This variable identifies the method the model will use to process wind speed data. There are two options: 1 measured data read for each subbasin 2 wind speed generated for each subbasin Potential evapotranspiration method. There are four options for potential ET calculations: 0 Priestley-Taylor method 1 Penman/Monteith method 2 Hargreaves method 3 read in potential ET values

228 CHAPTER 32:SWAT INPUT SIMULATION MANAGEMENT 59 Variable name IEVENT ICRK IRTE IDEG Definition Rainfall/runoff/routing option: 0 daily rainfall/curve number runoff/daily routing 1 daily rainfall/green & Ampt runoff/daily routing (sub-hourly rainfall required for Green & Ampt is generated from daily) this option not yet operational 2 sub-hourly rainfall/green & Ampt runoff/daily routing 3 sub-hourly rainfall/green & Ampt runoff/hourly routing Option 0 was the only active option in prior versions of the model and is the default. Crack flow code. There are two options: 0 do not model crack flow in soil 1 model crack flow in soil The default option is ICRK=0. Channel water routing method: 0 variable storage method 1 Muskingum method The default option is IRTE=0. The Muskingum method is a new option available with SWAT2000. The user must be careful to define MSK_CO1, MSK_CO2 and MSK_X (in.bsn) when the Muskingum method is chosen. Channel degradation code. There are two options: 0 channel dimensions are not updated as a result of degradation (the dimensions remain constant for the entire simulation) 1 channel dimensions are updated as a result of degradation Channel degradation refers to the downcutting and widening of the channel with time and is always calculated. The default option is IDEG=0 (the channel width and depth remain constant).

229 60 SWAT USER'S MANUAL, VERSION 2000 Variable name IRESQ IWQ ISPROJ Definition Lake water quality code. The variable identifies whether or not lake water quality is simulated in the reservoirs. There are two options: 0 do not model lake water quality 1 model lake water quality The default option is IRESQ=0. In-stream water quality code. The variable identifies whether in-stream transformation of nutrients is allowed to occur. 0 do not model in-stream nutrient transformations 1 model in-stream nutrient transformations The default option is IWQ=0. Special project flag. SWAT includes sections of code specific to particular projects. This variable flags the code used in the particular simulation. There are three options: 0 not a special project 1 HUMUS project 2 Missouri River climate change project A user will set this variable to something other than zero only if the SWAT programmers have told him to do so. For long runs, the output files can get so large that the user may have difficulty in opening the files to look at output. The user has the option of customizing the output printed to the output files. Lines of the.cod file are used to specify the variables to be printed to the reach output file (.rch), the subbasin output file (.bsb), and the HRU output file (.sbs). If these lines contain only zeros, the model will print all the output variables to the file. Variable name IPDVAR(:) Definition Output variables printed to the.rch file. (up to 20 variables may be chosen in customized output.) The codes for the output variables are: 1 FLOW_IN: Average daily streamflow into reach (m 3 /s) 2 FLOW_OUT: Average daily streamflow out of reach (m 3 /s)

230 CHAPTER 32:SWAT INPUT SIMULATION MANAGEMENT 61 Variable name Definition continued from previous page: 3 EVAP: Average daily loss of water from reach by evaporation (m 3 /s) 4 TLOSS: Average daily loss of water from reach by transmission (m 3 /s) 5 SED_IN: Sediment transported with water into reach (metric tons) 6 SED_OUT: Sediment transported with water out of reach (metric tons) 7 SEDCONC: Concentration of sediment in reach (mg/l) 8 ORGN_IN: Organic nitrogen transported with water into reach (kg N) 9 ORGN_OUT: Organic nitrogen transported with water out of reach (kg N) 10 ORGP_IN: Organic phosphorus transported with water into reach (kg P) 11 ORGP_OUT: Organic phosphorus transported with water out of reach (kg P) 12 NO3_IN: Nitrate transported with water into reach (kg N) 13 NO3_OUT: Nitrate transported with water out of reach (kg N) 14 NH4_IN: Ammonium transported with water into reach (kg N) 15 NH4_OUT: Ammonium transported with water out of reach (kg N) 16 NO2_IN: Nitrite transported with water into reach (kg N) 17 NO2_OUT: Nitrite transported with water out of reach (kg N) 18 MINP_IN: Mineral phosphorus transported with water into reach (kg P) 19 MINP_OUT: Mineral phosphorus transported with water out of reach (kg P) 20 CHLA_IN: Chlorophyll-a transported with water into reach (kg) 21 CHLA_OUT: Chlorophyll-a transported with water out of reach (kg) 22 CBOD_IN: Carbonaceous biochemical oxygen demand transported into reach (kg O 2 ) 23 CBOD_OUT: Carbonaceous biochemical oxygen demand transported out of reach (kg O 2 ) 24 DISOX_IN: Dissolved oxygen transported into reach (kg O 2 ) 25 DISOX_OUT: Dissolved oxygen transported out of reach (kg O 2 ) 26 SOLPST_IN: Soluble pesticide transported with water into reach (mg a.i.) 27 SOLPST_OUT: Soluble pesticide transported with water out of reach (mg a.i.) 28 SORPST_IN: Pesticide sorbed to sediment transported with water into reach (mg a.i.) 29 SORPST_OUT: Pesticide sorbed to sediment transported with water out of reach (mg a.i.) 30 REACTPST: Loss of pesticide from water by reaction (mg a.i.) 31 VOLPST: Loss of pesticide from water by volatilization (mg a.i.) 32 SETTLPST: Transfer of pesticide from water to river bed sediment by settling (mg a.i.) 33 RESUSP_PST: Transfer of pesticide from river bed sediment to water by resuspension (mg a.i.) 34 DIFFUSEPST: Transfer of pesticide from water to river bed sediment by diffusion (mg a.i.)

231 62 SWAT USER'S MANUAL, VERSION 2000 Variable name Definition continued from previous page: 35 REACBEDPST: Loss of pesticide from river bed sediment by reaction (mg a.i.) 36 BURYPST: Loss of pesticide from river bed sediment by burial (mg a.i.) 37 BED_PST: Pesticide in river bed sediment (mg a.i.) 38 BACTP_OUT: Number of persistent bacteria transported out of reach 39 BACTLP_OUT: Number of less persistent bacteria transported out of reach 40 CMETAL#1: Conservative metal #1 transported out of reach (kg) 41 CMETAL#2: Conservative metal #2 transported out of reach (kg) 42 CMETAL#3: Conservative metal #3 transported out of reach (kg) IPDVAB(:) IPDVAS(:) Output variables printed to the.bsb file (up to 15 variables may be chosen in customized output.) The codes for the output variables are: 1 PRECIP: Average total precipitation on subbasin (mm H 2 O) 2 SNOMELT: Snow melt (mm H 2 O) 3 PET: Potential evapotranspiration (mm H 2 O) 4 ET: Actual evapotranspiration (mm H 2 O) 5 SW: Soil water content (mm H 2 O) 6 PERC: Amount of water percolating out of root zone (mm H 2 O) 7 SURQ: Surface runoff (mm H 2 O) 8 GW_Q: Groundwater discharge into reach (mm H 2 O) 9 WYLD: Net water yield to reach (mm H 2 O) 10 SYLD: Sediment yield (metric tons/ha) 11 ORGN: Organic N released into reach (kg/ha) 12 ORGP: Organic P released into reach (kg/ha) 13 NSURQ: Nitrate released into reach (kg/ha) 14 SOLP: Soluble P released into reach (kg/ha) 15 SEDP: Mineral P attached to sediment released into reach (kg/ha) Output variables printed to the.sbs file (up to 20 variables may be chosen in customized output.) The codes for the output variables are: 1 PRECIP: Total precipitation on HRU (mm H 2 O) 2 SNOFALL: Precipitation falling as snow, sleet, or freezing rain (mm H 2 O) 3 SNOMELT: Amount of snow or ice melting (mm H 2 O) 4 IRR: Amount of irrigation water applied to HRU (mm H 2 O) 5 PET: Potential evapotranspiration (mm H 2 O) 6 ET: Amount of water removed by evapotranspiration (mm H 2 O) 7 SW: Soil water content at end of time period (mm H 2 O) 8 PERC: Amount of water percolating out of the root zone (mm H 2 O) 9 GW_RCHG: Amount of water entering both aquifers (mm H 2 O) 10 DA_RCHG: Amount of water entering deep aquifer from root zone (mm H 2 O) 11 REVAP: Water in shallow aquifer returning to root zone (mm H 2 O)

232 CHAPTER 32:SWAT INPUT SIMULATION MANAGEMENT 63 Variable name Definition continued from previous page: 12 SA_IRR: Amount of water removed from shallow aquifer for irrigation (mm H 2 O) 13 DA_IRR: Amount of water removed from deep aquifer for irrigation (mm H 2 O) 14 SA_ST: Amount of water in shallow groundwater storage at end of time period (mm H 2 O) 15 DA_ST: Amount of water in deep groundwater storage at end of time period (mm H 2 O) 16 SURQ: Surface runoff contribution to reach (mm H 2 O) 17 TLOSS: Amount of water removed from tributary channels by transmission (mm H 2 O) 18 LATQ: Lateral flow contribution to reach (mm H 2 O) 19 GW_Q: Groundwater discharge into reach (mm H 2 O) 20 WYLD: Net amount of water contributed by the HRU to the reach (mm H 2 O) 21 SYLD: Amount of sediment contributed by the HRU to the reach (metric tons/ha) 22 USLE: USLE soil loss (metric tons/ha) 23 N_APP: Amount of N fertilizer applied (kg N/ha) 24 P_APP: Amount of P fertilizer applied (kg P/ha) 25 NAUTO: Amount of N fertilizer applied automatically (kg N/ha) 26 PAUTO: Amount of P fertilizer applied automatically (kg P/ha) 27 NGRZ: Nitrogen applied to HRU in grazing operation during time step (kg N/ha) 28 PGRZ: Phosphorus applied to HRU in grazing operation during time step (kg P/ha) 29 NRAIN: Nitrate added in rainfall (kg N/ha) 30 NFIX: Amount of N fixed by legumes (kg N/ha) 31 F-MN: Transformation of N from fresh organic to mineral pool (kg N/ha) 32 A-MN: Transformation of N from active organic to mineral pool (kg N/ha) 33 A-SN: Transformation of N from active organic to stable organic pool (kg N/ha) 34 F-MP: Transformation of P from fresh organic to mineral pool (kg P/ha) 35 AO-LP: Transformation of P from organic to labile pool (kg P/ha) 36 L-AP: Transformation of P from labile to active mineral pool (kg P/ha) 37 A-SP: Transformation of P from active mineral to stable mineral pool (kg P/ha) 38 DNIT: Amount of N removed from soil by denitrification (kg N/ha) 39 NUP: Nitrogen uptake by plants (kg N/ha) 40 PUP: Phosphorus uptake by plants (kg P/ha) 41 ORGN: Organic N contributed by HRU to reach (kg N/ha) 42 ORGP: Organic P contributed by HRU to reach (kg P/ha) 43 SEDP: Mineral P attached to sediment contributed by HRU to reach (kg P/ha) 44 NSURQ: NO 3 contributed by HRU in surface runoff to reach (kg N/ha)

233 64 SWAT USER'S MANUAL, VERSION 2000 Variable name Definition continued from previous page: 45 NLATQ: NO 3 contributed by HRU in lateral flow to reach (kg N/ha) 46 NO3L: NO 3 leached below the soil profile (kg N/ha) 47 NO3GW: NO 3 contributed by HRU in groundwater flow to reach (kg N/ha) 48 SOLP: Soluble phosphorus contributed by HRU in surface runoff to reach (kg P/ha) 49 P_GW: Soluble phosphorus contributed by HRU in groundwater flow to reach (kg P/ha) 50 W_STRS: Number of water stress days. 51 TMP_STRS: Number of temperature stress days 52 N_STRS: Number of nitrogen stress days. 53 P_STRS: Number of phosphorus stress days. 54 BIOM: Total plant biomass (metric tons/ha) 55 LAI: Leaf area index 56 YLD: Harvested yield (metric tons/ha) 57 BACTP: Number of persistent bacteria in surface runoff (count) 58 BACTLP: Number of less persistent bacteria in surface runoff (count) The input control code file is a free format file. The variables may be placed in any position the user wishes on the line. Values for variables classified as integers should not include a decimal while values for variables classified as reals must contain a decimal. A blank space denotes the end of an input value and the beginning of the next value if there is another on the line Variable name Line # Format F90 Format TITLE 1 character a80 NBYR 2 integer free IYR 3 integer free IDAF 4 integer free IDAL 5 integer free IPD 6 integer free NYSKIP 7 integer free IPRN 8 integer free ILOG 9 integer free IPRP 10 integer free IGN 11 integer free PCPSIM 12 integer free IDT 13 integer free IDIST 14 integer free REXP 15 real free TMPSIM 16 integer free

234 CHAPTER 32:SWAT INPUT SIMULATION MANAGEMENT 65 Variable name Line # Format F90 Format SLRSIM 17 integer free RHSIM 18 integer free WNDSIM 19 integer free IPET 20 integer free IEVENT 21 integer free ICRK 22 integer free IRTE 23 integer free IDEG 24 integer free IRESQ 25 integer free IWQ 26 integer free ISPROJ 27 integer free COMMENT LINE 28 character a80 IPDVAR(1) 29 integer free IPDVAR(2) 29 integer free IPDVAR(3) 29 integer free IPDVAR(4) 29 integer free IPDVAR(5) 29 integer free IPDVAR(6) 29 integer free IPDVAR(7) 29 integer free IPDVAR(8) 29 integer free IPDVAR(9) 29 integer free IPDVAR(10) 29 integer free IPDVAR(11) 29 integer free IPDVAR(12) 29 integer free IPDVAR(13) 29 integer free IPDVAR(14) 29 integer free IPDVAR(15) 29 integer free IPDVAR(16) 29 integer free IPDVAR(17) 29 integer free IPDVAR(18) 29 integer free IPDVAR(19) 29 integer free IPDVAR(20) 29 integer free COMMENT LINE 30 character a80 IPDVAB(1) 31 integer free IPDVAB(2) 31 integer free

235 66 SWAT USER'S MANUAL, VERSION 2000 Variable name Line # Format F90 Format IPDVAB(3) 31 integer free IPDVAB(4) 31 integer free IPDVAB(5) 31 integer free IPDVAB(6) 31 integer free IPDVAB(7) 31 integer free IPDVAB(8) 31 integer free IPDVAB(9) 31 integer free IPDVAB(10) 31 integer free IPDVAB(11) 31 integer free IPDVAB(12) 31 integer free IPDVAB(13) 31 integer free IPDVAB(14) 31 integer free IPDVAB(15) 31 integer free COMMENT LINE 32 character a80 IPDVAS(1) 33 integer free IPDVAS(2) 33 integer free IPDVAS(3) 33 integer free IPDVAS(4) 33 integer free IPDVAS(5) 33 integer free IPDVAS(6) 33 integer free IPDVAS(7) 33 integer free IPDVAS(8) 33 integer free IPDVAS(9) 33 integer free IPDVAS(10) 33 integer free IPDVAS(11) 33 integer free IPDVAS(12) 33 integer free IPDVAS(13) 33 integer free IPDVAS(14) 33 integer free IPDVAS(15) 33 integer free IPDVAS(16) 33 integer free IPDVAS(17) 33 integer free IPDVAS(18) 33 integer free IPDVAS(19) 33 integer free IPDVAS(20) 33 integer free

236 CHAPTER 33 SWAT INPUT DATA: GENERAL WATERSHED ATTRIBUTES General watershed attributes are defined in the basin input file. These attributes control physical processes at the watershed level. Other than the variable DA_KM, the area of the watershed, the variables in this file are calibration variables or variables normally modified only for advanced or research applications. 69

237 70 SWAT USER'S MANUAL, VERSION BASIN INPUT FILE (.BSN) Following is a brief description of the variables in the basin input file. They are listed in the order they appear within the file. Variable name TITLE Definition The first line is reserved for a description. The description may take up to 80 spaces. Optional. DA_KM Area of the watershed (km 2 ) DT Variable not currently used. SFTMP Snowfall temperature (ºC). Mean air temperature at which precipitation is equally likely to be rain as snow/freezing rain. The snowfall temperature should be between 5 ºC and 5 ºC. A default recommended for this variable is SFTMP = 1.0. Optional. SMTMP Snow melt base temperature (ºC). Snow pack temperature above which snow melt will occur. The snow melt base temperature should be between 5 ºC and 5 ºC. A default recommended for this variable is SMTMP = Optional. SMFMX Melt factor for snow on June 21 (mm H 2 O/ºC-day). If the watershed is in the Northern Hemisphere, SMFMX will be the maximum melt factor. If the watershed is in the Southern Hemisphere, SMFMX will be the minimum melt factor. SMFMX and SMFMN allow the rate of snow melt to vary through the year. The variables account for the impact of snow pack density on snow melt. If no value for SMFMX is entered, the model will set SMFMX = 4.5. Optional. SMFMN Melt factor for snow on December 21 (mm H 2 O/ºC-day). If the watershed is in the Northern Hemisphere, SMFMN will be the minimum melt factor. If the watershed is in the Southern Hemisphere, SMFMN will be the maximum melt factor. SMFMX and SMFMN allow the rate of snow melt to vary through the year. The variables account for the impact of snow pack density on snow melt. If no value for SMFMN is entered, the model will set SMFMN = 4.5. Optional.

238 CHAPTER 33: SWAT INPUT GENERAL WATERSHED ATTRIBUTES 71 Variable name TIMP SNOCOVMX SNO50COV RCN SURLAG APM Definition Snow pack temperature lag factor. This parameter controls the impact of the current day's air temperature on the snow pack temperature. TIMP can vary between 0.0 and 1.0. When TIMP=1.0 there is no lag, i.e. the snow pack temperature is the same as the current day's air temperature. As TIMP goes to zero, the snow pack's temperature will be less influenced by the current day's air temperature. If no value for TIMP is entered, the model will set TIMP = 1.0. Optional. Minimum snow water content that corresponds to 100% snow cover (mm H 2 O). If the snow water content is less than SNOCOVMX, then a certain percentage of ground cover will be bare. If no value for SNOCOVMX is entered, the model will set SNOCOVMX = Optional. Fraction of snow volume represented by SNOCOVMX that corresponds to 50% snow cover. SWAT assumes a nonlinear relationship between snow water and snow cover. If no value for SNO50COV is entered, the model will set SNO50COV = 0.50, i.e. 50% of SNOCOVMX. Optional. Concentration of nitrogen in rainfall (mg N/L). If no value for RCN is entered, the model will set RCN = 1.0. Optional. Surface runoff lag time (days). This parameter is needed in subbasins where the time of concentration is greater than 1 day. SURLAG is used to create a "storage" for surface runoff to allow runoff to take longer than one day to reach the subbasin outlet. If no value for SURLAG is entered, the model will set SURLAG = 4.0. Optional. Peak rate adjustment factor for sediment routing in the subbasin (tributary channels). Sediment routing is a function of peak flow rate and mean daily flow. Because SWAT can not directly calculate the sub-daily hydrograph due to the use of precipitation summarized on a daily basis, this variable was incorporated to allow adjustment for the effect of the peak flow rate on sediment routing. This factor is used in the MUSLE equation and impacts the amount of erosion generated in the HRUs. If no value for APM is entered, the model will set APM=1.0. Optional.

239 72 SWAT USER'S MANUAL, VERSION 2000 Variable name PRF SPCON SPEXP Definition Peak rate adjustment factor for sediment routing in the main channel. Sediment routing is a function of peak flow rate and mean daily flow. Because SWAT can not directly calculate the sub-daily hydrograph, this variable was incorporated to allow adjustment for the effect of the peak flow rate on sediment routing. This variable impacts channel degradation. If no value for PRF is entered, the model will set PRF = 1.0. Optional. Linear parameter for calculating the maximum amount of sediment that can be reentrained during channel sediment routing ( DEG r =SPCON (V c ) SPEXP where DEG r is the amount of sediment reentrained and V c is stream velocity in the channel). SPCON should be between and If no value for SPCON is entered, the model will set SPCON = Optional. Exponent parameter for calculating sediment reentrained in channel sediment routing ( DEG r =SPCON (V c ) SPEXP where DEG r is the amount of sediment reentrained and V c is stream velocity in the channel). SPEXP should be between 1.0 and 1.5. If no value for SPEXP is entered, the model will set SPEXP = 1.0. Optional. The general equation for outgoing long-wave radiation is reviewed in Chapter 2. The following four variables define values for constants in this equation. RBO_A RBO_B RBO_A1 Constant a in cloud cover portion of outgoing long-wave radiation equation. This variable should not be set to a value other than the default unless the user has obtained constants for the region modeled from an experienced climatologist. If no value for RBO_A is entered, the model will set RBO_A = 0.9. Optional. Constant b in cloud cover portion of outgoing long-wave radiation equation. This variable should not be set to a value other than the default unless the user has obtained constants for the region modeled from an experienced climatologist. If no value for RBO_B is entered, the model will set RBO_B = Optional. Constant a 1 in net emissivity portion of outgoing long-wave radiation equation. This variable should not be set to a value other than the default unless the user has obtained constants for the region modeled from an experienced climatologist. If no value for RBO_A1 is entered, the model will set RBO_A1 = Optional.

240 CHAPTER 33: SWAT INPUT GENERAL WATERSHED ATTRIBUTES 73 Variable name RBO_B1 PET_ALPHA EVRCH EVLAI FFCB CMN UBN Definition Constant b 1 in net emissivity portion of outgoing long-wave radiation equation. This variable should not be set to a value other than the default unless the user has obtained constants for the region modeled from an experienced climatologist. If no value for RBO_B1 is entered, the model will set RBO_B1 = Optional. Value for alpha constant in Priestley-Taylor equation for potential evapotranspiration. If no value for PET_ALPHA is entered, the model will set PET_ALPHA = Optional. Reach evaporation adjustment factor. If no value for EVRCH is entered, the model will set EVRCH = Optional Leaf area index at which no evaporation occurs from water surface. EVLAI is used in HRUs where a plant is growing in a ponded environment (e.g. rice). Evaporation from the water surface is allowed until the leaf area of the plant reaches the value specified for EVLAI. EVLAI should be between 0.0 and If no value for EVLAI is entered, the model will set EVLAI = 3.0. Optional. Initial soil water storage expressed as a fraction of field capacity water content. All soils in the watershed will be initialized to the same fraction. If FFCB is not set to a value, the model will calculate it as a function of average annual precipitation. FFCB should be between 0.0 and 1.0. The default method is to allow the model to calculate FFCB (set FFCB = 0.0). Optional. Rate factor for humus mineralization of active organic nitrogen. If no value for CMN is specified, the model will set CMN = Optional. Nitrogen uptake distribution parameter. This parameter controls the amount of nitrogen removed from the different soil layers by the plant. In particular, this parameter controls the amount of nitrogen removed from the surface layer via plant uptake. While the relationship between UBN and nitrogen removed from the surface layer is affected by the depth of the soil profile, in general as UBN increases the amount of N removed from the surface layer relative to the amount removed from the entire profile increases. If no value for UBN is entered, the model will set UBN = Optional.

241 74 SWAT USER'S MANUAL, VERSION 2000 Variable name UBP NPERCO PPERCO PHOSKD PSP RSDCO PERCOP Definition Phosphorus uptake distribution parameter. This parameter controls plant uptake of phosphorus from the different soil horizons in the same way that UBN controls nitrogen uptake. If no value for UBP is entered, the model will set UBP = Optional. Nitrogen percolation coefficient. NPERCO controls the amount of mineral N removed from the surface layer in runoff relative to the amount removed via percolation. The value of NPERCO can range from 0.0 to 1.0. When NPERCO = 0.0, the concentration of mineral N in the runoff is 0. When NPERCO = 1.0, surface runoff has the same concentration of mineral N as the percolate. If no value for NPERCO is entered, the model will set NPERCO = Optional. Phosphorus percolation coefficient. PPERCO is the ratio of the amount of soluble P removed from the surface layer in runoff relative to the amount of soluble P removed via percolation. The value of PPERCO can range from 10.0 to 17.5 If no value for PPERCO is entered, the model will set PPERCO = Optional. Phosphorus soil partitioning coefficient. The ratio of phosphorus attached to sediment to phosphorus dissolved in soil water. If no value for PHOSKD is entered, the model will set PHOSKD = Optional. Phosphorus sorption coefficient. The fraction of mineral phosphorus remaining in the labile pool after initial rapid sorption to soil. If no value for PSP is entered, the model will set PSP = Optional. Residue decomposition coefficient. The fraction of residue which will decompose in a day assuming optimal moisture, temperature, C:N ratio and C:P ratio. If no value for RSDCO is entered, the model will set RSDCO = Optional. Pesticide percolation coefficient. PERCOP controls the amount of pesticide removed from the surface layer in runoff relative to the amount removed via percolation. The value of PERCOP can range from 0.0 to 1.0. When PERCOP = 0.0, the concentration of pesticide in the runoff is 0. When PERCOP = 1.0, surface runoff has the same concentration of pesticide as the percolate. If no value for PERCOP is entered, the model will set PERCOP = Optional.

242 CHAPTER 33: SWAT INPUT GENERAL WATERSHED ATTRIBUTES 75 Variable name IRTPEST WDPQ WGPQ WDLPQ WGLPQ WDPS WGPS WDLPS WGLPS BACTKDQ THBACT MSK_CO1 MSK_CO2 Definition Number of pesticide to be routed through the watershed channel network. This is the pesticide ID number from the pesticide database. While more than one type of pesticide may be applied to the HRUs, the model will monitor the movement of only one pesticide through the channel network. Optional. Die-off factor for persistent bacteria in soil solution. (1/day) Optional. Growth factor for persistent bacteria in soil solution. (1/day) Optional. Die-off factor for less persistent bacteria in soil solution. (1/day) Optional. Growth factor for less persistent bacteria in soil solution. (1/day) Optional. Die-off factor for persistent bacteria adsorbed to soil particles. (1/day) Optional. Growth factor for persistent bacteria adsorbed to soil particles. (1/day) Optional. Die-off factor for less persistent bacteria adsorbed to soil particles. (1/day) Optional. Growth factor for less persistent bacteria adsorbed to soil particles. (1/day) Optional. Bacteria partition coefficient. Partition coefficient for bacteria between soluble and sorbed phase in surface runoff. If no value for BACTKDQ is entered, the model will set BACTKDQ = Optional. Temperature adjustment factor for bacteria die-off/growth. If no value for THBACT is entered, the model will set THBACT = Optional. Calibration coefficient used to control impact of the storage time constant (K m ) for normal flow (where normal flow is when river is at bankfull depth) upon the K m value calculated for the reach. Required only if IRTE = 1 in.cod file. Calibration coefficient used to control impact of the storage time constant (K m ) for low flow (where low flow is when river is at 0.1 bankfull depth) upon the K m value calculated for the reach. Required only if IRTE = 1 in.cod file.

243 76 SWAT USER'S MANUAL, VERSION 2000 Variable name MSK_X Definition Weighting factor controlling relative importance of inflow rate and outflow rate in determining water storage in reach segment. The values for MSK_X can range from If no value for MSK_X is entered, the model will set MSK_X = 0.2. Required only if IRTE = 1 in.cod file. The basin input file is a free format file. The variables may be placed in any position the user wishes on the line. Values for variables classified as integers should not include a decimal while values for variables classified as reals must contain a decimal. A blank space denotes the end of an input value and the beginning of the next value if there is another on the line Variable name Line # Format F90 Format TITLE 1 character a80 DA_KM 2 real free DT 3 real free SFTMP 4 real free SMTMP 5 real free SMFMX 6 real free SMFMN 7 real free TIMP 8 real free SNOCOVMX 9 real free SNO50COV 10 real free RCN 11 real free SURLAG 12 real free APM 13 real free PRF 14 real free SPCON 15 real free SPEXP 16 real free RBO_A 17 real free RBO_B 18 real free RBO_A1 19 real free RBO_B1 20 real free PET_ALPHA 21 real free EVRCH 22 real free EVLAI 23 real free

244 CHAPTER 33: SWAT INPUT GENERAL WATERSHED ATTRIBUTES 77 Variable name Line # Format F90 Format FFCB 24 real free CMN 25 real free UBN 26 real free UBP 27 real free NPERCO 28 real free PPERCO 29 real free PHOSKD 30 real free PSP 31 real free RSDCO 32 real free PERCOP 33 real free IRTPEST 34 integer free WDPQ 35 real free WGPQ 36 real free WDLPQ 37 real free WGLPQ 38 real free WDPS 39 real free WGPS 40 real free WDLPS 41 real free WGLPS 42 real free BACTKDQ 43 real free THBACT 44 real free MSK_CO1 45 real free MSK_CO2 46 real free MSK_X 47 real free

245 78 SWAT USER'S MANUAL, VERSION 2000

246 CHAPTER 34 SWAT INPUT DATA: CLIMATE SWAT requires daily precipitation, maximum/minimum air temperature, solar radiation, wind speed and relative humidity. Values for all these parameters may be read from records of observed data or they may be generated Seven types of files store the climatic data required by SWAT the weather generator input file (.wgn), the measured precipitation file (.pcp), the measured temperature file (.tmp), the solar radiation input file (.slr), the wind speed input file (.wnd), the relative humidity input file (.hmd), and the potential evapotranspiration input file (.pet). Up to 18 precipitation files and 18 temperature files may be utilized in a simulation. The precipitation and temperature files are able to hold records for more than one gage, so there is not a limitation on the number of gages that can be used in a simulation. One solar radiation file, wind 77

247 78 SWAT USER'S MANUAL, VERSION 2000 speed file and relative humidity input file may be used in a simulation. As for precipitation and temperature, these files are able to hold records for more than one gage, so there is not a limitation on the number of gages that can be used in a simulation. The potential evapotranspiration file holds only one record that is used for the entire watershed WEATHER GENERATOR INPUT FILE (.WGN) The weather generator input file contains the statistical data needed to generate representative daily climate data for the subbasins. Climatic data will be generated in two instances: when the user specifies that simulated weather will be used or when measured data is missing. Following is a brief description of the variables in the weather generator input file. They are listed in the order they appear within the file. Variable name TITLE WLATITUDE WLONGITUDE WELEV RAIN_YRS TMPMX(mon) TMPMN(mon) TMPSTDMX(mon) Definition The first line of the.wgn file is reserved for user comments. The comments may take up to 80 spaces. (optional) Latitude of weather station used to create statistical parameters (degrees). The latitude is expressed as a real number with minutes and seconds converted to fractions of a degree. Optional. Longitude of weather station (degrees). This variable is not used by the model. Optional. Elevation of weather station (m). Optional. The number of years of maximum monthly 0.5 h rainfall data used to define values for RAIN_HHMX(1,:) - RAIN_HHMX(12,:). Average daily maximum air temperature for month (ºC). Average daily minimum air temperature for month (ºC). Standard deviation for daily maximum air temperature in month (ºC).

248 CHAPTER 34: SWAT INPUT CLIMATE 79 Variable name TMPSTDMN(mon) PCPMM(mon) PCPSTD(mon) PCPSKW(mon) PR_W(1,mon) PR_W(2,mon) PCPD(mon) RAINHHMX(mon) SOLARAV(mon) DEWPT(mon) WNDAV(mon) Definition Standard deviation for daily minimum air temperature in month (ºC). Average amount of precipitation falling in month (mm H 2 O). Standard deviation for daily precipitation in month (mm H 2 O/day ). Skew coefficient for daily precipitation in month. Probability of a wet day following a dry day in the month. Probability of a wet day following a wet day in the month. Average number of days of precipitation in month. Maximum 0.5 hour rainfall in entire period of record for month (mm). Average daily solar radiation for month (MJ/m 2 /day). Average daily dew point temperature in month (ºC). Average daily wind speed in month (m/s). The forma of the weather generator input file is: Variable name Line # Position Format F90 Format TITLE 1 space 1-80 character a80 WLATITUDE 2 space decimal(xxxx.xx) f7.2 WLONGITUDE 2 space decimal(xxxx.xx) f7.2 WELEV 3 space decimal(xxxx.xx) f7.2 RAIN_YRS 4 space decimal(xxxx.xx) f7.2 TMPMX(1) 5 space 1-6 decimal(xxx.xx) f6.2 TMPMX(2) 5 space 7-12 decimal(xxx.xx) f6.2 TMPMX(3) 5 space decimal(xxx.xx) f6.2 TMPMX(4) 5 space decimal(xxx.xx) f6.2 TMPMX(5) 5 space decimal(xxx.xx) f6.2 TMPMX(6) 5 space decimal(xxx.xx) f6.2 TMPMX(7) 5 space decimal(xxx.xx) f6.2 TMPMX(8) 5 space decimal(xxx.xx) f6.2 TMPMX(9) 5 space decimal(xxx.xx) f6.2 TMPMX(10) 5 space decimal(xxx.xx) f6.2

249 80 SWAT USER'S MANUAL, VERSION 2000 Variable name Line # Position Format F90 Format TMPMX(11) 5 space decimal(xxx.xx) f6.2 TMPMX(12) 5 space decimal(xxx.xx) f6.2 TMPMN(1) 6 space 1-6 decimal(xxx.xx) f6.2 TMPMN(2) 6 space 7-12 decimal(xxx.xx) f6.2 TMPMN(3) 6 space decimal(xxx.xx) f6.2 TMPMN(4) 6 space decimal(xxx.xx) f6.2 TMPMN(5) 6 space decimal(xxx.xx) f6.2 TMPMN(6) 6 space decimal(xxx.xx) f6.2 TMPMN(7) 6 space decimal(xxx.xx) f6.2 TMPMN(8) 6 space decimal(xxx.xx) f6.2 TMPMN(9) 6 space decimal(xxx.xx) f6.2 TMPMN(10) 6 space decimal(xxx.xx) f6.2 TMPMN(11) 6 space decimal(xxx.xx) f6.2 TMPMN(12) 6 space decimal(xxx.xx) f6.2 TMPSTDMX(1) 7 space 1-6 decimal(xxx.xx) f6.2 TMPSTDMX(2) 7 space 7-12 decimal(xxx.xx) f6.2 TMPSTDMX(3) 7 space decimal(xxx.xx) f6.2 TMPSTDMX(4) 7 space decimal(xxx.xx) f6.2 TMPSTDMX(5) 7 space decimal(xxx.xx) f6.2 TMPSTDMX(6) 7 space decimal(xxx.xx) f6.2 TMPSTDMX(7) 7 space decimal(xxx.xx) f6.2 TMPSTDMX(8) 7 space decimal(xxx.xx) f6.2 TMPSTDMX(9) 7 space decimal(xxx.xx) f6.2 TMPSTDMX(10) 7 space decimal(xxx.xx) f6.2 TMPSTDMX(11) 7 space decimal(xxx.xx) f6.2 TMPSTDMX(12) 7 space decimal(xxx.xx) f6.2 TMPSTDMN(1) 8 space 1-6 decimal(xxx.xx) f6.2 TMPSTDMN(2) 8 space 7-12 decimal(xxx.xx) f6.2 TMPSTDMN(3) 8 space decimal(xxx.xx) f6.2 TMPSTDMN(4) 8 space decimal(xxx.xx) f6.2 TMPSTDMN(5) 8 space decimal(xxx.xx) f6.2 TMPSTDMN(6) 8 space decimal(xxx.xx) f6.2 TMPSTDMN(7) 8 space decimal(xxx.xx) f6.2 TMPSTDMN(8) 8 space decimal(xxx.xx) f6.2 TMPSTDMN(9) 8 space decimal(xxx.xx) f6.2

250 CHAPTER 34: SWAT INPUT CLIMATE 81 Variable name Line # Position Format F90 Format TMPSTDMN(10) 8 space decimal(xxx.xx) f6.2 TMPSTDMN(11) 8 space decimal(xxx.xx) f6.2 TMPSTDMN(12) 8 space decimal(xxx.xx) f6.2 PCPMM(1) 9 space 1-6 decimal(xxx.xx) f6.2 PCPMM(2) 9 space 7-12 decimal(xxx.xx) f6.2 PCPMM(3) 9 space decimal(xxx.xx) f6.2 PCPMM(4) 9 space decimal(xxx.xx) f6.2 PCPMM(5) 9 space decimal(xxx.xx) f6.2 PCPMM(6) 9 space decimal(xxx.xx) f6.2 PCPMM(7) 9 space decimal(xxx.xx) f6.2 PCPMM(8) 9 space decimal(xxx.xx) f6.2 PCPMM(9) 9 space decimal(xxx.xx) f6.2 PCPMM(10) 9 space decimal(xxx.xx) f6.2 PCPMM(11) 9 space decimal(xxx.xx) f6.2 PCPMM(12) 9 space decimal(xxx.xx) f6.2 PCPSTD(1) 10 space 1-6 decimal(xxx.xx) f6.2 PCPSTD(2) 10 space 7-12 decimal(xxx.xx) f6.2 PCPSTD(3) 10 space decimal(xxx.xx) f6.2 PCPSTD(4) 10 space decimal(xxx.xx) f6.2 PCPSTD(5) 10 space decimal(xxx.xx) f6.2 PCPSTD(6) 10 space decimal(xxx.xx) f6.2 PCPSTD(7) 10 space decimal(xxx.xx) f6.2 PCPSTD(8) 10 space decimal(xxx.xx) f6.2 PCPSTD(9) 10 space decimal(xxx.xx) f6.2 PCPSTD(10) 10 space decimal(xxx.xx) f6.2 PCPSTD(11) 10 space decimal(xxx.xx) f6.2 PCPSTD(12) 10 space decimal(xxx.xx) f6.2 PCPSKW(1) 11 space 1-6 decimal(xxx.xx) f6.2 PCPSKW(2) 11 space 7-12 decimal(xxx.xx) f6.2 PCPSKW(3) 11 space decimal(xxx.xx) f6.2 PCPSKW(4) 11 space decimal(xxx.xx) f6.2 PCPSKW(5) 11 space decimal(xxx.xx) f6.2 PCPSKW(6) 11 space decimal(xxx.xx) f6.2 PCPSKW(7) 11 space decimal(xxx.xx) f6.2 PCPSKW(8) 11 space decimal(xxx.xx) f6.2

251 82 SWAT USER'S MANUAL, VERSION 2000 Variable name Line # Position Format F90 Format PCPSKW(9) 11 space decimal(xxx.xx) f6.2 PCPSKW(10) 11 space decimal(xxx.xx) f6.2 PCPSKW(11) 11 space decimal(xxx.xx) f6.2 PCPSKW(12) 11 space decimal(xxx.xx) f6.2 PR_W(1,1) 12 space 1-6 decimal(xxx.xx) f6.2 PR_W(1,2) 12 space 7-12 decimal(xxx.xx) f6.2 PR_W(1,3) 12 space decimal(xxx.xx) f6.2 PR_W(1,4) 12 space decimal(xxx.xx) f6.2 PR_W(1,5) 12 space decimal(xxx.xx) f6.2 PR_W(1,6) 12 space decimal(xxx.xx) f6.2 PR_W(1,7) 12 space decimal(xxx.xx) f6.2 PR_W(1,8) 12 space decimal(xxx.xx) f6.2 PR_W(1,9) 12 space decimal(xxx.xx) f6.2 PR_W(1,10) 12 space decimal(xxx.xx) f6.2 PR_W(1,11) 12 space decimal(xxx.xx) f6.2 PR_W(1,12) 12 space decimal(xxx.xx) f6.2 PR_W(2,1) 13 space 1-6 decimal(xxx.xx) f6.2 PR_W(2,2) 13 space 7-12 decimal(xxx.xx) f6.2 PR_W(2,3) 13 space decimal(xxx.xx) f6.2 PR_W(2,4) 13 space decimal(xxx.xx) f6.2 PR_W(2,5) 13 space decimal(xxx.xx) f6.2 PR_W(2,6) 13 space decimal(xxx.xx) f6.2 PR_W(2,7) 13 space decimal(xxx.xx) f6.2 PR_W(2,8) 13 space decimal(xxx.xx) f6.2 PR_W(2,9) 13 space decimal(xxx.xx) f6.2 PR_W(2,10) 13 space decimal(xxx.xx) f6.2 PR_W(2,11) 13 space decimal(xxx.xx) f6.2 PR_W(2,12) 13 space decimal(xxx.xx) f6.2 PCPD(1) 14 space 1-6 decimal(xxx.xx) f6.2 PCPD(2) 14 space 7-12 decimal(xxx.xx) f6.2 PCPD(3) 14 space decimal(xxx.xx) f6.2 PCPD(4) 14 space decimal(xxx.xx) f6.2 PCPD(5) 14 space decimal(xxx.xx) f6.2 PCPD(6) 14 space decimal(xxx.xx) f6.2 PCPD(7) 14 space decimal(xxx.xx) f6.2

252 CHAPTER 34: SWAT INPUT CLIMATE 83 Variable name Line # Position Format F90 Format PCPD(8) 14 space decimal(xxx.xx) f6.2 PCPD(9) 14 space decimal(xxx.xx) f6.2 PCPD(10) 14 space decimal(xxx.xx) f6.2 PCPD(11) 14 space decimal(xxx.xx) f6.2 PCPD(12) 14 space decimal(xxx.xx) f6.2 RAINHHMX(1) 15 space 1-6 decimal(xxx.xx) f6.2 RAINHHMX(2) 15 space 7-12 decimal(xxx.xx) f6.2 RAINHHMX(3) 15 space decimal(xxx.xx) f6.2 RAINHHMX(4) 15 space decimal(xxx.xx) f6.2 RAINHHMX(5) 15 space decimal(xxx.xx) f6.2 RAINHHMX(6) 15 space decimal(xxx.xx) f6.2 RAINHHMX(7) 15 space decimal(xxx.xx) f6.2 RAINHHMX(8) 15 space decimal(xxx.xx) f6.2 RAINHHMX(9) 15 space decimal(xxx.xx) f6.2 RAINHHMX(10) 15 space decimal(xxx.xx) f6.2 RAINHHMX(11) 15 space decimal(xxx.xx) f6.2 RAINHHMX(12) 15 space decimal(xxx.xx) f6.2 SOLARAV(1) 16 space 1-6 decimal(xxx.xx) f6.2 SOLARAV(2) 16 space 7-12 decimal(xxx.xx) f6.2 SOLARAV(3) 16 space decimal(xxx.xx) f6.2 SOLARAV(4) 16 space decimal(xxx.xx) f6.2 SOLARAV(5) 16 space decimal(xxx.xx) f6.2 SOLARAV(6) 16 space decimal(xxx.xx) f6.2 SOLARAV(7) 16 space decimal(xxx.xx) f6.2 SOLARAV(8) 16 space decimal(xxx.xx) f6.2 SOLARAV(9) 16 space decimal(xxx.xx) f6.2 SOLARAV(10) 16 space decimal(xxx.xx) f6.2 SOLARAV(11) 16 space decimal(xxx.xx) f6.2 SOLARAV(12) 16 space decimal(xxx.xx) f6.2 DEWPT(1) 17 space 1-6 decimal(xxx.xx) f6.2 DEWPT(2) 17 space 7-12 decimal(xxx.xx) f6.2 DEWPT(3) 17 space decimal(xxx.xx) f6.2 DEWPT(4) 17 space decimal(xxx.xx) f6.2 DEWPT(5) 17 space decimal(xxx.xx) f6.2 DEWPT(6) 17 space decimal(xxx.xx) f6.2

253 84 SWAT USER'S MANUAL, VERSION 2000 Variable name Line # Position Format F90 Format DEWPT(7) 17 space decimal(xxx.xx) f6.2 DEWPT(8) 17 space decimal(xxx.xx) f6.2 DEWPT(9) 17 space decimal(xxx.xx) f6.2 DEWPT(10) 17 space decimal(xxx.xx) f6.2 DEWPT(11) 17 space decimal(xxx.xx) f6.2 DEWPT(12) 17 space decimal(xxx.xx) f6.2 WNDAV(1) 18 space 1-6 decimal(xxx.xx) f6.2 WNDAV(2) 18 space 7-12 decimal(xxx.xx) f6.2 WNDAV(3) 18 space decimal(xxx.xx) f6.2 WNDAV(4) 18 space decimal(xxx.xx) f6.2 WNDAV(5) 18 space decimal(xxx.xx) f6.2 WNDAV(6) 18 space decimal(xxx.xx) f6.2 WNDAV(7) 18 space decimal(xxx.xx) f6.2 WNDAV(8) 18 space decimal(xxx.xx) f6.2 WNDAV(9) 18 space decimal(xxx.xx) f6.2 WNDAV(10) 18 space decimal(xxx.xx) f6.2 WNDAV(11) 18 space decimal(xxx.xx) f6.2 WNDAV(12) 18 space decimal(xxx.xx) f PRECIPITATION INPUT FILE (.PCP) Measured precipitation data is read into the model from the.pcp file. The precipitation data may be read into the model in daily or sub-daily time increments. The following sections describe the format for a daily and a subdaily precipitation file DAILY PRECIPITATION DATA Daily precipitation data is used when the SCS curve number method is chosen to model surface runoff (Set by IEVENT in the.cod file). While the input file must contain data for the entire period of simulation, the record does not have to begin with the first day of simulation. SWAT is able to search for the beginning date in the file, saving editing time on the user's part. Once SWAT locates the record for the beginning day of simulation, it no longer

254 CHAPTER 34: SWAT INPUT CLIMATE 85 processes the year and date. Because it does not check the subsequent dates, it is very important that the data for the remaining days in the simulation are listed sequentially. (If no year and date are entered for any of the records, the model assumes the first line data corresponds to the first day of simulation.) A negative 99.0 (-99.0) should be inserted for missing data. This value tells SWAT to generate precipitation for that day. Following is a brief description of the variables in the precipitation input file. They are listed in the order they appear within the file. Variable name TITLE LATITUDE LONGITUDE ELEVATION YEAR DATE PRECIPITATION Definition The first line of the precipitation file is reserved for comments. Latitude of precipitation recording gage location. This value is not used by the model. Longitude of precipitation recording gage location. This value is not used by the model. Elevation of precipitation recording gage station (m). Precipitation values are adjusted for elevation in subbasins where elevation bands are defined. Year (4-digit) Julian date Amount of precipitation falling in the time period (mm) The format of the daily precipitation file is: Variable name Line # Position Format F90 Format TITLE 1 unrestricted character unrestricted LATITUDE 2 space 8-12 free unrestricted LONGITUDE 3 space 8-12 free unrestricted ELEVATION 4 space 8-12 integer i5 YEAR 5-END space 1-4 integer i4 DATE 5-END space 5-7 integer i3 PRECIPITATION 5-END space 8-12 decimal(xxx.x) f5.1

255 86 SWAT USER'S MANUAL, VERSION SUB-DAILY PRECIPITATION Sub-daily precipitation data is required if the Green & Ampt infiltration method is being used (Set by IEVENT in the.cod file). When the Green & Ampt infiltration method is used to calculate surface runoff, SWAT is unable to generate precipitation data. Because of this, PCPSIM in the.cod file must be set to 1 and negative 99.0 (-99.0) should not be inserted for missing data. An independent weather generator or extrapolation from adjacent weather stations should be used to fill in missing data. While the input file must contain data for the entire period of simulation, the record does not have to begin with the first day of simulation. SWAT is able to search for the beginning date in the file, saving editing time on the user's part. Unlike the daily precipitation data, SWAT verifies that the date is correct on all lines. If the model reads in an incorrect date, it will print an error message to the input.std file stating the day and year in the precipitation record where the inconsistency is located and the program will stop. The number of lines of precipitation data per day is governed by the time step used (IDT in the.cod file). To save space, only one line is required for days with no rain at all. When SWAT reads a blank for the delimiter (see variable list below), it knows that all time steps on the day have no precipitation and that there are no more lines of precipitation data for that day. Following is a brief description of the variables in the sub-daily precipitation input file. They are listed in the order they appear within the file. Variable name TITLE LATITUDE LONGITUDE Definition The first line of the precipitation file is reserved for comments. Latitude of precipitation recording gage location. This value is not used by the model. Longitude of precipitation recording gage location. This value is not used by the model.

256 CHAPTER 34: SWAT INPUT CLIMATE 87 Variable name ELEVATION YEAR DATE HOUR DELIMITER MINUTE PRECIPITATION Definition Elevation of precipitation recording gage station (m). Precipitation values are adjusted for elevation in subbasins where elevation bands are defined. Year (4-digit) Julian date Hour of day (0-23). The hour and minute are at the end of the time step. Space is allowed on the line for a colon to separate the hour and minute readings. The delimiter is used by the model to identify days where there is no rain and only one line is present for the day in the.pcp file. If a blank space is inserted instead of the colon, the model will assign zero precipitation to all time steps on the day. Minute of hour (0-59). The hour and minute are at the end of the time step. Amount of precipitation falling in the time period (mm) The format of the sub-daily precipitation file is: Variable name Line # Position Format F90 Format TITLE 1 unrestricted character unrestricted LATITUDE 2 space 8-12 free unrestricted LONGITUDE 3 space 8-12 free unrestricted ELEVATION 4 space 8-12 integer i5 YEAR 5-END space 1-4 integer i4 DATE 5-END space 5-7 integer i3 HOUR 5-END space 8-9 integer i2 DELIMITER 5-END space 10 character a1 MINUTE 5-END space integer i2 PRECIPITATION 5-END space decimal(xxx.x) f5.1

257 88 SWAT USER'S MANUAL, VERSION TEMPERATURE INPUT FILE (.TMP) Measured temperature data is read into the model from the.tmp file. A negative 99.0 (-99.0) should be inserted for missing maximum or minimum temperatures. This value tells SWAT to generate the missing value(s). As with the precipitation file, the record in the temperature input file does not have to begin with the first day of simulation. SWAT is able to search for the beginning date in the temperature file and all the comments made for this feature in the discussion of the precipitation file pertain to the temperature file as well. Following is a brief description of the variables in the temperature input file. They are listed in the order they appear within the file. Variable name TITLE LATITUDE LONGITUDE ELEVATION YEAR DATE MAX TEMP MIN TEMP Definition The first line of the temperature file is reserved for comments. Latitude of temperature recording gage location. This value is not used by the model. Longitude of temperature recording gage location. This value is not used by the model. Elevation of temperature recording gage station (m). Temperature values are adjusted for elevation in subbasins where elevation bands are defined. Year (4-digit) Julian date Daily maximum temperature (ºC). Daily minimum temperature (ºC).

258 CHAPTER 34: SWAT INPUT CLIMATE 89 The format of the temperature file is: Variable name Line # Position Format F90 Format TITLE 1 unrestricted character unrestricted LATITUDE 2 space 8-17 free LONGITUDE 3 space 8-17 free ELEVATION 4 space 8-17 integer i10 YEAR 5-END space digit integer i4 DATE 5-END space digit integer i3 MAX TEMP 5-END space 8-12 decimal(xxx.x) f5.1 MIN TEMP 5-END space decimal(xxx.x) f SOLAR RADIATION INPUT FILE (.SLR) Measured solar radiation data is read into the model from the.slr file. A negative 99.0 (-99.0) should be inserted for missing radiation values. This value tells SWAT to generate the missing value(s). As with the precipitation file, the record in the solar radiation input file does not have to begin with the first day of simulation. SWAT is able to search for the beginning date in the solar radiation file and all the comments made for this feature in the discussion of the precipitation file pertain to the solar radiation file as well. Following is a brief description of the variables in the solar radiation input file. They are listed in the order they appear within the file. Variable name TITLE Definition The first line of the solar radiation file is reserved for comments. YEAR Year (4-digit) DATE Julian date SOL_RAD Daily total solar radiation (MJ/m 2 ).

259 90 SWAT USER'S MANUAL, VERSION 2000 The format of the solar radiation input file is: Variable name Line # Position Format F90 Format TITLE 1 unrestricted character unrestricted YEAR 2-END space digit integer i4 DATE 2-END space digit integer i3 SOL_RAD 2-END space 8-12 decimal(xxxx.xxx) f WIND SPEED INPUT FILE (.WND) Measured wind speed data is read into the model from the.wnd file. A negative 99.0 (-99.0) should be inserted for missing wind speed values. This value tells SWAT to generate the missing value(s). As with the precipitation file, the record in the wind speed input file does not have to begin with the first day of simulation. SWAT is able to search for the beginning date in the wind speed file and all the comments made for this feature in the discussion of the precipitation file pertain to the wind speed file as well. Following is a brief description of the variables in the wind speed input file. They are listed in the order they appear within the file. Variable name TITLE YEAR DATE WND_SP Definition The first line of the wind speed radiation file is reserved for comments. Year (4-digit) Julian date Daily average wind speed (m/s). The format of the wind speed input file is: Variable name Line # Position Format F90 Format TITLE 1 unrestricted character unrestricted YEAR 2-END space digit integer i4 DATE 2-END space digit integer i3 WND_SP 2-END space 8-12 decimal(xxxx.xxx) f8.3

260 CHAPTER 34: SWAT INPUT CLIMATE RELATIVE HUMIDITY INPUT FILE (.HMD) Measured relative humidity data is read into the model from the.hmd file. A negative 99.0 (-99.0) should be inserted for missing relative humidity values. This value tells SWAT to generate the missing value(s). As with the precipitation file, the record in the relative humidity input file does not have to begin with the first day of simulation. SWAT is able to search for the beginning date in the relative humidity file and all the comments made for this feature in the discussion of the precipitation file pertain to the relative humidity file as well. Following is a brief description of the variables in the relative humidity input file. They are listed in the order they appear within the file. Variable name TITLE YEAR DATE RHD Definition The first line of the wind speed radiation file is reserved for comments. Year (4-digit) Julian date Daily average relative humidity expressed as a fraction. The format of the relative humidity input file is: Variable name Line # Position Format F90 Format TITLE 1 unrestricted character unrestricted YEAR 2-END space digit integer i4 DATE 2-END space digit integer i3 RHD 2-END space 8-12 decimal(xxxx.xxx) f POTENTIAL EVAPOTRANSPIRATION INPUT FILE (.PET) Daily potential evapotranspiration data is read into the model from the.pet file. As with the precipitation file, the record in the potential evapotranspiration input file does not have to begin with the first day of simulation. SWAT is able to

261 92 SWAT USER'S MANUAL, VERSION 2000 search for the beginning date in the potential evapotranspiration input file and all the comments made for this feature in the discussion of the precipitation file pertain to the potential evapotranspiration file as well. Following is a brief description of the variables in the potential evapotranspiration input file. They are listed in the order they appear within the file. Variable name TITLE YEAR DATE PETMEAS Definition The first line of the wind speed radiation file is reserved for comments. Year (4-digit) Julian date Daily potential evapotranspiration for watershed (mm H 2 O). The format of the potential evapotranspiration input file is: Variable name Line # Position Format F90 Format TITLE 1 unrestricted character unrestricted YEAR 2-END space digit integer i4 DATE 2-END space digit integer i3 RHD 2-END space 8-12 decimal(xxx.x) f MULTIPLE RECORDS IN CLIMATE FILES To place more than one data record within a.pcp,.tmp,.slr,.wnd, or.hmd file, repeat the original formatting for the recorded data to the right of the existing data. Simulations have been run with 200 records placed in the precipitation and temperature files. For example, assume there are 18 precipitation input files, each containing records for ten different rain gages. The formatting of each file is

262 CHAPTER 34: SWAT INPUT CLIMATE 93 Gage Variable name Line # Position Format F90 Format ALL YEAR 5-END space digit integer i4 ALL DATE 5-END space digit integer i3 1 PRECIPITATION 5-END space 8-12 decimal(xxx.x) f5.1 2 PRECIPITATION 5-END space decimal(xxx.x) f5.1 3 PRECIPITATION 5-END space decimal(xxx.x) f5.1 4 PRECIPITATION 5-END space decimal(xxx.x) f5.1 5 PRECIPITATION 5-END space decimal(xxx.x) f5.1 6 PRECIPITATION 5-END space decimal(xxx.x) f5.1 7 PRECIPITATION 5-END space decimal(xxx.x) f5.1 8 PRECIPITATION 5-END space decimal(xxx.x) f5.1 9 PRECIPITATION 5-END space decimal(xxx.x) f PRECIPITATION 5-END space decimal(xxx.x) f5.1 When assigning the different gages to the subbasins in file.cio, instead of inputting the number of the precipitation file for IRGAGE, a gage number is input. Unique gage numbers are assigned to all records files in the following manner: Numbering is begun in the file assigned to RFILE(1): the ten gages in this file are numbered from left to right: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10. Moving to the next precipitation file, RFILE(2), the gages are numbered from left to right beginning where the previous file left off: 11, 12, 13, 14, 15, 16, 17, 18, 19, 20. In the same manner, the gages in RFILE(3), RFILE(4), RFILE(5), RFILE(6), etc. will be processed. Multiple records in temperature files are handled in the same manner, with the formatting of the records in the temperature files repeating every 10 spaces instead of every 5 spaces. For solar radiation, wind speed and relative humidity, the formatting of the records repeats every 8 spaces.

263 94 SWAT USER'S MANUAL, VERSION 2000

264 CHAPTER 35 SWAT INPUT DATA: GENERAL ATTRIBUTES The subbasin and HRU general input files contain information related to a diversity of features within the HRU and its subbasin. Data contained in the subbasin input file can be grouped into the following categories: properties of tributary channels within the subbasin, the amount of topographic relief within the subbasin and its impact on the climate, variables related to climate change, the number of HRUs in the subbasin and the names of HRU input files. Data contained in the HRU input file can be grouped into the following categories: area contained in HRU, parameters affecting surface and subsurface water flow, parameters affecting erosion and management inputs related to the simulation of urban areas, irrigation, tile drains and potholes. 89

265 90 SWAT USER'S MANUAL, VERSION SUBBASIN GENERAL INPUT FILE (.SUB) Following is a brief description of the variables in the subbasin general input file. They are listed in the order they appear within the file. Variable name TITLE HRUTOT LATITUDE ELEV Definition The first line of the.sub file is reserved for user comments. The comments may take up to 80 spaces. Optional. Total number of HRUs modeled in the subbasin. Latitude of subbasin (degrees). The latitude is expressed as a real number with minutes and seconds converted to fractions of a degree. Elevation of subbasin (m). ELEVB(band) Elevation at the center of the elevation band (m). Up to 10 zones may be specified. Optional. ELEVB_FR(band) SNOEB(band) PLAPS Fraction of subbasin area within the elevation band. Values for ELEVB_FR should be between 0.0 and 1.0. Optional. Initial snow water content in elevation band (mm H 2 O). Optional. Precipitation lapse rate (mm H 2 O/km). A positive value denotes an increase in precipitation with an increase in elevation while a negative value denotes a decrease in precipitation with an increase in elevation. The lapse rate is used to adjust precipitation for elevation bands in the subbasin. If no elevation bands are defined, the precipitation generated or read in from the.pcp file is used for the subbasin with no adjustment. To adjust the precipitation, the elevation of the recording station or the weather station is compared to the elevation specified for the elevation band. Optional.

266 CHAPTER 35: SWAT INPUT GENERAL HRU ATTRIBUTES 91 Variable name TLAPS SNO_SUB CH_L(1) CH_S(1) CH_W(1) CH_K(1) CH_N(1) CO2 RFINC(mon) Definition Temperature lapse rate (ºC/km). A positive value denotes an increase in temperature with an increase in elevation while a negative value denotes a decrease in temperature with an increase in elevation. If no value is entered for TLAPS, the model sets TLAPS = -6 ºC/km. The lapse rate is used to adjust temperature for elevation bands in the subbasin. If no elevation bands are defined, the temperature generated or read in from the.tmp file is used for the subbasin with no adjustment. To adjust the temperature, the elevation of the recording station or the weather station is compared to the elevation specified for the elevation band. Optional. Initial snow water content (mm H 2 O). This value is not needed if the subbasin is divided into elevation bands (see variables ELEVB, ELEVB_FR and SNOEB in this file). Optional. Longest tributary channel length in subbasin (km). The channel length is the distance along the channel from the subbasin outlet to the most distant point in the subbasin. Average slope of tributary channels (m/m). The average channel slope is computed by taking the difference in elevation between the subbasin outlet and the most distant point in the subbasin and dividing by CH_L. Average width of tributary channels (m). Effective hydraulic conductivity in tributary channel alluvium (mm/hr). Manning's "n" value for the tributary channels. Carbon dioxide concentration (ppmv). If no value for CO2 is entered the model will set CO2 = 330 ppmv (ambient CO 2 concentration). (Optional used in climate change studies only) Rainfall adjustment (% change). (Optional used in climate change studies only). Daily rainfall within the month is adjusted by the specified percentage. For example, setting RFINC = 10 will make rainfall equal to 110% of the original value.

267 92 SWAT USER'S MANUAL, VERSION 2000 Variable name TMPINC(mon) RADINC(mon) HUMINC(mon) HRUDAT MGTDAT SOILDAT CHEMDAT GWDAT Definition Temperature adjustment (ºC). (Optional used in climate change studies only). Daily maximum and minimum temperatures within the month are raised or lowered by the specified amount. Radiation adjustment (MJ/m 2 -day). (Optional used in climate change studies only). Daily radiation within the month is raised or lowered by the specified amount. Humidity adjustment. (Optional used in climate change studies only). Daily values for relative humidity within the month are raised or lowered by the specified amount. The relative humidity in SWAT is reported as a fraction. Name of HRU general input data file (.hru). Name of HRU land use management data file (.mgt). Name of HRU soil data file (.sol). Name of HRU soil chemical data file (.chm). Name of HRU groundwater data file (.gw). The subbasin general input file is partially free format and partially fixed format. The variables that are free format will have free listed in the F90Format column and will not have a position defined. The variables that are fixed format will have a FORTRAN format and position specified. The free format variables may be placed in any position the user wishes on the line. Values for variables classified as integers should not include a decimal while values for variables classified as reals must contain a decimal. A blank space denotes the end of an input value and the beginning of the next value if there is another on the line. The fixed format variables must be entered using the specified format and positioning on the line in order for the model to read them properly.

268 CHAPTER 35: SWAT INPUT GENERAL HRU ATTRIBUTES 93 The format for the subbasin general input file is: Variable name Line # Position Format F90 Format TITLE 1 space 1-80 character a80 HRUTOT 2 integer free LATITUDE 3 real free ELEV 4 real free COMMENT LINE 5 space 1-80 character a80 ELEVB(1) 6 space 1-8 decimal (xxxx.xxx) f8.3 ELEVB(2) 6 space 9-16 decimal (xxxx.xxx) f8.3 ELEVB(3) 6 space decimal (xxxx.xxx) f8.3 ELEVB(4) 6 space decimal (xxxx.xxx) f8.3 ELEVB(5) 6 space decimal (xxxx.xxx) f8.3 ELEVB(6) 6 space decimal (xxxx.xxx) f8.3 ELEVB(7) 6 space decimal (xxxx.xxx) f8.3 ELEVB(8) 6 space decimal (xxxx.xxx) f8.3 ELEVB(9) 6 space decimal (xxxx.xxx) f8.3 ELEVB(10) 6 space decimal (xxxx.xxx) f8.3 COMMENT LINE 7 space 1-80 character a80 ELEVB_FR(1) 8 space 1-8 decimal (xxxx.xxx) f8.3 ELEVB_FR(2) 8 space 9-16 decimal (xxxx.xxx) f8.3 ELEVB_FR(3) 8 space decimal (xxxx.xxx) f8.3 ELEVB_FR(4) 8 space decimal (xxxx.xxx) f8.3 ELEVB_FR(5) 8 space decimal (xxxx.xxx) f8.3 ELEVB_FR(6) 8 space decimal (xxxx.xxx) f8.3 ELEVB_FR(7) 8 space decimal (xxxx.xxx) f8.3 ELEVB_FR(8) 8 space decimal (xxxx.xxx) f8.3 ELEVB_FR(9) 8 space decimal (xxxx.xxx) f8.3 ELEVB_FR(10) 8 space decimal (xxxx.xxx) f8.3 COMMENT LINE 9 space 1-80 character a80 SNOEB(1) 10 space 1-8 decimal (xxxx.xxx) f8.3 SNOEB(2) 10 space 9-16 decimal (xxxx.xxx) f8.3 SNOEB(3) 10 space decimal (xxxx.xxx) f8.3 SNOEB(4) 10 space decimal (xxxx.xxx) f8.3 SNOEB(5) 10 space decimal (xxxx.xxx) f8.3

269 94 SWAT USER'S MANUAL, VERSION 2000 Variable name Line # Position Format F90 Format SNOEB(6) 10 space decimal (xxxx.xxx) f8.3 SNOEB(7) 10 space decimal (xxxx.xxx) f8.3 SNOEB(8) 10 space decimal (xxxx.xxx) f8.3 SNOEB(9) 10 space decimal (xxxx.xxx) f8.3 SNOEB(10) 10 space decimal (xxxx.xxx) f8.3 PLAPS 11 real free TLAPS 12 real free SNO_SUB 13 real free CH_L(1) 14 real free CH_S(1) 15 real free CH_W(1) 16 real free CH_K(1) 17 real free CH_N(1) 18 real free CO2 19 real free COMMENT LINE 20 space 1-80 character a80 RFINC(1) 21 space 1-8 decimal (xxxx.xxx) f8.3 RFINC(2) 21 space 9-16 decimal (xxxx.xxx) f8.3 RFINC(3) 21 space decimal (xxxx.xxx) f8.3 RFINC(4) 21 space decimal (xxxx.xxx) f8.3 RFINC(5) 21 space decimal (xxxx.xxx) f8.3 RFINC(6) 21 space decimal (xxxx.xxx) f8.3 COMMENT LINE 22 space 1-80 character a80 RFINC(7) 23 space 1-8 decimal (xxxx.xxx) f8.3 RFINC(8) 23 space 9-16 decimal (xxxx.xxx) f8.3 RFINC(9) 23 space decimal (xxxx.xxx) f8.3 RFINC(10) 23 space decimal (xxxx.xxx) f8.3 RFINC(11) 23 space decimal (xxxx.xxx) f8.3 RFINC(12) 23 space decimal (xxxx.xxx) f8.3 COMMENT LINE 24 space 1-80 character a80 TMPINC(1) 25 space 1-8 decimal (xxxx.xxx) f8.3 TMPINC(2) 25 space 9-16 decimal (xxxx.xxx) f8.3 TMPINC(3) 25 space decimal (xxxx.xxx) f8.3 TMPINC(4) 25 space decimal (xxxx.xxx) f8.3 TMPINC(5) 25 space decimal (xxxx.xxx) f8.3 TMPINC(6) 25 space decimal (xxxx.xxx) f8.3

270 CHAPTER 35: SWAT INPUT GENERAL HRU ATTRIBUTES 95 Variable name Line # Position Format F90 Format COMMENT LINE 26 space 1-80 character a80 TMPINC(7) 27 space 1-8 decimal (xxxx.xxx) f8.3 TMPINC(8) 27 space 9-16 decimal (xxxx.xxx) f8.3 TMPINC(9) 27 space decimal (xxxx.xxx) f8.3 TMPINC(10) 27 space decimal (xxxx.xxx) f8.3 TMPINC(11) 27 space decimal (xxxx.xxx) f8.3 TMPINC(12) 27 space decimal (xxxx.xxx) f8.3 COMMENT LINE 28 space 1-80 character a80 RADINC(1) 29 space 1-8 decimal (xxxx.xxx) f8.3 RADINC(2) 29 space 9-16 decimal (xxxx.xxx) f8.3 RADINC(3) 29 space decimal (xxxx.xxx) f8.3 RADINC(4) 29 space decimal (xxxx.xxx) f8.3 RADINC(5) 29 space decimal (xxxx.xxx) f8.3 RADINC(6) 29 space decimal (xxxx.xxx) f8.3 COMMENT LINE 30 space 1-80 character a80 RADINC(7) 31 space 1-8 decimal (xxxx.xxx) f8.3 RADINC(8) 31 space 9-16 decimal (xxxx.xxx) f8.3 RADINC(9) 31 space decimal (xxxx.xxx) f8.3 RADINC(10) 31 space decimal (xxxx.xxx) f8.3 RADINC(11) 31 space decimal (xxxx.xxx) f8.3 RADINC(12) 31 space decimal (xxxx.xxx) f8.3 COMMENT LINE 32 space 1-80 character a80 HUMINC(1) 33 space 1-8 decimal (xxxx.xxx) f8.3 HUMINC(2) 33 space 9-16 decimal (xxxx.xxx) f8.3 HUMINC(3) 33 space decimal (xxxx.xxx) f8.3 HUMINC(4) 33 space decimal (xxxx.xxx) f8.3 HUMINC(5) 33 space decimal (xxxx.xxx) f8.3 HUMINC(6) 33 space decimal (xxxx.xxx) f8.3 COMMENT LINE 34 space 1-80 character a80 HUMINC(7) 35 space 1-8 decimal (xxxx.xxx) f8.3 HUMINC(8) 35 space 9-16 decimal (xxxx.xxx) f8.3 HUMINC(9) 35 space decimal (xxxx.xxx) f8.3 HUMINC(10) 35 space decimal (xxxx.xxx) f8.3 HUMINC(11) 35 space decimal (xxxx.xxx) f8.3 HUMINC(12) 35 space decimal (xxxx.xxx) f8.3

271 96 SWAT USER'S MANUAL, VERSION 2000 Variable name Line # Position Format F90 Format COMMENT LINE 36 space 1-80 character a80 HRUDAT 37-END space 1-13 character a13 MGTDAT 37-END space character a13 SOILDAT 37-END space character a13 CHEMDAT 37-END space character a13 GWDAT 37-END space character a13

272 CHAPTER 35: SWAT INPUT GENERAL HRU ATTRIBUTES HRU GENERAL INPUT FILE (.HRU) Following is a brief description of the variables in the HRU general input file. They are listed in the order they appear within the file. Variable name TITLE Definition The first line of the.hru file is reserved for user comments. The comments may take up to 80 spaces. (optional) HRU_FR Fraction of total watershed area contained in HRU (km 2 /km 2 ). If no value for HRU_FR is entered, the model will set HRU_FR = SLSUBBSN Average slope length (m). If no value for SLSUBBSN is entered, the model will set SLSUBBSN = 50. The GIS interfaces will assign the same value to this variable for all HRUs within a subbasin. However, some users like to vary this value by soil type and land cover. SLOPE Average slope steepness (m/m). If no value for slope is entered, the model will set SLOPE = The GIS interfaces will assign the same value to this variable for all HRUs within a subbasin. However, some users like to vary this value by soil type and land cover. OV_N Manning's "n" value for overland flow. LAT_TTIME Lateral flow travel time (days). Setting LAT_TTIME = 0.0 will allow the model to calculate the travel time based on soil hydraulic properties. This variable should be set to a specific value only by hydrologists familiar with the base flow characteristics of the watershed. LAT_SED Sediment concentration in lateral and groundwater flow (mg/l). Sediment concentration in lateral and groundwater flow is usually very low and does not contribute significantly to total sediment yields unless return flow is very high. SLSOIL Slope length for lateral subsurface flow (m). If no value is entered for SLSOIL, the model sets SLSOIL = SLSUBBSN. The GIS interfaces will assign the same value to this variable for all HRUs within a subbasin. However, some users like to vary this value by soil type and land cover.

273 98 SWAT USER'S MANUAL, VERSION 2000 Variable name CANMX ESCO EPCO RSDIN ERORGN ERORGP FILTERW IURBAN URBLU Definition Maximum canopy storage (mm H 2 O). (Optional) Soil evaporation compensation factor. This factor adjusts the depth distribution for evaporation from the soil to account for the effect of capillary action, crusting and cracks. ESCO must be between 0.0 and 1.0. If no value for ESCO is entered, the model will set ESCO = Plant uptake compensation factor. This factor adjusts the depth distribution for plant uptake of water from the soil to account for the variation in root density with depth. EPCO must be between 0.0 and 1.0. If no value for EPCO is entered, the model will set EPCO = 1.0. Initial residue cover (kg/ha). (Optional) Organic N enrichment ratio. If the value for ERORGN is set to zero, the model will calculate an enrichment ratio for every storm event. The default option is to allow the model to calculate the enrichment ratio. Organic P enrichment ratio. If the value for ERORGP is set to zero, the model will calculate an enrichment ratio for every storm event. The default option is to allow the model to calculate the enrichment ratio. Not currently active. Urban simulation code: 0 no urban sections in HRU 1 urban sections in HRU, simulate using USGS regression equations 2 urban sections in HRU, simulate using build up/wash off algorithm. Urban land type identification number from urban.dat.

274 CHAPTER 35: SWAT INPUT GENERAL HRU ATTRIBUTES 99 Variable name IRR IRRNO FLOWMIN DIVMAX Definition Irrigation code. This variable, along with IRRNO, specifies the source of irrigation water applied in the HRU. Irrigation water may be diverted from anywhere in the watershed or outside the watershed. IRR tells the model what type of water body the irrigation water is being diverted from. The options are: 0 no irrigation 1 divert water from reach 2 divert water from reservoir 3 divert water from shallow aquifer 4 divert water from deep aquifer 5 divert water from unlimited source outside watershed Irrigation source location. The definition of this variable depends on the setting of IRR. If IRR = 1, IRRNO is the number of the reach that water is removed from. If IRR = 2, IRRNO is the number of the reservoir that water is removed from. If IRR = 3 or 4, IRRNO is the number of the subbasin that water is removed from. If IRR = 0 or 5, this variable is not used. Minimum in-stream flow for irrigation diversions (m 3 /s). If irrigation water being applied in the HRU is from a reach (IRR = 1), a threshhold level of streamflow can be specified. Irrigation water will be diverted from the reach only if flow in the reach is at or above FLOWMIN. Maximum daily irrigation diversion from the reach (if value entered for DIVMAX is positive the units are mm, if the value entered for DIVMAX is negative the units are 10 4 m 3 ). If irrigation water being applied in the HRU is from a reach (IRR = 1), a value can be defined which specifies the maximum amount of water that can be removed from the reach and applied to the HRU on any one day. FLOWFR Fraction of available flow (total flow in reach FLOWMIN) that is allowed to be applied to the HRU. If FLOWMIN is left at zero, the fraction of available flow becomes the fraction of total flow in reach that is allowed to be applied to the reach. The value for FLOWFR should be between 0.0 and 1.0. The model will default FLOWFR = 1.0 if no value is entered. Used only if IRR = 1.

275 100 SWAT USER'S MANUAL, VERSION 2000 Variable name DDRAIN Definition Depth to subsurface drain (mm). If drainage tiles are installed in the HRU, the depth to the tiles is needed (optional). TDRAIN Time to drain soil to field capacity (hours). If tile drainage is installed in the HRU, the time required to drain the soil from saturation to field capacity is needed (optional). GDRAIN Drain tile lag time (hours). The amount of time between the transfer of water from the soil to the drain tile and the release of the water from the drain tile to the reach (optional). NPTOT The total number of different types of pesticides applied/modeled in the.mgt and.chm files. This is not the total number of pesticide applications. If the management file applies DDT to the HRU four different times, NPTOT equals 1, not 4. Remember to account for unique pesticides listed in the soil chemical file (.chm) when calculating this number. IPOT Number of HRU (must be located in subbasin) that is ponding water, i.e. the number of the HRU into which surface runoff from the current HRU drains. This variable identifies closed depressional areas or impounded areas used to grow plants in water (e.g. rice paddies). These areas are commonly referred to as potholes. Optional. POT_FR Fraction of HRU area that drains into the pothole. Required if IPOT is set to a number other than zero. POT_TILE Average daily outflow to main channel from tile flow if drainage tiles are installed in the pothole (m 3 /s). Required only for the HRU that is ponding water (IPOT = current HRU number). POT_VOLX Maximum volume of water stored in the pothole (10 4 m 3 H 2 O). Required only for the HRU that is ponding water (IPOT = current HRU number). POT_VOL Initial volume of water stored in the pothole (10 4 m 3 H 2 O). Required only for the HRU that is ponding water (IPOT = current HRU number). POT_NSED Normal sediment concentration in pothole (mg/l). Required only for the HRU that is ponding water (IPOT = current HRU number).

276 CHAPTER 35: SWAT INPUT GENERAL HRU ATTRIBUTES 101 Variable name POT_NO3L Definition Not currently active. Nitrate decay rate in pothole (1/day). Required only for the HRU that is ponding water (IPOT = current HRU number). The HRU general input file is a free format file. The variables may be placed in any position the user wishes on the line. Values for variables classified as integers should not include a decimal while values for variables classified as reals must contain a decimal. A blank space denotes the end of an input value and the beginning of the next value if there is another on the line. The format for the HRU general input file is: Variable name Line # Format F90 Format TITLE 1 character a80 HRU_FR 2 real free SLSUBBSN 3 real free SLOPE 4 real free OV_N 5 real free LAT_TTIME 6 real free LAT_SED 7 real free SLSOIL 8 real free CANMX 9 real free ESCO 10 real free EPCO 11 real free RSDIN 12 real free ERORGN 13 real free ERORGP 14 real free FILTERW 15 real free IURBAN 16 integer free URBLU 17 integer free IRR 18 integer free IRRNO 19 integer free FLOWMIN 20 real free DIVMAX 21 real free FLOWFR 22 real free DDRAIN 23 real free TDRAIN 24 real free GDRAIN 25 real free

277 102 SWAT USER'S MANUAL, VERSION 2000 Variable name Line # Format F90 Format NPTOT 26 integer free IPOT 27 integer free POT_FR 28 real free POT_TILE 29 real free POT_VOLX 30 real free POT_VOL 31 real free POT_NSED 32 real free POT_NO3L 33 real free

278 CHAPTER 36 SWAT INPUT DATA: SOIL The soils data used by SWAT can be divided into two groups, physical characteristics and chemical characteristics. The physical properties of the soil govern the movement of water and air through the profile and have a major impact on the cycling of water within the HRU. Inputs for chemical characteristics are used to set initial levels of the different chemicals in the soil. While the physical properties are required, information on chemical properties is optional. Two files, the soil input file (.sol) and the soil chemical input file (.chm), contain the soil properties used by SWAT. The soil input file defines the physical properties and initializes chemical quantities for all layers in the soil. The soil chemical input file initializes additional chemical quantities for the first soil layer. 97

279 98 SWAT USER'S MANUAL, VERSION SOIL INPUT FILE (.SOL) Following is a brief description of the variables in the soil input file. They are listed in the order they appear within the file. The soil input file will hold data for up to 10 layers. Variable name TITLE/TEXT SNAM HYDGRP SOL_ZMX ANION_EXCL Definition The first line of the.sol file is reserved for user comments. The comments may take up to 80 spaces. (optional) Soil name. If given, the soil name is used in data summarization. Soil hydrologic group (A, B, C, or D (required by the SWAT ArcView interface) The criteria for placement in hydrologic groups are: A B C D Minimum saturated hydraulic conductivity in the uppermost 0.5 m is > 110 mm/hr and internal free water occurrence is below 1.5 m. Minimum saturated hydraulic conductivity in the uppermost 0.5 m is between 11 and 110 mm/hr and internal free water occurrence is below 1.0 m. Minimum saturated hydraulic conductivity in the uppermost 0.5 m is between 1.1 and 11 mm/hr and internal free water occurrence is below 0.25 m. Minimum saturated hydraulic conductivity in the uppermost 0.5 m is below 1.1 mm/hr and internal free water occurrence may be at any depth. Maximum rooting depth of soil profile (mm). If no depth is specified, the model assumes the roots can develop throughout the entire depth of the soil profile. Fraction of porosity (void space) from which anions are excluded. This parameter is currently used only in nitrate transport. If no value for ANION_EXCL is entered, the model will set ANION_EXCL = 0.50

280 CHAPTER 36: SWAT INPUT SOIL 99 Variable name SOL_CRK TEXTURE SOL_Z(layer #) SOL_BD(layer #) SOL_AWC(layer #) SOL_K(layer #) SOL_CBN(layer #) CLAY(layer #) SILT(layer #) SAND(layer #) Definition Crack volume potential of soil (optional) Texture of soil layer (optional). This data is not used by the model. Depth from soil surface to bottom of layer (mm). Moist bulk density (Mg/m 3 or g/cm 3 ). The soil bulk density expresses the ratio of the mass of solid particles to the total volume of the soil, ρ b = M S /V T. In moist bulk density determinations, the mass of the soil is the oven dry weight and the total volume of the soil is determined when the soil is at or near field capacity. Bulk density values should fall between 1.1 and 1.9 Mg/m 3. Available water capacity of the soil layer (mm H 2 O/mm soil). This is the volume of water that should be available to plants if the soil, inclusive of rock fragments, was at field capacity. Available water capacity is estimated by determining the amount of water released between in situ field capacity (the soil water content at soil matric potential of MPa) and the permanent wilting point (the soil water content at soil matric potential of -1.5 MPa). Saturated hydraulic conductivity (mm/hr). The saturated hydraulic conductivity, K sat, relates soil water flow rate (flux density) to the hydraulic gradient and is a measure of the ease of water movement through in the soil. K sat is the reciprocal of the resistance of the soil matrix to water flow. Organic carbon content (% soil weight). When defining by soil weight, the soil is the portion of the sample that passes through a 2 mm sieve. Clay content (% soil weight). The percent of soil particles which are < mm in equivalent diameter. Silt content (% soil weight). The percentage of soil particles which have an equivalent diameter between 0.05 and mm. Sand content (% soil weight). The percentage of soil particles which have a diameter between 2.0 and 0.05 mm.

281 100 SWAT USER'S MANUAL, VERSION 2000 Variable name ROCK(layer #) Definition Rock fragment content (% total weight). The percent of the sample which has a particle diameter > 2 mm, i.e. the percent of the sample which does not pass through a 2 mm sieve. SOL_ALB(layer #) Moist soil albedo. The ratio of the amount of solar radiation reflected by a body to the amount incident upon it, expressed as a fraction. The value for albedo should be reported when the soil is at or near field capacity. USLE_K(layer #) USLE equation soil erodibility (K) factor (units: (metric ton m 2 hr)/(m 3 -metric ton cm)). The units given are numerically equivalent to the traditional English units (0.01 (ton acre hr)/(acre ft-ton inch)). The values for the metric units will be exactly the same as those for the English units. SOL_EC(layer #) Not currently active Electrical conductivity (ds/m). The format of the soil input file is: Variable name Line # Position Format F90 Format TITLE 1 space 1-80 character a80 SNAM 2 space character a16 HYDGRP 3 space 25 character a1 SOL_ZMX 4 space decimal(xxxxxxxxx.xx) f12.2 ANION_EXCL 5 space decimal(x.xxx) f5.3 SOL_CRK 6 space decimal(x.xxx) f5.3 COMMENT LINE 7 space character a80 SOL_Z(1) 8 space decimal(xxxxxxxxx.xx) f12.2 SOL_Z(2) 8 space decimal(xxxxxxxxx.xx) f12.2 SOL_Z(3) 8 space decimal(xxxxxxxxx.xx) f12.2 SOL_Z(4) 8 space decimal(xxxxxxxxx.xx) f12.2 SOL_Z(5) 8 space decimal(xxxxxxxxx.xx) f12.2 SOL_Z(6) 8 space decimal(xxxxxxxxx.xx) f12.2 SOL_Z(7) 8 space decimal(xxxxxxxxx.xx) f12.2 SOL_Z(8) 8 space decimal(xxxxxxxxx.xx) f12.2 SOL_Z(9) 8 space decimal(xxxxxxxxx.xx) f12.2 SOL_Z(10) 8 space decimal(xxxxxxxxx.xx) f12.2 SOL_BD(1) 9 space decimal(xxxxxxxxx.xx) f12.2

282 CHAPTER 36: SWAT INPUT SOIL 101 Variable name Line # Position Format F90 Format SOL_BD(2) 9 space decimal(xxxxxxxxx.xx) f12.2 SOL_BD(3) 9 space decimal(xxxxxxxxx.xx) f12.2 SOL_BD(4) 9 space decimal(xxxxxxxxx.xx) f12.2 SOL_BD(5) 9 space decimal(xxxxxxxxx.xx) f12.2 SOL_BD(6) 9 space decimal(xxxxxxxxx.xx) f12.2 SOL_BD(7) 9 space decimal(xxxxxxxxx.xx) f12.2 SOL_BD(8) 9 space decimal(xxxxxxxxx.xx) f12.2 SOL_BD(9) 9 space decimal(xxxxxxxxx.xx) f12.2 SOL_BD(10) 9 space decimal(xxxxxxxxx.xx) f12.2 SOL_AWC(1) 10 space decimal(xxxxxxxxx.xx) f12.2 SOL_AWC(2) 10 space decimal(xxxxxxxxx.xx) f12.2 SOL_AWC(3) 10 space decimal(xxxxxxxxx.xx) f12.2 SOL_AWC(4) 10 space decimal(xxxxxxxxx.xx) f12.2 SOL_AWC(5) 10 space decimal(xxxxxxxxx.xx) f12.2 SOL_AWC(6) 10 space decimal(xxxxxxxxx.xx) f12.2 SOL_AWC(7) 10 space decimal(xxxxxxxxx.xx) f12.2 SOL_AWC(8) 10 space decimal(xxxxxxxxx.xx) f12.2 SOL_AWC(9) 10 space decimal(xxxxxxxxx.xx) f12.2 SOL_AWC(10) 10 space decimal(xxxxxxxxx.xx) f12.2 SOL_K(1) 11 space decimal(xxxxxxxxx.xx) f12.2 SOL_K(2) 11 space decimal(xxxxxxxxx.xx) f12.2 SOL_K(3) 11 space decimal(xxxxxxxxx.xx) f12.2 SOL_K(4) 11 space decimal(xxxxxxxxx.xx) f12.2 SOL_K(5) 11 space decimal(xxxxxxxxx.xx) f12.2 SOL_K(6) 11 space decimal(xxxxxxxxx.xx) f12.2 SOL_K(7) 11 space decimal(xxxxxxxxx.xx) f12.2 SOL_K(8) 11 space decimal(xxxxxxxxx.xx) f12.2 SOL_K(9) 11 space decimal(xxxxxxxxx.xx) f12.2 SOL_K(10) 11 space decimal(xxxxxxxxx.xx) f12.2 SOL_CBN(1) 12 space decimal(xxxxxxxxx.xx) f12.2 SOL_CBN(2) 12 space decimal(xxxxxxxxx.xx) f12.2 SOL_CBN(3) 12 space decimal(xxxxxxxxx.xx) f12.2 SOL_CBN(4) 12 space decimal(xxxxxxxxx.xx) f12.2 SOL_CBN(5) 12 space decimal(xxxxxxxxx.xx) f12.2 SOL_CBN(6) 12 space decimal(xxxxxxxxx.xx) f12.2

283 102 SWAT USER'S MANUAL, VERSION 2000 Variable name Line # Position Format F90 Format SOL_CBN(7) 12 space decimal(xxxxxxxxx.xx) f12.2 SOL_CBN(8) 12 space decimal(xxxxxxxxx.xx) f12.2 SOL_CBN(9) 12 space decimal(xxxxxxxxx.xx) f12.2 SOL_CBN(10) 12 space decimal(xxxxxxxxx.xx) f12.2 CLAY(1) 13 space decimal(xxxxxxxxx.xx) f12.2 CLAY(2) 13 space decimal(xxxxxxxxx.xx) f12.2 CLAY(3) 13 space decimal(xxxxxxxxx.xx) f12.2 CLAY(4) 13 space decimal(xxxxxxxxx.xx) f12.2 CLAY(5) 13 space decimal(xxxxxxxxx.xx) f12.2 CLAY(6) 13 space decimal(xxxxxxxxx.xx) f12.2 CLAY(7) 13 space decimal(xxxxxxxxx.xx) f12.2 CLAY(8) 13 space decimal(xxxxxxxxx.xx) f12.2 CLAY(9) 13 space decimal(xxxxxxxxx.xx) f12.2 CLAY(10) 13 space decimal(xxxxxxxxx.xx) f12.2 SILT(1) 14 space decimal(xxxxxxxxx.xx) f12.2 SILT(2) 14 space decimal(xxxxxxxxx.xx) f12.2 SILT(3) 14 space decimal(xxxxxxxxx.xx) f12.2 SILT(4) 14 space decimal(xxxxxxxxx.xx) f12.2 SILT(5) 14 space decimal(xxxxxxxxx.xx) f12.2 SILT(6) 14 space decimal(xxxxxxxxx.xx) f12.2 SILT(7) 14 space decimal(xxxxxxxxx.xx) f12.2 SILT(8) 14 space decimal(xxxxxxxxx.xx) f12.2 SILT(9) 14 space decimal(xxxxxxxxx.xx) f12.2 SILT(10) 14 space decimal(xxxxxxxxx.xx) f12.2 SAND(1) 15 space decimal(xxxxxxxxx.xx) f12.2 SAND(2) 15 space decimal(xxxxxxxxx.xx) f12.2 SAND(3) 15 space decimal(xxxxxxxxx.xx) f12.2 SAND(4) 15 space decimal(xxxxxxxxx.xx) f12.2 SAND(5) 15 space decimal(xxxxxxxxx.xx) f12.2 SAND(6) 15 space decimal(xxxxxxxxx.xx) f12.2 SAND(7) 15 space decimal(xxxxxxxxx.xx) f12.2 SAND(8) 15 space decimal(xxxxxxxxx.xx) f12.2 SAND(9) 15 space decimal(xxxxxxxxx.xx) f12.2 SAND(10) 15 space decimal(xxxxxxxxx.xx) f12.2 ROCK(1) 16 space decimal(xxxxxxxxx.xx) f12.2

284 CHAPTER 36: SWAT INPUT SOIL 103 Variable name Line # Position Format F90 Format ROCK(2) 16 space decimal(xxxxxxxxx.xx) f12.2 ROCK(3) 16 space decimal(xxxxxxxxx.xx) f12.2 ROCK(4) 16 space decimal(xxxxxxxxx.xx) f12.2 ROCK(5) 16 space decimal(xxxxxxxxx.xx) f12.2 ROCK(6) 16 space decimal(xxxxxxxxx.xx) f12.2 ROCK(7) 16 space decimal(xxxxxxxxx.xx) f12.2 ROCK(8) 16 space decimal(xxxxxxxxx.xx) f12.2 ROCK(9) 16 space decimal(xxxxxxxxx.xx) f12.2 ROCK(10) 16 space decimal(xxxxxxxxx.xx) f12.2 SOL_ALB(1) 17 space decimal(xxxxxxxxx.xx) f12.2 SOL_ALB(2) 17 space decimal(xxxxxxxxx.xx) f12.2 SOL_ALB(3) 17 space decimal(xxxxxxxxx.xx) f12.2 SOL_ALB(4) 17 space decimal(xxxxxxxxx.xx) f12.2 SOL_ALB(5) 17 space decimal(xxxxxxxxx.xx) f12.2 SOL_ALB(6) 17 space decimal(xxxxxxxxx.xx) f12.2 SOL_ALB(7) 17 space decimal(xxxxxxxxx.xx) f12.2 SOL_ALB(8) 17 space decimal(xxxxxxxxx.xx) f12.2 SOL_ALB(9) 17 space decimal(xxxxxxxxx.xx) f12.2 SOL_ALB(10) 17 space decimal(xxxxxxxxx.xx) f12.2 USLE_K(1) 18 space decimal(xxxxxxxxx.xx) f12.2 USLE_K(2) 18 space decimal(xxxxxxxxx.xx) f12.2 USLE_K(3) 18 space decimal(xxxxxxxxx.xx) f12.2 USLE_K(4) 18 space decimal(xxxxxxxxx.xx) f12.2 USLE_K(5) 18 space decimal(xxxxxxxxx.xx) f12.2 USLE_K(6) 18 space decimal(xxxxxxxxx.xx) f12.2 USLE_K(7) 18 space decimal(xxxxxxxxx.xx) f12.2 USLE_K(8) 18 space decimal(xxxxxxxxx.xx) f12.2 USLE_K(9) 18 space decimal(xxxxxxxxx.xx) f12.2 USLE_K(10) 18 space decimal(xxxxxxxxx.xx) f12.2 SOL_EC(1) 19 space decimal(xxxxxxxxx.xx) f12.2 SOL_EC(2) 19 space decimal(xxxxxxxxx.xx) f12.2 SOL_EC(3) 19 space decimal(xxxxxxxxx.xx) f12.2 SOL_EC(4) 19 space decimal(xxxxxxxxx.xx) f12.2 SOL_EC(5) 19 space decimal(xxxxxxxxx.xx) f12.2 SOL_EC(6) 19 space decimal(xxxxxxxxx.xx) f12.2

285 104 SWAT USER'S MANUAL, VERSION 2000 Variable name Line # Position Format F90 Format SOL_EC(7) 19 space decimal(xxxxxxxxx.xx) f12.2 SOL_EC(8) 19 space decimal(xxxxxxxxx.xx) f12.2 SOL_EC(9) 19 space decimal(xxxxxxxxx.xx) f12.2 SOL_EC(10) 19 space decimal(xxxxxxxxx.xx) f12.2

286 CHAPTER 36: SWAT INPUT SOIL SOIL CHEMICAL INPUT FILE (.CHM) Following is a brief description of the variables in the soil chemical input file. They are listed in the order they appear within the file. Variable name TITLE NUTRIENT TITLE SOIL LAYER SOL_NO3(layer #) SOL_ORGN(layer #) SOL_LABP(layer #) SOL_ORGP(layer #) PESTICIDE TITLE PESTNUM PLTPST SOLPST PSTENR Definition The first line of the.chm file is reserved for user comments. The comments may take up to 80 spaces. Optional. The second line of the.chm file is reserved for the nutrient data title. This is not used by the model. Optional. Number of soil layer. This line in the.chm file is not used by the model and may be left blank. Initial NO 3 concentration (mg/kg) in the soil layer Optional. Initial organic N concentration in the soil layer (mg/kg). Optional. Initial labile (soluble) P concentration in soil layer (mg/kg). Optional. Initial organic P concentration in soil layer (mg/kg). Optional. Lines 8-11 are reserved for pesticide data titles. The data on these lines are not used by the model. Number of pesticide from pesticide database (pest.dat) Required if pesticide amounts are given. Initial pesticide amount on foliage (kg/ha). Optional. Initial pesticide amount in soil (mg/kg). The pesticide is assumed to be found at this concentration in all soil layers. Optional. Enrichment ratio for pesticide in the soil. This is the ratio of the pesticide concentration on the sediment transported in surface runoff to the pesticide concentration in the soil. Optional.

287 106 SWAT USER'S MANUAL, VERSION 2000 The format of the soil chemical input file is: Variable name Line # Position Format F90 Format TITLE 1 space 1-80 character a80 NUTRIENT TITLE 2 space 1-80 character a80 SOIL LAYERS 3 space 1-80 character a80 SOL_NO3(1) 4 space decimal(xxxxxxxxx.xx) f12.2 SOL_NO3(2) 4 space decimal(xxxxxxxxx.xx) f12.2 SOL_NO3(3) 4 space decimal(xxxxxxxxx.xx) f12.2 SOL_NO3(4) 4 space decimal(xxxxxxxxx.xx) f12.2 SOL_NO3(5) 4 space decimal(xxxxxxxxx.xx) f12.2 SOL_NO3(6) 4 space decimal(xxxxxxxxx.xx) f12.2 SOL_NO3(7) 4 space decimal(xxxxxxxxx.xx) f12.2 SOL_NO3(8) 4 space decimal(xxxxxxxxx.xx) f12.2 SOL_NO3(9) 4 space decimal(xxxxxxxxx.xx) f12.2 SOL_NO3(10) 4 space decimal(xxxxxxxxx.xx) f12.2 SOL_ORGN(1) 5 space decimal(xxxxxxxxx.xx) f12.2 SOL_ORGN(2) 5 space decimal(xxxxxxxxx.xx) f12.2 SOL_ORGN(3) 5 space decimal(xxxxxxxxx.xx) f12.2 SOL_ORGN(4) 5 space decimal(xxxxxxxxx.xx) f12.2 SOL_ORGN(5) 5 space decimal(xxxxxxxxx.xx) f12.2 SOL_ORGN(6) 5 space decimal(xxxxxxxxx.xx) f12.2 SOL_ORGN(7) 5 space decimal(xxxxxxxxx.xx) f12.2 SOL_ORGN(8) 5 space decimal(xxxxxxxxx.xx) f12.2 SOL_ORGN(9) 5 space decimal(xxxxxxxxx.xx) f12.2 SOL_ORGN(10) 5 space decimal(xxxxxxxxx.xx) f12.2 SOL_LABP(1) 6 space decimal(xxxxxxxxx.xx) f12.2 SOL_LABP(2) 6 space decimal(xxxxxxxxx.xx) f12.2 SOL_LABP(3) 6 space decimal(xxxxxxxxx.xx) f12.2 SOL_LABP(4) 6 space decimal(xxxxxxxxx.xx) f12.2 SOL_LABP(5) 6 space decimal(xxxxxxxxx.xx) f12.2 SOL_LABP(6) 6 space decimal(xxxxxxxxx.xx) f12.2 SOL_LABP(7) 6 space decimal(xxxxxxxxx.xx) f12.2 SOL_LABP(8) 6 space decimal(xxxxxxxxx.xx) f12.2 SOL_LABP(9) 6 space decimal(xxxxxxxxx.xx) f12.2 SOL_LABP(10) 6 space decimal(xxxxxxxxx.xx) f12.2

288 CHAPTER 36: SWAT INPUT SOIL 107 Variable name Line # Position Format F90 Format SOL_ORGP(1) 7 space decimal(xxxxxxxxx.xx) f12.2 SOL_ORGP(2) 7 space decimal(xxxxxxxxx.xx) f12.2 SOL_ORGP(3) 7 space decimal(xxxxxxxxx.xx) f12.2 SOL_ORGP(4) 7 space decimal(xxxxxxxxx.xx) f12.2 SOL_ORGP(5) 7 space decimal(xxxxxxxxx.xx) f12.2 SOL_ORGP(6) 7 space decimal(xxxxxxxxx.xx) f12.2 SOL_ORGP(7) 7 space decimal(xxxxxxxxx.xx) f12.2 SOL_ORGP(8) 7 space decimal(xxxxxxxxx.xx) f12.2 SOL_ORGP(9) 7 space decimal(xxxxxxxxx.xx) f12.2 SOL_ORGP(10) 7 space decimal(xxxxxxxxx.xx) f12.2 PESTICIDE TITLE 8-11 space 1-80 character a80 PSTNUM 12-END integer free PLTPST 12-END real free SOLPST 12-END real free PSTENR 12-END real free

289 108 SWAT USER'S MANUAL, VERSION 2000

290 CHAPTER 37 SWAT INPUT DATA: LAND/WATER MANAGEMENT A primary goal of environmental modeling is to assess the impact of anthropogenic activities on a given system. Central to this assessment is the itemization of the land and water management practices taking place within the system. SWAT utilizes two files to summarize these practices within the HRUs, the HRU management file (.mgt) and the subbasin water use file (.wus). 105

291 106 SWAT USER'S MANUAL, VERSION MANAGEMENT INPUT FILE (.MGT) This file contains input data for planting, harvest, irrigation applications, nutrient applications, pesticide applications, and tillage operations. Operations may be scheduled by month and day or by heat units. If both month/day and heat units are given for a scheduled operation, the model will implement the operation on whichever occurs first. For example, assume a fertilizer operation is scheduled for April 1 or a heat unit index of 0.3. In year one, the heat unit index of the crop reaches 0.3 on April 14 while in year two the heat unit index of the crop reaches 0.3 on March 25. SWAT will apply the fertilizer on April 1 the first year and March 25 the second year. SWAT calculates two different heat unit indices throughout a year. The first is a base zero, or annual, heat unit index for the HRU. The total heat units that can be accumulated annually is equal to the sum of degrees C above 0 C in the daily mean temperature for every day of the year. Throughout each year of simulation, an index is calculated which tells the fraction of the total heat units accumulated. The base zero, or annual, heat unit index is reset to zero on January 1 st. This heat unit index is used to schedule operations when no plant is growing. The second heat unit index calculated by SWAT is the plant heat unit index. The base temperature for the plant heat unit index is the minimum temperature required by the plant for growth. The total number of heat units required to bring the plant to maturity, referred to as the potential heat units, is equal to the sum of degrees C above the plant base temperature in the daily mean temperature for every day of the plant growing season. The plant heat unit index is calculated only when something is growing in the HRU GENERAL MANAGEMENT VARIABLES The first two lines of the management input file contain general management variables. The remaining lines in the file list the sequence of management operations which occur throughout a year of simulation.

292 The general management variables are: CHAPTER 37: SWAT INPUT LAND/WATER MANAGEMENT 107 Variable name TITLE IGRO NROT NMGT NCRP ALAI BIO_MS PHU Definition The first line of the.mgt file is reserved for user comments. The comments may take up to 80 spaces. (optional) Land cover status code. This code informs the model whether or not a land cover is growing at the beginning of the simulation. 0 no land cover growing 1 land cover growing Number of years of rotation. This code identifies the number of years of management practices given in the.mgt file. (A blank line should be inserted between each different year of management.) If the management doesn't change from year to year, the management operations for only one year are needed. Two land covers/crops may not be grown simultaneously, but they may be grown in the same year. For two or more crops grown in the same year, NROT is equal to 1 for 1 year of management practices listed. NROT has nothing to do with the number of different crops grown. Management code. Used by SWAT/GRASS (GIS) interface. The model doesn't use this variable. Land cover identification number. If a land cover is growing at the beginning of the simulation (IGRO = 1), this variable defines the type of land cover. The identification number is the numeric code for the land cover given in the crop.dat file. Initial leaf area index. If a land cover is growing at the beginning of the simulation (IGRO = 1), the leaf area index of the land cover must be defined. Initial dry weight biomass (kg/ha). If a land cover is growing at the beginning of the simulation (IGRO = 1), the initial biomass must be defined. Total number of heat units or growing degree days needed to bring plant to maturity. This value is needed only if a land cover is growing at the beginning of the simulation (IGRO = 1).

293 108 SWAT USER'S MANUAL, VERSION 2000 Variable name BIO_MIN BIOMIX CN2 USLE_P Definition Minimum plant biomass for grazing (kg/ha). Grazing will not be simulated unless the biomass is at or above BIO_MIN. Biological mixing efficiency. Mixing of the soil due to activity of earthworms and other soil biota. Mixing is performed at the end of every calendar year. If no value for BIOMIX is entered, the model will set BIOMIX = 0.20 Initial SCS runoff curve number for moisture condition II. The curve number may be updated in plant, tillage, and harvest/ kill operations. If CNOP is never defined for these operations, the value set for CN2 will be used throughout the simulation. If CNOP is defined for an operation, the value for CN2 is used until the time of the operation containing the first CNOP value. From that point on, the model only uses operation CNOP values to define the curve number for moisture condition II. Values for CN2 and CNOP should be entered for pervious conditions. In HRUs with urban areas, the model will adjust the curve number to reflect the impact of the impervious areas. USLE equation support practice (P) factor. The ratio of soil loss with a support practice like contouring, stripcropping, or terracing to that with straight-row farming up and down the slope. The format of the first two lines in the management file are: Variable name Line # Position Format F90 Format TITLE 1 space 1-80 character a80 IGRO 2 space 1 1-digit integer i1 NROT 2 space digit integer i3 NMGT 2 space digit integer i4 NCRP 2 space digit integer i4 ALAI 2 space decimal (xxxxx.xx) f8.2 BIO_MS 2 space decimal (xxxxx.xx) f8.2 PHU 2 space decimal (xxxxx.xx) f8.2 BIO_MIN 2 space decimal (xxxxx.xx) f8.2 BIOMIX 2 space decimal (xxxxx.xx) f8.2 CN2 2 space decimal (xxxxx.xx) f8.2 USLE_P 2 space decimal (xxxxx.xx) f8.2

294 CHAPTER 37: SWAT INPUT LAND/WATER MANAGEMENT SCHEDULED MANAGEMENT OPERATIONS SWAT will simulate 14 different types of management operations. The first four variables on all management lines are identical while the remaining ten are operation specific. The variables for the different operations will be defined in separate sections. The type of operation simulated is identified by the code given for the variable MGT_OP. The different codes for MGT_OP are: 1 planting/beginning of growing season: this operation initializes the growth of a specific land cover/plant type in the HRU 2 irrigation operation: this operation applies water to the HRU 3 fertilizer application: this operation adds nutrients to the soil in the HRU 4 pesticide application: this operation applies a pesticide to the plant and/or soil in the HRU 5 harvest and kill operation: this operation harvests the portion of the plant designated as yield, removes the yield from the HRU and converts the remaining plant biomass to residue on the soil surface. It also sets IGRO = 0 which allows the next crop to be planted. 6 tillage operation: this operation mixes the upper soil layers and redistributes the nutrients/chemicals/etc. within those layers 7 harvest only operation: this operation harvests the portion of the plant designated as yield and removes the yield from the HRU, but allows the plant to continue growing. (this operation is used for hay cuttings) 8 kill/end of growing season: this operation stops all plant growth and converts all plant biomass to residue. It also sets IGRO = 0 which allows the next crop to be planted. 9 grazing operation: this operation removes plant biomass at a specified rate and allows simultaneous application of manure. 10 auto irrigation initialization: this operation initializes auto irrigation within the HRU. Auto irrigation applies water whenever the plant experiences a user-specified level of water stress. 11 auto fertilization initialization: this operation initializes auto fertilization within the HRU. Auto fertilization applies nutrients whenever the plant experiences a user-specified level of nitrogen stress. 12 street sweeping operation: this operation removes sediment and nutrient build-up on impervious areas in the HRU. This operation can only be used when the urban build up/wash off routines are activated for the HRU. 13 release/impound: this operation releases/impounds water in HRUs growing rice or other plants 0 end of year rotation flag: this operation identifies the end of the operation scheduling for the year. The operations must be listed in chronological order starting in January.

295 110 SWAT USER'S MANUAL, VERSION PLANTING/BEGINNING OF GROWING SEASON The variables which may be entered on the planting line are listed and described below Variable name Definition MONTH Month operation takes place. DAY Day operation takes place. HUSC Fraction of total base zero heat units at which operation takes place. (If MONTH and DAY are not provided, HUSC must be set to a value) MGT_OP Management operation number. MGT_OP = 1 for planting/beginning of growing season HEAT UNITS Total heat units for cover/plant to reach maturity. NCR Land cover/plant identification number from crop.dat. HITAR Harvest index target ((kg/ha)/(kg/ha)) (optional). This variable along with BIO_TARG allow the user to specify the harvest index and biomass produced by the plant every year. The model will then simulate plant growth to meet these specified values. If you are studying the effect of management practices on yields or you want the biomass to vary in response to different weather conditions, you would not want to use HITAR or BIO_TARG. BIO_TARG Biomass (dry weight) target (metric tons/ha) (optional). This variable along with HITAR allow the user to specify the harvest index and biomass produced by the plant every year. The model will then simulate plant growth to meet these specified values. If you are studying the effect of management practices on yields or you want the biomass to vary in response to different weather conditions, you would not want to use HITAR or BIO_TARG. ALAINIT Initial leaf area index (optional). This variable would be used only for covers/plants which are transplanted rather than established from seeds.

296 CHAPTER 37: SWAT INPUT LAND/WATER MANAGEMENT 111 Variable name BIO_INIT CNOP Definition Initial dry weight biomass (kg/ha) (optional). This variable would be used only for covers/plants that are transplanted rather than established from seeds. SCS runoff curve number for moisture condition II (optional). The initial curve number for the HRU is input in the second line of the.mgt file. If you wish to use one moisture condition II curve number for the entire year, place that value in the second line of the.mgt file and do not enter values for CNOP in the operation lines. If you want the moisture condition II value to vary through the year, management operations 1, 5, and 6 allow new runoff curve numbers to be entered. The curve number value for CNOP should be for pervious ground. In HRUs with urban areas, the model will adjust the curve number to reflect the impact of the impervious areas. The format of the planting operation line is Variable name Position Format F90 Format MONTH space digit integer i4 DAY space digit integer i4 HUSC space 9-16 decimal (xxxx.xxx) f8.3 MGT_OP space digit integer i4 HEAT UNITS space decimal (xxxx.xxx) f8.3 NCR space digit integer i4 HITAR space decimal (xxxx.xxx) f8.3 BIO_TARG space decimal (xxxx.xxx) f8.3 ALAINIT space decimal (xxxx.xxx) f8.3 BIO_INIT space decimal (xx.xxx) f6.3 CNOP space decimal (xx.xxx) f6.3

297 112 SWAT USER'S MANUAL, VERSION IRRIGATION OPERATION The variables which may be entered on the irrigation line are listed and described below Variable name Definition MONTH Month operation takes place. DAY Day operation takes place. HUSC Fraction of total heat units for the year at which operation takes place. (If MONTH and DAY are not provided, HUSC must be set to a value) MGT_OP Management operation number. MGT_OP = 2 for irrigation operation IRR_AMT Depth of irrigation water applied on HRU (mm). IRR_SALT Concentration of salt in irrigation water (mg/l) (optional). not currently active The format of the irrigation operation line is Variable name Position Format F90 Format MONTH space digit integer i4 DAY space digit integer i4 HUSC space 9-16 decimal (xxxx.xxx) f8.3 MGT_OP space digit integer i4 IRR_AMT space decimal (xxxx.xxx) f8.3 IRR_SALT space decimal (xxxx.xxx) f FERTILIZER APPLICATION The variables which may be entered on the fertilization line are listed and described below Variable name Definition MONTH Month operation takes place. DAY Day operation takes place. HUSC Fraction of total heat units for the year at which operation takes place. (If MONTH and DAY are not provided, HUSC must be set to a value)

298 Variable name MGT_OP FRT_LY1 FERT_ID FRT_KG FRMINN FRMINP FRORGN FRORGP CHAPTER 37: SWAT INPUT LAND/WATER MANAGEMENT 113 Definition Management operation number. MGT_OP = 3 for fertilizer application Fraction of fertilizer applied to top 10mm of soil. The remaining fraction is applied to the 1 st soil layer below 10 mm. If FRT_LY1 is set to 0, the model applies 20% of the fertilizer to the top 10mm and the remainder to the 1 st soil layer below 10mm. Fertilizer identification number (optional). This corresponds to the line number of the fertilizer in fert.dat. If this variable is left blank or set to zero, values must be entered for FRMINN, FRMINP, FRORGN, FRORGP and FRNH3N. Amount of fertilizer applied to HRU (kg/ha). Fraction of fertilizer that is mineral N (NO 3 + NH 4 ) (kg min-n/kg fert). The model will process this variable only if FERT_ID is blank or set to zero. Fraction of fertilizer that is mineral P (kg min-p/kg fert). The model will process this variable only if FERT_ID is blank or set to zero. Fraction of fertilizer that is organic N (kg org-n/kg fert). The model will process this variable only if FERT_ID is blank or set to zero. Fraction of fertilizer that is organic P (kg org-p/kg fert). The model will process this variable only if FERT_ID is blank or set to zero. FRNH3N Fraction of mineral N in fertilizer that is NH 3 -N (kg NH 3 - N/kg min-n). The model will process this variable only if FERT_ID is blank or set to zero. The format of the fertilizer application line is Variable name Position Format F90 Format MONTH space digit integer i4 DAY space digit integer i4 HUSC space 9-16 decimal (xxxx.xxx) f8.3 MGT_OP space digit integer i4 FRY_LY1 space decimal (xxxx.xxx) f8.3 FERT_ID space digit integer i4

299 114 SWAT USER'S MANUAL, VERSION 2000 Variable name Position Format F90 Format FRT_KG space decimal (xxxx.xxx) f8.3 FRMINN space decimal (xxxx.xxx) f8.3 FRMINP space decimal (xxxx.xxx) f8.3 FRORGN space decimal (xx.xxx) f6.3 FRORGP space decimal (xx.xxx) f6.3 FRNH3N space decimal (xx.xxx) f PESTICIDE APPLICATION The variables which may be entered on the pesticide application line are listed and described below Variable name Definition MONTH Month operation takes place. DAY Day operation takes place. HUSC Fraction of total heat units for the year at which operation takes place. (If MONTH and DAY are not provided, HUSC must be set to a value) MGT_OP Management operation number. MGT_OP = 4 for pesticide application PEST_ID Pesticide identification code from pesticide database (pest.dat). PST_KG Amount of pesticide applied to HRU (kg/ha). The format of the pesticide application line is Variable name Position Format F90 Format MONTH space digit integer i4 DAY space digit integer i4 HUSC space 9-16 decimal (xxxx.xxx) f8.3 MGT_OP space digit integer i4 PEST_ID space digit integer i4 PST_KG space decimal (xx.xxx) f6.3

300 CHAPTER 37: SWAT INPUT LAND/WATER MANAGEMENT HARVEST AND KILL OPERATION The variables which may be entered on the harvest and kill line are listed and described below Variable name Definition MONTH Month operation takes place. DAY Day operation takes place. HUSC Fraction of total heat units for the year at which operation takes place. (If MONTH and DAY are not provided, HUSC must be set to a value) MGT_OP Management operation number. MGT_OP = 5 for harvest and kill operation CNOP SCS runoff curve number for moisture condition II (optional). The initial curve number for the HRU is input in the second line of the.mgt file. If you wish to use one moisture condition II curve number for the entire year, place that value in the second line of the.mgt file and do not enter values for CNOP in the operation lines. If you want the moisture condition II value to vary through the year, management operations 1, 5, and 6 allow new runoff curve numbers to be entered. The curve number value for CNOP should be for pervious ground. In HRUs with urban areas, the model will adjust the curve number to reflect the impact of the impervious areas. The format of the harvest and kill line is Variable name Position Format F90 Format MONTH space digit integer i4 DAY space digit integer i4 HUSC space 9-16 decimal (xxxx.xxx) f8.3 MGT_OP space digit integer i4 CNOP space decimal (xx.xxx) f6.3

301 116 SWAT USER'S MANUAL, VERSION TILLAGE OPERATION The variables which may be entered on the tillage line are listed and described below Variable name Definition MONTH Month operation takes place. DAY Day operation takes place. HUSC Fraction of total heat units for the year at which operation takes place. (If MONTH and DAY are not provided, HUSC must be set to a value) MGT_OP Management operation number. MGT_OP = 6 for tillage operation TILLAGE_ID Tillage implement code from till.dat CNOP SCS runoff curve number for moisture condition II (optional). The initial curve number for the HRU is input in the second line of the.mgt file. If you wish to use one moisture condition II curve number for the entire year, place that value in the second line of the.mgt file and do not enter values for CNOP in the operation lines. If you want the moisture condition II value to vary through the year, management operations 1, 5, and 6 allow new runoff curve numbers to be entered. The curve number value for CNOP should be for pervious ground. In HRUs with urban areas, the model will adjust the curve number to reflect the impact of the impervious areas. The format of the tillage operation line is Variable name Position Format F90 Format MONTH space digit integer i4 DAY space digit integer i4 HUSC space 9-16 decimal (xxxx.xxx) f8.3 MGT_OP space digit integer i4 TILLAGE_ID space digit integer i4 CNOP space decimal (xx.xxx) f6.3

302 HARVEST OPERATION CHAPTER 37: SWAT INPUT LAND/WATER MANAGEMENT 117 The variables which may be entered on the harvest line are listed and described below Variable name Definition MONTH Month operation takes place. DAY Day operation takes place. HUSC Fraction of total heat units for the year at which operation takes place. (If MONTH and DAY are not provided, HUSC must be set to a value) MGT_OP Management operation number. MGT_OP = 7 for the harvest only operation HIOVR Harvest index override ((kg/ha)/(kg/ha)) Optional. This variable will force the ratio of yield to total aboveground biomass to the specified value. The harvest index in the plant growth database (crop.dat) assumes only the seed is being harvested. If biomass is cut and removed (for example, in hay cuttings), HIOVR must be used to specify the amount of biomass removed. HARVEFF Harvest efficiency. Optional. This variable defines the efficiency of the harvest operation and is set to a value between 0.0 and 1.0. If the efficiency is set to a value less than 1.0 the fraction of biomass or yield removed is the fraction defined by the harvest efficiency. The remainder is converted to residue. If no value is defined for HARVEFF, the model assumes all of the biomass/yield is removed. The format of the harvest operation line is Variable name Position Format F90 Format MONTH space digit integer i4 DAY space digit integer i4 HUSC space 9-16 decimal (xxxx.xxx) f8.3 MGT_OP space digit integer i4 HIOVR space decimal (xxxx.xxx) f8.3 HARVEFF space decimal (xxxx.xxx) f8.3

303 118 SWAT USER'S MANUAL, VERSION KILL OPERATION The variables which may be entered on the kill line are listed and described below Variable name Definition MONTH Month operation takes place. DAY Day operation takes place. HUSC Fraction of total heat units for the year at which operation takes place. (If MONTH and DAY are not provided, HUSC must be set to a value) MGT_OP Management operation number. MGT_OP = 8 for kill operation The format of the kill line is Variable name Position Format F90 Format MONTH space digit integer i4 DAY space digit integer i4 HUSC space 9-16 decimal (xxxx.xxx) f8.3 MGT_OP space digit integer i GRAZING OPERATION The variables which may be entered on the grazing line are listed and described below Variable name Definition MONTH Month grazing begins. DAY Day grazing begins. HUSC Fraction of total heat units for the year at which grazing begins. (If MONTH and DAY are not provided, HUSC must be set to a value) MGT_OP Management operation number. MGT_OP = 9 for grazing operation BMEAT Dry weight of biomass consumed daily ((kg/ha)/day). NDGRAZ Number of consecutive days grazing takes place in the HRU.

304 CHAPTER 37: SWAT INPUT LAND/WATER MANAGEMENT 119 Variable name BMTRMP WMANURE IGFTYP Definition Dry weight of biomass trampled daily ((kg/ha)/day) (optional). Trampling becomes significant as the number of animals grazed per hectare increases. This is a very subjective value which is typically set equal to BMEAT, i.e. the animals trample as much as they eat. Dry weight of manure deposited daily ((kg/ha)/day). Manure identification code from fert.dat. The format of the grazing operation line is Variable name Position Format F90 Format MONTH space digit integer i4 DAY space digit integer i4 HUSC space 9-16 decimal (xxxx.xxx) f8.3 MGT_OP space digit integer i4 BMEAT space decimal (xxxx.xxx) f8.3 NDGRAZ space digit integer i4 BMTRMP space decimal (xxxx.xxx) f8.3 WMANURE space decimal (xxxx.xxx) f8.3 IGFTYP space digit integer i AUTO IRRIGATION INITIALIZATION The variables which may be entered on the auto irrigation line are listed and described below Variable name Definition MONTH Month auto irrigation is initialized. DAY Day auto irrigation is initialized. HUSC Fraction of total heat units for the year at which auto irrigation is initialized. (If MONTH and DAY are not provided, HUSC must be set to a value) MGT_OP Management operation number. MGT_OP = 10 for auto irrigation initialization

305 120 SWAT USER'S MANUAL, VERSION 2000 Variable name AUTO_WSTR Definition Water stress factor of cover/plant that triggers irrigation. The water stress factor is calculated by dividing the growth of the plant undergoing water stress by the growth of the plant if there was no water stress. This factor ranges from 0.0 to 1.0 where 0.0 indicates there is no growth of the plant due to water stress and 1.0 indicates there is no reduction of plant growth due to water stress. The format of the auto irrigation line is Variable name Position Format F90 Format MONTH space digit integer i4 DAY space digit integer i4 HUSC space 9-16 decimal (xxxx.xxx) f8.3 MGT_OP space digit integer i4 AUTO_WSTR space decimal (xxxx.xxx) f AUTO FERTILIZATION INITIALIZATION Auto fertilization needs to be initialized only once in the management file. The variables which may be entered on the auto fertilization line are listed and described below. Variable name Definition MONTH Month initialization takes place. DAY Day initialization takes place. HUSC Fraction of total heat units for the year at which initialization takes place. (If MONTH and DAY are not provided, HUSC must be set to a value) MGT_OP Management operation number. MGT_OP = 11 for auto fertilization initialization

306 CHAPTER 37: SWAT INPUT LAND/WATER MANAGEMENT 121 Variable name AUTO_NSTR FERT_ID AUTO_NMXS AUTO_NMXA AUTO_EFF AFRT_LY1 Definition Nitrogen stress factor of cover/plant that triggers fertilization. The nitrogen stress factor is calculated by dividing the growth of the plant undergoing nitrogen stress by the growth of the plant if there was no nitrogen stress. This factor ranges from 0.0 to 1.0 where 0.0 indicates there is no growth of the plant due to nitrogen stress and 1.0 indicates there is no reduction of plant growth due to nitrogen stress. Fertilizer identification number. This corresponds to the line number of the fertilizer in fert.dat. If this variable is left blank or set to zero, the model will apply the commercial fertilizer Maximum amount of NO 3 -N allowed in any one application (kg NO 3 -N/ha). If this variable is left blank, the model will set AUTO_NMXS = 200. Maximum amount of NO 3 -N allowed to be applied in any one year (kg NO 3 -N/ha). If this variable is left blank, the model will set AUTO_NMXA = 300. Application efficiency. The amount of fertilizer applied in auto fertilization is based on the amount of nitrogen removed at harvest. If you set AUTO_EFF = 1.0, the model will apply enough fertilizer to replace the amount of nitrogen removed at harvest. If AUTO_EFF > 1.0, the model will apply fertilizer to meet harvest removal plus an extra amount to make up for nitrogen losses due to surface runoff/leaching. If AUTO_EFF < 1.0, the model will apply fertilizer at the specified fraction below the amount removed at harvest. If this variable is left blank, the model will set AUTO_EFF = 1.3. Fraction of fertilizer applied to top 10mm of soil. The remaining fraction is applied to the 1 st soil layer below 10mm. If this variable is left blank, the model will set AFRT_LY1 = 0.2.

307 122 SWAT USER'S MANUAL, VERSION 2000 The format of the auto fertilization line is Variable name Position Format F90 Format MONTH space digit integer i4 DAY space digit integer i4 HUSC space 9-16 decimal (xxxx.xxx) f8.3 MGT_OP space digit integer i4 AUTO_NSTR space decimal (xxxx.xxx) f8.3 FERT_ID space digit integer i4 AUTO_NMXS space decimal (xxxx.xxx) f8.3 AUTO_NMXA space decimal (xxxx.xxx) f8.3 AUTO_EFF space decimal (xx.xxx) f6.3 AFRT_LY1 space decimal (xx.xxx) f STREET SWEEPING OPERATION The street sweeping operation can be used only if the urban build up/wash off routines have been selected for the HRU. The variables which may be entered on the street sweeping line are listed and described below. Variable name Definition MONTH Month operation takes place. DAY Day operation takes place. HUSC Fraction of heat units at which street sweeping takes place. (If MONTH and DAY are not provided, HUSC must be set to a value) MGT_OP Management operation number. MGT_OP = 12 for street sweeping SWEEPEFF Removal efficiency of sweeping operation. SWEEPEFF is a fraction that ranges between 0.0 and 1.0. A value of 0.0 indicates that none of the built-up sediments are removed while a value of 1.0 indicates that all of the built-up sediments are removed.

308 CHAPTER 37: SWAT INPUT LAND/WATER MANAGEMENT 123 Variable name AVWSP Definition Fraction of curb length available for sweeping. The amount of curb length available for sweeping may be less than the total length due to the presence of parked cars and other obstructions. AVWSP can range from 0.01 to If no value is entered for AVWSP (AVWSP left blank or set to 0.0, the model will assume 100% of the curb length is available for sweeping. The format of the street sweeping line is Variable name Position Format F90 Format MONTH space digit integer i4 DAY space digit integer i4 HUSC space 9-16 decimal (xxxx.xxx) f8.3 MGT_OP space digit integer i4 SWEEPEFF space decimal (xxxx.xxx) f8.3 AVWSP space decimal (xxxx.xxx) f RELEASE/IMPOUND OPERATION The release/impound operation can be used only in the HRU designated as a depressional/impounded area in the subbasin (IPOT in.hru). The variables which may be entered on the release/impound line are listed and described below. Variable name Definition MONTH Month operation takes place. DAY Day operation takes place. HUSC Fraction of total heat units at which release/impounding takes place. (If MONTH and DAY are not provided, HUSC must be set to a value) MGT_OP Management operation number. MGT_OP = 13 for release/impoundment of water IREL_IMP Release/impound action code: 0 initiate water impoundment 1 initiate water release

309 124 SWAT USER'S MANUAL, VERSION 2000 The format of the release/impound line is Variable name Position Format F90 Format MONTH space digit integer i4 DAY space digit integer i4 HUSC space 9-16 decimal (xxxx.xxx) f8.3 MGT_OP space digit integer i4 IREL_IMP space digit integer i END OF YEAR OPERATION SWAT requires a blank line to be inserted after all operations for a single year are listed. The blank line lets the model know that there will be no more operations in the year. If a rotation is being simulated in which the land is left fallow for one of the years with no operations occurring, a blank line should be entered for the fallow year.

310 CHAPTER 37: SWAT INPUT LAND/WATER MANAGEMENT WATER USE INPUT FILE (.WUS) The water use file quantifies consumptive water use in the watershed. The water removed is considered to be lost from the system. This file is used to simulate removal of water for irrigation outside the watershed or removal of water for urban/industrial use. Following is a brief description of the variables in the water use input file. They are listed in the order they appear within the file. Variable name TITLE WUPND(mon) WURCH(mon) WUSHAL(mon) WUDEEP(mon) Definition The first three lines of the.wus file are reserved for user comments. The comments may take up to 80 spaces on each line. (optional) Average daily water removal from the pond for the month (10 4 m 3 /day). (optional) Average daily water removal from the reach for the month (10 4 m 3 /day). (optional) Average daily water removal from the shallow aquifer for the month (10 4 m 3 /day). (optional) Average daily water removal from the deep aquifer for the month (10 4 m 3 /day). (optional) The format of the water use file is: Variable name Line # Position Format F90 Format TITLE 1-3 space 1-80 character a80 WUPND(1) 4 space 1-10 decimal (xxxxxxxx.x) f10.1 WUPND(2) 4 space decimal (xxxxxxxx.x) f10.1 WUPND(3) 4 space decimal (xxxxxxxx.x) f10.1 WUPND(4:) 4 space decimal (xxxxxxxx.x) f10.1 WUPND(5) 4 space decimal (xxxxxxxx.x) f10.1 WUPND(6) 4 space decimal (xxxxxxxx.x) f10.1

311 126 SWAT USER'S MANUAL, VERSION 2000 Variable name Line # Position Format F90 Format WUPND(7) 5 space 1-10 decimal (xxxxxxxx.x) f10.1 WUPND(8) 5 space decimal (xxxxxxxx.x) f10.1 WUPND(9) 5 space decimal (xxxxxxxx.x) f10.1 WUPND(10) 5 space decimal (xxxxxxxx.x) f10.1 WUPND(11) 5 space decimal (xxxxxxxx.x) f10.1 WUPND(12) 5 space decimal (xxxxxxxx.x) f10.1 WURCH(1) 6 space 1-10 decimal (xxxxxxxx.x) f10.1 WURCH(2) 6 space decimal (xxxxxxxx.x) f10.1 WURCH(3) 6 space decimal (xxxxxxxx.x) f10.1 WURCH(4) 6 space decimal (xxxxxxxx.x) f10.1 WURCH(5) 6 space decimal (xxxxxxxx.x) f10.1 WURCH(6) 6 space decimal (xxxxxxxx.x) f10.1 WURCH(7) 7 space 1-10 decimal (xxxxxxxx.x) f10.1 WURCH(8) 7 space decimal (xxxxxxxx.x) f10.1 WURCH(9) 7 space decimal (xxxxxxxx.x) f10.1 WURCH(10) 7 space decimal (xxxxxxxx.x) f10.1 WURCH(11) 7 space decimal (xxxxxxxx.x) f10.1 WURCH(12) 7 space decimal (xxxxxxxx.x) f10.1 WUSHAL(1) 8 space 1-10 decimal (xxxxxxxx.x) f10.1 WUSHAL(2) 8 space decimal (xxxxxxxx.x) f10.1 WUSHAL(3) 8 space decimal (xxxxxxxx.x) f10.1 WUSHAL(4) 8 space decimal (xxxxxxxx.x) f10.1 WUSHAL(5) 8 space decimal (xxxxxxxx.x) f10.1 WUSHAL(6) 8 space decimal (xxxxxxxx.x) f10.1 WUSHAL(7) 9 space 1-10 decimal (xxxxxxxx.x) f10.1 WUSHAL(8) 9 space decimal (xxxxxxxx.x) f10.1 WUSHAL(9) 9 space decimal (xxxxxxxx.x) f10.1 WUSHAL(10) 9 space decimal (xxxxxxxx.x) f10.1 WUSHAL(11) 9 space decimal (xxxxxxxx.x) f10.1 WUSHAL(12) 9 space decimal (xxxxxxxx.x) f10.1 WUDEEP(1) 10 space 1-10 decimal (xxxxxxxx.x) f10.1 WUDEEP(2) 10 space decimal (xxxxxxxx.x) f10.1 WUDEEP(3) 10 space decimal (xxxxxxxx.x) f10.1 WUDEEP(4) 10 space decimal (xxxxxxxx.x) f10.1

312 CHAPTER 37: SWAT INPUT LAND/WATER MANAGEMENT 127 Variable name Line # Position Format F90 Format WUDEEP(5) 10 space decimal (xxxxxxxx.x) f10.1 WUDEEP(6) 10 space decimal (xxxxxxxx.x) f10.1 WUDEEP(7) 11 space 1-10 decimal (xxxxxxxx.x) f10.1 WUDEEP(8) 11 space decimal (xxxxxxxx.x) f10.1 WUDEEP(9) 11 space decimal (xxxxxxxx.x) f10.1 WUDEEP(10) 11 space decimal (xxxxxxxx.x) f10.1 WUDEEP(11) 11 space decimal (xxxxxxxx.x) f10.1 WUDEEP(12) 11 space decimal (xxxxxxxx.x) f10.1

313 128 SWAT USER'S MANUAL, VERSION 2000

314 CHAPTER 38 SWAT INPUT DATA: GROUNDWATER SWAT partitions groundwater into two aquifer systems: a shallow, unconfined aquifer which contributes return flow to streams within the watershed and a deep, confined aquifer which contributes return flow to streams outside the watershed. The properties governing water movement into and out of the aquifers are initialized in the groundwater input file. 127

315 128 SWAT USER'S MANUAL, VERSION GROUNDWATER INPUT FILE (.GW) Following is a brief description of the variables in the groundwater input file. They are listed in the order they appear within the file. Variable name TITLE SHALLST DEEPST GW_DELAY ALPHA_BF GWQMN GW_REVAP Definition The first line of the.gw file is reserved for user comments. The comments may take up to 80 spaces. (optional) Initial depth of water in the shallow aquifer (mm H 2 O). Initial depth of water in the deep aquifer (mm H 2 O). If no value for DEEPST is entered, the model sets DEEPST = Groundwater delay (days). The time required for water leaving the bottom of the root zone to reach the shallow aquifer. Baseflow alpha factor (days). The baseflow alpha factor, or recession constant, characterizes the groundwater recession curve. This constant will be some number less than 1.0, and will be large (approach one) for flat recessions and small (approach zero) for steep recessions. Threshold depth of water in the shallow aquifer required for return flow to occur (mm H 2 O). Groundwater flow to the reach is allowed only if the depth of water in the shallow aquifer is equal to or greater than GWQMN. Groundwater "revap" coefficient. This variable controls the amount of water which will move from the shallow aquifer to the root zone as a result of soil moisture depletion and the amount of direct water uptake from deep rooted trees and shrubs. As GW_REVAP approaches 0, movement of water from the shallow aquifer to the root zone is restricted. As GW_REVAP approaches 1, the rate of transfer from the shallow aquifer to the root zone approaches the rate of potential evapotranspiration. The value for GW_REVAP should be between 0.02 and 0.20.

316 CHAPTER 38: SWAT INPUT GROUNDWATER 129 Variable name REVAPMN RCHRG_DP GWHT GW_SPYLD GWNO3 GWSOLP Definition Threshold depth of water in the shallow aquifer for "revap" to occur (mm H 2 O). Movement of water from the shallow aquifer to the root zone or to plants is allowed only if the depth of water in the shallow aquifer is equal to or greater than REVAPMN. Deep aquifer percolation fraction. The fraction of percolation from the root zone which recharges the deep aquifer. The value for RCHRG_DP should be between 0.0 and 1.0. Initial groundwater height (m). Optional. Specific yield of the shallow aquifer (m 3 /m 3 ). Specific yield is defined as the ratio of the volume of water that drains by gravity to the total volume of rock. Optional. Concentration of nitrate in groundwater contribution to streamflow from subbasin (mg N/L). Optional. Concentration of soluble phosphorus in groundwater contribution to streamflow from subbasin (mg P/L). Optional. The groundwater file is a free format file. The variables may be placed in any position the user wishes on the line. Values for variables classified as integers should not include a decimal while values for variables classified as reals must contain a decimal. A blank space denotes the end of an input value and the beginning of the next value if there is another on the line. Variable name Line # Format F90 Format TITLE 1 character a80 SHALLST 2 real free DEEPST 3 real free GW_DELAY 4 real free ALPHA_BF 5 real free GWQMN 6 real free GW_REVAP 7 real free REVAPMN 8 real free RCHRG_DP 9 real free GWHT 10 real free GW_SPYLD 11 real free GWNO3 12 real free GWSOLP 13 real free

317 130 SWAT USER'S MANUAL, VERSION 2000

318 CHAPTER 39 SWAT INPUT DATA: MAIN CHANNEL In order to simulate the physical processes affecting the flow of water and transport of sediment in the channel network of the watershed, SWAT requires information on the physical characteristics of the main channel within each subbasin. The main channel input file (.rte) summarizes the physical characteristics of the channel which affect water flow and sediment and pesticide transport. 131

319 132 SWAT USER'S MANUAL, VERSION MAIN CHANNEL INPUT FILE (.RTE) Following is a brief description of the variables in the main channel input file. They are listed in the order they appear within the file. Variable name TITLE CH_W(2) CH_D CH_S(2) CH_L(2) CH_N(2) CH_K(2) CH_EROD CH_COV CH_WDR ALPHA_BNK Definition The first line of the.rte file is reserved for user comments. The comments may take up to 80 spaces. (optional) Average width of main channel at top of bank (m). Depth of main channel from top of bank to bottom (m). Average slope of main channel along the channel length (m/m). Length of main channel (km). If no value for CH_L is entered, the model will set CH_L = Manning's "n" value for the main channel. Effective hydraulic conductivity in main channel alluvium (mm/hr). Channel erodibility factor. CH_EROD is set to a value between 0.0 and 1.0. A value of 0.0 indicates a nonerosive channel while a value of 1.0 indicates no resistance to erosion. Channel cover factor. CH_COV is set to a value between 0.0 and 1.0. A value of 0.0 indicates that the channel is completely protected from degradation by cover while a value of 1.0 indicates there is no vegetative cover on the channel. Channel width-depth ratio (m/m). Required only if channel degradation is being modeled (IDEG = 1 in.cod). Baseflow alpha factor for bank storage (days). The baseflow alpha factor, or recession constant, characterizes the bank storage recession curve. This constant will be some number less than 1.0, and will be large (approach one) for flat recessions and small (approach zero) for steep recessions. If no value is entered for ALPHA_BNK, the variable will be set to the same value as ALPHA_BF from the groundwater (.gw) file.

320 CHAPTER 39: SWAT INPUT MAIN CHANNEL 133 The main channel file is a free format file. The variables may be placed in any position the user wishes on the line. Values for variables classified as integers should not include a decimal while values for variables classified as reals must contain a decimal. A blank space denotes the end of an input value and the beginning of the next value if there is another on the line. The format of the main channel input file is: Variable name Line # Format F90 Format TITLE 1 character a80 CH_W(2) 2 real free CH_D 3 real free CH_S(2) 4 real free CH_L(2) 5 real free CH_N(2) 6 real free CH_K(2) 7 real free CH_EROD 8 real free CH_COV 9 real free CH_WDR 10 real free ALPHA_BNK 11 real free

321 134 SWAT USER'S MANUAL, VERSION 2000

322 CHAPTER 40 SWAT INPUT DATA: RESERVOIRS/PONDS Impoundment structures modify the movement of water in the channel network by lowering the peak flow and volume of flood discharges. Because impoundments slow down the flow of water, sediment will fall from suspension, removing nutrient and chemicals adsorbed to the soil particles. SWAT is able to model three types of impoundments. The first type is a small structure with one spillway. Releases occur only when the storage volume of the structure is exceeded and the excess volume is released within one day. The second type of impoundment is a small, uncontrolled reservoir with a principal and emergency spillway. Water is released at a specified rate when the volume of the reservoir exceeds the principal spillway volume. Volume exceeding the 135

323 136 SWAT USER'S MANUAL, VERSION 2000 emergency spillway storage is released within one day. The third type of impoundment is a managed reservoir. Water may be released from the managed reservoir based on measured outflow or target reservoir volumes. The features of an impoundment are shown in Figure Figure 40.1: Components of a reservoir with flood water detention features. SWAT uses two files to store information on impoundments, the reservoir input file (.res) and the pond input file (.pnd). An unlimited number of reservoirs may be modeled in a watershed, while a pond may be modeling in each subbasin. Originally, the pond input file contained data for simple impoundment structures with only one spillway while data for the more complex impoundments was stored in the reservoir input file. Due to user needs, the options allowed for impoundments directly linked to subbasins have been increased over the years and the distinction between "reservoirs" and "ponds" as simulated by SWAT has become somewhat blurred. The key difference between the two structures is that a reservoir is located on the main channel network of the watershed while a pond is located off of the main channel within a subbasin. Consequently, water contribution from a pond is limited to the water loading generated within a subbasin. The following table has been prepared to assist the user in identifying the input file and required variables to be used for different situations. The structures are identified on the basis of how water is released.

324 CHAPTER 40: SWAT INPUT RESERVOIR/POND 137 Structure to be modeled: impoundment with one spillway where water is released when the storage capacity is exceeded. There is no control on the rate of water release from the impoundment. File:.pnd Additional comments: values are entered for the principal spillway only no data should be entered for the emergency spillway (PND_ESA, PND_EVOL) or target storage (IFLOD1, IFLOD2, NDTARG). Structure to be modeled: small, uncontrolled reservoir with a principal and emergency spillway where water release is passive (e.g. gravity driven). Water is not released until the level stored in the reservoir is above the height of the principal spillway. If the water level is above the principal spillway, water is released at a known rate. If the level of the reservoir rises above the emergency spillway, the volume of water exceeding the storage capacity of the emergency spillway is released within a day. File:.res Additional comments: the variable IRESCO should be set to 0 and the data required for this option entered. Structure to be modeled: large, managed reservoir where the daily or monthly values for outflow are known. File:.res Additional comments: the variable IRESCO should be set to 1 or 3 depending on the outflow data available. Structure to be modeled: a reservoir which is managed to maintain a certain volume of water (the target storage) at all times File:.pnd or.res Additional comments: In the.pnd file, the target storage is calculated by the model. The target storage varies between the principal and emergency storage as a function of the time of year the target storage approaches the principal spillway storage in the flood season while during the non-flood season it approaches the emergency spillway storage. In the.res file, the user specifies the target storage for each month of the year. To use target storage in the.pnd file, values must be entered for PND_ESA, PND_EVOL, IFLOD1, IFLOD2 and NDTARG. To use target storage in the.res file, IRESCO is set to 2 and the data required for this option is entered.

325 138 SWAT USER'S MANUAL, VERSION RESERVOIR INPUT FILE (.RES) Following is a brief description of the variables in the reservoir input file. They are listed in the order they appear within the file. Variable name TITLE RES_SUB MORES IYRES RES_ESA RES_EVOL RES_PSA RES_PVOL RES_VOL RES_SED RES_NSED Definition The first line of the file is reserved user comments. The comments may take up to 80 spaces. (optional) Number of the subbasin the reservoir is in (weather for subbasin is used for the reservoir). If no subbasin number is assigned to RES_SUB, the model uses weather data from subbasin 1 to model climatic processes on the reservoir. Month the reservoir became operational (1-12). If 0 is input for MORES and IYRES, the model assumes the reservoir is in operation at the beginning of the simulation. Year of the simulation the reservoir became operational (eg 1980). If 0 is input for MORES and IYRES, the model assumes the reservoir is in operation at the beginning of the simulation. Reservoir surface area when the reservoir is filled to the emergency spillway (ha) Volume of water needed to fill the reservoir to the emergency spillway (10 4 m 3 ). Reservoir surface area when the reservoir is filled to the principal spillway (ha). Volume of water needed to fill the reservoir to the principal spillway (10 4 m 3 ). Initial reservoir volume. If the reservoir is in existence at the beginning of the simulation period, the initial reservoir volume is the volume on the first day of simulation. If the reservoir begins operation in the midst of a SWAT simulation, the initial reservoir volume is the volume of the reservoir the day the reservoir becomes operational (10 4 m 3 ). Initial sediment concentration in the reservoir (mg/l). Normal sediment concentration in the reservoir (mg/l).

326 CHAPTER 40: SWAT INPUT RESERVOIR/POND 139 Variable name RES_K IRESCO OFLOWMX(mon) Definition Hydraulic conductivity of the reservoir bottom (mm/hr). Outflow simulation code: 0 compute outflow for uncontrolled reservoir with average annual release rate (if IRESCO=0, need RES_RR) 1 measured monthly outflow (if IRESCO=1, need RESOUT) 2 simulated controlled outflow target release (if IRESCO=2, need STARG, IFLOD1R, IFLOD2D, and NDTARGR 3 measured daily outflow (if IRESCO=3, need RESDAYO) Maximum daily outflow for the month (m 3 /s). Set all months to zero if you do not want to trigger this requirement. OFLOWMN(mon) Minimum daily outflow for the month (m 3 /s). Set all months to zero if you do not want to trigger this requirement. RES_RR Average daily principal spillway release rate (m 3 /s). Needed if IRESCO = 0. RESMONO Name of monthly reservoir outflow file. Required if IRESCO = 1. IFLOD1R Beginning month of non-flood season. Needed if IRESCO = 2. IFLOD2R Ending month of non-flood season. Needed if IRESCO = 2. NDTARGR Number of days to reach target storage from current reservoir storage. Needed if IRESCO = 2. STARG(mon) Monthly target reservoir storage (10 4 m 3 ). Needed if IRESCO = 2. RESDAYO Name of daily reservoir outflow file. Required if IRESCO = 3. WURESN(mon,:) Average amount of water withdrawn from reservoir each day in the month for consumptive use (10 4 m 3 ). This variable allows water to be removed from the reservoir for use outside the watershed. (optional)

327 140 SWAT USER'S MANUAL, VERSION 2000 Variable name WURTNF(:) Definition Fraction of water removed from the reservoir via WURESN that is returned and becomes flow out of reservoir (m 3 /m 3 ). (optional) The reservoir file is a free format file. The variables may be placed in any position the user wishes on the line. Values for variables classified as integers should not include a decimal while values for variables classified as reals must contain a decimal. A blank space denotes the end of an input value and the beginning of the next value if there is another on the line. The format of the reservoir input file is: Variable name Line # Format F90 Format TITLE 1 character a80 RES_SUB 2 integer free MORES 3 integer free IYRES 4 integer free RES_ESA 5 real free RES_EVOL 6 real free RES_PSA 7 real free RES_PVOL 8 real free RES_VOL 9 real free RES_SED 10 real free RES_NSED 11 real free RES_K 12 real free IRESCO 13 integer free COMMENT LINE 14 character a80 OFLOWMX(1) 15 real free OFLOWMX(2) 15 real free OFLOWMX(3) 15 real free OFLOWMX(4) 15 real free OFLOWMX(5) 15 real free OFLOWMX(6) 15 real free COMMENT LINE 16 character a80 OFLOWMX(7) 17 real free OFLOWMX(8) 17 real free OFLOWMX(9) 17 real free OFLOWMX(10) 17 real free OFLOWMX(11) 17 real free

328 CHAPTER 40: SWAT INPUT RESERVOIR/POND 141 Variable name Line # Format F90 Format OFLOWMX(12) 17 real free COMMENT LINE 18 character a80 OFLOWMN(1) 19 real free OFLOWMN(2) 19 real free OFLOWMN(3) 19 real free OFLOWMN(4) 19 real free OFLOWMN(5) 19 real free OFLOWMN(6) 19 real free COMMENT LINE 20 character a80 OFLOWMN(7) 21 real free OFLOWMN(8) 21 real free OFLOWMN(9) 21 real free OFLOWMN(10) 21 real free OFLOWMN(11) 21 real free OFLOWMN(12) 21 real free RES_RR 22 real free RESMONO 23 character (len=13) a13 IFLOD1R 24 integer free IFLOD2R 25 integer free NDTARGR 26 integer free COMMENT LINE 27 character a80 STARG(1) 28 real free STARG(2) 28 real free STARG(3) 28 real free STARG(4) 28 real free STARG(5) 28 real free STARG(6) 28 real free COMMENT LINE 29 character a80 STARG(7) 30 real free STARG(8) 30 real free STARG(9) 30 real free STARG(10) 30 real free STARG(11) 30 real free STARG(12) 30 real free RESDAYO 31 character (len=13) a13

329 142 SWAT USER'S MANUAL, VERSION 2000 Variable name Line # Format F90 Format COMMENT LINE 32 character a80 WURESN(1) 33 real free WURESN(2) 33 real free WURESN(3) 33 real free WURESN(4) 33 real free WURESN(5) 33 real free WURESN(6) 33 real free COMMENT LINE 34 character a80 WURESN(7) 35 real free WURESN(8) 35 real free WURESN(9) 35 real free WURESN(10) 35 real free WURESN(11) 35 real free WURESN(12) 35 real free WURTNF 36 real free 40.2 DAILY RESERVOIR OUTFLOW FILE When measured daily outflow is used for a reservoir, the name of the file containing the data is assigned to the variable RESDAYO. The daily outflow file contains the flow rate for every day of operation of the reservoir, beginning with the first day of operation in the simulation. The daily outflow file contains one variable: Variable name TITLE RES_OUTFLOW Definition The first line of the file is reserved for a description. The description may take up to 80 spaces. (optional) The water release rate for the day (m 3 /sec). The format of the daily reservoir outflow file is: Variable name Line # Position Format F90 Format TITLE 1 space 1-80 character a80 RES_OUTFLOW 2-END space 1-8 decimal(xxxxx.xx) f8.2

330 CHAPTER 40: SWAT INPUT RESERVOIR/POND MONTHLY RESERVOIR OUTFLOW FILE When outflow data average over a month is used for a reservoir, the name of the file containing the data is assigned to the variable RESMONO. The monthly outflow file contains the average daily flow rate for every month of operation of the reservoir, beginning with the first month of operation in the simulation. The monthly outflow file contains the following variables: Variable name TITLE RESOUT(mon,yr) Definition The first line of the file is reserved for a description. The description may take up to 80 spaces. (optional) Measured average daily outflow from the reservoir for the month (m 3 /s). Needed when IRESCO = 1. There must be a line of input for every year of simulation. Variable name Line # Format F90 Format TITLE 1 character a80 If IRESCO = 1, the model will read the input data for RESOUT. There should be one line for data for RESOUT for each year of simulation beginning with the 1 st year of simulation. RESOUT(1,yr) 2-END real free RESOUT(2,yr) 2-END real free RESOUT(3,yr) 2-END real free RESOUT(4,yr) 2-END real free RESOUT(5,yr) 2-END real free RESOUT(6,yr) 2-END real free RESOUT(7,yr) 2-END real free RESOUT(8,yr) 2-END real free RESOUT(9,yr) 2-END real free RESOUT(10,yr) 2-END real free RESOUT(11,yr) 2-END real free RESOUT(12,yr) 2-END real free

331 144 SWAT USER'S MANUAL, VERSION POND INPUT FILE (.PND) Following is a brief description of the variables in the subbasin pond input file. They are listed in the order they appear within the file. Variable name TITLE POND SECTION TITLE PND_FR PND_PSA PND_PVOL PND_ESA PND_EVOL PND_VOL PND_SED PND_NSED PND_K IFLOD1 IFLOD2 NDTARG PSETL1 Definition The first line of the file is reserved user comments. The comments may take up to 80 spaces. Optional. The second line of the file is reserved for a section title for the pond data. The model does not process this line. The title may take up to 80 spaces. Optional. Fraction of subbasin area that drains into ponds. The value for PND_FR should be between 0.0 and 1.0. Surface area of ponds when filled to principal spillway (ha). Volume of water stored in ponds when filled to the principal spillway (10 4 m 3 H 2 O). Surface area of ponds when filled to emergency spillway (ha). Optional. Volume of water stored in ponds when filled to the emergency spillway (10 4 m 3 H 2 O). Optional. Initial volume of water in ponds (10 4 m 3 H 2 O). Initial sediment concentration in pond water (mg/l). Normal sediment concentration in pond water (mg/l). Hydraulic conductivity through bottom of ponds (mm/hr). Beginning month of non-flood season. Optional. Ending month of non-flood season. Optional. Number of days needed to reach target storage from current pond storage. The default value for NDTARG is 15 days. Optional. Phosphorus settling rate in pond for months IPND1 through IPND2 (m/year). Optional.

332 CHAPTER 40: SWAT INPUT RESERVOIR/POND 145 Variable name PSETL2 NSETL1 NSETL2 CHLA SECCI PND_NO3 PND_SOLP PND_ORGN PND_ORGP COMMON VARIABLES SECTION TITLE IPND1 IPND2 Definition Phosphorus settling rate in pond for months other than IPND1-IPND2 (m/year). Optional. Nitrogen settling rate in pond for months IPND1 through IPND2 (m/year). Optional. Nitrogen settling rate in pond for months other than IPND1-IPND2 (m/year). Optional. Chlorophyll a production coefficient for ponds. Chlorophyll a concentration in the pond is calculated from the total phosphorus concentration. The equation assumes the system is phosphorus limited. The chlorophyll a coefficient was added to the equation to allow the user to adjust results to account for factors ignored by the basic equation such as nitrogen limitations. The default value for CHLA is 1.00, which uses the original equation. Optional. Water clarity coefficient for ponds. The clarity of the pond is expressed by the secci-disk depth (m) which is calculated as a function of chlorophyll a. Because suspended sediment also can affect water clarity, the water clarity coefficient has been added to the equation to allow users to adjust for the impact of factors other than chlorophyll a on water clarity. The default value for SECCI is 1.00, which uses the original equation. Optional. Initial concentration of NO 3 -N in pond (mg N/L). Optional. Initial concentration of soluble P in pond (mg P/L). Optional. Initial concentration of organic N in pond (mg N/L). Optional. Initial concentration of organic P in pond (mg P/L). Optional. The 25 th line of the file is reserved for a section title for data used for ponds and wetlands. The model does not process this line. The title may take up to 80 spaces. Optional. Beginning month of mid-year nutrient settling season. Optional. Ending month of mid-year nutrient settling season. Optional.

333 146 SWAT USER'S MANUAL, VERSION 2000 Variable name WETLAND SECTION TITLE WET_FR WET_NSA WET_NVOL WET_MXSA WET_MXVOL WET_VOL WET_SED WET_NSED WET_K PSETLW1 PSETLW2 NSETLW1 NSETLW2 CHLAW Definition The 28 th line of the file is reserved for a section title for the wetland data. The model does not process this line. The title may take up to 80 spaces. Optional. Fraction of subbasin area that drains into wetlands. Surface area of wetlands at normal water level (ha). Volume of water stored in wetlands when filled to normal water level (10 4 m 3 H 2 O). Surface area of wetlands at maximum water level (ha). Volume of water stored in wetlands when filled to maximum water level (10 4 m 3 H 2 O). Initial volume of water in wetlands (10 4 m 3 H 2 O). Initial sediment concentration in wetland water (mg/l). Normal sediment concentration in wetland water (mg/l). Hydraulic conductivity of bottom of wetlands (mm/hr). Phosphorus settling rate in wetland for months IPND1 through IPND2 (m/year). Optional. Phosphorus settling rate in wetlands for months other than IPND1-IPND2 (m/year). Optional. Nitrogen settling rate in wetlands for months IPND1 through IPND2 (m/year). Optional. Nitrogen settling rate in wetlands for months other than IPND1-IPND2 (m/year). Optional. Chlorophyll a production coefficient for wetlands. Chlorophyll a concentration in the wetland is calculated from the total phosphorus concentration. The equation assumes the system is phosphorus limited. The chlorophyll a coefficient was added to the equation to allow the user to adjust results to account for other factors ignored by the basic equation such as nitrogen limitations. The default value for CHLA is 1.00, which uses the original equation. Optional.

334 CHAPTER 40: SWAT INPUT RESERVOIR/POND 147 Variable name SECCIW WET_NO3 WET_SOLP WET_ORGN WET_ORGP Definition Water clarity coefficient for wetlands. The clarity of the wetland is expressed by the secci-disk depth (m) which is calculated as a function of chlorophyll a. Because suspended sediment also can affect water clarity, the water clarity coefficient has been added to the equation to allow users to adjust for the impact of factors other than chlorophyll a on water clarity. The default value for SECCI is 1.00, which uses the original equation. Optional. Initial concentration of NO 3 -N in wetland (mg N/L). Optional. Initial concentration of soluble P in wetland (mg P/L). Optional. Initial concentration of organic N in wetland (mg N/L). Optional. Initial concentration of organic P in wetland (mg P/L). Optional. The pond input file is a free format file. The variables may be placed in any position the user wishes on the line. Values for variables classified as integers should not include a decimal while values for variables classified as reals must contain a decimal. A blank space denotes the end of an input value and the beginning of the next value if there is another on the line. The format of the pond input file is: Variable name Line # Format F90 Format TITLE 1 character a80 POND SECT. TITLE 2 character a80 PND_FR 3 real free PND_PSA 4 real free PND_PVOL 5 real free PND_ESA 6 real free PND_EVOL 7 real free PND_VOL 8 real free PND_SED 9 real free PND_NSED 10 real free PND_K 11 real free IFLOD1 12 integer free IFLOD2 13 integer free

335 148 SWAT USER'S MANUAL, VERSION 2000 Variable name Line # Format F90 Format NDTARG 14 integer free PSETL1 15 real free PSETL2 16 real free NSETL1 17 real free NSETL2 18 real free CHLA 19 real free SECCI 20 real free PND_NO3 21 real free PND_SOLP 22 real free PND_ORGN 23 real free PND_ORGP 24 real free POND/WETLAND SECT. TITLE 25 character a80 IPND1 26 integer free IPND2 27 integer free WETLAND SECT. TITLE 28 character a80 WET_FR 29 real free WET_NSA 30 real free WET_NVOL 31 real free WET_MXSA 32 real free WET_MXVOL 33 real free WET_VOL 34 real free WET_SED 35 real free WET_NSED 36 real free WET_K 37 real free PSETLW1 38 real free PSETLW2 39 real free NSETLW1 40 real free NSETLW2 41 real free CHLAW 42 real free SECCIW 43 real free WET_NO3 44 real free WET_SOLP 45 real free WET_ORGN 46 real free WET_ORGP 47 real free

336 CHAPTER 41 SWAT INPUT DATA: WATER QUALITY While water quality is a broad subject, the primary areas of concern are nutrients, organic chemicals both agricultural (pesticide) and industrial, heavy metals, bacteria and sediment levels in streams and large water bodies. SWAT is able to model processes affecting nutrient, pesticide and sediment levels in the main channels and reservoirs. The data used by SWAT for water quality is primarily contained within three files: the stream water quality input file (.swq), the general water quality input file (.wwq), and the lake water quality input file (.lwq). The stream water quality input file and the general water quality input file contain input data used in the QUAL2E subroutines in the model. 147

337 148 SWAT USER'S MANUAL, VERSION GENERAL WATER QUALITY INPUT FILE (.WWQ) The general water quality input file contains information used by SWAT to initialize stream water quality variables that apply to the entire watershed. Following is a brief description of the variables in the general water quality input file. The variables are listed in the order they appear within the file. Variable name TITLE LAO IGROPT Definition The first line is reserved for user comments. This line is not processed by the model. Qual2E light averaging option. Qual2E defines four light averaging options. 1 Depth-averaged algal growth attenuation factor for light (FL) is computed from one daylight average solar radiation value calculated in the steady state temperature heat balance. 2 FL is computed from one daylight average solar radiation value supplied by the user. 3 FL is obtained by averaging the hourly daylight values of FL computed from the hourly daylight values of solar radiation calculated in the steady state temperature heat balance. 4 FL is obtained by averaging the hourly daylight values of FL computed from the hourly daylight values of solar radiation calculated from a single value of total daily, photosynthetically active, solar radiation and an assumed cosine function. The only option currently active in SWAT is 2. Qual2E algal specific growth rate option. Qual2E provides three different options for computing the algal growth rate. 1 Multiplicative: the effects of nitrogen, phosphorus and light are multiplied together to calculate the net effect on the local algal growth rate

338 Variable name IGROPT, cont. AI0 AI1 AI2 AI3 AI4 AI5 AI6 CHAPTER 41: SWAT INPUT WATER QUALITY 149 Definition 2 Limiting nutrient: the local algal growth rate is limited by light and one of the nutrients (nitrogen or phosphorus) 3 Harmonic mean: the local algal growth rate is limited by light and the harmonic mean of the nutrient interactions The default option is the limiting nutrient option (2). Ratio of chlorophyll-a to algal biomass (µg-chla/mg algae). Values for AI0 should fall in the range If no value for AI0 is entered, the model will set AI0 = Fraction of algal biomass that is nitrogen (mg N/mg alg). Values for AI1 should fall in the range If no value for AI1 is entered, the model will set AI1 = Fraction of algal biomass that is phosphorus (mg P/mg alg). Values for AI2 should fall in the range If no value for AI2 is entered, the model will set AI2 = The rate of oxygen production per unit of algal photosynthesis (mg O 2 /mg alg). Values for AI3 should fall in the range If no value for AI3 is entered, the model will set AI3 = 1.6. The rate of oxygen uptake per unit of algal respiration (mg O 2 /mg alg). Values for AI4 should fall in the range If no value for AI4 is entered, the model will set AI4 = 2.0. The rate of oxygen uptake per unit of NH 3 -N oxidation (mg O 2 /mg NH 3 -N). Values for AI5 should fall in the range If no value for AI5 is entered, the model will set AI5 = 3.5. The rate of oxygen uptake per unit of NO 2 -N oxidation (mg O 2 /mg NO 2 -N). Values for AI6 should fall in the range If no value for AI6 is entered, the model will set AI6 = MUMAX Maximum specific algal growth rate at 20º C (day -1 ). Values for MUMAX should fall in the range If no value for MUMAX is entered, the model will set MUMAX = 2.0. RHOQ Algal respiration rate at 20º C (day -1 ). Values for RHOQ should fall in the range If no value for RHOQ is entered, the model will set RHOQ = 0.30.

339 150 SWAT USER'S MANUAL, VERSION 2000 Variable name TFACT Definition Fraction of solar radiation computed in the temperature heat balance that is photosynthetically active. Values for TFACT should fall in the range If no value for TFACT is entered, the model will set TFACT = 0.3. K_L Half-saturation coefficient for light (kj/(m 2 min)). Values for K_L should fall in the range If no value for K_L is entered, the model will set K_L = K_N Michaelis-Menton half-saturation constant for nitrogen (mg N/L). Values for K_N should fall in the range If no value for K_N is entered, the model will set K_N = K_P Michaelis-Menton half-saturation constant for phosphorus (mg P/L). Values for K_P should fall in the range If no value for K_P is entered, the model will set K_P = LAMBDA0 Non-algal portion of the light extinction coefficient (m -1 ). If no value for LAMBDA0 is entered, the model will set LAMBDA0 = 1.0. LAMBDA1 Linear algal self-shading coefficient (m -1 (µg chla/l) -1 ). Values for LAMBDA1 should fall in the range If no value for LAMBDA1 is entered, the model will set LAMBDA1 = LAMBDA2 Nonlinear algal self-shading coefficient (m -1 (µg chla/l) -2/3 ). The recommended value for LAMBDA2 is If no value for LAMBDA2 is entered, the model will set LAMBDA2 = P_N Algal preference factor for ammonia. Values for P_N should fall in the range If no value for P_N is entered, the model will set P_N = 0.5. The watershed water quality file is a free format file. The variables may be placed in any position the user wishes on the line. Values for variables classified as integers should not include a decimal while values for variables classified as reals must contain a decimal. A blank space denotes the end of an input value and the beginning of the next value if there is another on the line. The format of the general water quality input file is:

340 CHAPTER 41: SWAT INPUT WATER QUALITY 151 Variable name Line # Format F90 Format TITLE 1 character a80 LAO 2 integer free IGROPT 3 integer free AI0 4 real free AI1 5 real free AI2 6 real free AI3 7 real free AI4 8 real free AI5 9 real free AI6 10 real free MUMAX 11 real free RHOQ 12 real free TFACT 13 real free K_L 14 real free K_N 15 real free K_P 16 real free LAMBDA0 17 real free LAMBDA1 18 real free LAMBDA2 19 real free P_N 20 real free

341 152 SWAT USER'S MANUAL, VERSION STREAM WATER QUALITY INPUT FILE (.SWQ) The stream water quality input file contains information used by SWAT to set main channel water quality attributes in the subbasins. Following is a brief description of the variables in the stream water quality input file. The variables are listed in the order they appear within the file. Variable name TITLE NUTRIENT TITLE DISOX BOD ALGAE ORGANICN AMMONIAN NITRITEN NITRATEN Definition The first line is reserved for user comments. This line is not processed by the model. The second line is reserved for the nutrient section title. This line is not processed by the model. Initial dissolved oxygen concentration in the reach (mg O 2 /L). If no value for DISOX is entered, the model sets DISOX = 0.0. Initial carbonaceous biochemical oxygen demand in the reach (mg O 2 /L). If no value for BOD is entered, the model sets BOD = 0.0. Initial chlorophyll-a concentration in the reach (mg chla/l). If no value for ALGAE is entered, the model sets ALGAE = 0.0. Initial organic nitrogen concentration in the reach (mg org N-N/L). If no value for ORGANICN is entered, the model sets ORGANICN = 0.0. Initial ammonia concentration in the reach (mg NH 3 -N/L). If no value for AMMONIAN is entered, the model sets AMMONIAN = 0.0. Initial nitrite concentration in the reach (mg NO 2 -N/L). If no value for NITRITEN is entered, the model sets NITRITEN = 0.0. Initial nitrate concentration in the reach (mg NO 3 -N/L). If no value for NITRATEN is entered, the model sets NITRATEN = 0.0.

342 Variable name ORGANICP CHAPTER 41: SWAT INPUT WATER QUALITY 153 Definition Initial organic phosphorus concentration in the reach (mg org P-P/L). If no value for ORGANICP is entered, the model sets ORGANICP = 0.0. DISOLVP Initial dissolved phosphorus concentration in the reach (mg sol P-P/L). If no value for DISOLVP is entered, the model sets DISOLVP = 0.0. RS1 Local algal settling rate in the reach at 20º C (m/day). Values for RS1 should fall in the range 0.15 to If no value for RS1 is entered, the model sets RS1 = 1.0. RS2 Benthic (sediment) source rate for dissolved phosphorus in the reach at 20º C (mg dissolved P/(m 2 day)). If no value for RS2 is entered, the model sets RS2 = RS3 Benthic source rate for NH 4 -N in the reach at 20º C (mg NH 4 -N/(m 2 day)). If no value for RS3 is entered, the model sets RS3 = 0.5. RS4 Rate coefficient for organic N settling in the reach at 20º C (day -1 ). Values for RS4 should fall in the range to If no value for RS4 is entered, the model sets RS4 = RS5 Organic phosphorus settling rate in the reach at 20º C (day -1 ). Values for RS5 should fall in the range to 0.1. If no value for RS5 is entered, the model sets RS5 = RS6 Rate coefficient for settling of arbitrary non-conservative constituent in the reach at 20º C (day -1 ). If no value for RS6 is entered, the model sets RS6 = 2.5. (not currently used by the model) RS7 Benthic source rate for arbitrary non-conservative constituent in the reach at 20º C (mg ANC/(m 2 day)). If no value for RS7 is entered, the model sets RS7 = 2.5. (not currently used by the model) RK1 Carbonaceous biological oxygen demand deoxygenation rate coefficient in the reach at 20º C (day -1 ). Values for RK1 should fall in the range 0.02 to 3.4. If no value for RK1 is entered, the model sets RK1 = RK2 Oxygen reaeration rate in accordance with Fickian diffusion in the reach at 20º C (day -1 ). Values for RK2 should fall in the range 0.0 to If no value for RK2 is entered, the model sets RK2 = 50.0.

343 154 SWAT USER'S MANUAL, VERSION 2000 Variable name RK3 RK4 RK5 RK6 BC1 BC2 BC3 BC4 PESTICIDE TITLE CHPST_CONC CHPST_REA Definition Rate of loss of carbonaceous biological oxygen demand due to settling in the reach at 20º C (day -1 ). Values for RK3 should fall in the range to If no value for RK3 is entered, the model sets RK3 = Benthic oxygen demand rate in the reach at 20º C (mg O 2 /(m 2 day)). If no value for RK4 is entered, the model sets RK4 = 2.0. Coliform die-off rate in the reach at 20º C (day -1 ). Values for RK5 should fall in the range 0.05 to 4.0. If no value for RK5 is entered, the model sets RK5 = 2.0. Decay rate for arbitrary non-conservative constituent in the reach at 20º C (day -1 ). If no value for RK6 is entered, the model sets RK6 = (not currently used by the model) Rate constant for biological oxidation of NH 4 to NO 2 in the reach at 20º C (day -1 ). Values for BC1 should fall in the range 0.1 to 1.0. If no value for BC1 is entered, the model sets BC1 = Rate constant for biological oxidation of NO 2 to NO 3 in the reach at 20º C (day -1 ). Values for BC2 should fall in the range 0.2 to 2.0. If no value for BC2 is entered, the model sets BC2 = 1.1. Rate constant for hydrolysis of organic N to NH 4 in the reach at 20º C (day -1 ). Values for BC3 should fall in the range 0.2 to 0.4. If no value for BC3 is entered, the model sets BC3 = Rate constant for mineralization of organic P to dissolved P in the reach at 20º C (day -1 ). Values for BC4 should fall in the range 0.01 to If no value for BC4 is entered, the model sets BC4 = This line is reserved for the pesticide section title. This line is not processed by the model. Initial pesticide concentration in reach (mg/m 3 H 2 O). (Optional) Pesticide reaction coefficient in reach (day -1 ). If no value for CHPST_REA is entered, the model will set CHPST_REA = (Optional)

344 CHAPTER 41: SWAT INPUT WATER QUALITY 155 Variable name CHPST_VOL CHPST_KOC CHPST_STL CHPST_RSP CHPST_MIX SEDPST_CONC SEDPST_REA SEDPST_BRY SEDPST_ACT Definition Pesticide volatilization coefficient in reach (m/day). If no value for CHPST_VOL is entered, the model will set CHPST_VOL = (Optional) Pesticide partition coefficient between water and air in reach (m 3 /day). If no value for CHPST_KOC is entered, the model will set CHPST_KOC = 0. (Optional) Settling velocity for pesticide sorbed to sediment (m/day). If no value for CHPST_STL is entered, the model will set CHPST_STL = 1.0. (Optional) Resuspension velocity for pesticide sorbed to sediment (m/day). If no value for CHPST_RSP is entered, the model will set CHPST_RSP = (Optional) Mixing velocity (diffusion/dispersion) for pesticide in reach (m/day). If no value for CHPST_MIX is entered, the model will set CHPST_MIX = (Optional) Initial pesticide concentration in reach bed sediment (mg/m 3 sediment). (Optional) Pesticide reaction coefficient in reach bed sediment (day -1 ). If no value for SEDPST_REA is entered, the model will set SEDPST_REA = (Optional) Pesticide burial velocity in reach bed sediment (m/day). If no value for SEDPST_BRY is entered, the model will set SEDPST_BRY = (Optional) Depth of active sediment layer for pesticide (m). If no value for SEDPST_ACT is entered, the model will set SEDPST_ACT = (Optional) The stream water quality file is a free format file. The variables may be placed in any position the user wishes on the line. Values for variables classified as integers should not include a decimal while values for variables classified as reals must contain a decimal. A blank space denotes the end of an input value and the beginning of the next value if there is another on the line. The format of the stream water quality input file is: Variable name Line # Format F90 Format TITLE 1 character a80 NUTRIENT TITLE 2 character a80 DISOX 3 real free

345 156 SWAT USER'S MANUAL, VERSION 2000 Variable name Line # Format F90 Format BOD 4 real free ALGAE 5 real free ORGANICN 6 real free AMMONIAN 7 real free NITRITEN 8 real free NITRATEN 9 real free ORGANICP 10 real free DISOLVP 11 real free RS1 12 real free RS2 13 real free RS3 14 real free RS4 15 real free RS5 16 real free RS6 17 real free RS7 18 real free RK1 19 real free RK2 20 real free RK3 21 real free RK4 22 real free RK5 23 real free RK6 24 real free BC1 25 real free BC2 26 real free BC3 27 real free BC4 28 real free PESTICIDE TITLE 29 character a80 CHPST_CONC 30 real free CHPST_REA 31 real free CHPST_VOL 32 real free CHPST_KOC 33 real free CHPST_STL 34 real free CHPST_RSP 35 real free CHPST_MIX 36 real free SEDPST_CONC 37 real free SEDPST_REA 38 real free

346 CHAPTER 41: SWAT INPUT WATER QUALITY 157 Variable name Line # Format F90 Format SEDPST_BRY 39 real free SEDPST_ACT 40 real free

347 158 SWAT USER'S MANUAL, VERSION LAKE WATER QUALITY INPUT FILE (.LWQ) The lake water quality input file contains information used by SWAT to model nutrient and pesticide water quality in reservoirs. Following is a brief description of the variables in the lake water quality input file. They are listed in the order they appear within the file. Variable name TITLE NUTRIENT TITLE IRES1 IRES2 PSETLR1 PSETLR2 NSETLR1 NSETLR2 CHLAR Definition The first line is reserved for user comments. This line is not processed by the model. The second line is reserved for the nutrient section title. This line is not processed by the model. Beginning month of mid-year nutrient settling period. Optional. Ending month of mid-year nutrient settling period. Optional. Phosphorus settling rate in reservoir for months IRES1 through IRES2 (m/year). Optional. Phosphorus settling rate in reservoir for months other than IRES1-IRES2 (m/year). Optional. Nitrogen settling rate in reservoir for months IRES1 through IRES2 (m/year). Optional. Nitrogen settling rate in reservoir for months other than IRES1-IRES2 (m/year). Optional. Chlorophyll a production coefficient for reservoir. Chlorophyll a concentration in the reservoir is calculated from the total phosphorus concentration. The equation assumes the system is phosphorus limited. The chlorophyll a coefficient was added to the equation to allow the user to adjust results to account for other factors not taken into account by the basic equation such as nitrogen limitations. The default value for CHLA is 1.00, which uses the original equation. Optional.

348 CHAPTER 41: SWAT INPUT WATER QUALITY 159 Variable name SECCIR RES_ORGP RES_SOLP RES_ORGN RES_NO3 RES_NH3 RES_NO2 PESTICIDE TITLE LKPST_CONC LKPST_REA LKPST_VOL LKPST_KOC LKPST_STL LKPST_RSP Definition Water clarity coefficient for the reservoir. The clarity of the reservoir is expressed by the secci-disk depth (m) which is calculated as a function of chlorophyll a. Because suspended sediment also can affect water clarity, the water clarity coefficient has been added to the equation to allow users to adjust for the impact of factors other than chlorophyll a on water clarity. The default value for SECCI is 1.00, which uses the original equation. Optional. Initial concentration of organic P in reservoir (mg P/L). Optional. Initial concentration of soluble P in reservoir (mg P/L). Optional. Initial concentration of organic N in reservoir (mg N/L). Optional. Initial concentration of NO 3 -N in reservoir (mg N/L). Optional. Initial concentration of NH 3 -N in reservoir (mg N/L). Optional. Initial concentration of NO 2 -N in reservoir (mg N/L). Optional. This line is reserved for the pesticide section title. This line is not processed by the model. Initial pesticide concentration in the reservoir water for the pesticide defined by IRTPEST (.bsn). While up to ten pesticides may be applied in a SWAT simulation, only one pesticide (IRTPEST) is routed through the channel network. (mg/m 3 ) Reaction coefficient of the pesticide in reservoir water (day -1 ) Volatilization coefficient of the pesticide from the reservoir water (m/day) Partition coefficient (m 3 /day) Settling velocity of pesticide sorbed to sediment (m/day) Resuspension velocity of pesticide sorbed to sediment (m/day).

349 160 SWAT USER'S MANUAL, VERSION 2000 Variable name LKPST_MIX LKSPST_CONC LKSPST_REA LKSPST_BRY LKSPST_ACT Definition Mixing velocity (m/day) Initial pesticide concentration in the reservoir bottom sediments. (mg/m 3 ) Reaction coefficient of pesticide in reservoir bottom sediment (day -1 ) Burial velocity of pesticide in reservoir bottom sediment (m/day) Depth of active sediment layer in reservoir (m) The lake water quality file is a free format file. The variables may be placed in any position the user wishes on the line. Values for variables classified as integers should not include a decimal while values for variables classified as reals must contain a decimal. A blank space denotes the end of an input value and the beginning of the next value if there is another on the line. The format of the lake water quality input file is: Variable name Line # Format F90 Format TITLE 1 character a80 NUTRIENT TITLE 2 character a80 IRES1 3 integer free IRES2 4 integer free PSETLR1 5 real free PSETLR2 6 real free NSETLR1 7 real free NSETLR2 8 real free CHLAR 9 real free SECCIR 10 real free RES_ORGP 11 real free RES_SOLP 12 real free RES_ORGN 13 real free RES_NO3 14 real free RES_NH3 15 real free RES_NO2 16 real free

350 CHAPTER 41: SWAT INPUT WATER QUALITY 161 Variable name Line # Format F90 Format PESTICIDE TITLE 17 character a80 LKPST_CONC 18 real free LKPST_REA 19 real free LKPST_VOL 20 real free LKPST_KOC 21 real free LKPST_STL 22 real free LKPST_RSP 23 real free LKPST_MIX 24 real free LKSPST_CONC 25 real free LKSPST_REA 26 real free LKSPST_BRY 27 real free LKSPST_ACT 28 real free

351 162 SWAT USER'S MANUAL, VERSION 2000

352 CHAPTER 42 SWAT INPUT DATA: DATABASES SWAT uses five databases to store information required for plant growth, urban land characteristics, tillage, fertilizer components and pesticide properties. These databases are supplied with the model. The following sections summarize the required information needed within the five databases. 157

353 158 SWAT USER'S MANUAL, VERSION LAND COVER/PLANT GROWTH DATABASE FILE (CROP.DAT) Following is a brief description of the variables in the land cover/plant growth database file. They are listed in the order they appear within the file. Variable name ICNUM CPNM IDC DESCRIPTION BIO_E HVSTI Definition Land cover/plant code. The different plants listed in crop.dat must have consecutive values for ICNUM. ICNUM is the numeric code used in the management file to identify the land cover to be modeled. A four character code to represent the land cover/plant name. This code is printed to the output files. Land cover/plant classification: 1 warm season annual legume 2 cold season annual legume 3 perennial legume 4 warm season annual 5 cold season annual 6 perennial 7 trees Full land cover/plant name. This description is not used by the model and is present to assist the user in differentiating between plant species. Radiation-use efficiency ((kg/ha)/(mj/m 2 )). This is the potential (unstressed) growth rate (including roots) per unit of intercepted photosynthetically active radiation. This parameter can greatly change the rate of growth, incidence of stress during the season and the resultant yield. This parameter should be one of the last to be adjusted. Adjustments should be based on research results. Care should be taken to make adjustments based only on data with no drought, nutrient or temperature stress. Harvest index. This is the plant yield divided by the total aboveground biomass ((kg/ha)/(kg/ha)). This plant parameter should be based on experimental data where crop stresses have been minimized to allow the crop to attain its potential. SWAT will adjust the harvest index if water stress occurs near flowering.

354 CHAPTER 42: SWAT INPUT DATABASES 159 Variable name BLAI FRGRW1 LAIMX1 FRGRW2 LAIMX2 DLAI CHTMX RDMX T_OPT T_BASE CNYLD CPYLD BN(1) BN(2) Definition Maximum potential leaf area index. The values for BLAI in the plant growth database are based on average plant densities in dryland (rainfed) agriculture. BLAI may need to be adjusted for drought-prone regions where planting densities are much smaller or irrigated conditions where densities are much greater. Fraction of the plant growing season or fraction of total potential heat units corresponding to the 1 st point on the optimal leaf area development curve. The total potential heat units are the number of heat units required to bring the plant to maturity. Fraction of the maximum leaf area index corresponding to the 1 st point on the optimal leaf area development curve. Fraction of the plant growing season or fraction of total potential heat units corresponding to the 2 nd point on the optimal leaf area development curve.. The total potential heat units are the number of heat units required to bring the plant to maturity. Fraction of the maximum leaf area index corresponding to the 2 nd point on the optimal leaf area development curve. Fraction of growing season when leaf area declines (heat units/heat units). Maximum canopy height (m). Maximum root depth (m). Optimal temperature for plant growth (ºC). Both optimal and base temperatures are very stable for cultivars within a species. Minimum (base) temperature for plant growth (ºC). Normal fraction of nitrogen in yield (kg N/kg yield). This value is estimated on a dry weight basis. Normal fraction of phosphorus in yield (kg P/kg yield). This value is estimated on a dry weight basis. Nitrogen uptake parameter #1: normal fraction of nitrogen in plant biomass at emergence (kg N/kg biomass) Nitrogen uptake parameter #2: normal fraction of nitrogen in plant biomass at 50% maturity (kg N/kg biomass)

355 160 SWAT USER'S MANUAL, VERSION 2000 Variable name BN(3) BP(1) BP(2) BP(3) WSYF USLE_C GSI VPTH WAVP VPD2 CO2HI Definition Nitrogen uptake parameter #3: normal fraction of nitrogen in plant biomass at maturity (kg N/kg biomass) Phosphorus uptake parameter #1: normal fraction of phosphorus in plant biomass at emergence (kg P/kg biomass) Phosphorus uptake parameter #2: normal fraction of phosphorus in plant biomass at 50% maturity (kg P/kg biomass) Phosphorus uptake parameter #3: normal fraction of phosphorus in plant biomass at maturity (kg P/kg biomass) Lower limit of harvest index ((kg/ha)/(kg/ha)). The value between 0.0 and HVSTI which represents the lowest harvest index expected due to water stress. Minimum value of USLE C factor for water erosion applicable to the land cover/plant. Maximum stomatal conductance at high solar radiation and low vapor pressure deficit (m s -1 ). Used in Penman- Monteith evapotranspiration calculations. Threshold vapor pressure deficit (kpa). Leaf conductance is insensitive to vapor pressure deficit until the deficit exceeds the threshold value (usually 0.5 to 1.0 kpa). Rate of decline in radiation use efficiency per unit increase in vapor pressure deficit. The value of WAVP varies among species, but a value of 6 to 8 is suggested as an approximation for most plants. Rate of decline in leaf conductance per unit increase in vapor pressure deficit once the vapor pressure deficit exceeds the threshold value ((m/s) (kpa) -1 ). Elevated CO 2 atmospheric concentration (µl CO 2 /L air) corresponding the 2 nd point on the radiation use efficiency curve. (The 1 st point on the radiation use efficiency curve is comprised of the ambient CO 2 concentration, 330 µl CO 2 /L air, and the biomass-energy ratio reported for BIO_E)

356 CHAPTER 42: SWAT INPUT DATABASES 161 Variable name BIOEHI RSDCO_PL Definition Biomass-energy ratio corresponding to the 2 nd point on the radiation use efficiency curve. (The 1 st point on the radiation use efficiency curve is comprised of the ambient CO 2 concentration, 330 µl CO 2 /L air, and the biomassenergy ratio reported for BIO_E.) Plant residue decomposition coefficient. The fraction of residue that will decompose in a day assuming optimal moisture, temperature, C:N ratio, and C:P ratio. Optional. If no value is entered for RSDCO_PL, it is set equal to the value given for RSDCO in the watershed general attribute (.bsn) file. Four lines are required to store the plant growth parameters for a land cover/plant in the database (crop.dat) file. The plant growth database file is a free format file. The variables may be placed in any position the user wishes on the line. Values for variables classified as integers should not include a decimal while values for variables classified as reals must contain a decimal. A blank space denotes the end of an input value and the beginning of the next value if there is another on the line. Variable name Line # Format F90 Format ICNUM 1 integer free CPNM 1 character a4 IDC 1 integer free BIO_E 2 real free HVSTI 2 real free BLAI 2 real free FRGRW1 2 real free LAIMX1 2 real free FRGRW2 2 real free LAIMX2 2 real free DLAI 2 real free CHTMX 2 real free RDMX 2 real free T_OPT 3 real free T_BASE 3 real free

357 162 SWAT USER'S MANUAL, VERSION 2000 Variable name Line # Format F90 Format CNYLD 3 real free CPYLD 3 real free BN(1) 3 real free BN(2) 3 real free BN(3) 3 real free BP(1) 3 real free BP(2) 3 real free BP(3) 3 real free WSYF 4 real free USLE_C 4 real free GSI 4 real free VPTH 4 real free WAVP 4 real free VPD2 4 real free CO2HI 4 real free BIOEHI 4 real free RSDCO_PL 4 real free

358 CHAPTER 42: SWAT INPUT DATABASES TILLAGE DATABASE FILE (TILL.DAT) Following is a brief description of the variables in the tillage database file. They are listed in the order they appear within the file. Variable name ITNUM TILLNM EFFMIX DEPTIL Definition Tillage number. The different tillage operations in till.dat must have consecutive values for ITNUM. ITNUM is the numeric code used in the management file to identify the tillage practice to be modeled. An eight character code representing the tillage operation name. Mixing efficiency of tillage operation. The mixing efficiency specifies the fraction of materials (residue and nutrients) on the soil surface which are mixed uniformly throughout the soil depth mixed by the implement. The remaining fraction of residue and nutrients is left on the soil surface. Depth of mixing caused by the tillage operation (mm). The format of the tillage database file is: Variable name Line # Position Format F90 Format ITNUM ALL space digit integer i4 TILLNM ALL space 9-16 character a8 EFFMIX ALL space decimal(xxxx.xxx) f8.3 DEPTIL ALL space decimal(xxxx.xxx) f8.3

359 164 SWAT USER'S MANUAL, VERSION PESTICIDE/TOXIN DATABASE FILE (PEST.DAT) Following is a brief description of the variables in the pesticide/toxin database file. They are listed in the order they appear within the file. Variable name IPNUM PNAME SKOC WOF HLIFE_F HLIFE_S AP_EF WSOL Definition Pesticide/toxin number. The different toxins in pest.dat must have consecutive values for IPNUM. IPNUM is the numeric code used in the management file to identify the pesticide/toxin to be applied. Name of pesticide/toxin. (up to 17 characters allowed) Soil adsorption coefficient normalized for soil organic carbon content (mg/kg)/(mg/l). K oc is equal to the soil adsorption coefficient, K p, divided by the fraction of organic carbon in the soil. K p is calculated by dividing C solid phase by C solution where C solid phase is the concentration of the chemical sorbed to the solid phase (expressed as mg chemical/kg solid material) and C solution is the concentration of the chemical in the solution (expressed as mg chemical/l solution). K oc and K p have the same units. Wash-off fraction. Fraction of pesticide on foliage available for wash off by rainfall ( ). The pesticide is deposited on the soil surface. Degradation half-life of the chemical on the foliage (days). Degradation half-life of the chemical in the soil (days). Application efficiency. The fraction of pesticide applied which is deposited on the foliage and soil surface ( ). The remainder is lost. Solubility of the chemical in water (mg/l or ppm)

360 CHAPTER 42: SWAT INPUT DATABASES 165 Variable name HENRY Definition Henry's Law Constant (K H ) for the chemical (unitless). Henry's Law Constant characterizes the partitioning of the chemical between the air and water. Values for Henry's Law are reported in several different units and care must be taken when obtaining values to make sure they are in the correct units. For calculations in SWAT, K H is defined as C gas /C solution where C gas is the concentration of the chemical in the gas phase (mg/l) and C solution is defined as the concentration of the chemical in solution. (not currently operational) The format of the pesticide/toxin database file is: Variable name Line # Position Format F90 Format IPNUM ALL space 1-3 integer i3 PNAME ALL space 4-20 character a17 SKOC ALL space decimal(xxxxxxxx.x) f10.1 WOF ALL space decimal(xx.xx) f5.2 HLIFE_F ALL space decimal(xxxxxx.x) f8.1 HLIFE_S ALL space decimal(xxxxxx.x) f8.1 AP_EF ALL space decimal(xx.xx) f5.2 WSOL ALL space decimal(xxxxxxx.xxx) f11.3 HENRY ALL space exponential(x.xxxxexxx) e12.4

361 166 SWAT USER'S MANUAL, VERSION FERTILIZER DATABASE FILE (FERT.DAT) Following is a brief description of the variables in the fertilizer database file. They are listed in the order they appear within the file. Variable name IFNUM FERTNM FMINN FMINP FORGN FORGP FNH3N Definition Number of fertilizer in database. This number should be equivalent to the line number and is the reference number used in the management file to identify the fertilizer type being applied. Name of fertilizer/manure (up to 8 characters allowed). Fraction of mineral N (NO 3 and NH 4 ) in fertilizer (kg min-n/kg fertilizer). Value should be between 0.0 and 1.0. Fraction of mineral P in fertilizer (kg min-p/kg fertilizer). Value should be between 0.0 and 1.0. Fraction of organic N in fertilizer (kg org-n/kg fertilizer). Value should be between 0.0 and 1.0. Fraction of organic P in fertilizer (kg org-p/kg fertilizer). Value should be between 0.0 and 1.0. Fraction of mineral N in fertilizer applied as ammonia (kg NH 3 -N/kg min-n). Value should be between 0.0 and 1.0. BACTPDB Concentration of persistent bacteria in manure/fertilizer (# bacteria/kg manure). Optional. BACTLPDB Concentration of less-persistent bacteria in manure/fertilizer (# bacteria/kg manure). Optional. BACTKDDB Bacteria partition coefficient. Value should be between 0.0 and 1.0. When the bacteria partition coefficient is 0.0, all bacteria are sorbed to soil particles. When the bacteria partition coefficient is 1.0 all bacteria is in solution. Optional.

362 The format of the fertilizer database file is: CHAPTER 42: SWAT INPUT DATABASES 167 Variable name Line # Position Format F90 Format IFNUM ALL space 1-4 integer i4 FERTNM ALL space 6-13 character a8 FMINN ALL space decimal(xxxx.xxx) f8.3 FMINP ALL space decimal(xxxx.xxx) f8.3 FORGN ALL space decimal(xxxx.xxx) f8.3 FORGP ALL space decimal(xxxx.xxx) f8.3 FNH3N ALL space decimal(xxxx.xxx) f8.3 BACTPDB ALL space decimal(xxxx.xxx) f8.3 BACTLPDB ALL space decimal(xxxx.xxx) f8.3 BACTKDDB ALL space decimal(xxxx.xxx) f8.3

363 168 SWAT USER'S MANUAL, VERSION URBAN DATABASE FILE (URBAN.DAT) Following is a brief description of the variables in the urban database file. They are listed in the order they appear within the file. Variable name IUNUM Definition Number of urban land type. This value should be equivalent to the line number. URBNAME 4-character code for urban land type. URBFLNM Full description for urban land type may take up to 54 characters. (not used by SWAT) FIMP Fraction total impervious area in urban land type. This includes directly and indirectly connected impervious areas. FCIMP Fraction directly connected impervious area in urban land type. CURBDEN Curb length density in urban land type (km/ha). URBCOEF Wash-off coefficient for removal of constituents from impervious area (mm -1 ) DIRTMX Maximum amount of solids allowed to build up on impervious areas (kg/curb km). THALF Number of days for amount of solids on impervious areas to build up from 0 kg/curb km to half the maximum allowed, i.e. 1/2 DIRTMX (days). TNCONC Concentration of total nitrogen in suspended solid load from impervious areas (mg N/kg sed). TPCONC Concentration of total phosphorus in suspended solid load from impervious areas (mg P/kg sed). TNO3CONC Concentration of nitrate in suspended solid load from impervious areas (mg NO 3 -N/kg sed).

364 CHAPTER 42: SWAT INPUT DATABASES 169 Every urban land type uses two lines in the urban.dat file to store input values. The format of every set of two lines is described below. Variable name Line # Position Format F90 Format IUNUM 1 space 1-3 integer i3 URBNAME 1 space 5-8 character a4 URBFLNM 1 space character a54 FIMP 1 space decimal(xxxx.xxx) f8.3 FCIMP 1 space decimal(xxxx.xxx) f8.3 CURBDEN 2 space 5-12 decimal(xxxx.xxx) f8.3 URBCOEF 2 space decimal(xxxx.xxx) f8.3 DIRTMX 2 space decimal(xxxx.xxx) f8.3 THALF 2 space decimal(xxxx.xxx) f8.3 TNCONC 2 space decimal(xxxx.xxx) f8.3 TPCONC 2 space decimal(xxxx.xxx) f8.3 TNO3CONC 2 space decimal(xxxx.xxx) f8.3

365 170 SWAT USER'S MANUAL, VERSION 2000

366 CHAPTER 43 SWAT INPUT DATA: MEASURED Four different file formats may be used to store stream loading data that is incorporated directly into the watershed routing. This stream loading data may come from a point source, such as a town's sewage treatment discharge, or it may be output from simulation of an upstream area. The four different file formats allow the user to summarize the data in one of four ways: daily, monthly, yearly, or average annual. 167

367 168 SWAT USER'S MANUAL, VERSION DAILY RECORDS (RECDAY.DAT FILE) The recday command in the watershed configuration (.fig) file requires a file containing SWAT input data summarized on a daily time step. An unlimited number of files with daily flow data are allowed in the simulation. The file numbers assigned to the recday files in the watershed configuration file (.fig) must be 1 and numbered sequentially. Following is a brief description of the variables in the recday input file. They are listed in the order they appear within the file. Variable name TITLE Definition The first six lines of the file are reserved for user comments. The comments may take up to 80 spaces per line. DAY Julian date for record (optional). If the julian date and year are provided for the records, SWAT will search for the beginning day of simulation in the record. If the julian date and year are left blank, SWAT assumes that the first line of record corresponds to the first day of simulation. (SWAT uses the date and year to locate the record corresponding to the first day of simulation. From that point on, the day and year are ignored.) YEAR Four-digit year for record (optional). See description of DAY for more information. FLODAY Contribution to streamflow for the day (m 3 ) SEDDAY Sediment loading to reach for the day (metric tons) ORGNDAY Organic N loading to reach for the day (kg N) ORGPDAY Organic P loading to reach for the day (kg P) NO3DAY NO 3 loading to reach for the day (kg N) MINPDAY Mineral P loading to reach for the day (kg P) NH3DAY NH 3 loading to reach for the day (kg N) NO2DAY NO 2 loading to reach for the day (kg N) CMTL1DAY Loading of conservative metal #1 to reach for the day (kg) Please keep in mind that FORTRAN limits the total number of files that can be open at one time to something in the neighborhood of 250. The input files containing daily data (.pcp,.tmp, and recday) remain open throughout the simulation.

368 CHAPTER 43: SWAT INPUT MEASURED 169 Variable name Definition CMTL2DAY Loading of conservative metal #2 to reach for the day (kg) CMTL3DAY Loading of conservative metal #3 to reach for the day (kg) BACTPDAY Loading of persistent bacteria to reach for the day (# bact) BACTLPDAY Loading of less persistent bacteria to reach for the day (# bact) One line of data is required for every day of the simulation period. The recday data file is a free format file. The variables may be placed in any position the user wishes on the line. Values for variables classified as integers should not include a decimal while values for variables classified as reals must contain a decimal. A blank space denotes the end of an input value and the beginning of the next value if there is another on the line. The format of the recday data file is: Variable name Line # Format F90 Format TITLE 1-6 character a80 DAY 7-END integer free YEAR 7-END integer free FLODAY 7-END real or exponential free SEDDAY 7-END real or exponential free ORGNDAY 7-END real or exponential free ORGPDAY 7-END real or exponential free NO3DAY 7-END real or exponential free MINPDAY 7-END real or exponential free NH3DAY 7-END real or exponential free NO2DAY 7-END real or exponential free CMTL1DAY 7-END real or exponential free CMTL2DAY 7-END real or exponential free CMTL3DAY 7-END real or exponential free BACTPDAY 7-END real or exponential free BACTLPDAY 7-END real or exponential free

369 170 SWAT USER'S MANUAL, VERSION MONTHLY RECORDS (RECMON.DAT FILE) The recmon command in the watershed configuration (.fig) file requires a file containing input data summarized on a monthly time step. SWAT will accept an unlimited number of data files with monthly flow data. The file numbers assigned to the files in the watershed configuration file (.fig) must be numbered sequentially and begin at 1. Following is a brief description of the variables in the recmon data file. They are listed in the order they appear within the file. Variable name TITLE MONTH YEAR FLOMON SEDMON ORGNMON ORGPMON NO3MON MINPMON Definition The first 6 lines of the data file is reserved for user comments. The comments may take up to 80 spaces. Month of measured data. This variable is provided for the user it is ignored by SWAT. The model assumes the first line of measured data in the file contains data for January of the first year of simulation. The monthly data file must contain a line of data for every month of simulation in consecutive order. 4-digit year of measured data. This variable is provided for the user it is ignored by SWAT. The model assumes the first line of measured data in the file contains data for January of the first year of simulation. The monthly data file must contain a line of data for every month of simulation in consecutive order. Average daily water loading for month (m 3 /day). Average daily sediment loading for month (metric tons/day). Average daily organic nitrogen loading for month (kg N/day). Average daily organic phosphorus loading for month (kg P/day). Average daily nitrate loading for month (kg N/day). Average daily mineral (soluble) P loading for month (kg P/day).

370 Variable name NH3MON NO2MON CMTL1MON CMTL2MON CMTL3MON CHAPTER 43: SWAT INPUT MEASURED 171 Definition Average daily ammonia loading for month (kg N/day). Average daily nitrite loading for month (kg N/day). Average daily loading of conservative metal #1 for month (kg/day). Average daily loading of conservative metal #2 for month (kg/day). Average daily loading of conservative metal #3 for month (kg /day). BACTPMON Average daily loading of persistent bacteria for month (# bact/day). BACTLPMON Average daily loading of less persistent bacteria for month (# bact/day). The file must contain one line of data for every month of simulation (Even if the simulation begins in a month other than January, the file must contain lines for every month of the first year.) The recmon data file is a free format file. The variables may be placed in any position the user wishes on the line. Values for variables classified as integers should not include a decimal while values for variables classified as reals must contain a decimal. A blank space denotes the end of an input value and the beginning of the next value if there is another on the line. The format of the recmon data file is: Variable name Line # Format F90 Format TITLE 1-6 character a80 MONTH 7 - END integer free YEAR 7 - END integer free FLOMON 7 - END real or exponential free SEDMON 7 - END real or exponential free ORGNMON 7 - END real or exponential free ORGPMON 7 - END real or exponential free NO3MON 7 - END real or exponential free MINPMON 7 - END real or exponential free NH3MON 7 - END real or exponential free NO2MON 7 - END real or exponential free CMTL1MON 7 - END real or exponential free CMTL2MON 7 - END real or exponential free CMTL3MON 7 - END real or exponential free

371 172 SWAT USER'S MANUAL, VERSION 2000 Variable name Line # Format F90 Format BACTPMON 7 - END real or exponential free BACTLPMON 7 - END real or exponential free 43.3 YEARLY RECORDS (RECYEAR.DAT FILE) The recyear command in the watershed configuration (.fig) file requires a file containing SWAT input data summarized on an annual time step. SWAT will accept an unlimited number of data files with yearly flow data. The file numbers assigned to the recyear files in the watershed configuration file (.fig) must be numbered sequentially and begin at 1. Following is a brief description of the variables in the recyear data file. They are listed in the order they appear within the file. Variable name TITLE YEAR FLOYR SEDYR ORGNYR ORGPYR NO3YR Definition The first six lines of the data file are reserved for user comments. The comments may take up to 80 spaces per line. 4-digit year of measured data. This variable is provided for the user it is ignored by SWAT. The model assumes the first line of measured data in the file contains data for the first year of simulation. The yearly data file must contain a line of data for every year of simulation in consecutive order. Average daily water loading for year (m 3 /day). Average daily sediment loading for year (metric tons/day). Average daily organic nitrogen loading for year (kg N/day). Average daily organic phosphorus loading for year (kg P/day). Average daily nitrate loading for year (kg N/day).

372 Variable name MINPYR NH3YR NO2YR CMTL1YR CMTL2YR CMTL3YR CHAPTER 43: SWAT INPUT MEASURED 173 Definition Average daily mineral (soluble) P loading for year (kg P/day). Average daily ammonia loading for year (kg N/day). Average daily nitrite loading for year (kg N/day). Average daily loading of conservative metal #1 for year (kg/day). Average daily loading of conservative metal #2 for year (kg/day). Average daily loading of conservative metal #3 for year (kg/day). BACTPYR Average daily loading of persistent bacteria for year (# bact/day). BACTLPYR Average daily loading of less persistent bacteria for year (# bact/day). The recyear data file is a free format file. The variables may be placed in any position the user wishes on the line. Values for variables classified as integers should not include a decimal while values for variables classified as reals must contain a decimal. A blank space denotes the end of an input value and the beginning of the next value if there is another on the line.the format of the recyear data file is: Variable name Line # Format F90 Format TITLE 1-6 character a80 YEAR 7 - END integer free FLOYR 7 - END real or exponential free SEDYR 7 - END real or exponential free ORGNYR 7 - END real or exponential free ORGPYR 7 - END real or exponential free NO3YR 7 - END real or exponential free MINPYR 7 - END real or exponential free NH3YR 7 - END real or exponential free NO2YR 7 - END real or exponential free CMTL1YR 7 - END real or exponential free CMTL2YR 7 - END real or exponential free CMTL3YR 7 - END real or exponential free

373 174 SWAT USER'S MANUAL, VERSION 2000 Variable name Line # Format F90 Format BACTPYR 7 - END real or exponential free BACTLPYR 7 - END real or exponential free 43.4 AVERAGE ANNUAL RECORDS (RECCNST.DAT FILE) The reccnst command in the watershed configuration (.fig) file requires a file containing average annual SWAT input data. SWAT will accept an unlimited number of data files with average annual flow data. The file numbers assigned to the reccnst files in the watershed configuration file (.fig) must be numbered sequentially and begin at 1. Following is a brief description of the variables in the reccnst data file. They are listed in the order they appear within the file. Variable name TITLE FLOCNST SEDCNST ORGNCNST ORGPCNST NO3CNST MINPCNST NH3CNST NO2CNST CMTL1CNST CMTL2CNST CMTL3CNST BACTPCNST Definition The first six lines of the data file are reserved for user comments. The comments may take up to 80 spaces on each line. Average daily water loading (m 3 /day) Average daily sediment loading (metric tons/day) Average daily organic N loading (kg N/day) Average daily organic P loading (kg P/day) Average daily NO 3 loading (kg N/day) Average daily mineral P loading (kg P/day) Average daily NH 3 loading (kg N/day) Average daily NO 2 loading (kg N/day) Average daily loading of conservative metal #1 (kg/day) Average daily loading of conservative metal #2 (kg/day) Average daily loading of conservative metal #3 (kg/day) Average daily loading of persistent bacteria (# bact/day) BACTLPCNST Average daily loading of less persistent bacteria (# bact/day)

374 The format of the reccnst data file is: CHAPTER 43: SWAT INPUT MEASURED 175 Variable name Line # Format F90 Format TITLE 1-6 character a80 FLOCNST 7 real or exponential free SEDCNST 7 real or exponential free ORGNCNST 7 real or exponential free ORGPCNST 7 real or exponential free NO3CNST 7 real or exponential free MINPCNST 7 real or exponential free NH3CNST 7 real or exponential free NO2CNST 7 real or exponential free CMTL1CNST 7 real or exponential free CMTL2CNST 7 real or exponential free CMTL3CNST 7 real or exponential free BACTPCNST 7 real or exponential free BACTLPCNST 7 real or exponential free

375 176 SWAT USER'S MANUAL, VERSION 2000

376 CHAPTER 44 SWAT OUTPUT DATA: PRIMARY OUTPUT FILES A number of output files are generated in every SWAT simulation. These files are: the summary output file (output.std), the HRU output file (.sbs), the subbasin output file (.bsb), and the main channel or reach output file (.rch). The detail of the data printed out in each file is controlled by the print codes in the input control code (.cod) file. Average daily values are always printed in the HRU, subbasin and reach files, but the time period they are summarized over will vary. Depending on the print code selected, the output files may include all daily values, daily amounts averaged over the month, daily amounts averaged over the year, or daily amounts averaged over the entire simulation period. 173

377 174 SWAT USER'S MANUAL, VERSION INPUT SUMMARY FILE (INPUT.STD) The input summary file prints summary tables of important input values. This file provides the user with a mechanism to spot-check input values. All model inputs are not printed, but the file does contain some of the most important OUTPUT SUMMARY FILE (OUTPUT.STD) The output summary file provides watershed average loadings from the HRUs to the streams. Tables are also included that present average annual HRU and subbasin values for a few parameters.

378 44.3 HRU OUTPUT FILE (.SBS) CHAPTER 44: SWAT OUTPUT PRIMARY FILES 175 The HRU output file contains summary information for each of the hydrologic response units in the watershed. The file is written in spreadsheet format. Following is a brief description of the output variables in the HRU output file. Variable name LULC Definition Four letter character code for the cover/plant on the HRU. (code from crop.dat file) HRU Hydrologic response unit number GIS GIS code reprinted from watershed configuration file (.fig). See explanation of subbasin command. SUB Topographically-defined subbasin to which the HRU belongs. MGT Management number. This is pulled from the management (.mgt) file. Used by the SWAT/GRASS interface to allow development of output maps by landuse/management type. MON Daily time step: the julian date Monthly time step: the month (1-12) Annual time step: four-digit year Average annual summary lines: total number of years averaged together AREA Drainage area of the HRU (km 2 ). PRECIP Total amount of precipitation falling on the HRU during time step (mm H 2 O). SNOFALL Amount of precipitation falling as snow, sleet or freezing rain during time step (water-equivalent mm H 2 O). SNOMELT Amount of snow or ice melting during time step (waterequivalent mm H 2 O). IRR Irrigation (mm H 2 O). Amount of irrigation water applied to HRU during the time step. PET Potential evapotranspiration (mm H 2 O). Potential evapotranspiration from the HRU during the time step.

379 176 SWAT USER'S MANUAL, VERSION 2000 Variable name ET SW PERC GW_RCHG DA_RCHG REVAP SA_IRR DA_IRR SA_ST DA_ST SURQ TLOSS LATQ Definition Actual evapotranspiration (soil evaporation and plant transpiration) from the HRU during the time step (mm H 2 O). Soil water content (mm H 2 O). Amount of water in the soil profile at the end of the time period. Water that percolates past the root zone during the time step (mm H 2 O). There is usually a lag between the time the water leaves the bottom of the root zone and reaches the shallow aquifer. Over a long period of time, this variable should equal groundwater recharge (PERC = GW_RCHG as time ). Recharge entering aquifers during time step (total amount of water entering shallow and deep aquifers during time step) (mm H 2 O). Deep aquifer recharge (mm H 2 O). The amount of water from the root zone that recharges the deep aquifer during the time step. (shallow aquifer recharge = GW_RCHG - DA_RCHG) Water in the shallow aquifer returning to the root zone in response to a moisture deficit during the time step (mm H 2 O). The variable also includes water uptake directly from the shallow aquifer by deep tree and shrub roots. Irrigation from shallow aquifer (mm H 2 O). Amount of water removed from the shallow aquifer for irrigation during the time step. Irrigation from deep aquifer (mm H 2 O). Amount of water removed from the deep aquifer for irrigation during the time step. Shallow aquifer storage (mm H 2 O). Amount of water in the shallow aquifer at the end of the time period. Deep aquifer storage (mm H 2 O). Amount of water in the deep aquifer at the end of the time period. Surface runoff contribution to streamflow in the main channel during time step (mm H 2 O). Transmission losses (mm H 2 O). Water lost from tributary channels in the HRU via transmission through the bed. This water becomes recharge for the shallow aquifer during the time step. Net surface runoff contribution to the main channel streamflow is calculated by subtracting TLOSS from SURQ. Lateral flow contribution to streamflow (mm H 2 O). Water flowing laterally within the soil profile that enters the main channel during time step.

380 CHAPTER 44: SWAT OUTPUT PRIMARY FILES 177 Variable name GW_Q WYLD SYLD USLE N_APP P_APP NAUTO PAUTO NGRZ PGRZ NRAIN NFIX Definition Groundwater contribution to streamflow (mm H 2 O). Water from the shallow aquifer that enters the main channel during the time step. Groundwater flow is also referred to as baseflow. Water yield (mm H 2 O). Total amount of water leaving the HRU and entering main channel during the time step. (WYLD = SURQ + LATQ + GWQ TLOSS pond abstractions) Sediment yield (metric tons/ha). Sediment from the HRU that is transported into the main channel during the time step. Soil loss during the time step calculated with the USLE equation (metric tons/ha). This value is reported for comparison purposes only. Nitrogen fertilizer applied (kg N/ha). Total amount of nitrogen (mineral and organic) applied in fertilizer during the time step. Phosphorus fertilizer applied (kg P/ha). Total amount of phosphorus (mineral and organic) applied in fertilizer during the time step. Nitrogen fertilizer auto-applied (kg N/ha). Total amount of nitrogen (mineral and organic) auto-applied during the time step. Phosphorus fertilizer auto-applied (kg P/ha). Total amount of phosphorus (mineral and organic) auto-applied during the time step. Nitrogen applied during grazing operation (kg N/ha). Total amount of nitrogen (mineral and organic) added to soil by grazing operation during the time step. Phosphorus applied during grazing operation (kg P/ha). Total amount of phosphorus (mineral and organic) added to soil by grazing operation during the time step. Nitrate added to soil profile by rain (kg N/ha). Nitrogen fixation (kg N/ha). Amount of nitrogen fixed by legumes during the time step.

381 178 SWAT USER'S MANUAL, VERSION 2000 Variable name F-MN A-MN A-SN F-MP AO-LP L-AP A-SP Definition Fresh organic to mineral N (kg N/ha). Mineralization of nitrogen from the fresh residue pool to the nitrate (80%) pool and active organic nitrogen (20%) pool during the time step. A positive value denotes a net gain in the nitrate and active organic pools from the fresh organic pool while a negative value denotes a net gain in the fresh organic pool from the nitrate and active organic pools. Active organic to mineral N (kg N/ha). Movement of nitrogen from the active organic pool to the nitrate pool during the time step. Active organic to stable organic N (kg N/ha). Movement of nitrogen from the active organic pool to the stable organic pool during the time step. Fresh organic to mineral P (kg P/ha). Mineralization of phosphorus from the fresh residue pool to the "active" mineral (80%) pool (P sorbed to soil surface) and the active organic (20%) pool. A positive value denotes a net gain in the active mineral and active organic pools from the fresh organic pool while a negative value denotes a net gain in the fresh organic pool from the active mineral and active organic pools. Organic to labile mineral P (kg P/ha). Movement of phosphorus between the organic pool and the labile mineral pool during the time step. A positive value denotes a net gain in the labile pool from the organic pool while a negative value denotes a net gain in the organic pool from the labile pool. Labile to active mineral P (kg P/ha). Movement or transformation of phosphorus between the "labile" mineral pool (P in solution) and the "active" mineral pool (P sorbed to the surface of soil particles) during the time step. A positive value denotes a net gain in the active pool from the labile pool while a negative value denotes a net gain in the labile pool from the active pool. Active to stable P (kg P/ha). Movement or transformation of phosphorus between the "active" mineral pool (P sorbed to the surface of soil particles) and the "stable" mineral pool (P fixed in soil) during the time step. A positive value denotes a net gain in the stable pool from the active pool while a negative value denotes a net gain in the active pool from the stable pool.

382 CHAPTER 44: SWAT OUTPUT PRIMARY FILES 179 Variable name DNIT NUP PUP ORGN ORGP SEDP NSURQ NLATQ NO3L NO3GW SOLP P_GW W_STRS TMP_STRS N_STRS P_STRS BIOM LAI Definition Denitrification (kg N/ha). Transformation of nitrate to gaseous compounds during the time step. Plant uptake of nitrogen (kg N/ha). Nitrogen removed from soil by plants during the time step. Plant uptake of phosphorus (kg P/ha). Phosphorus removed from soil by plants during the time step. Organic N yield (kg N/ha). Organic nitrogen transported out of the HRU and into the reach during the time step. Organic P yield (kg P/ha). Organic phosphorus transported with sediment into the reach during the time step. Sediment P yield (kg P/ha). Mineral phosphorus sorbed to sediment transported into the reach during the time step. NO 3 in surface runoff (kg N/ha). Nitrate transported with surface runoff into the reach during the time step. NO 3 in lateral flow (kg N/ha). Nitrate transported by lateral flow into the reach during the time step. NO 3 leached from the soil profile (kg N/ha). Nitrate that leaches past the bottom of the soil profile during the time step. The nitrate is not tracked through the shallow aquifer. NO 3 transported into main channel in the groundwater loading from the HRU (kg N/ha). Soluble P yield (kg P/ha). Soluble mineral forms of phosphorus transported by surface runoff into the reach during the time step. Soluble phosphorus transported by groundwater flow into main channel during the time step (kg P/ha). Water stress days during the time step (days). Temperature stress days during the time step (days). Nitrogen stress days during the time step (days). Phosphorus stress days during the time step (days). Biomass (metric tons/ha). Total biomass, i.e. aboveground and roots at the end of the time period reported as dry weight. Leaf area index at the end of the time period.

383 180 SWAT USER'S MANUAL, VERSION 2000 Variable name YLD BACTP BACTLP Definition Harvested yield (metric tons/ha). The model partitions yield from the total biomass on a daily basis (and reports it). However, the actual yield is not known until it is harvested. The harvested yield is reported as dry weight. Number of persistent bacteria in surface runoff entering reach (count). Number of less persistent bacteria in surface runoff entering reach (count). The file format for the HRU output file (.sbs) is: Variable name Line # Position Format F90 Format LULC All space 1-4 character a4 HRU All space digit integer i4 GIS All space digit integer i8 SUB All space digit integer i4 MGT All space digit integer i4 MON All space digit integer i4 AREA All space decimal(xxxxxx.xxx) f10.3 PRECIP All space decimal(xxxxxx.xxx) f10.3 SNOFALL All space decimal(xxxxxx.xxx) f10.3 SNOMELT All space decimal(xxxxxx.xxx) f10.3 IRR All space decimal(xxxxxx.xxx) f10.3 PET All space decimal(xxxxxx.xxx) f10.3 ET All space decimal(xxxxxx.xxx) f10.3 SW All space decimal(xxxxxx.xxx) f10.3 PERC All space decimal(xxxxxx.xxx) f10.3 GW_RCHG All space decimal(xxxxxx.xxx) f10.3 DA_RCHG All space decimal(xxxxxx.xxx) f10.3 REVAP All space decimal(xxxxxx.xxx) f10.3 SA_IRR All space decimal(xxxxxx.xxx) f10.3 DA_IRR All space decimal(xxxxxx.xxx) f10.3 SA_ST All space decimal(xxxxxx.xxx) f10.3 DA_ST All space decimal(xxxxxx.xxx) f10.3 SURQ All space decimal(xxxxxx.xxx) f10.3

384 CHAPTER 44: SWAT OUTPUT PRIMARY FILES 181 Variable name Line # Position Format F90 Format TLOSS All space decimal(xxxxxx.xxx) f10.3 LATQ All space decimal(xxxxxx.xxx) f10.3 GW_Q All space decimal(xxxxxx.xxx) f10.3 WYLD All space decimal(xxxxxx.xxx) f10.3 SYLD All space decimal(xxxxxx.xxx) f10.3 USLE All space decimal(xxxxxx.xxx) f10.3 N_APP All space decimal(xxxxxx.xxx) f10.3 P_APP All space decimal(xxxxxx.xxx) f10.3 NAUTO All space decimal(xxxxxx.xxx) f10.3 PAUTO All space decimal(xxxxxx.xxx) f10.3 NGRZ All space decimal(xxxxxx.xxx) f10.3 PGRZ All space decimal(xxxxxx.xxx) f10.3 NRAIN All space decimal(xxxxxx.xxx) f10.3 NFIX All space decimal(xxxxxx.xxx) f10.3 F-MN All space decimal(xxxxxx.xxx) f10.3 A-MN All space decimal(xxxxxx.xxx) f10.3 A-SN All space decimal(xxxxxx.xxx) f10.3 F-MP All space decimal(xxxxxx.xxx) f10.3 AO-LP All space decimal(xxxxxx.xxx) f10.3 L-AP All space decimal(xxxxxx.xxx) f10.3 A-SP All space decimal(xxxxxx.xxx) f10.3 DNIT All space decimal(xxxxxx.xxx) f10.3 NUP All space decimal(xxxxxx.xxx) f10.3 PUP All space decimal(xxxxxx.xxx) f10.3 ORGN All space decimal(xxxxxx.xxx) f10.3 ORGP All space decimal(xxxxxx.xxx) f10.3 SEDP All space decimal(xxxxxx.xxx) f10.3 NSURQ All space decimal(xxxxxx.xxx) f10.3 NLATQ All space decimal(xxxxxx.xxx) f10.3 NO3L All space decimal(xxxxxx.xxx) f10.3 NO3GW All space decimal(xxxxxx.xxx) f10.3 SOLP All space decimal(xxxxxx.xxx) f10.3 P_GW All space decimal(xxxxxx.xxx) f10.3 W_STRS All space decimal(xxxxxx.xxx) f10.3 TMP_STRS All space decimal(xxxxxx.xxx) f10.3

385 182 SWAT USER'S MANUAL, VERSION 2000 Variable name Line # Position Format F90 Format N_STRS All space decimal(xxxxxx.xxx) f10.3 P_STRS All space decimal(xxxxxx.xxx) f10.3 BIOM All space decimal(xxxxxx.xxx) f10.3 LAI All space decimal(xxxxxx.xxx) f10.3 YLD All space decimal(xxxxxx.xxx) f10.3 BACTP All space decimal(xxxxxx.xxx) f10.3 BACTLP All space decimal(xxxxxx.xxx) f10.3

386 CHAPTER 44: SWAT OUTPUT PRIMARY FILES SUBBASIN OUTPUT FILE (.BSB) The subbasin output file contains summary information for each of the subbasins in the watershed. The reported values for the different variables are the total amount or weighted average of all HRUs within the subbasin. The subbasin output file is written in spreadsheet format. Following is a brief description of the output variables in the subbasin output file. Variable name Definition SUB Subbasin number. GIS GIS code reprinted from watershed configuration file (.fig). See explanation of subbasin command. MON Daily time step: julian date Monthly time step: the month (1-12) Annual time step: four-digit year Average annual summary lines: total number of years averaged together AREA Area of the subbasin (km 2 ). PRECIP Total amount of precipitation falling on the subbasin during time step (mm H 2 O). SNOMELT Amount of snow or ice melting during time step (waterequivalent mm H 2 O). PET Potential evapotranspiration from the subbasin during the time step (mm H 2 O). ET Actual evapotranspiration from the subbasin during the time step (mm). SW Soil water content (mm). Amount of water in the soil profile at the end of the time period.

387 184 SWAT USER'S MANUAL, VERSION 2000 Variable name PERC SURQ GW_Q WYLD SYLD ORGN ORGP NSURQ SOLP SEDP Definition Water that percolates past the root zone during the time step (mm). There is potentially a lag between the time the water leaves the bottom of the root zone and reaches the shallow aquifer. Over a long period of time, this variable should equal groundwater percolation. Surface runoff contribution to streamflow during time step (mm H 2 O). Groundwater contribution to streamflow (mm). Water from the shallow aquifer that returns to the reach during the time step. Water yield (mm H 2 O). The net amount of water that leaves the subbasin and contributes to streamflow in the reach during the time step. (WYLD = SURQ + LATQ + GWQ TLOSS pond abstractions) Sediment yield (metric tons/ha). Sediment from the subbasin that is transported into the reach during the time step. Organic N yield (kg N/ha). Organic nitrogen transported out of the subbasin and into the reach during the time step. Organic P yield (kg P/ha). Organic phosphorus transported with sediment into the reach during the time step. NO 3 in surface runoff (kg N/ha). Nitrate transported by the surface runoff into the reach during the time step. Soluble P yield (kg P/ha). Phosphorus that is transported by surface runoff into the reach during the time step. Mineral P yield (kg P/ha). Mineral phosphorus attached to sediment that is transported by surface runoff into the reach during the time step.

388 CHAPTER 44: SWAT OUTPUT PRIMARY FILES 185 The format of the subbasin output file (.bsb) is: Variable name Line # Position Format F90 Format SUB All space digit integer i4 GIS All space digit integer i8 MON All space digit integer i4 AREA All space decimal(xxxxxx.xxx) f10.3 PRECIP All space decimal(xxxxxx.xxx) f10.3 SNOMELT All space decimal(xxxxxx.xxx) f10.3 PET All space decimal(xxxxxx.xxx) f10.3 ET All space decimal(xxxxxx.xxx) f10.3 SW All space decimal(xxxxxx.xxx) f10.3 PERC All space decimal(xxxxxx.xxx) f10.3 SURQ All space decimal(xxxxxx.xxx) f10.3 GW_Q All space decimal(xxxxxx.xxx) f10.3 WYLD All space decimal(xxxxxx.xxx) f10.3 SYLD All space decimal(xxxxxx.xxx) f10.3 ORGN All space decimal(xxxxxx.xxx) f10.3 ORGP All space decimal(xxxxxx.xxx) f10.3 NSURQ All space decimal(xxxxxx.xxx) f10.3 SOLP All space decimal(xxxxxx.xxx) f10.3 SEDP All space decimal(xxxxxx.xxx) f10.3

389 186 SWAT USER'S MANUAL, VERSION MAIN CHANNEL OUTPUT FILE (.RCH) The main channel output file contains summary information for each routing reach in the watershed. The file is written in spreadsheet format. Following is a brief description of the output variables in the.rch file. Variable name RCH Definition Reach number. The reach number is also the hydrograph number of the subbasin as defined in the.fig file. GIS GIS number reprinted from watershed configuration (.fig) file. See explanation of subbasin command. MON Daily time step: the julian date Monthly time step: the month (1-12) Annual time step: 4-digit year Average annual summary lines: number of years averaged together AREA Area drained by reach (km 2 ). FLOW_IN Average daily streamflow into reach during time step (m 3 /s). FLOW_OUT Average daily streamflow out of reach during time step (m 3 /s). EVAP Average daily rate of water loss from reach by evaporation during time step (m 3 /s). TLOSS Average daily rate of water loss from reach by transmission through the streambed during time step (m 3 /s). SED_IN Sediment transported with water into reach during time step (metric tons). SED_OUT Sediment transported with water out of reach during time step (metric tons). SEDCONC Concentration of sediment in reach during time step (mg/l). ORGN_IN Organic nitrogen transported with water into reach during time step (kg N). ORGN_OUT Organic nitrogen transported with water out of reach during time step (kg N). ORGP_IN Organic phosphorus transported with water into reach during time step (kg P). ORGP_OUT Organic phosphorus transported with water out of reach during time step (kg P).

390 Variable name NO3_IN CHAPTER 44: SWAT OUTPUT PRIMARY FILES 187 Definition Nitrate transported with water into reach during time step (kg N). NO3_OUT Nitrate transported with water out of reach during time step (kg N). NH4_IN Ammonium transported with water into reach during time step (kg N). NH4_OUT Ammonium transported with water out of reach during time step (kg N). NO2_IN Nitrite transported with water into reach during time step (kg N). NO2_OUT Nitrite transported with water out of reach during time step (kg N). MINP_IN Mineral phosphorus transported with water into reach during time step (kg P). MINP_OUT Mineral phosphorus transported with water out of reach during time step (kg P). ALGAE_IN Algal biomass transported with water into reach during time step (kg). ALGAE_OUT Algal biomass transported with water out of reach during time step (kg). CBOD_IN Carbonaceous biochemical oxygen demand of material transported into reach during time step (kg O 2 ). CBOD_OUT Carbonaceous biochemical oxygen demand of material transported out of reach during time step (kg O 2 ). DISOX_IN Amount of dissolved oxygen transported into reach during time step (kg O 2 ). DISOX_OUT Amount of dissolved oxygen transported out of reach during time step (kg O 2 ). While more than one pesticide may be applied to the HRUs, due to the complexity of the pesticide equations only the pesticide listed in.bsn is routed through the stream network. SOLPST_IN SOLPST_OUT Soluble pesticide transported with water into reach during time step (mg active ingredient) Soluble pesticide transported with water out of reach during time step (mg active ingredient).

391 188 SWAT USER'S MANUAL, VERSION 2000 Variable name SORPST_IN SORPST_OUT REACTPST VOLPST SETTLPST RESUSP_PST DIFFUSEPST REACBEDPST BURYPST BED_PST BACTP_OUT BACTLP_OUT CMETAL#1 CMETAL#2 CMETAL#3 Definition Pesticide sorbed to sediment transported with water into reach during time step (mg active ingredient). Pesticide sorbed to sediment transported with water out of reach during time step (mg active ingredient). Loss of pesticide from water by reaction during time step (mg active ingredient). Loss of pesticide from water by volatilization during time step (mg active ingredient). Transfer of pesticide from water to river bed sediment by settling during time step (mg active ingredient). Transfer of pesticide from river bed sediment to water by resuspension during time step (mg active ingredient). Transfer of pesticide from water to river bed sediment by diffusion during time step (mg active ingredient). Loss of pesticide from river bed sediment by reaction during time step (mg active ingredient). Loss of pesticide from river bed sediment by burial during time step (mg active ingredient). Pesticide in river bed sediment during time step (mg active ingredient). Number of persistent bacteria transported out of reach during time step. Number of less persistent bacteria transported out of reach during time step. Conservative metal #1 transported out of reach (kg). Conservative metal #2 transported out of reach (kg). Conservative metal #3 transported out of reach (kg).

392 The format of the main channel output file (.rch) is: CHAPTER 44: SWAT OUTPUT PRIMARY FILES 189 Variable name Line # Position Format F90 Format RCH All space digit integer i4 GIS All space digit integer i8 MON All space digit integer i5 AREA All space exponential e12.4 FLOW_IN All space exponential e12.4 FLOW_OUT All space exponential e12.4 EVAP All space exponential e12.4 TLOSS All space exponential e12.4 SED_IN All space exponential e12.4 SED_OUT All space exponential e12.4 SEDCONC All space exponential e12.4 ORGN_IN All space exponential e12.4 ORGN_OUT All space exponential e12.4 ORGP_IN All space exponential e12.4 ORGP_OUT All space exponential e12.4 NO3_IN All space exponential e12.4 NO3_OUT All space exponential e12.4 NH4_IN All space exponential e12.4 NH4_OUT All space exponential e12.4 NO2_IN All space exponential e12.4 NO2_OUT All space exponential e12.4 MINP_IN All space exponential e12.4 MINP_OUT All space exponential e12.4 CHLA_IN All space exponential e12.4 CHLA_OUT All space exponential e12.4 CBOD_IN All space exponential e12.4 CBOD_OUT All space exponential e12.4 DISOX_IN All space exponential e12.4 DISOX_OUT All space exponential e12.4 SOLPST_IN All space exponential e12.4 SOLPST_OUT All space exponential e12.4 SORPST_IN All space exponential e12.4 SORPST_OUT All space exponential e12.4 REACTPST All space exponential e12.4

393 190 SWAT USER'S MANUAL, VERSION 2000 Variable name Line # Position Format F90 Format VOLPST All space exponential e12.4 SETTLPST All space exponential e12.4 RESUSP_PST All space exponential e12.4 DIFFUSEPST All space exponential e12.4 REACBEDPST All space exponential e12.4 BURYPST All space exponential e12.4 BED_PST All space exponential e12.4 BACTP_OUT All space exponential e12.4 BACTLP_OUT All space exponential e12.4 CMETAL#1 All space exponential e12.4 CMETAL#2 All space exponential e12.4 CMETAL#3 All space exponential e12.4

394 CHAPTER 44: SWAT OUTPUT PRIMARY FILES HRU IMPOUNDMENT OUTPUT FILE (.WTR) The HRU impoundment output file contains summary information for ponds, wetlands and depressional/impounded areas in the HRUs. The file is written in spreadsheet format. Following is a brief description of the output variables in the HRU impoundment output file. Variable name LULC Definition Four letter character code for the cover/plant on the HRU. (code from crop.dat file) HRU Hydrologic response unit number GIS GIS code reprinted from watershed configuration file (.fig). See explanation of subbasin command. SUB Topographically-defined subbasin to which the HRU belongs. MGT Management number. This is pulled from the management (.mgt) file. Used by the SWAT/GRASS interface to allow development of output maps by landuse/management type. MON Daily time step: the julian date Monthly time step: the month (1-12) Annual time step: year Average annual summary lines: total number of years averaged together AREA Drainage area of the HRU (km 2 ). PNDPCP Precipitation falling directly on the pond during the time step (mm H 2 O). The depth of water is the volume divided by the area of the HRU. PND_IN Pond inflow (mm H 2 O). Surface runoff entering the pond during the time step. The depth of water is the volume divided by the area of the HRU. PSED_I Pond sediment inflow (metric tons/ha). Sediment transported into the pond during the time step. The loading is the mass divided by the area of the HRU. PNDEVP Evaporation from the pond surface during the time step (mm H 2 O). The depth of water is the volume divided by the area of the HRU.

395 192 SWAT USER'S MANUAL, VERSION 2000 Variable name PNDSEP PND_OUT PSED_O PNDVOL PNDORGN PNDNO3 PNDORGP PNDMINP PNDCHLA PNDSECI WETPCP WET_IN WSED_I WETEVP WETSEP Definition Water that seeps through the bottom of the pond and recharges the shallow aquifer during the time step (mm H 2 O). The depth of water is the volume divided by the area of the HRU. Pond outflow (mm H 2 O). Water leaving the pond and entering the reach during the time step. The depth of water is the volume divided by the area of the HRU. Pond sediment outflow (metric tons/ha). Sediment transported out of the pond and entering the reach during the time step.. The loading is the mass divided by the area of the HRU. Volume of water in pond at end of time step (m 3 H 2 O). Concentration of organic N in pond at end of time step (mg N/L or ppm). Concentration of nitrate in pond at end of time step (mg N/L or ppm). Concentration of organic P in pond at end of tile step (mg P/L or ppm). Concentration of mineral P in pond at end of time step (mg P/L or ppm). Concentration of chlorophyll-a in pond at end of time step (mg chl-a/l or ppm). Secchi-disk depth of pond at end of time step (m). Precipitation falling directly on the wetland during the time step (mm H 2 O). The depth of water is the volume divided by the area of the HRU. Wetland inflow (mm H 2 O). Surface runoff entering the wetland during the time step. The depth of water is the volume divided by the area of the HRU. Wetland sediment inflow (metric tons/ha). Sediment transported into the wetland during the time step. The loading is the mass divided by the area of the HRU. Evaporation from the wetland during the time step (mm H 2 O). The depth of water is the volume divided by the area of the HRU. Water that seeps through the bottom of the wetland and recharges the shallow aquifer during the time step (mm H 2 O). The depth of water is the volume divided by the area of the HRU.

396 CHAPTER 44: SWAT OUTPUT PRIMARY FILES 193 Variable name WET_OUT WSED_O WET_VOL WETORGN WETNO3 WETORGP WETMINP WETCHLA WETSECI POTPCP POT_IN OSED_I POTEVP POTSEP POT_OUT Definition Wetland outflow (mm H 2 O). Water leaving the wetland and entering the reach during the time step. The depth of water is the volume divided by the area of the HRU. Wetland sediment outflow (metric tons/ha). Sediment transported out of the wetland and entering the reach during the time step.. The loading is the mass divided by the area of the HRU. Volume of water in wetland at end of time step (m 3 H 2 O). Concentration of organic N in wetland at end of time step (mg N/L or ppm). Concentration of nitrate in wetland at end of time step (mg N/L or ppm). Concentration of organic P in wetland at end of tile step (mg P/L or ppm). Concentration of mineral P in wetland at end of time step (mg P/L or ppm). Concentration of chlorophyll-a in wetland at end of time step (mg chl-a/l or ppm). Secchi-disk depth of wetland at end of time step (m). Precipitation falling directly on the pothole during the time step (mm H 2 O). The depth of water is the volume divided by the area of the HRU. Pothole inflow (mm H 2 O). Surface runoff entering the pothole during the time step. The depth of water is the volume divided by the area of the HRU. Pothole sediment inflow (metric tons/ha). Sediment transported into the pothole during the time step. The loading is the mass divided by the area of the HRU. Evaporation from the pothole during the time step (mm H 2 O). The depth of water is the volume divided by the area of the HRU. Water that seeps through the bottom of the pothole and enters the underlying soil during the time step (mm H 2 O). The depth of water is the volume divided by the area of the HRU. Pothole outflow (mm H 2 O). Water leaving the pothole and entering the reach during the time step. The depth of water is the volume divided by the area of the HRU.

397 194 SWAT USER'S MANUAL, VERSION 2000 Variable name OSED_O POTVOL POT_SA HRU_SURQ PLANT_ET SOIL_ET Definition Pothole sediment outflow (metric tons/ha). Sediment transported out of the pothole and entering the reach during the time step.. The loading is the mass divided by the area of the HRU. Volume of water in pothole at end of time step (m 3 H 2 O). Surface area of pothole at end of time step (ha). Surface runoff contribution to streamflow in the main channel from entire HRU during the time step (mm H 2 O). Amount of water removed by transpiration from plants during the time step (mm H 2 O). Amount of water removed by evaporation from the soil during the time step (mm H 2 O). The format of the HRU impoundment output file (.wtr) is: Variable name Line # Position Format F90 Format LULC All space 1-4 character a4 HRU All space digit integer i4 GIS All space digit integer i8 SUB All space digit integer i4 MGT All space digit integer i4 MON All space digit integer i4 AREA All space decimal(xxxxxx.xxx) f10.3 PNDPCP All space decimal(xxxxxx.xxx) f10.3 PND_IN All space decimal(xxxxxx.xxx) f10.3 PSED_I All space decimal(xxxxxx.xxx) f10.3 PNDEVP All space decimal(xxxxxx.xxx) f10.3 PNDSEP All space decimal(xxxxxx.xxx) f10.3 PND_OUT All space decimal(xxxxxx.xxx) f10.3 PSED_O All space decimal(xxxxxx.xxx) f10.3 PNDVOL All space exponential e10.4 PNDORGN All space decimal(xxxxxx.xxx) f10.3 PNDNO3 All space decimal(xxxxxx.xxx) f10.3 PNDORGP All space decimal(xxxxxx.xxx) f10.3 PNDMINP All space decimal(xxxxxx.xxx) f10.3 PNDCHLA All space decimal(xxxxxx.xxx) f10.3 PNDSECI All space decimal(xxxxxx.xxx) f10.3

398 CHAPTER 44: SWAT OUTPUT PRIMARY FILES 195 Variable name Line # Position Format F90 Format WETPCP All space decimal(xxxxxx.xxx) f10.3 WET_IN All space decimal(xxxxxx.xxx) f10.3 WSED_I All space decimal(xxxxxx.xxx) f10.3 WETEVP All space decimal(xxxxxx.xxx) f10.3 WETSEP All space decimal(xxxxxx.xxx) f10.3 WET_OUT All space decimal(xxxxxx.xxx) f10.3 WSED_O All space decimal(xxxxxx.xxx) f10.3 WET_VOL All space exponential e10.4 WETORGN All space decimal(xxxxxx.xxx) f10.3 WETNO3 All space decimal(xxxxxx.xxx) f10.3 WETORGP All space decimal(xxxxxx.xxx) f10.3 WETMINP All space decimal(xxxxxx.xxx) f10.3 WETCHLA All space decimal(xxxxxx.xxx) f10.3 WETSECI All space decimal(xxxxxx.xxx) f10.3 POTPCP All space decimal(xxxxxx.xxx) f10.3 POT_IN All space decimal(xxxxxx.xxx) f10.3 OSED_I All space decimal(xxxxxx.xxx) f10.3 POTEVP All space decimal(xxxxxx.xxx) f10.3 POTSEP All space decimal(xxxxxx.xxx) f10.3 POT_OUT All space decimal(xxxxxx.xxx) f10.3 OSED_O All space decimal(xxxxxx.xxx) f10.3 POTVOL All space exponential e10.4 POT_SA All space decimal(xxxxxx.xxx) f10.3 HRU_SURQ All space decimal(xxxxxx.xxx) f10.3 PLANT_ET All space decimal(xxxxxx.xxx) f10.3 SOIL_ET All space decimal(xxxxxx.xxx) f10.3

399 196 SWAT USER'S MANUAL, VERSION RESERVOIR OUTPUT FILE (.RSV) The reservoir output file contains summary information for reservoirs in the watershed. The file is written in spreadsheet format. Following is a brief description of the output variables in the reservoir output file. Variable name RES MON VOLUME FLOW_IN FLOW_OUT PRECIP Definition Reservoir number (assigned in.fig file) Daily time step: the julian date Monthly time step: the month (1-12) Annual time step: four-digit year Volume of water in reservoir at end of time step (m 3 H 2 O). Average flow into reservoir during time step (m 3 /s H 2 O). Average flow out of reservoir during time step (m 3 /s H 2 O). Precipitation falling directly on the reservoir during the time step (m 3 H 2 O). EVAP Evaporation from the reservoir during the time step (m 3 H 2 O). SEEPAGE Water that seeps through the bottom of the reservoir and enters the shallow aquifer during the time step (m 3 H 2 O). SED_IN Reservoir sediment inflow (metric tons). Sediment transported into the reservoir during the time step. SED_OUT Reservoir sediment outflow (metric tons). Sediment transported out of the reservoir during the time step. ORGN_IN Amount of organic nitrogen transported into reservoir during the time step (kg N). ORGN_OUT Amount of organic nitrogen transported out of reservoir during the time step (kg N). ORGP_IN Amount of organic phosphorus transported into reservoir during the time step (kg P). ORGP_OUT Amount of organic phosphorus transported out of reservoir during the time step (kg P). NO3_IN Amount of nitrate transported into reservoir during the time step (kg N).

400 CHAPTER 44: SWAT OUTPUT PRIMARY FILES 197 Variable name NO3_OUT NO2_IN NO2_OUT NH3_IN NH3_OUT MINP_IN MINP_OUT CHLA_IN CHLA_OUT SECCHIDEPTH PEST_IN REACTPST VOLPST SETTLPST RESUSP_PST DIFFUSEPST REACBEDPST BURYPST Definition Amount of nitrate transported out of reservoir during the time step (kg N). Amount of nitrite transported into reservoir during the time step (kg N). Amount of nitrite transported out of reservoir during the time step (kg N). Amount of ammonia transported into reservoir during the time step (kg N). Amount of ammonia transported out of reservoir during the time step (kg N). Amount of mineral phosphorus transported into reservoir during the time step (kg P). Amount of mineral phosphorus transported out of reservoir during the time step (kg P). Amount of chlorophyll a transported into reservoir during the time step (kg chla). Amount of chlorophyll a transported out of reservoir during the time step (kg chla). Secchi-disk depth of reservoir at end of time step (m). Amount of pesticide transported into reservoir during the time step (mg pesticide active ingredient). Loss of pesticide from water by reaction during time step (mg active ingredient). Loss of pesticide from water by volatilization during time step (mg active ingredient). Transfer of pesticide from water to reservoir bed sediment by settling during time step (mg active ingredient). Transfer of pesticide from reservoir bed sediment to water by resuspension during time step (mg active ingredient). Transfer of pesticide from water to reservoir bed sediment by diffusion during time step (mg active ingredient). Loss of pesticide from reservoir bed sediment by reaction during time step (mg active ingredient). Loss of pesticide from reservoir sediment by burial during time step (mg active ingredient).

401 198 SWAT USER'S MANUAL, VERSION 2000 Variable name PEST_OUT PSTCNCW PSTCNCB Definition Amount of pesticide transported out of reservoir during the time step (mg pesticide active ingredient). Average concentration of pesticide in reservoir water during time step (mg active ingredient/m 3 H 2 O or ppb). Average concentration of pesticide in reservoir bed sediment during time step (mg active ingredient/m 3 H 2 O or ppb). The format of the reservoir output file (.rsv) is: Variable name Line # Position Format F90 Format RES All space 7-14 integer i8 MON All space integer i4 VOLUME All space exponential e12.4 FLOW_IN All space exponential e12.4 FLOW_OUT All space exponential e12.4 PRECIP All space exponential e12.4 EVAP All space exponential e12.4 SEEPAGE All space exponential e12.4 SED_IN All space exponential e12.4 SED_OUT All space exponential e12.4 ORGN_IN All space exponential e12.4 ORGN_OUT All space exponential e12.4 ORGP_IN All space exponential e12.4 ORGP_OUT All space exponential e12.4 NO3_IN All space exponential e12.4 NO3_OUT All space exponential e12.4 NO2_IN All space exponential e12.4 NO2_OUT All space exponential e12.4 NH3_IN All space exponential e12.4 NH3_OUT All space exponential e12.4 MINP_IN All space exponential e12.4 MINP_OUT All space exponential e12.4 CHLA_IN All space exponential e12.4 CHLA_OUT All space exponential e12.4 SECCHIDEPTH All space exponential e12.4 PEST_IN All space exponential e12.4

402 CHAPTER 44: SWAT OUTPUT PRIMARY FILES 199 Variable name Line # Position Format F90 Format REACTPST All space exponential e12.4 VOLPST All space exponential e12.4 SETTLPST All space exponential e12.4 RESUSP_PST All space exponential e12.4 DIFFUSEPST All space exponential e12.4 REACBEDPST All space exponential e12.4 BURYPST All space exponential e12.4 PEST_OUT All space exponential e12.4 PSTCNCW All space exponential e12.4 PSTCNCB All space exponential e12.4

403 200 SWAT USER'S MANUAL, VERSION 2000

404 SWAT MODEL CALIBRATION Calibration of a model run can be divided into several steps: water balance and stream flow sediment nutrients pesticides WATER BALANCE AND STREAM FLOW To calibrate the water balance and stream flow you need to have some understanding of the actual conditions occurring in the watershed. Ideally, you have data from a stream gage located within or at the outlet of your watershed. The U.S. Geological Survey maintains a website ( with daily records for all stream gages in the U.S. available for downloading. Calibration for water balance and stream flow is first done for average annual conditions. Once the run is calibrated for average annual conditions, the user can shift to monthly or daily records to fine-tune the calibration. The average annual observed and simulated results should be summarized in a manner similar to the following table: Total Water Yield Baseflow Surface Flow Actual 200 mm 80 mm 120 mm SWAT 300 mm 20 mm 280 mm (When calibrating, we usually summarize data as depth of water in millimeters over the drainage area. Feel free to use whatever units you prefer.) If you are calibrating at the watershed outlet, the SWAT values for the table are provided in the.std file. These values are listed in the table titled "Ave Annual Basin Values" located near the end of the file. If you are calibrating a gage located within the watershed, the total water yield can be calculated from the FLOW_OUT variable in the reach (.rch) file. The values for Baseflow and Surface Flow have to be estimated from the HRU output (.sbs) file or the subbasin output file (.bsb). To estimate the contributions by baseflow and streamflow, the average annual values for GWQ, SURQ and WYLD need to be averaged so that an areally weighted value for the drainage area of interest is obtained. The surface flow and baseflow then need to be converted to fractions by dividing by the total water yield (WYLD). These fractions are then multiplied by the total water yield obtained from the reach output file. The values for GWQ and SURQ cannot be used directly because in-stream precipitation, evaporation, transmission losses, etc. will alter the net water yield from that predicted by the WYLD variable in the HRU or Subbasin Output files.

405 There are a number of methods available for partitioning observed stream flow into fractions contributed by baseflow and surface runoff. If daily steam flow is available, a baseflow filter program can be run which performs this analysis. I. BASIC WATER BALANCE & TOTAL FLOW CALIBRATION CALIBRATE SURFACE RUNOFF: Step 1: Adjust the curve number (CN2 in.sub or.mgt) until surface runoff is acceptable. Appendix A contains tables of curve number values for a wide variety of land covers. Appendix B contains tables summarizing ranges for the general categories of land cover and lists the land cover category for all plants in the SWAT Land Cover/Plant database. If surface runoff values are still not reasonable after adjusting curve numbers, adjust: -soil available water capacity (±0.04) (SOL_AWC in.sol) and/or -soil evaporation compensation factor (ESCO in.sub). CALIBRATE SUBSURFACE FLOW: Step 2: Once surface runoff is calibrated, compare measured and simulated values of baseflow. If simulated baseflow is too high: -increase the groundwater "revap" coefficient (GW_REVAP in.gw) the maximum value that GW_REVAP should be set at is decrease the threshold depth of water in the shallow aquifer for "revap" to occur (REVAPMN in.gw) the minimum value that REVAPMN should be set at is increase the threshold depth of water in the shallow aquifer required for base flow to occur (GWQMN in.gw) the maximum value that GWQMN should be set at is left to user discretion. If simulated baseflow is too low, check the movement of water into the aquifer. If groundwater recharge (GWQ in.sbs or.bsb) is greater than or equal to the desired baseflow: -decrease the groundwater "revap" coefficient (GW_REVAP in.gw) the minimum value that GW_REVAP should be set at is increase the threshold depth of water in the shallow aquifer for "revap" to occur (REVAPMN in.gw). -decrease the threshold depth of water in the shallow aquifer required for base flow to occur (GWQMN in.gw) the minimum value that GWQMN should be set at is 0.0. Step 3: Repeat steps 1 and 2 until values are acceptable. It may take several reiterations to get the surface runoff and baseflow correct. II. TEMPORAL FLOW CALIBRATION

406 Once average annual and annual surface runoff and baseflow are realistic, the temporal flow should look reasonable as well. A few problems that may still be present include: Flow Observed Simulated Time (days) 1) Peaks are reasonable, but the recessions "bottom out": Check the transmission losses/values for channel hydraulic conductivity (CH_K in.rte). The value for channel hydraulic conductivity is an effective hydraulic conductivity for movement of water out of the stream bed. For perennial streams receiving groundwater contribution to flow, the groundwater enters the stream through the sides and bottom of the stream bed, making the effective hydraulic conductivity of the channel beds to water losses equal to zero. The only time the channel hydraulic conductivity would be greater than zero is for ephemeral and transient streams that do not receive continuous groundwater contributions to streamflow. A second variable that will affect the shape of the hydrograph is the baseflow alpha factor (ALPHA_BF in.gw). Flow Observed Simulated Time (days) 2) In snow melt months, the peaks are too high and recessions are too low: Check the values for maximum and minimum melt rates for snow (SMFMX and SMFMN in.bsn). These values may need to be lowered. Another variable that will impact snow melt is the temperature lapse rate (TLAPS in.sub). These values may need to be increased. Finally, the baseflow alpha factor may need to be modified (ALPHA_BF in.gw).

407 III. SPATIAL FLOW CALIBRATION If you are calibrating a watershed with multiple stream gages, calibrate streamflow for the gage furthest upstream. Once that gage is calibrated, move downstream to the next gage and calibrate for that area. It is important that, as you calibrate downstream gages, you do not change parameters within the files associated with the drainage area of the upstream gages already calibrated. SEDIMENT There are two sources of sediment in the SWAT simulation: loadings from HRUs/subbasins and channel degradation/deposition. Once the ratio of surface runoff to baseflow contribution to streamflow is being simulated correctly, the sediment contribution (loadings from HRUs/subbasins) should be close to measured values. In most situations, the user will probably have little information about channel degradation/deposition. For those unable to go out and assess the channel, we suggest that you adjust the loadings from the subbasins until they look reasonable and then assume that the remaining difference between actual and observed is due to channel degradation/deposition. The average annual observed and simulated results should be summarized in a manner similar to the following table. A more detailed table which contains the loadings by land use on a given soil type may be used also. Sediment Loadings from mixed forest 187 metric tons/yr 0.14 metric tons/ha/yr Loadings from bermuda pasture 354 metric tons/yr 0.23 metric tons/ha/yr Loadings from range 1459 metric tons/yr 0.35 metric tons/ha/yr Loading from HRUs/subbasins 2,000 metric tons/yr 0.28 metric tons/ha/yr Amount of sediment leaving reach 2,873 metric tons/yr Actual 2,321 metric tons/yr Sediment loadings from the HRUs/subbasins can be calculated by summing values for SYLD in either the.sbs or.bsb file. The amount of sediment leaving the reach can be obtained from values reported for SED_OUT in the.rch file. CHECK RESERVOIR/POND SIMULATION:

408 Reservoirs and ponds have a big impact on sediment loadings. If the amount of sediment being simulated in the watershed is off, first verify that you are accounting for all the ponds and reservoirs in the watershed and that they are being simulated properly. CALIBRATE SUBBASIN LOADINGS: While surface runoff is the primary factor controlling sediment loadings to the stream, there are a few other variables that affect sediment movement into the stream. 1) Tillage has a great impact on sediment transport. With tillage, plant residue is removed from the surface causing erosion to increase. Verify that the tillage practices are being accurately simulated. 2) USLE equation support practices (P) factor (USLE_P in the.sub file): Verify that you have accurately accounted for contouring and terracing in agricultural areas. In general, agricultural land with a slope greater that 5% will be terraced. 3) USLE equation slope length factor (SLSUBBSN in.sub file): There is usually a large amount of uncertainty in slope length measurements. The slope length will also be affected by support practices used in the HRU. 4) Slope in the HRUs (SLOPE in.sub file): Verify that the slopes given for the subbasin are correct. 5) USLE equation cropping practices (C) factor (USLE_C in crop.dat): In some cases, the minimum C value reported for the plant cover may not be accurate for your area. CALIBRATE CHANNEL DEGRADATION/DEPOSITION: Channel degradation will be significant during extreme storm events and in unstable subbasins. Unstable subbasins are those undergoing a significant change in land use patterns such as urbanization. Variables that affect channel degradation/deposition include: 1) The linear and exponential parameters used in the equation to calculate sediment reentrained in channel sediment routing (SPCON and SPEXP in.bsn file). These variables affect sediment routing in the entire watershed. 2) The channel erodibility factor (CH_EROD in.rte) 3) The channel cover factor (CH_COV in.rte) NUTRIENTS The nutrients of concern in SWAT are nitrate, soluble phosphorus, organic nitrogen and organic phosphorus. When calibrating for a nutrient, keep in mind that changes made will have an effect all the nutrient levels. Nutrient calibration can be divided into two steps: calibration of nutrient loadings and calibration of in-stream water quality processes.

409 CALIBRATE NUTRIENT LOADINGS (ALL NUTRIENTS): 1) Check that the initial concentrations of the nutrients in the soil are correct. These are set in the soil chemical input file (.chm) and in the soil input file (.sol): nitrate (SOL_NO3 in.sol) soluble P (SOL_MINP in.chm) organic N (SOL_ORGN in.chm) organic P (SOL_ORGP in.chm) 2) Verify that fertilizer applications are correct. Check amounts and the soil layer that the fertilizer is applied to. The fertilizer may be applied to the top 10mm of soil or incorporated in the first soil layer. The variable FRT_LY1 identifies the fraction of fertilizer applied to the top 10mm of soil. (If this variable is left at zero, the model will set FRT_LY1 = 0.20). 3) Verify that tillage operations are correct. Tillage redistributes nutrients in the soil and will alter the amount available for interaction or transport by surface runoff. 4) Alter the biological mixing efficiency (BIOMIX in.bsn file). Biological mixing acts the same as a tillage operation in that it incorporates residue and nutrients into the soil. This variable controls mixing due to biological activity in the entire watershed. CALIBRATE NUTRIENT LOADINGS (NITRATE): In addition to the variables mentioned above, 1) Modify the nitrogen percolation coefficient (NPERCO in.bsn file) CALIBRATE NUTRIENT LOADINGS (SOLUBLE P): In addition to the variables mentioned in the section for all nutrients, 1) Modify the phosphorus percolation coefficient (PPERCO in.bsn file) 2) Modify the phosphorus soil partitioning coefficient (PHOSKD in.bsn file). CALIBRATE NUTRIENT LOADINGS (ORGANIC N & P): Organics are transported to the stream attached to sediment, so the movement of sediment will greatly impact the movement of organics. CALIBRATE IN-STREAM NUTRIENT PROCESSES: SWAT includes in-stream nutrient cycling processes as described in the QUAL2E documentation. Variables in the watershed water quality (.wwq) and stream water quality (.swq) files control these processes.

410 Tables of Runoff Curve Number Values Table 1: Runoff curve numbers for cultivated agricultural lands Cover Hydrologic Soil Group Land Use Treatment or practice Hydrologic condition A B C D Fallow Bare soil Crop residue cover Poor Good Row crops Straight row Poor Good Straight row w/ residue Poor Good Contoured Poor Good Contoured w/ residue Poor Good Contoured & terraced Poor Good Contoured & terraced w/ residue Poor Good Small grains Straight row Poor Good Straight row w/ residue Poor Good Contoured Poor Good Contoured w/ residue Poor Good Contoured & terraced Poor Good Contoured & terraced w/ residue Poor Good Close-seeded or Straight row Poor broadcast legumes Good or rotation Contoured Poor Good Contoured & terraced Poor Good These tables are reproduced from Urban Hydrology for Small Watersheds, USDA Soil Conservation Service Engineering Division, Technical Release 55, June Crop residue cover applies only if residue is on at least 5% of the surface throughout the year.

411 Table 2: Runoff curve numbers for other agricultural lands Cover Hydrologic Soil Group Cover Type Hydrologic condition A B C D Pasture, grassland, or range continuous forage for grazing 1 Poor Fair Good Meadow continuous grass, protected from grazing and generally mowed for hay Brush brush-weed-grass mixture with brush the major element 2 Poor Fair Good Woods grass combination (orchard or tree farm) Poor Fair Good Woods 3 Poor Fair Good Farmsteads buildings, lanes, driveways, and surrounding lots Poor: < 50% ground cover or heavily grazed with no mulch Fair: 50 to 75% ground cover and not heavily grazed Good: > 75% ground cover and lightly or only occasionally grazed 2 Poor: < 50% ground cover Fair: 50 to 75% ground cover Good: > 75% ground cover 3 Poor: Forest litter, small trees, and brush are destroyed by heavy grazing or regular burning Fair: Woods are grazed but not burned, and some forest litter covers the soil. Good: Woods are protected from grazing, and litter and brush adequately cover the soil.

412 Table 3: Runoff curve numbers for urban areas Cover Cover Type Fully developed urban areas Hydrologic condition Average % impervious area Hydrologic Soil Group A B C D Open spaces (lawns, parks, golf courses, cemeteries, etc.) 4 Poor Fair Good Impervious areas: Paved parking lots, roofs, driveways, etc. (excluding right-of-way) Paved streets and roads; curbs and storm sewers (excluding right-of-way) Paved streets and roads; open ditches (including right-of-way) Gravel streets and roads (including right-ofway) Dirt streets and roads (including right-of way) Urban districts: Commercial and business 85% Industrial 72% Residential Districts by average lot size: 1/8 acre (0.05 ha) or less (town houses) 65% /4 acre (0.10 ha) 38% /3 acre (0.13 ha) 30% /2 acre (0.20 ha) 25% acre (0.40 ha) 20% acres (0.81 ha) 12% Developing urban areas: Newly graded areas (pervious areas only, no vegetation) Poor: grass cover < 50% Fair: grass cover 50 to 75% Good: grass cover > 75%

413 Table 4: Runoff curve numbers for arid and semiarid rangelands Cover Cover Type Hydrologic Soil Group Hydrologic condition 5 A B C D Herbaceous mixture of grass, weeds, and low-growing brush, with brush the minor element. Poor Fair Good Oak-aspen mountain brush mixture of oak brush, aspen, mountain mahogany, bitter brush, maple, and other brush. Poor Fair Good Pinyon-juniper pinyon, juniper, or both: grass understory. Poor Fair Good Sagebrush with grass understory. Poor Desert shrub major plants include saltbrush, greasewood, creosotebush, blackbrush, bursage, palo verde, mesquite, and cactus. Fair Good Poor Fair Good Poor: < 30% ground cover (litter, grass, and brush overstory) Fair: 30 to 70% ground cover Good: > 70% ground cover

414 Curve Number Calibration Table 1: Guideline runoff curve number ranges Hydrologic Soil Group Land Cover Category A B C D Row crop Small grain/close grown crop Perennial grasses Annual grasses (close-seeded legumes) Range Semiarid/arid range Brush Woods Orchard/tree farm Urban

415 APPENDIX A DATABASES The following sections describe the source of input for databases included with the model and any assumptions used in compilation of the database. Also, a methodology for appending additional information to the various databases is summarized. 29

416 30 SWAT USER S MANUAL, VERSION 2000 A.1 LAND COVER/PLANT GROWTH DATABASE The land cover/plant growth database contains information needed by SWAT to simulate the growth of a particular land cover. This information can be grouped into several categories: radiation use of the plant, plant growing season, biomass development, plant water use, plant nutrient uptake and plant response to stress. The growth parameters in the plant growth database define plant growth under ideal conditions and quantify the impact of some stresses on plant growth. Table A-1 lists all the default plant species and Table A-2 lists all the generic land covers included in the database. Table A-1: Plants included in plant growth database. Plant Common Name Code Taxonomic Name Plant type Corn CORN Zea mays L. warm season annual Corn silage CSIL Zea mays L. warm season annual Sweet corn SCRN Zea mays L. saccharata warm season annual Eastern gamagrass EGAM Tripsacum dactyloides (L.) L. perennial Grain sorghum GRSG Sorghum bicolor L. (Moench) warm season annual Sorghum hay SGHY Sorghum bicolor L. (Moench) warm season annual Johnsongrass JHGR Sorghum halepense (L.) Pers. perennial Sugarcane SUGC Saccharum officinarum L. perennial Spring wheat SWHT Triticum aestivum L. cool season annual Winter wheat WWHT Triticum aestivum L. cool season annual Durum wheat DWHT Triticum durum Desf. cool season annual Rye RYE Secale cereale L. cool season annual Spring barley BARL Hordeum vulgare L. cool season annual Oats OATS Avena sativa L. cool season annual Rice RICE Oryza sativa L. warm season annual Pearl millet PMIL Pennisetum glaucum L. warm season annual Timothy TIMO Phleum pratense L. perennial Smooth bromegrass BROS Bromus inermis Leysser perennial Meadow bromegrass BROM Bromus biebersteinii Roemer & Schultes perennial Tall fescue FESC Festuca arundinacea perennial Kentucky bluegrass BLUG Poa pratensis perennial Bermudagrass BERM Cynodon dactylon perennial Crested wheatgrass CWGR Agropyron cristatum (L.) Gaertner perennial Western wheatgrass WWGR Agropyron smithii (Rydb.) Gould perennial Slender wheatgrass SWGR Agropyron trachycaulum Malte perennial Italian (annual) ryegrass RYEG Lolium multiflorum Lam. cool season annual Russian wildrye RYER Psathyrostachys juncea (Fisch.) Nevski perennial

417 APPENDIX A: DATABASES 31 Common Name Plant Code Taxonomic Name Plant type Altai wildrye RYEA Leymus angustus (Trin.) Pilger perennial Sideoats grama SIDE Bouteloua curtipendula (Michaux) Torrey perennial Big bluestem BBLS Andropogon gerardii Vitman perennial Little bluestem LBLS Schizachyrium scoparium (Michaux) Nash perennial Alamo switchgrass SWCH Panicum virgatum L. perennial Indiangrass INDN Sorghastrum nutans (L.) Nash perennial Alfalfa ALFA Medicago sativa L. perennial legume Sweetclover CLVS Melilotus alba Med. perennial legume Red clover CLVR Trifolium pratense L. cool season annual legume Alsike clover CLVA Trifolium hybridum L. perennial legume Soybean SOYB Glycine max L., Merr. warm season annual legume Cowpeas CWPS Vigna sinensis warm season annual legume Mung bean MUNG Phaseolus aureus Roxb. warm season annual legume Lima beans LIMA Phaseolus lunatus L. warm season annual legume Lentils LENT Lens esculenta Moench J. warm season annual legume Peanut PNUT Arachis hypogaea L. warm season annual legume Field peas FPEA Pisum arvense L. cool season annual legume Garden or canning peas PEAS Pisum sativum L. ssp. sativum cool season annual legume Sesbania SESB Sesbania macrocarpa Muhl [exaltata] warm season annual legume Flax FLAX Linum usitatissum L. cool season annual Upland cotton COTS Gossypium hirsutum L. warm season annual (harvested with stripper) Upland cotton COTP Gossypium hirsutum L. warm season annual (harvested with picker) Tobacco TOBC Nicotiana tabacum L. warm season annual Sugarbeet SGBT Beta vulgaris (saccharifera) L. warm season annual Potato POTA Solanum tuberosum L. cool season annual Sweetpotato SPOT Ipomoea batatas Lam. warm season annual Carrot CRRT Daucus carota L. subsp. sativus (Hoffm.) Arcang. cool season annual Onion ONIO Allium cepa L. var cepa cool season annual Sunflower SUNF Helianthus annuus L. warm season annual Spring canola-polish CANP Brassica campestris cool season annual Spring canola-argentine CANA Brassica napus cool season annual Asparagus ASPR Asparagus officinalis L. perennial Broccoli BROC Brassica oleracea L. var italica Plenck. cool season annual Cabbage CABG Brassica oleracea L. var capitata L. perennial Cauliflower CAUF Brassica oleracea L. var botrytis L. cool season annual Celery CELR Apium graveolens L. var dulce (Mill.) Pers. perennial Head lettuce LETT Lactuca sativa L. var capitata L. cool season annual Spinach SPIN Spinacia oleracea L. cool season annual Green beans GRBN Phaseolus vulgaris warm season annual legume Cucumber CUCM Cucumis sativus L. warm season annual Eggplant EGGP Solanum melongena L. warm season annual Cantaloupe CANT Cucumis melo L. Cantaloupensis group warm season annual Honeydew melon HMEL Cucumis melo L. Inodorus group warm season annual

418 32 SWAT USER S MANUAL, VERSION 2000 Common Name Plant Code Taxonomic Name Plant Type Watermelon WMEL Citrullus lanatus (Thunb.) Matsum and Nakai warm season annual Bell pepper PEPR Capsicum annuum L. Grossum group warm season annual Strawberry STRW Fragaria X Ananassa Duchesne. perennial Tomato TOMA Lycopersicon esculentum Mill. warm season annual Apple APPL Malus domestica Borkh. trees Pine PINE Pinus trees Oak OAK Quercus trees Poplar POPL Populus trees Honey mesquite MESQ Prosopis glandulosa Torr. var. glandulosa trees Table A-2: Generic Land Covers included in database. Plant Name Code Origin of Plant Growth Values Plant Type Agricultural Land-Generic AGRL use values for Grain Sorghum warm season annual Agricultural Land-Row Crops AGRR use values for Corn warm season annual Agricultual Land-Close-grown AGRC use values for Winter Wheat cool season annual Orchard ORCD use values for Apples trees Hay HAY use values for Bermudagrass perennial Forest-mixed FRST use values for Oak trees Forest-deciduous FRSD use values for Oak trees Forest-evergreen FRSE use values for Pine trees Wetlands WETL use values for Alamo Switchgrass perennial Wetlands-forested WETF use values for Oak trees Wetlands-nonforested WETN use values for Alamo Switchgrass perennial Pasture PAST use values for Bermudagrass perennial Summer pasture SPAS use values for Bermudagrass perennial Winter pasture WPAS use values for Fescue perennial Range-grasses RNGE use values for Little Bluestem (LAI max =2.5) perennial Range-brush RNGB use values for Little Bluestem (LAI max =2.0) perennial Range-southwestern US SWRN use values for Little Bluestem (LAI max =1.5) perennial Water WATR not applicable A.1.1 LAND COVER/PLANT TYPES IN DATABASE When compiling the list of plants in the default database, we attempted to include the most economically important plants as well as those that are widely distributed in the landscape. This list is by no exhaustive and users may need to add plants to the list. A number of generic land cover types were also compiled to facilitate linkage of land use/land cover maps to SWAT plant categories. Because The Bermudagrass parameters input for Hay and Pasture are valid only in latitudes less than 35 to 37. At higher latitudes, Fescue parameters should be used to model generic Hay and Pasture. Water was included in the plant growth database in order to process USGS map layers in the HUMUS project. This land cover should not be used as a land cover in an HRU. To model water bodies, create ponds, wetlands or reservoirs.

419 APPENDIX A: DATABASES 33 of the broad nature of the some of the categories, a number of assumptions had to be made when compiling the plant growth parameter values. The user is strongly recommended to use parameters for a specific plant rather than those of the generic land covers any time information about plant types is available for the region being modeled. Plant code (CPNM): The 4-letter codes in the plant growth and urban databases are used by the GIS interfaces to link land use/land cover maps to SWAT plant types. When adding a new plant species or land cover category, the four letter code for the new plant must be unique. Land cover/plant classification (IDC): SWAT groups plants into seven categories: warm season annual legume, cold season annual legume, perennial legume, warm season annual, cold season annual, perennial and trees. (Biannual plants are classified as perennials.) The differences between the categories as modeled by SWAT are summarized in Chapter 17. Plant classifications can be easily found in horticulture books that summarize characteristics for different species. The classifications assigned to the plants in Table A-1 were obtained from Martin et al. (1976) and Bailey (1935). A.1.2 TEMPERATURE RESPONSES SWAT uses the base temperature to calculate the number of heat units accrued every day. The optimal temperature is used to calculate temperature stress for the plant during the growing season. A.1.3 LEAF AREA DEVELOPMENT In order to predict the conversion of radiant energy to biomass, the amount of leaf surface area available for light interception must be quantified. Plant growth database variables used to quantify leaf area development are: BLAI, FRGRW1, LAIMX1, FRGRW2, LAIMX2, and DLAI. To define the leaf area development parameters, record the leaf area index and number of accumulated heat units at different intervals in the year. A detailed discussion of heat units is given in Chapter 17.

420 34 SWAT USER S MANUAL, VERSION 2000 Although measuring leaf area can be laborious for large samples, there is no intrinsic difficulty in the process. The most common method is to obtain an electronic scanner and feed the harvested leaves into the scanner. Older methods for estimating leaf area include tracing of the leaves or weighed subsamples of them onto paper, the use of planimeters, the punch disk method of Watson (1958) and the linear dimension method of Duncan and Hesketh (1968). Remember that the leaf area index is defined as the area of green leaf per unit area of land, so only the green leaves should be measured. To define the leaf area development parameters, record the leaf area index and number of accumulated heat units at different intervals in the year.

421 A.2 TILLAGE DATABASE APPENDIX A: DATABASES 35

422 36 SWAT USER S MANUAL, VERSION 2000 A.3 PESTICIDE DATABASE The pesticide database file (pest.dat) summarizes pesticide attribute information for various pesticides. The pesticide data included in the database was originally compiled for the GLEAMS model in the early nineties (Knisel, 1993). The following table lists the pesticides included in the pesticide database. Table A-1: SWAT Pesticide Database Wash- Half-Life Trade Name Common Name Koc off Frac. Foliar Soil Water Solubility (ml/g) (days) (mg/l) 2,4,5-TP Silvex Plus 2 Mecoprop Amine Aatrex Atrazine Abate Temephos Acaraben Chlorobenzilate Accelerate Endothall Salt Acclaim Fenoxaprop-Ethyl Alanap Naptalam Sodium Salt Alar Daminozide Aldrin Aldrin Aliette Fosetyl-Aluminum Ally Metsulfuron-Methyl Amiben Chloramben Salts Amid-Thin W NAA Amide Amitrol T Amitrole Ammo Cypermethrin Antor Diethatyl-Ethyl A-Rest Ancymidol Arsenal Imazapyr Acid Arsonate MSMA Asana Esfenvalerate Assert (m) Imazamethabenz-m Assert (p) Imazamethabenz-p Assure Quizalofop-Ethyl Asulox Asulam Sodium Salt Avenge Difenzoquat Azodrin Monocrotophos Balan Benefin Banol Propamocarb Banvel Dicamba Basagran Bentazon Basta Glufosinate Ammonia Bayleton Triadimefon

423 APPENDIX A: DATABASES 37 Wash- Half-Life Trade Name Common Name Koc off Frac. Foliar Soil Water Solubility (ml/g) (days) (mg/l) Baytex Fenthion Baythroid Cyfluthrin Benlate Benomyl Benzex BHC Betamix Phenmedipham Betanex Desmedipham Bidrin Dicrotophos Bladex Cyanazine Bolero Thiobencarb Bolstar Sulprofos Bordermaster MCPA Ester Botran DCNA (Dicloran) Bravo Chlorothalonil Buctril Bromoxynil Octan. Ester Butyrac Ester 2,4-DB Ester Caparol Prometryn Carbamate Ferbam Carsoron Dichlobenil Carzol Formetanate Hydrochlor Cerone Ethephon Chem-Hoe Propham (IPC) Chlordane Chlordane Chopper Imazapyr Amine Classic Chlorimuron-ethyl Cobra Lactofen Comite Propargite Command Clomazone Cotoran Fluometuron Counter Terbufos Crossbow Triclopyr Amine Curacron Profenofos Cygon Dimethoate Cyprex Dodine Acetate Cythion Malathion Dacamine 2,4-D Acid Dacthal DCPA Dalapon Dalapon Sodium Salt Dasanit Fensulfothion DDT DDT Dedweed MCPA Amine DEF Tribufos Dessicant L-10 Arsenic Acid Devrinol Napropamide

424 38 SWAT USER S MANUAL, VERSION 2000 Wash- Half-Life Trade Name Common Name Koc off Frac. Foliar Soil Water Solubility (ml/g) (days) (mg/l) Di-Syston Disulfoton Dibrom Naled Dieldrin Dieldrin Dimilin Diflubenzuron Dinitro Dinoseb Phenol Diquat Diquat Dibromide Dithane Mancozeb Dowpon Dalapon Dropp Thidiazuron DSMA Methanearsonic Acid Na Du-ter Triphenyltin Hydroxide Dual Metolachlor Dyfonate Fonofos Dylox Trichlorfon Dymid Diphenamid Dyrene Anilazine Elgetol DNOC Sodium Salt EPN EPN Eradicane EPTC Ethanox Ethion Evik Ametryn Evital Norflurazon Far-Go Triallate Fenatrol Fenac Fenitox Fenitrothion Fruitone CPA 3-CPA Sodium Salt Fundal Chlordimeform Hydroclo Funginex Triforine Furadan Carbofuran Fusilade Fluazifop-P-Butyl Glean Chlorsulfuron Goal Oxyfluorfen Guthion Azinphos-Methyl Harmony Thifensulfuron-Methyl Harvade Dimethipin Hoelon Diclofop-Methyl Hyvar Bromacil Imidan Phosmet Isotox Lindane Karate Lambda-Cyhalothrin Karathane Dinocap Karmex Diuron Kelthane Dicofol

425 APPENDIX A: DATABASES 39 Wash- Half-Life Trade Name Common Name Koc off Frac. Foliar Soil Water Solubility (ml/g) (days) (mg/l) Kerb Pronamide Krenite Fosamine Ammon. Salt Lannate Methomyl Larvadex Cyromazine Larvin Thiodicarb Lasso Alachlor Limit Amidochlor Lontrel Clopyralid Lorox Linuron Lorsban Clorpyrifos Manzate Maneb Marlate Methoxychlor Matacil Aminocarb Mavrik Fluvalinate Metasystox Oxydemeton-Methyl Milogard Propazine Miral Isazofos Mitac Amitraz Modown Bifenox Monitor Methamidophos Morestan Oxythioquinox Nemacur Fenamiphos Nemacur Sulfone Fenamiphos Sulfone Nemacur Sulfoxide Fenamiphos Sulfoxide Norton Ethofumesate Octave Prochloraz Oftanol Isofenphos Orthene Acephate Orthocide Captan Oust Sulfometuron-Methyl Pay-Off Flucythrinate Penncap-M Methyl Parathion Phenatox Toxaphene Phosdrin Mevinphos Phoskil Parathion (Ethyl) Pipron Piperalin Pix Mepiquat Chlor. Salt Plantvax Oxycarboxin Poast Sethoxydim Polyram Metiram Pounce Permethrin Pramitol Prometon Prefar Bensulide

426 40 SWAT USER S MANUAL, VERSION 2000 Wash- Half-Life Trade Name Common Name Koc off Frac. Foliar Soil Water Solubility (ml/g) (days) (mg/l) Prelude Paraquat Prime Flumetralin Princep Simazine Probe Methazole Prowl Pendimethalin Pursuit AC 263, Pydrin Fenvalerate Pyramin Pyrazon Ramrod Propaclor Reflex Fomesafen Salt Rescue 2,4-DB Sodium Amine Ridomil Metalaxyl Ro-Neet Cycloate Ronstar Oxadiazon Roundup Glyphosate Amine Rovral Iprodione Royal Slo-Gro Maleic Hydrazide Rubigan Fenarimol Sancap Dipropetryn Savey Hexythiazox Scepter Imazaquin Ammonium Sencor Metribuzin Sevin Carbaryl Sinbar Terbacil Slug-Geta Methiocarb Sonalan Ethalfluralin Spectracide Diazinon Spike Tebuthiuron Sprout Nip Chlorpropham Stam Propanil Supracide Methidathion Surflan Oryzalin Sutan Butylate Swat Phosphamidon Tackle Acifluorfen Talstar Bifenthrin Tandem Tridiphane Tanone Phenthoate Tattoo Bendiocarb TBZ Thiabendazole Temik Aldicarb Temik Sulfone Aldicarb Sulfone Temik Sulfoxide Aldicarb Sulfoxide

427 APPENDIX A: DATABASES 41 Wash- Half-Life Trade Name Common Name Koc off Frac. Foliar Soil Water Solubility (ml/g) (days) (mg/l) Tenoran Chloroxuron Terbutrex Terbutryn Terrachlor PCNB Terraneb Chloroneb Terrazole Etridiazole Thimet Phorate Thiodan Endosulfan Thiram Thiram Thistrol MCPB Sodium Salt Tillam Pebulate Tilt Propiconazole Tolban Profluralin Topsin Thiophanate-Methyl Tordon Picloram Tralomethrin Tralomethrin Treflan Trifluralin Tre-Hold NAA Ethyl Ester Tupersan Siduron Turflon Triclopyr Ester Velpar Hexazinone Vendex Fenbutatin Oxide Vernam Vernolate Volck oils Petroleum oil Vydate Oxamyl Weedar 2,4-D amine Weed-B-Gon 2,4,5-T Amine Wedone Dichlorprop Ester Zolone Phosalone Knisel (1993) cites Wauchope et al. (1992) as the source for water solubility, soil half-life and K oc values. Wash-off fraction and foliar half-life were obtained from Willis et al. (1980) and Willis and McDowell (1987). A.3.1 WATER SOLUBILITY The water solubility value defines the highest concentration of pesticide that can be reached in the runoff and soil pore water. While this is an important characteristic, researchers have found that the soil adsorption coefficient, K oc, tends to limit the amount of pesticide entering solution so that the maximum

428 42 SWAT USER S MANUAL, VERSION 2000 possible concentration of pesticide in solution is seldom reached (Leonard and Knisel, 1988). Reported solubility values are determined under laboratory conditions at a constant temperature, typically between 20 C and 30 C. A.3.2 SOIL ADSORPTION COEFFICIENT The pesticide adsorption coefficient reported in the pesticide database can usually be obtained from a search through existing literature on the pesticide. A.3.3 SOIL HALF-LIFE The half-life for a pesticide defines the number of days required for a given pesticide concentration to be reduced by one-half. The soil half-life entered for a pesticide is a lumped parameter that includes the net effect of volatilization, photolysis, hydrolysis, biological degradation and chemical reactions. The pesticide half-life for a chemical will vary with a change in soil environment (e.g. change in soil temperature, water content, etc.). Soil half-life values provided in the database are average or representative values. Half-life values reported for a chemical commonly vary by a factor of 2 to 3 and sometimes by as much as a factor of 10. For example, the soil half-life for atrazine can range from 120 to 12 days when comparing values reported in cool, dry regions to those from warm, humid areas. Another significant factor is soil treatment history. Repeated soil treatment by the same or a chemically similar pesticide commonly results in a reduction in half-life for the pesticide. This reduction is attributed to the preferential build-up of microbial populations adapted to degrading the compound. Users are encouraged to replace the default soil half-life value with a site-specific or region-specific value whenever the information is available. A.3.4 FOLIAR HALF-LIFE As with the soil half-life, the foliar half-life entered for a pesticide is a lumped parameter describing the loss rate of pesticides on the plant canopy. For most pesticides, the foliar half-life is much less than the soil half-life due to enhanced volatilization and photodecomposition. While values for foliar half-life

429 APPENDIX A: DATABASES 43 were available for some pesticides in the database, the majority of foliar half-life values were calculated using the following rules: 1) Foliar half-life was assumed to be less than the soil half-life by a factor of 0.5 to 0.25, depending on vapor pressure and sensitivity to photodegradation. 2) Foliar half-life was adjusted downward for pesticides with vapor pressures less than 10-5 mm Hg. 3) The maximum foliar half-life assigned was 30 days. A.3.5 WASH-OFF FRACTION The wash-off fraction quantifies the fraction of pesticide on the plant canopy that may be dislodged. The wash-off fraction is a function of the nature of the leaf surface, plant morphology, pesticide solubility, polarity of the pesticide molecule, formulation of the commercial product and timing and volume of the rainfall event. Some wash-off fraction values were obtained from Willis et al. (1980). For the remaining pesticides, solubility was used as a guide for estimating the wash-off fraction. A.3.6 APPLICATION EFFICIENCY The application efficiency for all pesticides listed in the database is defaulted to This variable is a calibration parameter.

430 44 SWAT USER S MANUAL, VERSION 2000 A.4 FERTILIZER DATABASE The fertilizer database file (fert.dat) summarizes nutrient fractions for various fertilizers and types of manure. The following table lists the fertilizers and types of manure in the fertilizer database. Table A-1: SWAT Fertilizer Database Name Name Code Min-N Min-P Org-N Org-P NH 3 -N/ Min N Elemental Nitrogen Elem-N Elemental Phosphorous Elem-P Anhydrous Ammonia ANH-NH Urea UREA

431 APPENDIX A: DATABASES 45 Name Name Code Min-N Min-P Org-N Org-P NH 3 -N/ Min N Dairy-Fresh Manure DAIRY-FR Beef-Fresh Manure BEEF-FR Veal-Fresh Manure VEAL-FR Swine-Fresh Manure SWINE-FR Sheep-Fresh Manure SHEEP-FR Goat-Fresh Manure GOAT-FR Horse-Fresh Manure HORSE-FR Layer-Fresh Manure LAYER-FR Broiler-Fresh Manure BROIL-FR Turkey-Fresh Manure TRKEY-FR Duck-Fresh Manure DUCK-FR Values in bold italics are estimated (see section A.4.2) A.4.1 COMMERCIAL FERTILIZERS In compiling the list of commercial fertilizers in the database, we tried to identify and include commonly used fertilizers. This list is not comprehensive, so users may need to append the database with information for other fertilizers used in their watersheds. When calculating the fractions of N and P for the database, it is important to remember that the percentages reported for a fertilizer are %N-%P 2 O 5 -%K 2 O. The fraction of mineral N in the fertilizer is equal to %N divided by 100. To calculate the fraction of mineral P in the fertilizer, the fraction of P in P 2 O 5 must be known. The atomic weight of phosphorus is 31 and the atomic weight of oxygen is 16, making the molecular weight of P 2 O 5 equal to 142. The fraction of P in P 2 O 5 is 62/142 = 0.44 and the fraction of mineral P in the fertilizer is equal to 0.44 (%P 2 O 5 / 100).

432 46 SWAT USER S MANUAL, VERSION 2000 A.4.2 MANURE The values in the database for manure types were derived from manure production and characteristics compiled by the ASAE (1998). Table A-2 summarizes the levels of nitrogen and phosphorus in manure reported by the ASAE. The data summarized by ASAE is combined from a wide range of published and unpublished information. The mean values for each parameter are determined by an arithmetic average consisting of one data point per reference source per year and represent fresh (as voided) feces and urine. Table A-2: Fresh manure production and characteristics per 1000 kg live animal mass per day (from ASAE, 1998) Animal Type Parameter Dairy Beef Veal Swine Sheep Goat Horse Layer Broiler Turkey Duck Total Manure kg mean std dev ** Total Solids kg mean std dev Total Kjeldahl kg mean nitrogen std dev Ammonia kg mean ** ** ** 0.21 ** ** nitrogen std dev ** ** ** 0.18 ** ** Total kg mean phosphorus std dev Ortho- kg mean ** ** ** ** 0.25 phosphorus std dev ** ** ** ** ** ** ** ** Data not found. All values wet basis. Typical live animal masses for which manure values represent are: dairy, 640 kg; beef, 360 kg; veal, 91 kg; swine, 61 kg; sheep, 27 kg; goat, 64 kg; horse, 450 kg; layer, 1.8 kg; broiler, 0.9 kg; turkey, 6.8 kg; and duck, 1.4 kg. All nutrient values are given in elemental form. The fractions of the nutrient pools were calculated on a Total Solids basis, i.e. the water content of the manure was ignored. Assumptions used in the calculations are: 1) the mineral nitrogen pool is assumed to be entirely composed of NH 3 /NH + 4, 2) the organic nitrogen pool is equal to total Kjeldahl nitrogen minus ammonia nitrogen, 3) the mineral phosphorus pool is equal to the value given for orthophosphorus, and 4) the organic phosphorus pool is equal to total phosphorus minus orthophosphorus. Total amounts of nitrogen and phosphorus were available for all manure types. For manure types with either the ammonia nitrogen or orthophosphorus value missing, the ratio of organic to mineral forms of the provided element were used to partition the total amount of the other element. For example, in Table A-2

433 APPENDIX A: DATABASES 47 amounts of total Kjeldahl N, ammonia N, and total P are provided for veal but data for orthophosphorus is missing. To partition the total P into organic and mineral pools, the ratio of organic to mineral N for veal was used. If both ammonia nitrogen and orthophosphorus data are missing, the ratio of the organic to mineral pool for a similar animal were used to partition the total amounts of element into different fractions. This was required for goat and broiler manure calculations. The ratio of organic to mineral pools for sheep was used to partition the goat manure nutrient pools while layer manure nutrient ratios were used to partition the broiler manure nutrient pools. As can be seen from the standard deviations in Table A-2, values for nutrients in manure can vary widely. If site specific data are available for the region or watershed of interest, those values should be used in lieu of the default fractions provided in the database.

434 48 SWAT USER S MANUAL, VERSION 2000 A.5 URBAN DATABASE The urban database file (urban.dat) summarizes urban landscape attributes needed to model urban areas. These attributes tend to vary greatly from region to region and the user is recommended to use values specific to the area being modeled. The following tables list the urban land types and attributes that are provided in the urban database. Numerous urban land type classifications exist. For the default urban land types included in the database, an urban land use classification system created by Palmstrom and Walker (1990) was simplified slightly. Table A-3 lists the land type classifications used by Palmstrom and Walker and those provided in the database. Table A-3: Urban land type classification systems Palmstrom and Walker (1990) SWAT Urban Database Residential-High Density Residential-High Density Residential-Med/High Density Residential-Medium Density Residential-Med/Low Density Residential-Med/Low Density Residential-Low Density Residential-Low Density Residential-Rural Density Commercial Commercial Industrial Industrial-Heavy Transportation Industrial-Medium Institutional Transportation Institutional The urban database includes the following information for each urban land type: 1) fraction of urban land area that is impervious (total and directly connected); 2) curb length density; 3) wash-off coefficient; 4) maximum accumulated solids; 5) number of days for solid load to build from 0 kg/curb km to half of the maximum possible load; 6) concentration of total N in solid loading; 7) concentration of total P in solid loading; and 8) concentration of total NO 3 -N in solid loading. The fraction of total and directly connected impervious areas is needed for urban surface runoff calculations. The remaining information is used only when the urban build up/wash off algorithm is chosen to model sediment and nutrient loading from the urban impervious area.

435 A.5.1 DRAINAGE SYSTEM CONNECTEDNESS APPENDIX A: DATABASES 49 When modeling urban areas the connectedness of the drainage system must be quantified. The best methods for determining the fraction total and directly connected impervious areas is to conduct a field survey or analyze aerial photographs. However these methods are not always feasible. An alternative approach is to use data from other inventoried watersheds with similar land types. Table A-4 contains ranges and average values calculated from a number of different individual surveys (the average values from Table A-4 are the values included in the database). Table A-5 contains data collected from the cities of Madison and Milwaukee, Wisconsin and Marquett, Michigan. Table A-4: Range and average impervious fractions for different urban land types. Urban Land Type Average total impervious Range total impervious Average connected impervious Range connected impervious Residential-High Density (> 8 unit/acre or unit/2.5 ha) Residential-Medium Density (1-4 unit/acre or unit/2.5 ha) Residential-Med/Low Density (> unit/acre or unit/2.5 ha) Residential-Low Density (< 0.5 unit/acre or unit/2.5 ha) Commercial Industrial Transportation Institutional Table A-5: Impervious fractions for different urban land types in Madison and Milwaukee, WI and Marquett, MI. Urban Land Type Directly connected impervious Indirectly connected impervious Pervious Residential-High Density Residential-Medium Density Residential-Low Density Regional Mall Strip Mall Industrial-Heavy Industrial-Light Airport Institutional Park

436 50 SWAT USER S MANUAL, VERSION 2000 A.5.2 CURB LENGTH DENSITY Curb length may be measured directly by scaling the total length of streets off of maps and multiplying by two. To calculate the density the curb length is divided by the area represented by the map. The curb length densities assigned to the different land uses in the database were calculated by averaging measured curb length densities reported in studies by Heaney et al. (1977) and Sullivan et al. (1978). Table A-6 lists the reported values and the averages used in the database. Table A-6: Measured curb length density for various land types Location: Tulsa, 10 Ontario Average of OK Cities two values SWAT database categories Land type km/ha km/ha km/ha using average value: Residential All Residential Commercial Commercial Industrial Industrial Park Open Institutional Transportation, Institutional A.5.3 WASH-OFF COEFFICENT The database assigns the original default value, 0.18 mm -1, to the wash-off coefficient for all land types in the database (Huber and Heaney, 1982). This value was calculated assuming that 13 mm of total runoff in one hour would wash off 90% of the initial surface load. Using sediment transport theory, Sonnen (1980) estimated values for the wash-off coefficient ranging from mm -1. Huber and Dickinson (1988) noted that values between and mm -1 for the wash-off coefficient give sediment concentrations in the range of most observed values. This variable is used to calibrate the model to observed data. A.5.4 MAXIMUM SOLID ACCUMULATION AND RATE OF ACCUMULATION The shape of the solid build-up equation is defined by two variables: the maximum solid accumulation for the land type and the amount of time it takes to build up from 0 kg/curb km to one-half the maximum value. The values assigned

437 APPENDIX A: DATABASES 51 to the default land types in the database were extrapolated from a study performed by Sartor and Boyd (1972) in ten U.S. cities. They summarized the build-up of solids over time for residential, commercial, and industrial land types as well as providing results for all land types combined (Figure A-1). Figure A-1: Solid loading as a function of time (Sartor and Boyd, 1972) The lines plotted in Figure A-1 were adapted for use in the database. Table A-7 lists maximum load values and time to accumulate half the maximum load that were derived from the graph. The assignment of values to the different land types is provided in the table also. Table A-7: Maximum solid load and accumulation time (from Sartor and Boyd, 1972). Maximum loading time to accumulate ½ maximum load SWAT database categories Land type kg/curb km days using value: Residential All Residential Commercial Commercial Industrial Industrial All land types Transportation/Institutional

438 52 SWAT USER S MANUAL, VERSION 2000 A.5.5 NUTRIENT CONCENTRATION IN SOLIDS For the default land types in the database, nutrient concentrations in the solids were extrapolated from a nationwide study by Manning et al. (1977). The data published by Manning is summarized in Table A-8. Three concentration values are required: total nitrogen (mg N/kg), nitrate nitrogen (mg NO 3 -N/kg), and total phosphorus (mg P/kg). Manning provided total nitrogen values for all of his land use categories, nitrate values for one land use category and mineral phosphorus values for all the land use categories. To obtain nitrate concentrations for the other land use categories, the ratio of NO 3 -N to total N for commercial areas was assumed to be representative for all the categories. The nitrate to total N ratio for commercial land was multiplied by the total N concentrations for the other categories to obtain a nitrate concentration. The total phosphorus concentration was estimated by using the ratio of organic phosphorus to orthophosphate provided by the Northern Virginia Planning District Commission (1979). Total phosphorus loads from impervious areas are assumed to be 75 percent organic and 25 percent mineral. Table A-9 summarizes the assignment of values to the default land types in the urban database. Table A-8: Nationwide dust and dirt build-up rates and pollutant fractions (Manning et al., 1977) Pollutant Land Use Category Single Family Residential Mult. Family Residential Commercial Industrial All Data Dust & Dirt Accumulation mean (kg/curb km/day) range # obs Total N-N mean (mg/kg) range # obs NO 3 mean (mg/kg) range # obs PO 4-P mean (mg/kg) range # obs

439 Table A-9: Nutrient concentration assignments for default land types Manning et al (1977) Modifications: Final Value: APPENDIX A: DATABASES 53 SWAT database categories using value: Total Nitrogen-N Single Fam Res. 460 ppm ppm Residential: Med/Low & Low Mult. Fam. Res. 550 ppm ppm Residential: Med. & High Commercial 420 ppm ppm Commercial Industrial 430 ppm ppm Industrial All Data 480 ppm ppm Transportation/Institutional Nitrate-N: multiply reported value by fraction of weight that is nitrogen to get NO 3 -N Single Fam Res. (5.5/420) x ppm Residential: Med/Low & Low Mult. Fam. Res. (5.5/420) x ppm Residential: Med. & High Commercial 5.5 ppm ppm Commercial Industrial (5.5/420) x ppm Industrial All Data (5.5/420) x ppm Transportation/Institutional Total Phosphorus-P: assume PO 4 -P is 25% of total P Single Fam Res. 49 ppm PO 4 -P 49/(.25) 196 ppm Residential: Med/Low & Low Mult. Fam. Res. 58 ppm PO 4 -P 58/(.25) 232 ppm Residential: Med. & High Commercial 60 ppm PO 4 -P 60/(.25) 240 ppm Commercial Industrial 26 ppm PO 4 -P 26/(.25) 104 ppm Industrial All Data 53 ppm PO 4 -P 53/(.25) 212 ppm Transportation/Institutional A.6 REFERENCES American Society of Agricultural Engineers, Manure production and characteristics, p In ASAE Standards 1998, 45 th edition, Section D ASAE, St. Joseph. Bailey, L.H The Standard cyclopedia of horticulture. The Macmillan Publishing Co., New York, N.Y. Duncan, W.G. and Hesketh, J.D Net photosynthesis rates, relative leaf growth rates and leaf numbers of 22 races of maize grown at eight temperatures. Crop Sci. 8: Heaney, J.P., W.C. Huber, M.A. Medina, Jr., M.P. Murphy, S.J. Nix, and S.M. Haasan Nationwide evaluation of combined sewer overflows and urban stormwater discharges Vol. II: Cost assessment and impacts. EPA- 600/ b (NTIS PB ), U.S. Environmental Protection Agency, Cincinnati, OH. Huber, W.C. and R.E. Dickinson Storm water management model, version 4: user s manual. U.S. Environmental Protection Agency, Athens, GA. Huber, W.C. and J.P. Heaney Chapter 3: Analyzing residual discharge and generation from urban and non-urban land surfaces. p In D.J.

440 54 SWAT USER S MANUAL, VERSION 2000 Basta and B.T. Bower (eds). Analyzing natural systems, analysis for regional residuals environmental quality management. John Hopkins University Press, Baltimore, MD. Knisel, W.G. (ed) GLEAMS: Groundwater loading effects of agricultural management systems, Version UGA-CPES-BAED Publication No. 5. University of Georgia, Tifton, GA. Leonard, R.A. and W.G. Knisel Evaluating groundwater contamination potential from herbicide use. Weed Tech. 2: Manning, M.J., R.H. Sullivan, and T.M. Kipp Nationwide evaluation of combined sewer overflows and urban stormwater discharges Vol. III: Characterization of discharges. EPA-600/ c (NTIS PB ) U.S. Environmental Protection Agency, Cincinnati, OH. Martin, J.H., W.H. Leonard and D.L. Stamp Principles of field crop production, 3rd edition. Macmillan Publishing Co., Inc., New York. Northern Virginia Planning District Commission Guidebook for screening urban nonpoint pollution management strategies: a final report prepared for Metropolitan Washington Council of Governments. Northern Virginia Planning District Commission, Falls Church, VA. Palmstrom, N. and W.W. Walker, Jr P8 Urban Catchment Model: User s guide, program documentation, and evaluation of existing models, design concepts and Hunt-Potowomut data inventory. The Narragansett Bay Project Report No. NBP Sartor, J.D. and G.B. Boyd Water pollution aspects of street surface contaminants. EPA-R (NTIS PB ) U.S. Environmental Protection Agency, Washington, DC. Sonnen, M.B Urban runoff quality: information needs. ASCE Journal of the Technical Councils 106(TC1): Sullivan, R.H., W.D. Hurst, T.M. Kipp, J.P. Heaney, W.C. Huber, and S.J. Nix Evaluation of the magnitude and significance of pollution from urban storm water runoff in Ontario. Research Report No. 81, Canada-

441 APPENDIX A: DATABASES 55 Ontario Research Program, Environmental Protection Service, Environment Canada, Ottawa, Ontario. Watson, D.J The dependence of net assimilation rate on leaf area index. Ann. Bot. N.S. 22: Wauchope, R.D., T.M. Buttler, A.G. Hornsby, P.W.M. Augustijn-Beckers, and J.P. Burt The SCS/ARS/CES pesticide properties database for environmental decision-making. Environ. Contam. Toxicol. Reviews 123: Willis, G.H. and L.L. McDowell Pesticide persistence on foliage. Environ. Contam. Toxicol. Reviews 100: Willis, G.H., W.F. Spencer, and L.L. McDowell Chapter 18: The interception of applied pesticides by foliage and their persistence and washoff potential. p In W.G. Knisel (ed). CREAMS: A field scale model for chemicals, runoff, and erosion from agricultural management systems, Vol. 3. U.S. Dept. of Agri., Sci., and Education Adm., Conservation Research Report No. 26. U.S. Government Printing Office, Washington, D.C.

442 56 SWAT USER S MANUAL, VERSION 2000

443 APPENDIX B EXAMPLE WATERSHED CONFIGURATIONS The watershed configuration file defines the spatial relationship of objects within the watershed. The three techniques used to subdivide a watershed are the subwatershed discretization, the hillslope discretization, and the grid cell discretization. The following sections describe how to set up the watershed configuration file for each of the different discretization techniques.

444 B.1 SUBWATERSHED DISCRETIZATION The subwatershed discretization divides the watershed into subbasins based on topographic features of the watershed. This technique preserves the natural flow paths, boundaries, and channels required for realistic routing of water, sediment and chemicals. All of the GIS interfaces developed for SWAT use the subwatershed discretization to divide a watershed. The number of subbasins chosen to model the watershed depends on the size of the watershed, the spatial detail of available input data and the amount of detail required to meet the goals of the project. When subdividing the watershed, keep in mind that topographic attributes (slope, slope length, channel length, channel width, etc.) are calculated or summarized at the subbasin level. The subbasin delineation should be detailed enough to capture significant topographic variability within the watershed. Once the subbasin delineation has been completed, the user has the option of modeling a single soil/land use/management scheme for each subbasin or partitioning the subbasins into multiple hydrologic response units (HRUs). Hydrologic response units are unique soil/land use/management combinations within the subbasin which are modeled without regard to spatial positioning. When multiple HRUs are modeled within a subbasin, the land phase of the hydrologic cycle is modeled for each HRU and then the loadings from all HRUs within the subbasin are summed. The net loadings for the subbasin are then routed through the watershed channel network. HRUs are set up in the subbasin general attribute file (.sub). The following sections demonstrate how to create a SWAT watershed configuration file using the subwatershed discretization.

445 B.1.1 SUBWATERSHED DISCRETIZATION: 3 SUBBASINS Assume we have a watershed with 3 subbasins as illustrated in Figure B-1. Figure B-1: Subwatershed delineation Step 1: Write the subbasin command for each subbasin. (This command simulates the land phase of the hydrologic cycle.) column 1 column 2 column 3 column 4 column 5 column 6 column 7 space 1-10 space space space space space space space subbasin subbasin subbasin Writing subbasin in space 1-10 is optional. The model identifies the configuration command by the code in column 1. The option of writing the command in space 1-10 is provided to assist the user in interpreting the configuration file. Column 2 is the hydrograph storage location number (array location) where data for the loadings (water, sediment, chemicals) from the subbasin are stored. Column 3 is the subbasin number. The subbasin number tells SWAT which input files listed in file.cio contain the data used to model the subbasin. Subbasin numbers are assigned sequentially in file.cio to each pair of lines after line 14. The files listed on lines 15 & 16 of file.cio are used to model subbasin 1, the files listed on lines 17 & 18 of file.cio are used to model subbasin 2, the files listed on lines 19 & 20 of file.cio are used to model subbasin 3, and so on.

446 Step 2a: Route the stream loadings through the reach network. Begin by routing the headwater subbasin loadings through the main channel of the respective subbasin. (Headwater subbasins are those with no subbasins upstream.) Referring to Figure B-1, assume that subbasins 1 and 2 are upstream of subbasin 3. This would make subbasins 1 and 2 headwater subbasins. column 1 column 2 column 3 column 4 column 5 column 6 column 7 space 1-10 space space space space space space space subbasin subbasin subbasin route route As mentioned in the last step, column 1 is used to identify the command. Column 2 is the hydrograph storage location number identifying the location where results from the route simulation are placed. Column 3 provides the number of the reach, or main channel, the inputs are routed through. The number of the reach in a particular subbasin is the same as the number of the subbasin. Column 4 lists the number of the hydrograph storage location containing the data to be routed through the reach. The loadings from subbasin 1 are stored in hydrograph storage #1 and the loadings from subbasin 2 are stored in hydrograph storage #2. Column 6 lists the fraction of overland flow. For the subwatershed discretization, this value will always be zero flow is always considered to be channelized before entering the next subbasin. Step 2b: Route the stream loadings through the reach network. Use the add and route commands to continue routing through the watershed. For this example, the water, sediment and chemicals flowing out of subbasins 1 and 2 and the loadings from subbasin 3 must be added together and routed through the main channel of subbasin 3. The loadings from the outlet of subbasin 1 are stored in hydrograph location #4; the loadings from the outlet of subbasin 2 are stored in hydrograph location #5; and the loadings from subbasin 3 are stored in hydrograph location #3.

447 column 1 column 2 column 3 column 4 column 5 column 6 column 7 space 1-10 space space space space space space space subbasin subbasin subbasin route route add add route The add command is specified in column 1 by the number 5. The hydrograph storage location numbers of the 2 data sets to be added are listed in columns 3 and 4. The summation results are stored in the hydrograph location number given in column 2. Step 3: Once the stream loadings have been routed to the watershed outlet, append a finish command line to signify the end of the watershed routing file. column 1 column 2 column 3 column 4 column 5 column 6 column 7 space 1-10 space space space space space space space subbasin subbasin subbasin route route add add route finish 0

448 B.1.2 SUBWATERSHED DISCRETIZATION: SAVING SIMULATION RESULTS FOR DOWNSTREAM RUNS If the watershed of interest is split up into subwatersheds that are modeled with separate SWAT runs, the outflow from the upstream subwatersheds must be saved in a file using the save command. This data will then be input into the SWAT simulation of the downstream portion of the watershed using a recday command. In example B.1.1, the outflow from the watershed is stored in hydrograph location #8, so this is the data we need to store in a daily file for use in another SWAT simulation. The watershed configuration modified to store outflow data is: column 1 column 2 column 3 column 4 column 5 column 6 column 7 space 1-10 space space space space space space space subbasin subbasin subbasin route route add add route save 9 8 finish 0 The save command is specified in column 1 by the number 9. Column 2 lists the hydrograph storage location of the data to be saved in the event output file. The name of the event output file is listed in file.cio and usually possesses the.eve file extension. Only one save command is allowed in a simulation. The event file output is described in Chapter 44.

449 B.1.3 SUBWATERSHED DISCRETIZATION: INCORPORATING POINT SOURCE/UPSTREAM SIMULATION DATA Point source and upstream simulation data may be incorporated into a run using one of four record commands: recday, recmon, recyear, and reccnst. The recday command reads data from a file containing loadings of different constituents for each day of simulation. The recmon command reads data from a file containing average daily loadings for each month. The recyear command reads data from a file containing average daily loadings for each year. The reccnst command reads in average annual daily loadings. The record command chosen to read in the data is a function of the detail of data available. To read in upstream simulation data, the recday command is always used. Assuming the subbasin delineation in Figure B-1 is used with one point source (sewage treatment plants) per subbasin, the watershed configuration file is: column 1 column 2 column 3 column 4 column 5 column 6 column 7 space 1-10 space space space space space space space subbasin subbasin subbasin recday sub1.pnt add route recday sub2.pnt add route add recday sub3.pnt add add route finish 0 All of the record commands require 2 lines. On the first line, column 1 contains the command code for the specific record command, column 2 contains the hydrologic storage location where the data from the file is stored, and column 3 contains the file number. A different file number must be used for each point source of a specific type (e.g., all recday commands must have unique file numbers). The second line lists the name of the file containing the input data. A description of the four types of record files is given in Chapter 43.

450 B.1.4 SUBWATERSHED DISCRETIZATION: INCORPORATING RESERVOIRS Water bodies located along the main channel are modeled using reservoirs. To incorporate a reservoir into a simulation, a routres command is used. There is no limitation on the number of reservoirs modeled. Assuming the subbasin delineation in Figure B-1 is used with one reservoir located at the outlet, the watershed configuration file is: space 1-10 space space space space space space space subbasin subbasin subbasin route route add add route routres lakefork.res lakefork.lwq finish 0 The routres command requires 2 lines. On the first line, the routres command is identified with the number 3 in column 1. Column 2 gives the hydrograph storage location where outflow data from the reservoir is stored. Column 3 lists the reservoir number. Column 4 gives the hydrograph storage location of the data to be routed through the reservoir. Column 5 lists the subbasin with which the reservoir is associated. A different reservoir number must be assigned to each reservoir and the numbers should be sequential beginning with 1. The second line lists two file names, the reservoir input file (.res) and the reservoir water quality file (.lwq).

451 B.1.5 SUBWATERSHED DISCRETIZATION: SAVING SIMULATION RESULTS FOR ONE LOCATION Users often need to compare streamflow, sediment, nutrient and/or pesticide levels predicted by the model with levels measured in the stream. To save daily or hourly model output data for a particular location on the stream, the saveconc command is used. Assume there is a stream gage at the outlet of the watershed shown in Figure B-1 and that we want to compare simulated and measured streamflow for this location. Hydrograph storage location #8 stores the flow data for this location in the watershed, so this is the data we need to process to create the saveconc output file. The watershed configuration modified to process data for this location is: column 1 column 2 column 3 column 4 column 5 column 6 column 7 space 1-10 space space space space space space space subbasin subbasin subbasin route route add add route saveconc strgage.out finish 0 The saveconc command requires 2 lines. On the first line, the saveconc command is identified with the number 14 in column 1. Column 2 gives the hydrograph storage location of the data to be processed for the saveconc output file. Column 3 lists the file number. Column 4 gives the print frequency (daily or hourly). More than one saveconc command may be used in a simulation. A different file number must be assigned to each saveconc output file and the file numbers should be sequential beginning with 1. The second line lists the name of the saveconc output file. The saveconc command differs from the save command in that it converts the mass amounts of water, sediment, and chemicals to units that are commonly used to report measured values. Output files produced by the saveconc command cannot be read into another SWAT run the save command must be used to produce input for another simulation.

452 B.2 HILLSLOPE DISCRETIZATION The hillslope discretization allows overland flow from one subbasin to flow onto the land area of another subbasin. As the name implies, this discretization allows SWAT to model hillslope processes. The hillslope discretization incorporates more detail into the watershed configuration file than the subwatershed discretization. The number of subbasins chosen to model the watershed will depend on the size of the watershed, the spatial relationship of different land uses to one another, the spatial detail of available input data and the amount of detail required to meet the goals of the project. Because this discretization scheme places more emphasis on land use, the subbasins are delineated so that there is one land use and soil per subbasin. The hillslope discretization can be combined with the subwatershed discretization to provide detailed modeling of particular land use areas while modeling the remaining land use areas with the more generalized approach. Useful applications of this discretization include: watersheds with concentrated animal feeding operations, watersheds where detailed modeling of filter strips is desired, and microwatersheds where the scale of the simulation allows detail about relative land use positions to be incorporated.

453 B.2.1 HILLSLOPE DISCRETIZATION: MODELING A DAIRY OPERATION Assume a microwatershed containing a concentrated animal feeding operation with several different areas of land use and management is being modeled. Milking cows are confined in stalls. All waste produced by the milking cows is collected and applied over manure application fields also located in the microwatershed. The dry cows are kept in pastures. The pastured cows keep the areas adjacent to the farm buildings denuded of grass. Runoff from the denuded areas flows onto the pasture. Runoff from the pasture flows into a filter strip or buffer zone. Runoff exiting the filter strip enters the stream. The manure application fields are isolated from the rest of the dairy operation. Runoff from the application fields flows into a filter strip, and then enters the steam. Figure B-2 illustrates the relationship of land areas in the dairy operation. Areas of the microwatershed outside of the daily operation are forested. Figure B-2: Spatial positioning of land areas in dairy operation. This microwatershed will be divided into 6 subbasins: Subbasin 1: loafing area Subbasin 2: pasture Subbasin 3: filter strip associated with pasture Subbasin 4: waste application area Subbasin 5: filter strip associated with waste application area Subbasin 6: completely channelized stream and forest in microwatershed

454 Step 1: Write the subbasin command for each subbasin. (This command simulates the land phase of the hydrologic cycle.) column 1 column 2 column 3 column 4 column 5 column 6 column 7 space 1-10 space space space space space space space subbasin subbasin subbasin subbasin subbasin subbasin Writing subbasin in space 1-10 is optional. The model identifies the configuration command by the code in column 1. The option of writing the command in space 1-10 is provided to assist the user in interpreting the configuration file. Column 2 is the hydrograph storage location number (array location) where data for the loadings (water, sediment, chemicals) from the subbasin are stored. Column 3 is the subbasin number. The subbasin number tells SWAT which input files listed in file.cio contain the data used to model the subbasin. Subbasin numbers are assigned sequentially in file.cio to each pair of lines after line 14. The files listed on lines 15 & 16 of file.cio are used to model subbasin 1, the files listed on lines 17 & 18 of file.cio are used to model subbasin 2, the files listed on lines 19 & 20 of file.cio are used to model subbasin 3, and so on. Step 2: Route the stream loadings. The hillslope discretization differs from the subwatershed discretization primarily in the method used to route loadings through the watershed. Loadings from subbasins are not routed through the subbasin if the flow leaving the subbasin is not completely channelized. For our example, subbasin 6 is the only subbasin completely channelized. Assume that runoff from the denuded areas (subbasin 1) is sheet flow, i.e. there are no rills, gullies or any other evidence of channelized flow in the denuded area. Runoff from the denuded area will be routed to the pasture (subbasin 2) using the route command: column 1 column 2 column 3 column 4 column 5 column 6 column 7 space 1-10 space space space space space space space route As mentioned in the last step, column 1 is used to identify the command. Column 2 is the hydrograph storage location number identifying the location where results from the channelized portion of the route simulation are placed. In this instance, because there is no channelized flow, this storage location will contain no data.

455 Column 3 provides the number of the reach or subbasin the inputs are routed through. (The number of the reach in a particular subbasin is the same as the number of the subbasin.) The fraction of the loadings classified as overland flow are applied to the subbasin land area while the fraction of the loadings classified as channelized flow are routed through the main channel of the subbasin and are exposed to in-stream processes. Channelized flow has no interaction with the land area in the subbasin. Column 4 lists the number of the hydrograph storage location containing the data to be routed through the reach. The loadings from subbasin 1 are stored in hydrograph storage #1. Column 6 lists the fraction of overland flow. For completely channelized flow this fraction is zero. For 100% overland flow, this fraction is The entire watershed configuration to this point looks like: column 1 column 2 column 3 column 4 column 5 column 6 column 7 space 1-10 space space space space space space space subbasin subbasin subbasin subbasin subbasin subbasin route Assume that runoff from the pasture is slightly channelized (10% channels). Flow from the pasture is routed to the filter strip (subbasin 3) using the next route command: column 1 column 2 column 3 column 4 column 5 column 6 column 7 space 1-10 space space space space space space space subbasin subbasin subbasin subbasin subbasin subbasin route route As mentioned previously, hydrograph storage location #7 contains no data because none of the runoff entering subbasin 2 is channelized. Consequently, when routing runoff leaving subbasin 2, this hydrograph storage location can be ignored. For subbasin 3, however, there will be data in hydrograph storage location #8 from the 10% of flow that is channelized in that subbasin. Loadings from subbasin 3 will enter the main stream in subbasin 6. The total loadings from the denuded area/pasture/filter strip section of the microwatershed are determined

456 by adding the runoff generated from subbasin 3 and the channelized flow routing results. column 1 column 2 column 3 column 4 column 5 column 6 column 7 space 1-10 space space space space space space space subbasin subbasin subbasin subbasin subbasin subbasin route route add The loadings from simulation of the land phase of the hydrologic cycle in subbasin 3 are stored in hydrograph storage location #3 and the loadings from simulation of the channelized flow in subbasin 3 are stored in hydrograph location #8. The add command is specified in column 1 by the number 5. The hydrograph storage location numbers of the 2 data sets to be added are listed in columns 3 and 4. The summation results are stored in the hydrograph location number given in column 2. Net loadings from the denuded area/pasture/filter strip is stored in hydrograph location #9. Assume that the manure application area (subbasin 4) is well managed and all runoff from this area is overland flow (no channelized flow). To route flow from the application area to the associated filter strip (subbasin 5) a route command will be appended to the end of the configuration: column 1 column 2 column 3 column 4 column 5 column 6 column 7 space 1-10 space space space space space space space subbasin subbasin subbasin subbasin subbasin subbasin route route add route Hydrograph storage location #10 contains no data because none of the runoff entering subbasin 5 is channelized. Consequently, when routing runoff leaving subbasin 5, this hydrograph storage location can be ignored. Net loadings from the waste application area/filter strip section of the watershed is stored in hydrograph location #5.

457 Flow through subbasin 6, which contains the stream, is completely channelized. All of the loadings for the stream must be summed together and then routed through the stream. There are 3 sources of loading to the stream: the denuded area/pasture/filter strip (hydrograph location #9), the waste application area/filter strip (hydrograph location #10), and the forest land area (hydrograph location #6). Add commands are used to sum the loadings. column 1 column 2 column 3 column 4 column 5 column 6 column 7 space 1-10 space space space space space space space subbasin subbasin subbasin subbasin subbasin subbasin route route add route add add Flow is routed through the stream using a route command: column 1 column 2 column 3 column 4 column 5 column 6 column 7 space 1-10 space space space space space space space subbasin subbasin subbasin subbasin subbasin subbasin route route add route add add route

458 Step 3: Once the stream loadings have been routed to the watershed outlet, append a finish command line to signify the end of the watershed routing file. column 1 column 2 column 3 column 4 column 5 column 6 column 7 space 1-10 space space space space space space space subbasin subbasin subbasin subbasin subbasin subbasin route route add route add add route finish 0

459 B.2.2 HILLSLOPE DISCRETIZATION: COMBINING WITH SUBWATERSHED DISCRETIZATION The hillslope discretization is a very detailed discretization scheme and is suited to small watersheds. However, it can be used in combination with the subwatershed discretization to provide detailed simulation of certain land uses in a large watershed whose spatial relationships are important to the study. As an example, assume that the dairy operation described in Section B.2.1 is located in a headwater region of the watershed example used in Section B.1. Figure B-3 illustrates the location of the dairy in the larger watershed. (Assume the microwatershed modeled in Section B.2.1 is subbasin B in Figure B-3.) Figure B-3: Watershed with dairy operation There are two options that may be used to combine the detailed modeling of the dairy with the less detailed modeling of the other land uses in the watershed. The first option is to model the dairy in a separate simulation and save the loadings from the microwatershed using the save command. These daily loadings will then be read into the simulation of the larger watershed using a recday command. The second option is to merge the watershed configuration given in Section B.2.1 with the watershed configuration given Section B.1.1