Technical Memorandum 2 Summary of Model Configuration Prepared for Jordan Watershed Modeling

Transcription

1 Technical Memorandum 2 Prepared for Jordan Watershed Modeling Prepared for Triangle J Council of Governments NC Division of Water Quality NSAB Model Subcommittee Prepared by 3200 Chapel Hill-Nelson Hwy, Suite 105 PO Box Research Triangle Park, NC 27709

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3 Contents List of Tables... iii List of Figures... iv 1 Introduction LSPC Hydrology Representation LSPC Water Quality Representation Simulation Period Calibration Period Validation Period Watershed Representation Model Subwatershed Delineation Watershed Physical Characteristics Land Elevation Water Reaches Lakes Low Head Dams Hydrologic Response Units Soils and Geology Land Use HRU Creation Model Representation of HRUs Other HRU/RMU Physical Characteristics HRU Simulation Atmospheric Forcing Files Direct Inputs NPDES Discharges Water Withdrawals Atmospheric Deposition of Nutrients Nitrogen Wet Deposition Nitrogen Dry Deposition Sanitary Sewer Overflows...43 i

4 6 Indirect Inputs Decentralized (Onsite and Cluster) Wastewater Systems Setup for Modeled Constituents Reach Group Water Temperature Dissolved Oxygen Sediment Nutrients and Plankton...59 References...62 ii

5 Tables Table 1-1. Hydrology Parameters for LSPC Model...3 Table 2-1. Example of an FTable used by LSPC Table 2-2. Comparison of Observed and Calculated Bankfull Widths and Depths Table 2-3. Reservoirs Included in the LSPC Watershed Model Table 2-4. Parameters for Calculating Lake FTables with the EPA Tool Table 2-5. Low Head Dams in the Jordan Lake Watershed Table 3-1. HSG and Geology Classification Schema Table 3-2. Model Land Use and Land Cover (LULC) Input Comparisons Table 3-3. Jordan Lake Watershed HRU s Table 3-4. Jordan Lake Watershed RMUs and Reclassifications Table 3-5. Jordan Lake Watershed Model Simulated RMUs Table 3-6. Model Land Use and Land Cover (LULC) Reclassified Input Comparisons Table 3-7. Length and Slope of the Overland Flow Plane for each RMU Table 3-8. Comparison of 1999 and 2010 Test Models Simulated Output Table 3-9. Comparison of 1999 and Time Varying Land Use Test Models Simulated Output Table Comparison of 2010 and Time Varying Land Use Test Models Simulated Output Table 4-1. Weather Files used for the Table 5-1. List of Actively Discharging NPDES Facilities used as Model Inputs Table 5-2. List of Historically Discharging NPDES Facilities used as Model Inputs Table 5-3. Water Withdrawal Information Obtained from the OASIS Model Table 5-4. Atmospheric Wet Deposition by Constituent and Month for Model Input Table 5-5. Atmospheric Wet Deposition by Constituent and Season for Model Input Table 6-1. Per Capita Loading Factors for Decentralized Wastewater Systems Table 6-2. Summary of Data Sources used to Estimate System Type Distribution Table 6-3. Design Flows and Reduction Efficiencies for Different System Types Table 6-4. Pollutant Attenuation Rates for Different System Types Table 6-5. Pollutant Speciation Assumptions Table 6-6. Example TN Load Worksheet for Single Subwatershed Table 6-7. Example Decentralized Wastewater Input Data for Single Subwatershed Table 7-1. Hourly Lapse Rates used in the LSPC Model iii

6 Figures Figure 1-1. Schematic of LSPC Hydrology Components and Pathways...2 Figure 1-2. Schematic Representation of Key Nutrient Simulation Processes...4 Figure 2-1. Model Subwatersheds and HUC-12 comparisons...8 Figure 2-2. Waterways and Waterbodies Pertinent to the Jordan Watershed model...9 Figure 2-3. Channel Geometry utilized for the LSPC watershed model Figure 2-4. Lakes and Reservoirs in the Jordan Lake Watershed Model Figure 2-5. Location of Low Head Dams in the Jordan Lake Watershed Figure 3-1. Hydrologic Soil Groups by Geology used for HRU Development Figure 3-2. Model Land Use and Land Cover (LULC) Inputs for 1999 (Baseline Model Scenario) Figure 3-3. Model Land Use and Land Cover (LULC) Inputs for 2010 (Existing Model Scenario) Figure 4-1. Meteorological Station Assignments Figure 5-1. Currently Active and Historically Active NPDES Permits in the Watershed Model Figure 5-2. NADP NTN and EPA CASTNET Monitoring Stations near Jordan Lake Watershed Figure and 2011 NTN Isopleths of Total Wet Deposition of N Figure 5-4. NADP NTN Precipitation-Weighted Annual Average Concentration of Ammonia as N.. 39 Figure 5-5. NADP NTN Precipitation-Weighted Annual Average Concentration of Nitrate as N Figure 5-6. NADP NTN Precipitation-Weighted Annual Average Concentration of Inorganic N Figure 5-7. NADP NTN Precipitation-Weighted Annual Average Inorganic N Loading Rate Figure 5-8. NADP NTN Precipitation-Weighted Monthly Average Concentrations Figure 5-9 CASTNET Annual Average Inorganic N Loading Rate Figure CASTNET Seasonal Average Inorganic N Loading Rate iv

7 1 Introduction This is the second technical memorandum prepared documenting the development of a dynamic flow and water quality watershed model, the Loading Simulation Program in C++ or LSPC, which is being developed for the Jordan Lake watershed in coordination with the North Carolina Division of Water Quality (DWQ) and the Nutrient Scientific Advisory Board (NSAB). The first technical memorandum (Tetra Tech, 2013) provided a summary of the data compiled to support model setup and calibration. This memorandum describes how the compiled data were used to configure LSPC for the Jordan Lake watershed. Data compilation and model configuration have been performed in accordance with the model Quality Assurance Project Plan (QAPP) developed to guide model development (Tetra Tech, 2012). LSPC uses Hydrologic Simulation Program FORTRAN (HSPF) algorithms for simulating watershed hydrology, erosion, and water quality processes, as well as in-stream transport processes ( ). LSPC integrates a geographical information system (GIS), comprehensive data storage and management capabilities, the original HSPF algorithms, and a data analysis/post-processing system into a convenient, PC-based, Windows interface. LSPC s algorithms are identical to a subset of those in the HSPF model. LSPC is freely distributed by EPA s Office of Research and Development in Athens, Georgia, and is a component of EPA s National TMDL Toolbox ( A key advantage of LSPC over HSPF and other watershed models is a data management feature that uses a Microsoft Access database to manage model data and weather files for driving the simulation. This provides great flexibility for data transfer and manipulation, which is critical for complex watershed studies. LSPC was designed specifically to handle very large-scale watershed and receiving water modeling applications at a high resolution. The model has been successfully used to model watershed systems composed of well over 1,000 sub-watersheds and at least as many individual stream elements. The highly adaptable design and programming architecture allows for future modular additions based on specific project needs. Furthermore, the entire system is designed to simplify model sharing. 1.1 LSPC HYDROLOGY REPRESENTATION Watershed hydrology plays an important role in the determination of nonpoint source flow and ultimately nonpoint source loadings to a waterbody. The watershed model must appropriately represent the spatial and temporal variability of hydrological characteristics within a watershed. Key hydrological characteristics include interception storage capacities, infiltration properties, evaporation and transpiration rates, and watershed slope and roughness. LSPC s algorithms are identical to those in the Hydrologic Simulation Program FORTRAN (HSPF). The LSPC/HSPF modules used to represent watershed hydrology include PWATER (water budget simulation for pervious land units) and IWATER (water budget simulation for impervious land units). A detailed description of relevant hydrological algorithms is presented in the HSPF (v12) User s Manual (Bicknell et al. 2004). For the Jordan Lake watershed model snow, utilizing the SNOW module, will not be simulated. A schematic of the LSPC hydrology model is provided in Figure 1-1. Rain falling toward the land first experiences interception storage (CEPSC). If there is space available in interception storage it is filled up and all remaining precipitation volume proceeds to the land surface. Once on the land surface water is divided into subsurface flow and surface flow by infiltration (INFILT). Any water not being infiltrated is divided between upper zone storage (UZSN), interflow (INTFW) and overland flow. If space exists in upper zone storage it is filled first before becoming interflow or overland flow. Overland flow travels directly to the stream and timing is based on the slope, length and Manning s n value of the overland flow plane. Interflow travels to the stream under the surface of the land and the timing of interflow outflow is 1

8 dependent on the interflow recession constant (IRC). Water in the upper zone storage is either evaporated or moves deeper into the soil profile through percolation. Infiltrated water first fills the capacity of lower zone storage (LZSN) and water is lost from lower zone storage through evapotranspiration (LZETP). Any remaining water then enters one of two groundwater storage components. Inactive groundwater (water not having the ability to become stream flow) is supplied by a value for DEEPFR. Active ground water storage is released to the stream through a groundwater recession constant (AGWRC). Water can be lost from both active groundwater storage and groundwater outflow by values supplied for AGWETP and BASETP respectively. The model simulates total actual ET by trying to fulfill PET by first removing water from baseflow outflow, then interception storage, then upper zone storage, then groundwater storage and finally lower zone storage. Some of the parameter values for the hydrology model are considered constant and others are allowed to vary by month but no parameters are allowed to vary by year. Table 1-1 provides the list of hydrology parameters and the variability that is be used for the Jordan Lake watershed model. During calibration these parameters are allowed to vary in the model and will be adjusted within reasonable constraints as outlined in Technical Note 6 (USEPA 2000). Initial parameters for model configuration were inferred from previous watershed modeling Tetra Tech has conducted in North Carolina in the High Rock Lake watershed and the Goose and Crooked Creek watersheds. Figure 1-1. Schematic of LSPC Hydrology Components and Pathways 2

9 Table 1-1. Hydrology Parameters for LSPC Model Parameter Definition Units Variability LZSN lower zone nominal soil moisture storage inches Constant INFILT index to the infiltration capacity of the soil in/hr Constant KVARY variable groundwater recession 1/inches Constant AGWRC base groundwater recession none Constant PETMAX air temperature below which e-t will is reduced deg F Constant PETMIN air temperature below which e-t is set to zero deg F Constant INFEXP exponent in the infiltration equation none Constant INFILD ratio between the maximum and mean infiltration capacities over the PLS none Constant DEEPFR fraction of groundwater inflow that will enter deep groundwater none Constant BASETP fraction of remaining potential e-t that can be satisfied from baseflow none Constant AGWETP fraction of remaining potential e-t that can be satisfied from active groundwater none Constant CEPSC interception storage capacity inches Monthly UZSN upper zone nominal storage inches Monthly NSUR Manning's n for the assumed overland flow plane none Monthly INTFW interflow inflow parameter none Monthly IRC interflow recession parameter none Monthly LZETP lower zone e-t parameter none Monthly 1.2 LSPC WATER QUALITY REPRESENTATION Once the LSPC watershed hydrology model is calibrated, the model is used to create a water quality model for the watershed. Many components of the water quality model were established during hydrology modeling. These components include watershed segmentation, meteorological data, HRUs/RMUs, reach characteristics, and point source discharges. The watershed water quality model includes all point and nonpoint source contributions. Nutrient loadings from point sources are represented by developing direct input time series, for each point source, using discharge monitoring report data. Non-point source nutrient loadings are represented by build-up and wash off algorithms and assigning nutrient concentrations to the interflow and groundwater flow paths. Nutrients in the stream experience dilutions, accumulations, assimilation, biochemical cycling, and transport downstream and out of the watershed. A general schematic of the water quality processes represented in LSPC is provided in Figure

10 Figure 1-2. Schematic Representation of Key Nutrient Simulation Processes 1.3 SIMULATION PERIOD A goal of the LSPC watershed model is to provide estimated annual and seasonal mass loads of nitrogen and phosphorus generated at-source and delivered to Jordan Lake in existence as of 2001 in the Jordan Lake watershed (baseline) and for the most recent time period feasible (current). The most recent time period feasible has been determined to be September 2012 due to USGS flow gaging data being considered provisional in October, November and December of The LSPC watershed model has been setup to simulate the conditions in the watershed from January 1, 1996 through September 30, To allow the model plenty of spin up time, for equilibration purposes, the first year of simulated output will not be considered Calibration Period Water supply protection and stormwater management regulations have evolved over time. Prior to 2002, few structural stormwater Best Management Practices (BMPs) were installed in the watershed other than detention for peak flow control. Few BMPs designed for water quality management were in existence during the baseline period of the model. Therefore model calibration will focus on that period. Model calibration for hydrology and water quality will be conducted from January 1, 1997 through December 31, This timeframe was chosen because it allows for the model to be calibrated for a full five year 4

11 period which provides a better opportunity for success in predicting future hydrological conditions. This time period also directly correlates with when the 1999 land use is being utilized by the model Validation Period Model validation for hydrology and water quality will be conducted from January 1, 2002 through September 30, This time period also directly correlates with when the 2010 land use is being utilized by the model. The following sections of this technical memorandum summarize how the LSPC model has been configured for the calibration and validation periods. 5

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13 2 Watershed Representation In order to evaluate the sources contributing to an impaired waterbody and to represent the spatial variability of those sources within the LSPC watershed model, the waterbodies contributing drainage area are represented by a series of hydrologically connected subwatersheds. Each subwatershed has a representative reach to receive runoff from the local subwatershed as well as receive the in-stream flow from any subwatersheds located upstream. 2.1 MODEL SUBWATERSHED DELINEATION NHDPlus Version 2 catchments in shapefile format provided the foundation for delineating the subwatersheds to be used in the Jordan Jurisdictional Allocation Model (Tetra Tech, 2013). The catchments were downloaded on October 12, 2012 from: The NHDPlus catchments are much smaller than the targeted size for ultimate model subwatersheds; however, in GIS it is more efficient to aggregate polygons than to split them along fine-scale drainage divides or at points of interest (e.g., confluences of interest, monitoring locations). In a few cases, manual editing to split NHDPlus catchments was needed to meet the goals of subsequent modeling efforts. To facilitate subsequent model calibration and validation, a process of aggregating the NHDPlus catchments was used to create model subwatersheds with the goal of having outlets at: Major water quality and/or stream flow monitoring stations Major regulatory boundaries Major waterbody outlets Major confluences Secondary objectives to be met through the catchment aggregation process were to minimize 1) subwatershed size ranges, and 2) variability in broad land use and land cover (LULC) groups (e.g., forest, agriculture, urban/suburban development). The aggregation process resulted in 152 model subwatersheds in total (compared to 56 HUC-12 watersheds that drain to Jordan Lake). The resultant model subwatersheds and descriptive statistics can be found in Figure 2-1. When comparing the final delineated watersheds pour points to the locations of hydrology and water quality calibration and validation stations used for the Jordan Lake watershed model it was noticed the four locations had two watersheds coming to a confluence at the station location. To overcome the issue of having to do numerous post processing exercises of summing flow, calculating and summing pollutant loads and subsequently calculating simulated pollutant concentrations in order to compare back to the observed data, small routing reaches were created. These reaches are used to compare the simulated results to the observed field data at those four locations and do not have an impact on the overall watershed simulation. 7

14 Figure 2-1. Model Subwatersheds and HUC-12 comparisons 2.2 WATERSHED PHYSICAL CHARACTERISTICS Land Elevation Digital Elevation Models (DEMs) are grid-based representations of the land surface of a particular area. There are a wide variety of resolutions available for the area of interest; however, higher resolution DEM datasets are memory intensive and can be limiting in use because of computer processing capabilities. The 30-meter resolution DEM provided as part of the NHDPlus Version 2 release is the most recently updated National Elevation Dataset (NED) release. Additionally, NHDPlus Version 2 also provides a conditioned DEM (HydroDEM) used to produce the NHDPlus Version 2 stream polyline and catchment polygon shapefiles ( These two DEMs are ideal for this project because there is complete alignment of NHDPlus catchments (and by extension model subwatersheds), DEM values, and NHDPlus Version 2 stream polylines maximizing the accuracy of model inputs with minimal processing effort. 8

15 2.2.2 Water Reaches Stream segments and lakes are represented in the model as water reaches. These reaches were created from the HydroDEM using ArcSWAT s automatic watershed delineation toolset (built upon ArcHydro tools). Because the NHDPlus Version 2 stream polylines and the HydroDEM are completely aligned, model reaches produced by ArcSWAT also match up perfectly with their NHDPlus Version 2 stream polyline counterparts. ArcSWAT allows the production of a significantly pared down reach coverage allowing for quick creation of model reaches by leaving out ancillary tributaries within each model subwatershed. For most map figures in this project a selection of the NHDPlus V2 stream polyline dataset (Figure 2-2) is being used to show continuous flow paths, as opposed to the disjointed look that can occur where model stream reaches are shown as straight line segments superimposed on land features. The NHDPlus Version 1 High-Resolution release was downloaded and used to identify major waterbodies of interest (ftp://nhdftp.usgs.gov/datasets/staged/states/filegdb/highresolution/). These waterbodies will be incorporated in their appropriate spatial location and represented by their surface area and storage in order to implicitly represent nutrient trapping/removal and altered timing of loads delivered downstream. Information provided about each reach for setting up the LSPC watershed model included the reach length, upstream elevation and downstream elevation. Figure 2-2. Waterways and Waterbodies Pertinent to the Jordan Watershed model 9

16 Reach Characteristics LSPC itself is not a hydraulic model. Instead, the stage-storage-discharge relationships for each stream reach are represented through a Functional Table (FTable). The FTable describes the hydraulic behavior of a waterbody segment by defining the functional relationship between water depth, surface area, water volume, and outflow in the segment. The assumption of a fixed depth-area-volume-outflow relationship rules out cases where flow reverses direction or where one reach influences another upstream of it in a time-dependent way. The routing technique falls in the class known as "storage routing" or "kinematic wave" methods. In these methods, momentum is not considered (USEPA, 2007). Table 2-1 provides an example of what an FTable for model input looks like (with allowance for potential output discharge to up to four different targets). If an Ftable is calculated and supplied into the models database then LSPC uses the supplied FTable otherwise it internally calculates the FTable from the supplied information when the model is loaded. Table 2-1. Example of an FTable used by LSPC RCHID DEPTH_FT AREA_AC VOL_AC-FT DISCH1_CFS DISCH2_CFS DISCH3_CFS DISCH4_CFS E FTables can be generated directly from the output of a hydraulic model such as HEC-RAS; however, such models are not available for the majority of stream reaches. Therefore, simpler default methods are used to generate FTables sufficient for evaluation of flow and pollutant concentrations and loads. The characteristics needed for each reach to estimate an FTable include reach length, reach slope, reach bankfull depth (DEP), reach bankfull width (WID), Manning s n, a reach bottom width factor (R1), slope of the sides of the overland flow channel (R2) and a floodplain width factor (W1). A schematic of the channel geometry in LSPC is provided in Figure 2-3. Reach length, upstream elevation and downstream elevation (to calculate reach slope) are obtained when creating the representative reach file during the watershed delineation process. Values for R1, R2 and W2 were left at default values of 0.2, 0.5 and 1.5 respectively. The assumed Manning s n value for all reaches in the model was Bankfull width and depth are estimated by using a Rosgen approach which uses the contributing upstream drainage area to calculate a theoretical width and depth. The Rosgen equation is as follows: Bankfull Depth, Width = a*contributing_area b Where (a) Width default = and Depth default = (b) Width default = and Depth default = 0.4 Initial bankfull width and depth calculations utilized the above stated default values. Detailed cross sectional information provided by the North Carolina Flood Mapping Program (NCFMP) for Alamance County were used to investigate if the default values provided reasonable estimates as compared to the field observations. The Haw River was checked at 7 locations and Reedy Fork Creek, Jordan Creek, Big Alamance Creek, Cane Creek and Haw Creek were each checked at one location (Table 2-2). The default values for bankfull width provided reasonable estimates when compared to field observations but bankfull 10

17 depth was too shallow. The exponent in the equation for bankfull depth was modified until an acceptable agreement was achieved between calculated and observed bankfull depth. The final exponent value used was For the streams an FTable is not supplied therefore one is generated each time the model is loaded and executed. Table 2-2. Comparison of Observed and Calculated Bankfull Widths and Depths SWS From Cross Section Measurement Initial Final Stream Name NCFMP Reference Bankfull Width (m) Bankfull Height (m) Width (m) Depth (m) Width (m) Depth (m) 109 Haw River A_HR_15X Haw River A_HR_17X Haw River A_HR_21X Haw River A_HR_26X Haw River A_HR_33X Haw River A_HR_40X Haw River A_HR_46X Reedy Fork A_RF_04X Jordan Creek A_SYC_04DSX Big Alamance A_GC_01X Cane Creek A_CC_10X Haw Creek A_HC_02X

18 R2 WID DEPINIT DEP 0.5 * W1 * WID R1 * WID Figure 2-3. Channel Geometry utilized for the LSPC watershed model Lakes There are 12 lakes or reservoirs within the Jordan Lake watershed that are explicitly simulated in the LSPC model. These are listed in Table 2-3 and shown spatially in Figure 2-4. Jordan Lake itself is not simulated in this project. Lake hydraulic behavior is also represented through FTables. Data from two different sources was used to help estimate FTables for the lake representation. DWQ provided Tetra Tech with access to the OASIS model of the Cape Fear River basin, which includes information on the stage-storage-area relationships of the reservoirs and also their normal operational range. Each lake with the data source listed as OASIS in Table 2-3 used the stage-storage-area relationship directly from the constructed FTable. Outflow characteristics were not provided so reservoir outflow will adjusted during the model calibration. USGS gages upstream of reservoirs will be used to calibrate the land use parameters and then USGS gages downstream will be used to adjust the stageoutflow relationship until an agreement is achieved between simulated and normal pool elevations and simulated and observed downstream flows. Four lakes included in this watershed model are not explicitly represented in OASIS. Each lake with the data source listed as Lake Assessment Reports in Table 2-3 used normal pool volumes and surface areas published in NCDENR (1992) and NCDENR (2009) along with weir width measurements made in Google Earth to help estimate the FTable. These FTables were calculated by using the Gray Infrastructure Tool as part of the HSPF BMP web Toolkit (USEPA, 2013). Each lake was considered to be a trapezoidal channel and provided to the tool were maximum channel depth, top channel width, channel side slope, channel length, channel Manning s n value, slope and outflow was represented by a broad crested weir where weir crest width and weir invert depth were supplied. The values used for each lake are provided in Table 2-4. Similar to the lakes represented by OASIS data reservoir outflow will be adjusted during the model calibration. Each of these values was determined by making measurements in GIS, calculating 12

19 them from the materials provided in the references or using best professional judgment. For the lakes an FTable is supplied in the model database therefore the model uses the supplied FTable each time the model is loaded and executed. Table 2-3. Reservoirs Included in the LSPC Watershed Model Name Normal Pool Volume (ac-ft) LSPC SWS Data Source Reidsville Lake OASIS Lake Brandt OASIS Lake Townsend OASIS Stony Creek Reservoir (aka Lake Burlington) OASIS Lake Cammack (Burlington Reservoir) Lake Assessment Reports Quaker Creek Reservoir (aka Graham-Mebane Reservoir) OASIS Lake Mackintosh OASIS Cane Creek Reservoir OASIS University Lake OASIS Lake Hunt Lake Assessment Reports Lake Higgins Lake Assessment Reports Lake Jeanette (aka Richland Lake) Lake Assessment Reports Table 2-4. Name Lake Cammack (Burlington Reservoir) Parameters for Calculating Lake FTables with the EPA Tool Depth (ft) Width (ft) Side Slope Length (ft) Mannings n Slope Weir Width(ft) Weir Invert (ft) , Lake Hunt , Lake Higgins , Lake Jeanette (aka Richland Lake) ,

20 Figure 2-4. Lakes and Reservoirs in the Jordan Lake Watershed Model Low Head Dams There are numerous low head dams located along the main-stem Haw River and its tributaries. Data provided by NCFMP were used to locate these low-head-dams in the Jordan Lake watershed. Once located, the NCFMP data was used to determine the weir height located at each location. It was found that weir height was generally the same as calculated bankfull height. The FTable for each watershed with a low head dam was modified by simply sliding the outflow data down the outflow column to the weir height used for each subwatershed and then supplying a value of zero for the outflow for water depths that are blocked from flowing by the dam. It was assumed that this approach would cause a reasonable expansion of volume in the watersheds with low head dams. Table 2-5 provides an inventory of the low head dams input into the Jordan Lake watershed model and Figure 2-5 shows their spatial location. Some model subwatersheds (SWS) contain more than one low head dam. In such cases, only the most downstream dam, which controls outflow from the reach, is represented in the model. For the low head dams an FTable is supplied in the model database therefore the model uses the supplied FTable each time the model is loaded and executed. 14

21 Table 2-5. Low Head Dams in the Jordan Lake Watershed Figure ID LSPC SWS Name NCFMP Reference Weir Height Bynum Dam Chatham County HECRAS unknown A_CC_05 N/A Unknown A_CC_ Unknown A_CC_ Saxapahaw Dam A_HR_ Puryer Dam A_HR_ Unknown A_HR_ Unknown A_BAC_ Unknown A_BB_ Unknown A_LAC_11 N/A Unknown A_WBCT Unknown A_MB_01 N/A Unknown A_MB_04 N/A Unknown A_EBC_ Old Stony A_SYC_02 N/A* Unknown A_SYC_03 N/A Irelands Dam A_HR_38 N/A Glencoe Mills Dam A_HR_ Unknown A_RF_ Altamahaw Mill Dam A_HR_ Unknown GU_HAW_03 N/A Unknown GU_BEN_05 N/A unknown GU_BEN_04 4 N/A* means already represented by a reservoir N/A means not represented due to being upstream of another dam 15

22 Figure 2-5. Location of Low Head Dams in the Jordan Lake Watershed 16

23 3 Hydrologic Response Units A key goal of the watershed model is to provide a tool that can provide accurate fine scale estimates of nutrient loads (both at source and delivered) for individual land uses and areas. This will provide the basis for allocations to individual jurisdictions. This can be accomplished by constructing the model using a hydrologic response unit (HRU) basis. During the calibration and validation process of the Jordan Lake watershed model each HRU will represent the intersection of land use/land cover, hydrologic soil group and geology. To ensure correct jurisdictional representation and load assessments, calibration/validation HRUs will be further distinguished by MS4 responsibility for the tabulation/load calculation run(s). 3.1 SOILS AND GEOLOGY The county-level Soil Survey Geographic (SSURGO) databases were downloaded and will be used to determine soil types and conditions for the model. However, SSURGO data has not yet been digitized for Caswell County. For this county the State Soil Geographic (STATSGO) data will be used to supplement SSURGO and ensure full model coverage soils input development. Both SSURGO and STATSGO are available for download directly from the US Department of Agriculture (USDA) at Two attributes from the SSURGO and STATSGO datasets will be used directly as model inputs Hydrologic Soil Group (HSG) and K factor which is a relative index of soil erodibility representing both the susceptibility of soil to erosion as well as the rate of runoff. These two attributes were extracted using the Soil Data Viewer tool for GIS available from Based on local knowledge of the region and geology, and the discrepancies between county-scale datasets (especially Chatham County around Jordan Lake), it was determined that it would be best to combine the HSGs into two classes (A + B) and (C + D) for modeling purposes. Additionally, there are areas in the soils data where HSG assignments are identified as Null. These areas generally represent water, rock and imperviousness in urban areas. More information on how these null areas were handled is provided in Section 0 below. For the Jordan Lake watershed model geology also plays an important factor. It was assumed that the portion of the watershed located in the Triassic Basins could potentially need different parameterization and assumptions applied to properly represent the hydrology and nutrients loadings in that area. Therefore, the watershed was split into two distinct geologic zones representing the Triassic Basins and everything else. The spatial coverage of HSG and geology used for HRU development is shown in Figure 3-1. The code and description used for HRU calculations is provided in Table 3-1. Table 3-1. HSG and Geology Classification Schema HSG Code Description 0 Water/Rock/Impervious 1 A + B 2 C + D 3 A + B in Triassic Basin 4 C + D in Triassic Basin 17

24 Figure 3-1. Hydrologic Soil Groups by Geology used for HRU Development 3.2 LAND USE Tetra Tech developed land use and land cover classification data for the Jordan Watershed area for two distinct temporal imagery datasets (1999 and 2010) to represent baseline and existing LULC (Tetra Tech, 2013). The final model land use products used for model setup can be viewed spatially in Figure 3-2 and Figure 3-3 with tabular information and comparisons provided in Table

25 Figure 3-2. Model Land Use and Land Cover (LULC) Inputs for 1999 (Baseline Model Scenario) Figure 3-3. Model Land Use and Land Cover (LULC) Inputs for 2010 (Existing Model Scenario) 19

26 Table 3-2. Model LULC Code Model Land Use and Land Cover (LULC) Input Comparisons Area (square miles) 1999 Model LULC Description Change in Area (1999 to 2010) 2010 Percent Change 11 Water Impervious Developed, Open Space Row Crops Pasture/Grassland Scrub/Shrub Forest 1, Wetland HRU CREATION Raster files of the soils/geology combination, land use and the watershed delineation were combined with the raster calculator in ArcGIS. This allowed for the tabulation of each soil/geology/land use intersection with each subwatershed in the delineation. The resultant table of data was exported to Excel and processed to provide a table of HRU area by subwatershed. This process was completed for each of the land uses (1999 and 2010) that are being used for the Jordan Lake watershed model. HRU s were organized by a two digit code for land use (Table 3-2) plus a one digit code for HSG/Geology (Table 3-1). The unique HRU s created for the Jordan Lake watershed model are provided in Table 3-3. For the tabulation run(s) each of these HRUs will be further split and coded to individual MS4 jurisdiction. Table 3-3. Jordan Lake Watershed HRU s HRU Code Description 110 Water HSG0 111 Water HSG1 112 Water HSG2 113 Water HSG3 114 Water HSG4 120 Impervious HSG0 121 Impervious HSG1 122 Impervious HSG2 123 Impervious HSG3 124 Impervious HSG4 130 Developed, Open Space HSG0 131 Developed, Open Space HSG1 132 Developed, Open Space HSG2 133 Developed, Open Space HSG3 134 Developed, Open Space HSG4 140 Row Crops HSG0 20

27 HRU Code Description 141 Row Crops HSG1 142 Row Crops HSG2 143 Row Crops HSG3 144 Row Crops HSG4 150 Pasture/Grassland HSG0 151 Pasture/Grassland HSG1 152 Pasture/Grassland HSG2 153 Pasture/Grassland HSG3 154 Pasture/Grassland HSG4 160 Scrub/Shrub HSG0 161 Scrub/Shrub HSG1 162 Scrub/Shrub HSG2 163 Scrub/Shrub HSG3 164 Scrub/Shrub HSG4 170 Forest HSG0 171 Forest HSG1 172 Forest HSG2 173 Forest HSG3 174 Forest HSG4 180 Wetland HSG0 181 Wetland HSG1 182 Wetland HSG2 183 Wetland HSG3 184 Wetland HSG4 3.4 MODEL REPRESENTATION OF HRUS The LSPC model allows for the creation of reduced modeling units (RMUs) from the list of developed HRUs. RMUs condense like land uses into a modeling group which eliminates the need to repeat a set of parameters multiple times (i.e. supplying parameters for water four different times). This reduces the amount of effort needed to parameterize a modeling application and also reduces the opportunity for a mistake to be made. The table which creates RMUs also provides an opportunity to fractionate an unwanted land use into RMUs for the simulation, i.e., HSG 0 (Null area in HSG) is not necessarily needed for model simulation but needed to be supplied for the raster calculator. Table 3-4 shows how HRUs have been condensed into RMUs. DELUID provides the ID number that is assigned to the land use group name and is used by the model for assigning parameters. DELUNAME provides the land use group name of the DELUID. LUCODE provides the HRU Code from the HRU processing. LUDESC provides the HRU description from the HRU processing. LU_PCT provides the percentage of the original LUCODE to DELUID assignment and PERIMP identifies the DELUID as either an impervious land unit (1) or a pervious land unit (2). 21

28 As can be seen in Table 3-4, all Water has been condensed into a single RMU and the same goes for Impervious area. Additionally, HSG0 (null areas in the HSG assignment) have be reclassified as follows: Water HSG0 became Water, Impervious HSG0 became Impervious, Row Crop HSG0, Pasture/Grassland HSG0, Scrub/Shrub HSG0, Forest HSG0 and Wetland HSG0 all were split equally into Water and Impervious. Lastly Developed, Open Space HSG0 was split into Impervious (10 percent), Developed, Open Space HSG1 (30 percent) and Developed, Open Space HSG2 (60 percent). The reclassification of Developed, Open Space HSG0 was based primarily on the area around the City of Burlington. Impervious area of 10 percent was a pure assumption and the split between HSG1 and HSG2 was made because there is more HSG2 in the area around the City of Burlington than HSG1. Table 3-4. Jordan Lake Watershed RMUs and Reclassifications DELUID DELUNAME LUCODE LUDESC LU_PCT PERIMP 1 Water 110 Water HSG0 100% 2 1 Water 111 Water HSG1 100% 2 1 Water 112 Water HSG2 100% 2 1 Water 113 Water HSG3 100% 2 1 Water 114 Water HSG4 100% 2 2 Impervious 120 Impervious HSG0 100% 1 2 Impervious 121 Impervious HSG1 100% 1 2 Impervious 122 Impervious HSG2 100% 1 2 Impervious 123 Impervious HSG3 100% 1 2 Impervious 124 Impervious HSG4 100% 1 2 Impervious 130 Developed, Open Space HSG0 10% 1 3 DevOpenSpaceHSG1 130 Developed, Open Space HSG0 30% 2 4 DevOpenSpaceHSG2 130 Developed, Open Space HSG0 60% 2 3 DevOpenSpaceHSG1 131 Developed, Open Space HSG1 100% 2 4 DevOpenSpaceHSG2 132 Developed, Open Space HSG2 100% 2 5 DevOpenSpaceHSG3 133 Developed, Open Space HSG3 100% 2 6 DevOpenSpaceHSG4 134 Developed, Open Space HSG4 100% 2 1 Water 140 Row Crops HSG0 50% 2 2 Impervious 140 Row Crops HSG0 50% 1 7 RowCropHSG1 141 Row Crops HSG1 100% 2 8 RowCropHSG2 142 Row Crops HSG2 100% 2 9 RowCropHSG3 143 Row Crops HSG3 100% 2 10 RowCropHSG4 144 Row Crops HSG4 100% 2 1 Water 150 Pasture/Grassland HSG0 50% 2 2 Impervious 150 Pasture/Grassland HSG0 50% 1 11 PastGrassHSG1 151 Pasture/Grassland HSG1 100% 2 12 PastGrassHSG2 152 Pasture/Grassland HSG2 100% 2 13 PastGrassHSG3 153 Pasture/Grassland HSG3 100% 2 14 PastGrassHSG4 154 Pasture/Grassland HSG4 100% 2 1 Water 160 Scrub/Shrub HSG0 50% 2 2 Impervious 160 Scrub/Shrub HSG0 50% 1 15 ScrubShrubHSG1 161 Scrub/Shrub HSG1 100% 2 16 ScrubShrubHSG2 162 Scrub/Shrub HSG2 100% 2 22

29 DELUID DELUNAME LUCODE LUDESC LU_PCT PERIMP 17 ScrubShrubHSG3 163 Scrub/Shrub HSG3 100% 2 18 ScrubShrubHSG4 164 Scrub/Shrub HSG4 100% 2 1 Water 170 Forest HSG0 50% 2 2 Impervious 170 Forest HSG0 50% 1 19 ForestHSG1 171 Forest HSG1 100% 2 20 ForestHSG2 172 Forest HSG2 100% 2 21 ForestHSG3 173 Forest HSG3 100% 2 22 ForestHSG4 174 Forest HSG4 100% 2 1 Water 180 Wetland HSG0 50% 2 2 Impervious 180 Wetland HSG0 50% 1 23 WetlandHSG1 181 Wetland HSG1 100% 2 24 WetlandHSG2 182 Wetland HSG2 100% 2 25 WetlandHSG3 183 Wetland HSG3 100% 2 26 WetlandHSG4 184 Wetland HSG4 100% 2 Table 3-5 provides the final list of RMUs for the Jordan Lake watershed model. This list is important as is it identifies the uniqueness in how parameters will be supplied and modified through the calibration process for hydrology and water quality. Table 3-5. DELUID Jordan Lake Watershed Model Simulated RMUs DELUNAME 1 Water 2 Impervious 3 DevOpenSpaceHSG1 4 DevOpenSpaceHSG2 5 DevOpenSpaceHSG3 6 DevOpenSpaceHSG4 7 RowCropHSG1 8 RowCropHSG2 9 RowCropHSG3 10 RowCropHSG4 11 PastGrassHSG1 12 PastGrassHSG2 13 PastGrassHSG3 14 PastGrassHSG4 15 ScrubShrubHSG1 16 ScrubShrubHSG2 17 ScrubShrubHSG3 18 ScrubShrubHSG4 19 ForestHSG1 23

30 DELUID DELUNAME 20 ForestHSG2 21 ForestHSG3 22 ForestHSG4 23 WetlandHSG1 24 WetlandHSG2 25 WetlandHSG3 26 WetlandHSG4 The simulated land use in the model for both the baseline condition (1999) and the current condition (2010) were summarized to examine the amount of change imparted by the land use reclassifications in the RMU creation. Table 3-6 shows the land use tabulations of what is actually included in the simulation. Generally, the simulated land use compares favorably with GIS summarized land use (Table 3-2) but water and impervious area have increased in both conditions coupled with a decrease in forest cover. Table 3-6. Model Land Use and Land Cover (LULC) Reclassified Input Comparisons Model LULC Code Area (square miles) Model LULC Description 1999 Change in Area (1999 to 2010) 2010 Percent Change 11 Water Impervious Developed, Open Space Row Crops Pasture/Grassland Scrub/Shrub Forest Wetland OTHER HRU/RMU PHYSICAL CHARACTERISTICS Along with the land use composition a number of other physical characteristics must be specified for each HRU/RMU. The length (LSUR) and slope (SLSUR) of the overland flow plane need to be supplied for each RMU, by subwatershed, in the model. These values can either be measured and summarized with GIS capabilities or estimated using best professional judgment. For the Jordan Lake watershed these values were estimated using best professional judgment. The decision to estimate these values was made because of our approach to utilize a set of calibration HRUs (HSG/geology/land use) and a set of tabulation HRUs (HSG/geology/land use/jurisdiction). When determining the tabulation HRUs the length and slope of the overland flow plane likely change, therefore if GIS was used for these parameters they would need to be re-summarized for the new HRUs and this has the potential to slightly alter the calibration. Table 3-7 provides the initial estimates of length and slope for each RMU in the Jordan Lake watershed model and these values have been used for every subwatershed. Water has been supplied an extremely flat slope and long overland flow plane in order to not have the precipitation falling on the water land use immediately added to the stream network and to provide an opportunity of evaporation to take place. 24

31 These values may be altered during the calibration process to obtain a better fit for storms but previous experiences indicates that daily average flow values are relatively insensitive to modifications in these parameters. The mean land elevation (MELEV) and mean reach elevation (RMELEV) also need to be supplied for the temperature lapse rate adjustments. MELEV can be supplied for each RMU by subwatershed. Due to having the two sets of HRU s for calibration and tabulation the MELEV value has been supplied by determining the average elevation of each subwatershed. RMELEV is supplied by reach segment and has been determine by averaging the upstream and downstream elevations. Table 3-7. Length and Slope of the Overland Flow Plane for each RMU DELUID DELUNAME SLSUR LSUR (ft) 1 Water ,000,000 2 Impervious DevOpenSpaceHSG DevOpenSpaceHSG DevOpenSpaceHSG DevOpenSpaceHSG RowCropHSG RowCropHSG RowCropHSG RowCropHSG PastGrassHSG PastGrassHSG PastGrassHSG PastGrassHSG ScrubShrubHSG ScrubShrubHSG ScrubShrubHSG ScrubShrubHSG ForestHSG ForestHSG ForestHSG ForestHSG WetlandHSG WetlandHSG WetlandHSG WetlandHSG

32 3.6 HRU SIMULATION To efficiently simulate two time periods of land use in the LSPC watershed model a component called time-variable land use is utilized. Time-variable land use allows the LSPC model to switch from one land use snapshot (i.e. the baseline 1999 snapshot) to another (i.e. the current 2010 snapshot) based on a user defined time interval. The time interval of the switch can be quick or gradual over a prolonged period of time and land use at any given point during the change is dependent on the time and a linear regression between the two land use snapshots. For the purpose of the Jordan Lake watershed model it was decided to do a quick, 1 day, change from the 1999 land use to the 2010 land use. The land use starts changing on 1/1/2002 and completes the change on 1/2/2002. These dates were selected because it is immediately after the baseline modeling period (2001) and provides a long length of time for the model to come back into equilibrium before the current period for which loads will be estimated to compare against the baseline period (just in case the change imparts any instability in the model). After time-varying land use was configured in the model a basic test of functionality was conducted. First, the model with the time-varying land use was parameterized with a basic set of default parameters and setup to run from 1/1/1996 through 12/31/2012. Then this model was used to create two additional models. Each of these models used either the 1999 land use or the 2010 land use for the entire simulation period. Comparisons of the simulated output from the three models were compared to ensure that timevariable land use was properly functioning. Table 3-8 compares the simulated output for the 1999 land use model and the 2010 land use model and shows that they are different during both comparison periods. Table 3-9 compares simulated output for the 1999 land use model and the time varying land use model and shows that they are identical from (indicating the same land use) but different in (indicating different land use). Further the simulated differences in are the same as the differences seen when comparing the 1999 model and 2010 model for the same time period (Table 3-8) which indicates that land use successfully changes from the 1999 snapshot to the 2010 snapshot. Lastly, Table 3-10 compares the 2010 land use model and the time varying land use model and shows that they are different from (indicating different land use) but are identical (indicating the same land use). Table 3-8. Comparison of 1999 and 2010 Test Models Simulated Output Comparison Period Model Setups compared 1/1/ /31/ /1/ /31/ Total Scenario In-stream Flow: Total of Scenario highest 10% flows: Total of Scenario lowest 50% flows: Scenario Summer Flow Volume (months 7-9): Scenario Fall Flow Volume (months 10-12): Scenario Winter Flow Volume (months 1-3): Scenario Spring Flow Volume (months 4-6): Total Scenario Storm Volume: Scenario Summer Storm Volume (7-9): Difference (%) Difference (%) Difference in total volume: Metric ( ) Difference in 50% lowest flows: Difference in 10% highest flows:

33 Metric ( ) Difference (%) Difference (%) Seasonal volume difference - Summer: Seasonal volume difference - Fall: Seasonal volume difference - Winter: Seasonal volume difference - Spring: Difference in storm volumes: Difference in summer storm volumes: Table 3-9. Comparison of 1999 and Time Varying Land Use Test Models Simulated Output Comparison Period 1/1/ /31/2001 1/1/ /31/2012 Model Setups compared 1999 Time Vary 1999 Time Vary Total Scenario In-stream Flow: Total of Scenario highest 10% flows: Total of Scenario lowest 50% flows: Scenario Summer Flow Volume (months 7-9): Scenario Fall Flow Volume (months 10-12): Scenario Winter Flow Volume (months 1-3): Scenario Spring Flow Volume (months 4-6): Total Scenario Storm Volume: Scenario Summer Storm Volume (7-9): Metric (1999-Time Vary) Difference (%) Difference (%) Difference in total volume: Difference in 50% lowest flows: Difference in 10% highest flows: Seasonal volume difference - Summer: Seasonal volume difference - Fall: Seasonal volume difference - Winter: Seasonal volume difference - Spring: Difference in storm volumes: Difference in summer storm volumes: