WetSpa Extension, A GIS-based Hydrologic Model for Flood Prediction and Watershed Management. Documentation and User Manual

Transcription

1 WetSpa Extenson, A GIS-based Hydrologc Model for Flood Predcton and Watershed Management Documentaton and User Manual Y.B. Lu, and F. De Smedt Department of Hydrology and Hydraulc Engneerng Vrje Unverstet Brussel Plenlaan 2, 1050 Brussel, Belgum March

2 Updated: July 2008 by Jef Dams February 2009 by Al Safar February 2009 by Elga Salvadore 2

3 WetSpa Extenson, A GIS-based Hydrologcal Model for Flood Predcton and Watershed Management Documentaton and User Manual Yongbo Lu and Flormond De Smedt Department of Hydrology and Hydraulc Engneerng, Vrje Unverstet Brussel Plenlaan 2, 1050 Brussels, Belgum Emal: yongblu@vub.ac.be, fdesmedt@vub.ac.be Abstract: A GIS-based dstrbuted watershed model, WetSpa Extenson, has been under development sutable for use of flood predcton and watershed management on catchment scale. The model s physcally based and smulates hydrologcal processes of precptaton, snowmelt, ntercepton, depresson, surface runoff, nfltraton, evapotranspraton, percolaton, nterflow, groundwater flow, etc. contnuously both n tme and space, for whch the water and energy balance are mantaned on each raster cell. Surface runoff s produced usng a modfed coeffcent method based on the cell characterstcs of slope, land use, and sol type, and allowed to vary wth sol mosture, ranfall ntensty and storm duraton. Interflow s computed based on the Darcy s law and the knematc approxmaton as a functon of the effectve hydraulc conductvty and the hydraulc gradent, whle groundwater flow s estmated wth a lnear reservor method on a small subcatchment scale as a functon of groundwater storage and a recesson coeffcent. Specal emphass s gven to the overland flow and channel flow routng usng the method of lnear dffusve wave approxmaton, whch s capable to predct flow dscharge at any convergng pont downstream by a unt response functon. The model accounts for spatally dstrbuted hydrologcal and geophyscal characterstcs of the catchment and therefore s sutable for studyng the mpact of land use change on the hydrologcal behavours of a rver basn. Keywords: Watershed modellng, WetSpa, GIS, Runoff, Flood predcton 3

4 TABLE OF CONTENTS ABSTRACT TABLE OF CONTENTS LIST OF TABLES v LIST OF FIGURES v 1. MODEL DESCRIPTION MODEL HISTORY WetSpa WetSpass WetSpa Extenson MODEL CONSTRUCTION Model objectves Model structure Model assumptons Model lmtatons DATA PREPARATION Dgtal data Hydro-meteorologcal data MODEL FORMULATION PRECIPITATION INTERCEPTION SNOWMELT RAINFALL EXCESS AND INFILTRATION DEPRESSION AND OVERLAND FLOW Formulaton of depresson storage Mass balance of depresson storage Formulaton of overland flow WATER BALANCE IN THE ROOT ZONE EVAPOTRANSPIRATION FROM SOIL Potental evapotranspraton 25 4

5 2.7.2 Actual evapotranspraton PERCOLATION AND INTERFLOW GROUNDWATER STORAGE AND BASEFLOW OVERLAND FLOW AND CHANNEL FLOW ROUTING Flow response at a cell level Flow response at a flow path level Flow response of the catchment SUBCATCHMENT INTEGRATION CATCHMENT WATER BALANCE PARAMETER IDENTIFICATION AND MODEL EVALUATION DEFAULT PARAMETERS Parameters characterzng sol texture classes Parameters characterzng land use classes Potental runoff coeffcent Depresson storage capacty GLOBAL PARAMETERS MODEL EVALUATION MODEL OPERATION PROGRAM INSTALLATION PROGRAM DESCRIPTION Avenue scrpts and ther tasks Lookup tables Fortran programs and ther tasks GIS PRE-PROCESSING Surface grd preparaton Sol based grd preparaton Land use based grd preparaton Potental runoff coeffcent and depresson storage capacty Flow routng parameters Thessen polygon Dranage systems for a complex terran 72 5

6 4.4 CREATION OF INPUT FILES Input fle of tme seres Global parameters and spatal output specfcatons MODEL CALIBRATION AND VERIFICATION Calbraton and verfcaton processes Parameter adjustment Parameter senstvty MODEL OUTPUT Intermedate output Fnal output Post processng of model outputs CASE STUDY: CASE 1: BISSEN CATCHMENT, LUXEMBOURG Descrpton of the study area Data avalable Basn delneaton and parameter determnaton Model calbraton and valdaton Dscusson CONCLUDING REMARKS 108 REFERENCES 112 6

7 LIST OF TABLES Table 3.1. Default parameters characterzng sol textural classes 43 Table 3.2. Default parameters characterzng land use classes 45 Table 3.3. Potental runoff coeffcent for dfferent land use, sol type and slope 47 Table 3.4. Slope constant S 0 for determnng potental runoff coeffcent 48 Table 3.5. Impervous percentages assocated wth selected land use classes 49 Table 3.6. Depresson storage capacty for dfferent land use, sol type and slope 51 Table 4.1. Sample fle of precptaton seres p.txt 74 Table 4.2. Sample fle of potental evapotranspraton seres pet.txt 74 Table 4.3. Sample fle of temperature seres t.txt 75 Table 4.4 Sample fle of dscharge seres q.txt 75 Table 4.5. Template of global model parameters 76 Table 4.6. Template of spatal output specfcatons 77 Table 4.7. Parameter senstvty for model calbraton 85 Table 4.8. Sample output fle of mean.txt 86 Table 4.9. Parts of output fle uh_cell_h.txt 87 Table Sample output fle of q_tot.txt 88 Table Sample output fle of q_sub.txt 89 Table Sample output fle of balance.txt 90 Table Parts of output fle runoff.asc 90 Table Model evaluaton result evaluaton.txt 91 Table 5.1. Default parameter values n the PET formula for dfferent land use 97 Table 5.2. Data avalable and characterstcs of the Bssen catchment 98 Table 5.3. Statstcs and model performance for the calbraton/valdaton perod 103 Table 5.4. Water balance estmaton at Bssen for the whole smulaton perod 106 7

8 LIST OF FIGURES Fg WetSpa model structure 2 Fg Schematc of a hypothetcal grd cell for WetSpass 3 Fg Structure of WetSpa Extenson at a pxel cell level 6 Fg Annual varaton of grass ntercepton storage capacty 17 Fg Relatonshp between ranfall excess coeffcent and sol mosture content 20 Fg Sketch of depresson storage as a functon of excess ranfall 22 Fg Graphcal presentaton of excess ranfall and overland flow 24 Fg Graphcal presentaton of sol water balance 24 Fg Observed and smulated daly EP at Ukkel for the year Fg Smulated hourly EP wth EP d = 3m 27 Fg Graphcal presentaton of sol evapotranspraton 29 Fg Effectve hydraulc conductvty as a functon of mosture content 30 2 Fg Flow path response functons wth dfferent t and σ 37 Fg Potental runoff coeffcent vs. slope for forest and dfferent sol types 48 Fg Depresson storage capactes vs. slope for grass and dfferent sol types 52 Fg Schematc vew of the model s project folders 61 Fg Screenshort of surface menu 65 Fg Screenshort of parameter menu 68 Fgure 5.1. Locaton of the Bssen catchment 93 Fgure 5.2. Watershed topography of Bssen 94 Fgure 5.3. Land use map of Bssen 94 Fgure 5.4. Sol type map of Bssen 94 Fgure 5.5. Rver network and Thessen polygons of Bssen 94 Fgure 5.6. Hydraulc radus of Bssen 99 Fgure 5.7. Runoff coeffcent of Bssen 99 Fgure 5.8. Mean travel tme to the basn outlet of Bssen 100 Fgure 5.9. Standard devaton of flow tme to the basn outlet of Bssen 100 Fgure Observed and calculated flow at Bssen for the floods n Dec Fgure Observed and calculated hourly flow at Bssen for the year Fgure Peak Qm Vs Peak Qc selected from the whole smulaton perod 104 Fgure Observed and calculated hourly flow frequency curves at Bssen 105 8

9 1. MODEL DESCRIPTION Recent development of GIS and remote sensng technology makes t possble to capture and manage a vast amount of spatally dstrbuted hydrologcal parameters and varables. Lnkng GIS and the dstrbuted hydrologcal model s of rapdly ncreasng mportance n studyng the mpact of human actvty on hydrologcal behavours n a rver basn. Ideally, watershed models should capture the essence of the physcal controls of topography, sol and land use on runoff producton as well as the water and energy balance. Dstrbuted parameter hydrologcal models are typcally structured n characterzng watershed condtons such as topography, sol type, land use, dranage densty, degree of sol saturaton, and ranfall propertes, for whch t s advantageous to use the data currently avalable n GIS format. Ths report descrbes such a model, called WetSpa Extenson. 1.1 Model Hstory The WetSpa Extenson s based on the prevously developed WetSpa model, and s parallel to another extenson WetSpass. A bref ntroducton of these two models s gven below WETSPA WetSpa s a physcally based and dstrbuted hydrologcal model for predctng the Water and Energy Transfer between Sol, Plants and Atmosphere on regonal or basn scale and daly tme step developed n the Vrje Unverstet Brussel, Belgum (Wang et al., 1997 and Batelaan et al., 1996). The model conceptualzes a basn hydrologcal system beng composed of atmosphere, canopy, root zone, transmsson zone and saturaton zone. The basn s dvded nto a number of grd cells n order to deal wth the heterogenety. Each cell s further dvded nto a bare sol and vegetated part, for whch the water and energy balance are mantaned. Fgure 1.1 shows schematcally the consdered hydrologcal processes. Water movement n the sol s smplfed as one-dmensonal vertcal flow, ncludng surface nfltraton, percolaton and capllary rse n the unsaturated zone and recharge to groundwater. The model was desgned to smulate the Hortonan overland flow and the varable source area concept of runoff generaton. In order to have a more realstc representaton of the nteracton between surface runoff and groundwater storage, 9

10 a groundwater flow model s ntegrated, for whch the groundwater balance n the saturated zone s descrbed by the two-dmensonal Duput-Forchhemer horzontal flow equaton. Under approprate boundary condtons, the water table poston s determned wth a fnte dfference scheme for each grd cell, and explctly for each tme step. The model was desgned for scentfc research wth tme resoluton of mnutes. Ths brngs dffcultes to the model n practcal applcaton due to the data avalable. Fg WetSpa model structure WETSPASS For the estmaton of long-term spatal patterns of the groundwater recharge, that could be used as nput n regonal groundwater flow models and for the analyss of regonal groundwater flow systems, a smplfed model WetSpass was developed by Batelaan & De Smedt (2001) based on WetSpa. WetSpass stands for Water and Energy Transfer between Sol, Plants and Atmosphere under quas-steady State condtons, whch s GIS based, spatally dstrbuted hydrologcal model for calculatng the spatally dstrbuted yearly and seasonal evapotranspraton, surface runoff, and groundwater recharge. The model accounts for the spatal varaton n the groundwater recharge, whch s the result of dstrbuted land use, sol type, slope, etc. Fgure 1.2 gves a schematc water balance of a hypothetcal grd cell for WetSpass from Batelaan & De Smedt (2001). The total water balance for a cell n a spatally dstrbuted grd s splt up n ndependent water balances for vegetated, bare-sol, open-water and mpervous parts of the grd cell. Ths allows 10

11 accountng for the non-unformty of the land use dependng on the resoluton of the grd cell. The processes n each part of a grd cell are set n a cascadng way. Ths means an order of occurrence of the processes, after the precptaton event, s assumed. Defnng such an order s a prerequste for the seasonal tme scale wth whch the processes are quantfed. Fg Schematc of a hypothetcal grd cell for WetSpass WETSPA EXTENSION The WetSpa Extenson, descrbed n ths report, s a GIS-based dstrbuted hydrologcal model for flood predcton and water balance smulaton on catchment scale, whch s capable of predctng outflow hydrograph at basn outlet or any convergng pont n a watershed wth a varable tme steps (De Smedt et al., 2000; Lu et al., 1999, 2002, 2003). The model ams not only at predctng flood, but also nvestgatng the reasons behnd t, especally the spatal dstrbuton of topography, land use and sol type. Comparng wth the orgnal WetSpa model, the major changes nvolved n ths extenson are: 1) The tme resoluton of all hydrologcal processes s changed to a varable tme scale (mnutely, hourly, daly, etc.) n order to meet the specfc requrement of flood predcton. 2) The flow routng component for both overland flow and channel flow are ncorporated usng the method of lnear dffusve wave approxmaton. 11

12 3) The component of shallow subsurface lateral flow s added to the orgnal model smulatng nterflow by the method of knematc approxmaton. 4) The component of snowmelt modellng s added to the orgnal model smulatng snowmelt by the degree-day approach. 5) The hydrologcal process of depresson storage s taken nto account beng one of the major losses of ntal abstracton. 6) Groundwater flow smulaton s performed on small subcatchment scale by the method of lnear reservor for the smplfcaton of model parameterzaton. 7) Some model formulas are modfed n order to make the model more physcally based and capable of usng readly avalable data. 8) All default parameter values nvolved n the model lookup tables are recalbrated based on the lterature revew and practcal case studes. 9) Model programs usng ArcVew Avenue and Fortran language are developed, whch makes use of spatal nputs and gves spatal outputs as well. Ths manual s desgned to provde a bref descrpton of the components n the WetSpa Extenson. It also descrbes the program structure, the gudelne for estmatng model parameters, the base maps requred to represent a catchment, as well as the nput and output datasets for model calbraton and valdaton. The ArcVew scrpts, lookup tables and Fortran programs, as well as the sample nput and output fles are ncluded n the ArcVew project n the enclosed dskette. Operatng nstructons and any revsons can be found n the project help scrpt. 1.2 MODEL CONSTRUCTION Model objectves 1) To provde a comprehensve GIS-based tool for flood predcton and watershed management on catchment scale, whch s compatble wth GIS technology and remote sensng nformaton. 2) To enable the use of the model for smulaton of the spatal dstrbuton of hydrologcal processes, such as runoff, sol mosture, groundwater recharge, etc. 12

13 3) To enable the use of the model for analyss of land use change and clmate change mpacts on hydrologcal processes. 4) To provde for a dstrbuted model that can operate on cell scale and a varable tme step, and a sem-dstrbuted model on small subwatershed scale. 5) To provde a platform on whch the future water qualty and sol eroson models can be developed at multple scales Model structure The model uses multple layers to represent the water and energy balance for each grd cell, takng nto account the processes of precptaton, ntercepton, snowmelt, depresson, nfltraton, evapotranspraton, percolaton, surface runoff, nterflow and groundwater flow. The smulated hydrologcal system conssts of four control volumes: the plant canopy, the sol surface, the root zone, and the saturated groundwater aqufer. The precptaton that falls from the atmosphere before t reaches the ground surface s abstracted by canopy ntercepton storage. The remanng ranfall reached to the ground s separated nto two parts dependng on the land cover, sol type, slope, the magntude of ranfall, and the antecedent mosture content of the sol. The frst component flls the depresson storage at the ntal stage and runs off the land surface smultaneously, whle the remanng part nfltrates nto the sol. The nfltrated part of the ranfall may stay as sol mosture n the root zone, move laterally as nterflow or percolate further as groundwater recharge dependng on the mosture content of the sol. Dranage water from a gven cell flows laterally dependng on the amount of groundwater storage and the recesson coeffcent. The percolaton out of the sol layer s assumed to recharge the groundwater storage. Interflow from the root zone s assumed to contrbute overland flow and routed to the watershed outlet together wth surface runoff. The total runoff from each pxel cell consttutes the sum of the surface runoff, the nterflow and the groundwater flow. Evaporaton takes place from ntercepted water, depressed water and the sol surface, whle transpraton takes place from the plant through root system n the sol layer, and a small part from the groundwater storage. The water balance for the ntercepton storage ncludes precptaton, evaporaton and through fall. The water balance for the depresson storage ncludes through fall, nfltraton, evaporaton and surface runoff. The water balance for the 13

14 sol column ncludes nfltraton, evapotranspraton, percolaton, and lateral subsurface runoff. The water balance for the groundwater storage ncludes groundwater recharge, deep evapotranspraton, and lateral groundwater flow. Fgure 1.3 shows schematcally the model structure at a pxel cell level. The smple structure n Fgure 1.3 s used n the model because the emphass here s on developng and testng parameterzatons for the root zone. Excess runoff, nfltraton, evapotranspraton, nterflow and percolaton estmates are pont calculatons. Dfferent slope, land use and sol propertes n dfferent grd cells of a watershed result n dfferent amounts of excess runoff when subjected to the same amount of ranfall. The routng of runoff from dfferent cells to the watershed outlet depends on flow velocty and wave dampng coeffcent usng the method of dffusve wave approxmaton. Although the spatal varablty of land use, sol and topographc propertes n a watershed are consdered n ths model, the groundwater response s modelled on small subcatchment scale for the convenence of model parameterzaton and model smulaton. Two alternatves for determnng groundwater flow are used n the model, smulatng groundwater flow wth a smple lnear reservor method and non-lnear reservor method. All model equatons are specfcally chosen to mantan a physcal bass and well supported by prevous studes. The nputs to the model are precptaton and potental evapotranspraton (PET). Evapotranspraton Precptaton Intercepton CANOP Y Depresson Through fall SOIL SURFACE Infltraton Recharge SOIL GROUNDWATER Surface runoff Interflow Dranage D I S C H A R G E Fg Structure of WetSpa Extenson at a pxel cell level 14

15 Temperature data are needed f snow accumulaton and snowmelt occur durng the smulaton perod. The dgtal maps of topography, land use and sol type are used to derve all necessary spatal dstrbuted model parameters. The man outputs of the model are rver flow hydrographs and spatally dstrbuted hydrologcal characterstcs, such as sol mosture, nfltraton rates, groundwater recharge, surface water retenton or runoff, etc Model assumptons 1) Sol characterstcs and landscape are sotropc and homogeneous for a sngle raster cell. 2) Canopy cover and ground cover are homogeneous for a sngle raster cell. 3) Precptaton s spatally homogeneous wthn a raster cell. 4) The form of Hortonan overland flow s vald for most of the areas. 5) Evapotranspraton s neglected durng a ranstorm and when the sol mosture s lower than resdual sol mosture. 6) Deep evapotranspraton takes place when sol s dry, and s restrcted by the amount of effectve groundwater storage. 7) Sol mosture content s homogeneous n a sngle cell, whle the groundwater storage s unformly dstrbuted on small subcatchment scale for each tme step. 8) Water flows along ts pathway from one cell to another, and cannot be parttoned to more than one adjacent raster cell. 9) The method of lnear dffusve wave approxmaton s vald for routng of both overland flow and channel flow. 10) Hydraulc radus s locaton dependent, vares wth flood frequency, but remans constant over a flood event. 11) Interflow occurs when sol mosture content s hgher than feld capacty and can be estmated by Darcy s law and knematc approxmaton. 12) The water losses durng overland and channel flow, as well as the losses of deep percolaton are not mportant. 15

16 1.2.4 Model lmtatons Hydrologcal modellng s an attempt to smulate real hydrologcal processes through the use of nput data descrbng physcal characterstcs of the system, a set of algorthms to transform nput data to output of nterest, and smplfyng assumptons to lmt the scope of the model. Model lmtatons must be consdered n runnng the model and nterpretng ts output. Followngs are the major lmtatons assocated wth model smulaton. 1) WetSpa Extenson runs wth a contnuous nput data seres. Therefore, the check of contnuty and relablty must be carred out n the phase of data preparaton. If mssng data exst n the precptaton or PET seres, artfcal nterpolaton must be done for the tme perod. For the purpose of contnuous model evaluaton, negatve values are taken the place n case of mssng flow records. 2) The land use categores are grouped, for whch some of the categores mght be somewhat ambguous. For nstance, the category agrculture may nclude farmsteads, lawns, dsturbed areas, dle land, and other land uses that are not dentfable as one of the other specfed land use categores. Further more, the annual crop rotaton s not taken nto account n the model. On the other hand, lower level hghways and country roads are not modelled unquely, but are combned wthn the rural resdental category, ths may reduce the amount of runoff and alter the flow drecton expected from these areas. 3) Values assgned to any raster or grd cell represents an average value over the area of each cell. The greater the varablty over the cell, the greater wll be the error nduced through the use of an average value. Therefore, the grd sze should be well defned. A small grd sze may better represent the varablty of physcal watershed characterstcs, but leads to more memory cost and tme consumpton durng the model smulaton, especally for large watersheds. Balance should be made between the model accuracy and computer effcency. 4) The tme resoluton should be well defned. As for nstance, t s not feasble to predct flood usng hourly or daly scale for a very small watershed, where excess water may flow out wthn the frst tme step. In ths case, a shorter tme nterval should be chosen, f feld measurements are avalable. 5) The snow accumulaton and snowmelt are modelled n a smple way by the degree-day 16

17 coeffcent method, where the redstrbuton of snow pack, the nfluence of aspect, local slope, land use, etc., to the snowmelt are not nto account. 6) WetSpa Extenson generates runoff by an emprcal-based modfed coeffcent method rather than from equatons more closely representng physcal processes. Though defntely a lmtaton, the use of the method has ts advantages of close lnkng runoff wth cell characterstcs such as slope, land use, sol type and mosture content, and has a great potental to predct the mpact of land use change on hydrologcal behavours n the watershed. 7) The mpervous fractons for urban areas are set subjectvely dependng upon cell sze, snce no detaled measurements are avalable. For nstance, for a 50X50 m grd, 30% s set for resdental area, 70% for commercal and ndustral area and 100% for major communcaton lnes, parkng lots, etc. Ths may not actually reflect the real world and may brng errors to model result. 8) WetSpa Extenson employs many default parameters, whch are nterpolated from the lterature and used over the entre catchment. Due to the vast varaton range, parameters such as hydraulc conductvty, roughness coeffcent, etc. may change greatly when applyng the model to another place wth qute dfferent envronment. Therefore, model calbraton s preferable, and ths brngs dffcultes n model parameterzaton n an un-gauged rver basn. 9) WetSpa Extenson smulates groundwater flow on small subcatchment scale. It estmates the groundwater flow and groundwater storage for each small subcatchment at each tme step, but cannot predct the spatal dstrbuton of groundwater table, as well as ts varaton durng the smulaton perod. 10) WetSpa Extenson assumes that the groundwater table s below the root zone. Ths constrans the use of the model n wetland areas. 1.3 DATA PREPARATION The preparaton of the database for WetSpa Extenson to a specfc watershed mples the determnaton of the complete dranage structure of the watershed, the spatal dstrbuton of land use classes and sol types, as well as the collecton of avalable hydro-meteorologcal data related to the project. 17

18 1.3.1 Dgtal data The model uses geo-spatally referenced data as nput for dervng model parameters, whch ncludes most data types supported by ArcVew, such as coverage, shape fle, grd and ASCII fle. Image can be used for reference wthn a vew, but s not used drectly by the model. The dgtal maps of topography, land use and sol type are 3 base maps used n the model, whle other dgtal data are optonal dependng upon the data avalable and the purpose and accuracy requrement of the project. 1) Dgtal Elevaton Model (DEM) The raster-type DEM, generated from pont or contour topographc map, s preferred n order to be compatble wth other remotely sensed data. The spatal and elevaton resolutons should be fne enough to capture the essental nformaton allowng takng care of the effects of spatal varablty of the watershed characterstcs on ts hydrologcal response. In practce, the chosen resoluton must allow adequate representaton of the actual topography and accurate determnaton of the watershed area, ts rver network, and ts subwatersheds. In the absence of large water surfaces (lakes, reservors, ponds, etc.) and large plans wth lttle or no elevaton varaton, processng of the DEM s relatvely straghtforward. After flterng of the ntal data to detect and remove erroneous extreme values, the slope, aspect, flow drecton, flow length and flow accumulaton of each grd cell are determned. Over flat areas, no slope and, hence, no drecton can be computed. Also, the DEM may contan artfcal pts from whch no water can flow out. These specfc problems have to be reserved by modfyng elevatons artfcally to lead to flow drectons as accurate as possble on any of the cells. Next, the dentfcaton of rver network s performed by assumng that all cells dranng more than a specfed upstream area are part of that network. More or less detaled rver networks can be dentfed, dependng on the selected upstream threshold area. Fnally, the stream lnks, stream orders and the subwatersheds correspondng to these rver reaches are dentfed. 2) Land use and sol types Land use nformaton s an mportant nput to the WetSpa Extenson, whch s normally obtaned from hgh-resoluton remotely sensed data for the same area as the DEM, and 18

19 wth the same grd cell sze. For hydrologcal smulaton purpose, all land use classes ntally determned are grouped together nto 14 WetSpa classes sgnfcantly dstngushed from each other on the bass of ther effect on hydrologcal processes, namely crop, short grass, evergreen needle leaf tree, decduous needle leaf tree, decduous broad leaf tree, evergreen broad leaf tree, tall grass, rrgated crop, bog marsh, evergreen shrub, decduous shrub, bare sol, mpervous area and open water surface. Each of these classes s characterzed by quanttatve attrbutes. The groups may vary accordng to the algorthms used n the model. For nstance, only 5 classes are consdered n defnng potental runoff coeffcent and depresson storage capacty,.e. crop, grass, forest, bare sol and urban areas. For smulaton purpose, the percentage of bare sol and mpervous areas are estmated for each grd cell based on the hgh-resoluton land use map. Sol types of the catchment are obtaned from the sol nformaton furnshed by sol maps. The sol code system used n WetSpa Extenson s based on the sol texture trangle developed by the Unted States Department of Agrculture (USDA), whch s characterzed by ts percentage of clay, slt and sand, rangng from the fne textures (clay), through the ntermedate textures (loam); and the coarser textures (sand). Therefore, the orgnal sol coverage map has to be converted to a raster map wth WetSpa sol codes n the phase of data preparaton. The grd must be adjusted to the same grd structure as the DEM and lmted to the same area by usng the mask grd of the catchment. The reclassfcaton can be done wthn GIS framework, whch makes use of a reclassfcaton table prepared n ArcInfo GIS or ArcVew Spatal Analyst. Ths work must be done wth cauton n order to make the converson as accurate as possble. The sol propertes and hydraulc characterstcs of those sol types are consdered constant n the present verson of the model. Default values are nterpolated from lterature as descrbed n secton 3.1, but users can substtute any other more approprate values for them. 3) Optonal dgtal data Other optonal dgtal data that can be used n the model nclude pont coverage or shape fle of gaugng staton locatons, lne coverage or shape fles of stream network and major traffc lnes, polygon coverage or shape fles of boundary and sewer systems, 19

20 etc. These data are of great help n delneatng watershed dranage path network, estmatng spatal ranfall dstrbuton, as well as properly determnng model routng parameters. If two or more ran gauges exst n or around the catchment wth measured data, the Thessen polygon weghtng method s then ntroduced to calculate the ranfall dstrbuton, for whch the weghtng factors are computed for each grd cell and subwatershed. Otherwse, a unform ranfall dstrbuton s assumed over the catchment. The nternal streamflow gauges can be used n the watershed dscretzaton process, for whch the watershed s splt at those locatons where gauges are present. Ths makes t possble to compare measured and computed flow hydrographs at a pont or seres ponts. The coverage of offcal rver network and catchment boundary s a very mportant geo-referenced data, whch can be combned wthn GIS n delneatng watershed dranage network, partcularly for meanderng rvers n flat areas. Usually, from the topographc nformaton present n a DEM, t s qute dffcult to represent watershed boundary and meanderng rvers n plan areas. To account those cases, data comng from the hydrographcal layer of dgtal maps (boundary, rvers, lakes, ponds, etc.) are used n combnaton wth the DEM to dentfy dranage areas, fnd nput and output cells for water bodes, and make any necessary correctons to flow drectons n order to have the rver reaches flow where they should and to be able to estmate the flow length closer to realty. For hydrologcal modellng n a complex terran, such as an urban or suburban watershed, the sewer systems, communcaton lnes, artfcal channels, etc. are mportant elements n dranage structure confguraton, and govern flow drecton more strongly than the derved aspect at a local scale. Snce most of these barrers are not suffcent to be represented n a DEM, addtonal procedures n term of dervng more realstc flow drecton map are performed usng GIS overlayng technque n the model, where the general flow drecton map s overlad by the sewer flow drecton map, the communcaton lne flow drecton map and the rver flow drecton map subsequently. Ths allows water dranng from the sewer areas at ts outlet and water crossng communcaton lnes at the concave ponts to jon the rver. The altered flow drecton map s then used for further dranage structure delneaton. 20

21 1.3.2 Hydro-meteorologcal data The basc nput requrements for the WetSpa Extenson consst of model parameters, ntal condtons, meteorologcal data and streamflow data for model calbraton and valdaton. The basc meteorologcal data requrements are ranfall and PET. Temperature data are optonal used for smulaton of snowmelt. In the case of calculatng PET by the Penman-Monteth equaton, addtonal meteorologcal data are requred, ncludng ar temperature, radaton, relatve humdty and wnd speed. In ths secton, the meteorologcal and hydrologcal data are descrbed. The model parameters and ntal condtons are descrbed n the subsequent sectons. 1) Ranfall Ranfall s the fundamental drvng force and pulsar nput behnd most hydrologcal processes. Ranfall-runoff models are partcularly senstve to the ranfall nput and any errors n estmates are amplfed n streamflow smulatons. The nput ranfall seres must be n the same nterval as the model runnng step. For nstance, hourly ranfall data are requred for each ran gauge when modellng n an hourly scale. In many cases, ranfall data at certan statons are n a daly scale rather than an hourly scale. These data can be used by dsaggregatng accordng to the temporal structure of ranfall of the neghbourng hourly reference ran gauges. The Thessen polygon method s then used to estmate areal ranfall durng model smulaton. Dependng upon the objectve of the study and on the tme scale of the catchment response, the tme resoluton of ranfall nput can be enlarged to a daly scale or reduced to a fner resoluton correspondng to the model tme scale. The ranfall data are treated as accumulated totals so that the ranfall assocated wth any partcular tme s the ranfall volume snce the end of last tme step. 2) Potental evapotranspraton WetSpa Extenson requres PET data as one of the nputs wth the same tme nterval as ranfall seres, whch can be obtaned from feld measurement or estmated by physcal or emprcal equatons. Normally, daly values of PET are suffcent, for whch the value s ether averaged to an hourly value or dsaggregated wth a smple emprcal equaton as a functon of hour as descrbed n secton 2.7. If only one measurng staton s avalable, the PET data can be unformly appled to the whole study area for a small 21

22 catchment. Otherwse, the value should be revsed for dfferent vrtual statons accordng to the local meteorologcal and geophyscal condtons, especally when modellng n mountanous areas. The areal PET s estmated usng the Thessen polygon method. The evapotranspraton data are treated as accumulated totals so that the evapotranspraton assocated wth any partcular tme s the evapotranspraton volume snce the end of last tme step. 3) Dscharge (m³/s) For the purpose of model calbraton and evaluaton, observed dscharge data at the basn outlet wth the same tme nterval as the precptaton seres are requred for vsual comparson and statstcal analyss. The dscharge data at nternal gaugng stes are optonal for model verfcaton. Data converson to another tme scale s necessary accordng to the smulaton tme step. The dscharge data at any partcular tme s the average dscharge snce the end of last tme step. 4) Optonal meteorologcal data Temperature data are requred when snow accumulaton and snowmelt occur n the catchment. Normally, daly average temperature data are suffcent n smulatng snow processes. Anyhow, the temperature data should keep the same tme nterval as the precptaton seres. If the Penman-Monteth equaton s chosen to calculate the PET, when there s no measured data avalable n the study area, the data of ar temperature, short wave radaton, relatve humdty, and wnd speed are requred n the model, whch can be obtaned from the routne meteorologcal statons. 2. MODEL FORMULATION WetSpa Extenson s a dstrbuted, contnuous, physcally based model descrbng the processes of precptaton, runoff and evapotranspraton for both smple and complex terran. It s a dstrbuted model because the watershed and channel network are represented by a grd of mesh. Each cell s descrbed by ts unque parameters, ntal condtons, and precptaton nputs. It s contnuous model because t has components descrbng evapotranspraton and sol water movement between storms, and therefore can mantan water and energy balance between storms. It s physcally based because the 22

23 mathematcal models used to descrbe the components are based on such physcal prncples as conservaton of mass and momentum. In ths secton, a bref s descrpton about the model formulaton nvolved n the processes of ntercepton, snowmelt, depresson, nfltraton, surface runoff, evapotranspraton, percolaton, nterflow and groundwater flow are presented. 2.1 PRECIPITATION Ranfall s a fundamental component of any hydrologcal model. As precptaton s commonly measured at fxed ranfall statons, ether nterpolaton or extrapolaton of the exstng data s requred to obtan nformaton at a specfc locaton n a catchment. The spatal dstrbuton of ranfall s often estmated by the elementary technques from a set of fxed ranfall gauges, whle the temporal dstrbuton s gnored by averagng the ranfall over a predetermned perod. The crudest method for estmatng the precptaton over a regon s to plot contours of equal precptaton wth the assstance of a structured grd. The average precptaton s computed between successve sohyets. Ths method s dffcult to realze for each modellng tme step wth sparse precptaton data, although the task of plottng sohyets s automated wth the advance of GIS technology. A common nterpolaton approach s the Thessen polygons, whch s also the method used n the current verson. In ths approach, areas closest to a ranfall gauge adopt the ranfall recorded at that gauge. Ths results n constant ranfall regons wth dscontnutes between regons. In addton, there s no justfcaton n assumng that pont ranfall measurements provde relable estmates of precptaton n the surroundng regon. The Thessen polygon method assgns an area called a Thessen polygon to each gage. The Thessen polygon of a gage s the regon for whch f we choose any pont at random n the polygon, that pont s closer to ths partcular gage than to any other gage. In effect, the precptaton surface s assumed to be constant and equal to the gage value throughout the regon. A FORTRAN code s developed to calculate mean areal precptaton over each subbasn usng Thessen polygon method, when model s ntended to run n sem-dstrbuted mode. Also, the same method s used for calculatng mean areal evapotranspraton and temperature for subbasns. Recall that, for the fully dstrbuted modellng, Model2 program does not use output 23

24 fle of the aforementoned developed code for the subbasns mean precptaton as well as evapotranspraton and temperature, snce t s cell-based not subbasn-based. 2.2 INTERCEPTION Intercepton s that porton of the precptaton, whch s stored or collected by vegetal cover and subsequently evaporated. In studes of major storm events, the ntercepton loss s generally neglected. However, t can be a consderable nfluencng factor for small or medum storms and water balance computatons would be sgnfcantly n error f evaporatve losses of ntercepted precptaton were not ncluded. 1) Mass balance of the ntercepton storage Intercepton s a complcated process, whch s affected by the storm characterstcs, the speces of vegetaton, percentage of canopy cover, growth stage, season, and wnd speed, etc. Intercepton loss s hgher durng the ntal phase of a storm and approaches zero thereafter. In WetSpa Extenson, the ranfall rate s reduced untl the ntercepton storage capacty s reached. If the total ranfall durng the frst tme ncrement s greater than the ntercepton storage capacty, the ranfall rate s reduced by the capacty. Otherwse, all ranfall s ntercepted n the canopy, and the remander of ntercepton s removed from the ranfall n the followng tme ncrements. The equaton can be expressed as I ( t ) I = P,0 SI ( t ) ( t 1) for P for P ( t ) f I SI ( t 1),0 ( t ) I SI ( t 1),0 (2.2) where I (t) s the ntercepton loss at cell over the tme nterval (mm), I,0 s the cell ntercepton storage capacty (mm), SI (t-1) s the cell ntercepton storage at tme step t-1 (mm), and P (t) s the cell precptaton amount (mm). The mass balance of ntercepton storage at a pxel cell s computed as: SI ( t) = SI ( t 1) + I ( t) EI ( t) (2.3) where SI (t-1) and SI (t) are cell ntercepton storage at tme step t-1 and t (mm), EI (t) s the cell evaporaton from ntercepton storage (mm). EI (t) = 0 when ntercepton 24

25 storage s zero, or durng the storm event. EI (t) = SI (t-1) under the condton of P (t) = 0 and EP > SI (t-1) > 0, n whch EP s the potental evaporaton (mm). And EI (t) = EP for the rest condtons. 2) Seasonal varaton of ntercepton storage capacty Intercepton storage capacty s a functon of leaf area ndex and vegetal speces. Evdently, t vares wth season n template regons. Typcal values can be found n the lterature (Horton, 1919; Clark, 1940; Lull, 1964; Smons, 1981; Rowe, 1983). Through physcal analyss and nterpolatons, a lookup table of maxmum and mnmum ntercepton storage capacty correspondng to summer and wnter extremes for dfferent vegetaton types are establshed (Table 3.2). Specfcally, the ntercepton storage capacty of crop s set to 0.8 mm durng growng season and null for the rest. For wettng losses on mpervous areas, the adsorpton storage capacty s set to 0.5 mm (Bauwens et al., 1996). Snce the ntercepton storage capacty vares contnuously wth tme, a smple sne-shaped varaton curve s proposed for the convenence of model programmng. The emprcal equaton s smlar as that of estmatng daly potental evaporaton based on statstcal analyss of long-term measurements (De Smedt, D., 1997), and s wrtten as I ( I I ) 1 2, 0 = I,mn +,max,mn + sn 2π 1 2 d b (2.4) n whch I,mn s the mnmum ntercepton storage capacty at cell (mm), I,max s the maxmum ntercepton storage capacty (mm), and d s the day of the year. The exponent b controls the shape of the varaton curve, and can be adjusted accordng to the local condtons. Hourly ntercepton storage capacty s assumed to be constant durng a day n the model. Therefore, the ntercepton storage capacty s only a functon of the date. Fgure 2.1 gves a graphcal presentaton for the annual varaton of grass ntercepton storage capacty, for whch the mnmum and maxmum ntercepton capacty s 0.5 and 2.0 mm respectvely, and the exponent b s set to

26 2.5 Intercepton storage capacty (mm) 2.0 b = /1 1 1/2 1 1/3 3 1/4 4 1/5 5 1/6 6 1/7 7 1/8 8 1/9 9 1/ / /12 Date (d/m) Fg Annual varaton of grass ntercepton storage capacty By substtutng Eq. (2.2) to Eq. (2.3), the ntercepton loss and ntercepton storage at each tme step can be estmated. No ntercepton loss exsts when the ntercepton storage capacty s acheved, and all precptaton reaches ground surface. The ntercepted water n canopy loses by evaporaton and returns to the hydrologcal cycle wth potental evaporaton rate modfed by a correcton factor. Although ntercepton losses may be hghly sgnfcant n the annual water balance, t s relatvely unmportant for flood-producng storms. 2.3 SNOWMELT Snow accumulaton and melt are mportant hydrologcal processes n rver basns, where the snow pack acts as storage n whch precptaton s retaned durng the cold season and subsequently released as melt water durng the warmer season. The snowmelt s ncorporated wthn WetSpa Extenson. Ths component s optonal and temperature data s requred addtonally f the sow routne s selected. The conceptual temperature ndex or degree-day method (Martnec et al., 1983) s wdely used n snowmelt modellng, n whch the full energy balance s replaced by a term lnked to ar temperature. It s physcally sound n the absence of short wave radaton, when much of the energy suppled to the snow pack s atmospherc long wave radaton. Its relance on daly temperature and precptaton data make t useful for modellng snow processes n regons wth a lack of regular snow observatons, or hstorcal perods wth lmted data. In WetSpa Extenson, an addtonal snowmelt caused by the advectve heat 26

27 transferred to the snow pack by precptaton s also consdered. The total snowmelt s calculated as M = C snow ( T T ) + C P ( T ) 0 ran T 0 (2.5) where M s the daly snowmelt at cell (mm/day), T s the cell daly mean temperature ( C), T 0 s a threshold temperature (usually 0 C), C snow s the degree-day or melt factor (mm/ C/day), and C ran s a degree-day coeffcent regardng to the heat contrbuton from ranfall (mm/mm/ C/day). Specfcally, temperature, precptaton and snow cover often vary sgnfcantly wthn a mountanous catchment, and n many cases, the hydro-meteorologcal nformaton from mountanous areas s qute sparse. To account for the large varatons n temperature wth alttude, the reference seres s adjusted for each grd cell by the lapse rate correcton T = T + ( H H )β ref ref (2.6) where T ref s the temperature at the reference staton ( C), H and H ref are the heght at cell and at the reference staton, and β s the temperature lapse rate. The degree-day coeffcent mplctly represents all terms of the energy budget that account for the mass balance of a snow pack, and s therefore hghly varable over tme (Sngh et al., 2000), and dfferent between vegetaton types (Kte & Kouwen, 1992). However, a constant value s used n the current verson for smplcty. Ths factor can be determned by feld experments, or wll have to be obtaned by calbraton otherwse. Moreover, the degree-day method by defnton s only vald for daly melt smulatons, whereas smulatons for short tme ntervals requre fner temporal resolutons. In ths case, a fully energy balance module s suggested, and t wll be ncorporated n the future verson. 2.4 EXCESS RAINFALL AND INFILTRATION Excess ranfall, or effectve ranfall, s that part of ranfall n a gven storm, whch falls at ntenstes exceedng the nfltraton capacty of the land surface. It may stay temporarly on the sol surface as depresson, or become drect runoff or surface runoff at the watershed outlet after flowng across the watershed surface under the assumpton of Hortonan 27

28 overland flow. Drect runoff forms the rapdly varyng portons of watershed hydrographs and s a key component for estmatng the watershed response. Infltraton s the downward flow of water nto the sol defned as the quantty of ranfall that does not contrbute to surface runoff. Under normal condtons, the nfltraton rate s manly a functon of: (1) ranfall characterstcs, (2) surface condtons, (3) sol characterstcs, (4) ntal mosture content of the sol, etc. It s desrable to relate loss rates to physcal characterstcs of the watershed n a contnuous smulaton so that loss rates may be computed as a functon of catchment characterstcs and sol mosture condtons durng a model smulaton. In WetSpa Extenson, a modfed coeffcent method for estmatng surface runoff and nfltraton processes s used relatng runoff and nfltraton wth topography, sol type, land use, sol mosture, and ranfall ntensty. The equatons can be expressed as ( t) θ PE ( t) = C P ( t) I ( t) θ, s F ( t) = P ( t) I ( t) PE ( t) a (2.7) (2.8) n whch PE (t) s the ranfall excess on cell over the tme nterval (mm), F (t) s the cell nfltraton (mm), I (t) s the ntercepton loss (mm), θ (t) s the cell sol mosture content at tme t (m³/m³), θ,s s the sol porosty (m³/m³), a s an exponent related wth ranfall ntensty (-), and C s the cell potental ranfall excess coeffcent or potental runoff coeffcent (-). Ths parameter C has a rather stable regularty under deal condtons. Default ranfall excess coeffcents for dfferent slope, sol type and land cover are taken the reference from the lterature (Krkby 1978, Chow et al. 1988, Browne 1990, Mallants & Feyen 1990, and Fetter 1980). Based on the physcal analyss and lnear nterpolatons of these values, a look up table s then establshed (Table 3.3), relatng potental ranfall excess coeffcent to the dfferent combnatons of slope, sol type and land use. The ranfall excess s closely related wth the relatve sol mosture content. No ranfall excess when sol s dry, and actual ranfall excess coeffcent approaches to the potental value when sol mosture content close to saturaton, under whch the nfltrated water s consdered to be used for percolaton, evapotranspraton and lateral nterflow. The exponent n the formula s a varable reflectng the effect of ranfall ntensty on the ranfall 28

29 excess coeffcent. The value s hgher for low ranfall ntenstes resultng less surface runoff, and approaches to 1 for hgh ranfall ntenstes. The threshold value can be defned durng model calbraton. If a = 1, a lnear relatonshp s assumed between ranfall excess and sol mosture. The effect of ranfall duraton s also accounted by the sol mosture content, n whch more excess produces due to the ncreased sol mosture content. Fgure 2.2 shows the relatonshp between actual ranfall excess coeffcent, relatve sol mosture content and potental ranfall excess coeffcent wth an exponent of 2.0. Ranfall excess coeffcent C = 0.2 C = 0.5 C C = 0.8 a = Relatve saturaton Fg Relatonshp between ranfall excess coeffcent and sol mosture content 2.5 DEPRESSION AND OVERLAND FLOW Precptaton that reaches the ground may nfltrate, or get trapped nto several small depressons, whch s retaned n puddles, dtches, and on the ground surface. As soon as ranfall ntensty exceeds the local nfltraton capacty, the ranfall excess begns to fll depresson. Water held n depresson at the end of ran ether evaporates or contrbutes to sol mosture and subsurface flow by the followng nfltraton. Depresson storage may be of consderable magntude and may play an mportant role n hydrologcal analyss. Stock ponds, terraces, and contour farmng etc. tend to moderate flood by ncreasng depresson storage. Depresson losses usually occur durng the ntal perod of the storm and are neglgble after a certan tme. Factors that affect depresson storage nclude: (1) nature of terran; (2) slope, the more slope gradent, the less depresson losses; (3) type of sol surface, the more sandy sol, the more depresson losses; (4) land use, the more woody land 29

30 use, the more depresson losses; (5) antecedent ranfall, the more sol water content, the less depresson storage; and (6) tme, for whch depresson losses decrease wth tme. Depresson s consdered ncluded n the potental ranfall excess coeffcent n the WetSpa Extenson, n order to emphasze ts effects on surface runoff producton, partcularly for the rough surfaces and for small flood events. Therefore, default potental ranfall excess coeffcent should be determned cautously from the lterature values, takng the nfluence of ntercepton and depresson nto account Formulaton of depresson storage Due to the extreme varablty of affectng factors, t s very dffcult to specfy a general relatonshp for the depresson losses. In WetSpa Extenson, a smple emprcal equaton suggested by Lnsley (1982) s used to estmate depresson storage: SD ( t) PC SD, 0 1 exp SD, = 0 (2.9) n whch SD (t) s the cell depresson storage at tme t (mm), SD,0 s the cell depresson storage capacty (mm), and PC s the accumulatve excess ranfall on the sol surface (mm). The concept of Eq. (2.9) s that both overland flow and depresson storage occurs smultaneously, allowng some of the water delverng as overland flow, even f excess ranfall s less than the depresson storage capacty. A sketch of SD (t) as a functon of PE s shown n Fgure 2.3. Depresson storage (mm) DS0 SD,0 = 3.5 mm Ranfall excess (mm) Fg Sketch of depresson storage as a functon of excess ranfall 30

31 The ncrement of depresson storage can be obtaned by dervaton of t both sde of Eq. (2.9) as SD PC ( ) = ( ) t PE exp t SD, 0 (2.10) where SD (t) s the ncrement of depresson storage at cell over the tme nterval (mm), and PE (t) s the excess ranfall for the tme ncrement (mm). Consderng that the ranfall s nterrupted between storm events, the accumulatve excess ranfall can be estmated based on Eq. (2.9), whch s the excess ranfall at present tme step plus an excess ranfall correspondng to the depresson storage at last tme step. PC = PE ( t) + SD,0 SD ln SD ( t 1),0 (2.11) Obvously, PC equals PE (t) when depresson storage at last tme step, SD t-1, s zero, and becomes a very large value when SD (t-1) approaches to SD,0, leadng to a very small depresson storage ncrement, SD,t, from Eq. (2.10). The capacty of depresson storage, SD,0, s manly affected by landform, sol type and vegetaton. Based upon the analyss and lnear nterpolaton of the typcal values collected n the lterature (ASCE, 1969; SINCE, 1972; Sheaffer, 1982), and default values n other popular hydrologcal models, a lookup table for default depresson storage capacty s set up, accordng to the categores and classes of slope, land use and sol type (Table 3.6), whch s smlar as the lookup table of potental ranfall excess coeffcent Mass balance of depresson storage As dscussed above, the depressed water on sol surface wll be depleted by evaporaton drectly or nfltrated nto the sol after the ranstorm. The mass balance of depresson storage can be expressed as SD ( t) = SD ( t 1) + SD ( t) ED ( t) F ( t) (2.12) where ED (t) and F (t) are cell evaporaton and nfltraton from depresson storage for the tme ncrement after the ranstorm (mm). ED (t) = 0 when P (t) > 0 or SD (t-1) = 0. ED (t) = 31

32 EP EI (t), when P (t) = 0 and SD (t-1) EP-EI (t), n whch EP and EI (t) are the potental evaporaton and the evaporaton from the cell ntercepton storage (mm). ED (t) = SD (t) when P (t) = 0 and 0 < SD (t) < EP-EI, (t). The nfltraton from depresson storage after ranstorm can be estmated usng Eq. (2.7) and Eq. (2.8) by takng the remanng depresson storage as the amount of ranfall on the ground surface Formulaton of overland flow Recall that the excess ranfall s a sum of overland flow and the change of depresson storage, the amount of overland flow over the tme nterval, RS (t) (mm), can be wrtten as PC RS ( t) = PE ( t) 1 exp SD,0 (2.13) Eq. (2.13) assumes that both overland flow and depresson storage occur smultaneously as descrbed n Fgure 2.4, for whch the overland flow approaches to zero when the accumulatve excess ranfall s very small, and approaches to PE (t) when the depresson storage closes to ts capacty. Ths s dfferent wth the assumpton that overland flow begns only after the depresson storage capacty s reached as the dashed lne shown n the fgure. 1.0 RS(t) / PE(t) 0.5 SD0,0 = 3.5 mm PE (mm) Fg Graphcal presentaton of excess ranfall and overland flow 32

33 2.6 WATER BALANCE IN THE ROOT ZONE Sol mosture storage s the actual quantty of water held n the sol at any gven nstant, usually appled to a sol layer of root depth. Based on the dfferent sol water content, the mosture storage can be dvded nto saturaton capacty, feld capacty, plant wltng pont, resdual sol mosture, etc. WetSpa Extenson calculates water balance n the root zone for each grd cell. Sol water s fed by nfltraton and removed from the root zone by evapotranspraton, lateral nterflow and percolaton to the groundwater storage, as descrbed n Fgure 2.5. F ES RS θ D RI RG Fg Graphcal presentaton of sol water balance The mosture storage n the root zone s expressed by a smple balance equaton as ( ) θ ( 1) = ( ) ( ) ( ) ( ) D θ t t F t ES t RG t RI t (2.14) n whch θ (t) and θ (t-1) are cell sol mosture content at tme step t and t-1 (m³/m³), D s the root depth (mm); F (t) s the nfltraton through sol surface for the tme ncrement (mm), ncludng the nfltraton durng the ranstorm and the nfltraton from depresson storage after the ranstorm (mm), ES (t) s the actual evapotranspraton from the sol for the tme ncrement (mm), RG (t) s the percolaton out of root zone or groundwater recharge (mm), and RI (t) s the nterflow or lateral shallow subsurface flow out of the cell for the tme ncrement (mm). 33

34 2.7 EVAPOTRANSPIRATION FROM SOIL Potental evapotranspraton (PET) PET s defned as the quantty of water vapour, whch could be emtted by a plant or sol surface per unt area and unt tme under the exstng condtons wthout water supply lmt. The WetSpa model requres the measured PET n the basn as an nput. Identcal to precptaton, PET s usually measured at meteorologcal statons or estmated usng numercal and expermental methods.e. Penman-Monteth equaton. Spatal dstrbuton of the PET s done n the same way as for the precptaton, usng the Thessen polygon approach. Most advanced measurng statons provde pan evaporaton measurements. These measurements combne the effect of temperature, humdty, wnd speed and sunshne on the PET. The potental evaporaton can be estmated wth the pan evaporaton multpled by a pan coeffcent. The man nfluencng factors to the potental evaporaton are: (1) solar radaton, provdng energy or heat; (2) wnd speed, transportng the mosture away from the surface, and (3) specfc humdty gradent n the ar above the water surface, beng the drvng forces for dffuson of water vapour. Ths means f no PET measurements are avalable equatons ncorporatng pervous mentoned varables can be used to estmate the PET. The FAO-56 Penman-Monteth equaton (Allen et al., 2000) s recommended as an approprate formula for PET estmatons. The calculatons of the potental evapotranspraton, f no measurements are avalable, have to be done outsde the WetSpa model Actual evapotranspraton Wthout consderng the evaporaton from ntercepton storage and depresson storage, actual evapotranspraton s defned as the sum of the quanttes of water vapour evaporated from the sol and the plants when the ground s at ts actual mosture content. Thus, f sol s fully saturated, then t s expected that the actual evapotranspraton rate equals to the PET rate. However, f the sol or vegetaton s water stressed, the evapotranspraton wll be less than potental evapotranspraton. Influencng factors to the actual evapotranspraton 34

35 nclude weather, vegetaton and sol condton, etc. Snce the actual evapotranspraton s governed by the avalablty of water, sol mosture content becomes a crucal factor, whch s determned by water recharge and the sol characterstcs. In the WetSpa Extenson, evapotranspraton conssts of four parts: (1) evaporaton from ntercepton storage, (2) evaporaton from depresson storage, (3) evapotranspraton from sol, and (4) evapotranspraton from groundwater storage. It s assumed that water evaporates to the atmosphere n a cascade way,.e. from ntercepton storage, depresson storage, sol matrxes, and groundwater storage consequently. The evaporaton from ntercepton storage and depresson storage has been descrbed n secton 2.2 and 2.5, and the groundwater contrbuton to the evapotranspraton wll be descrbed n secton 2.9. The actual evapotranspraton from sol and plant s calculated for each grd cell usng the relatonshp developed by Thornthwate and Mather (1955) as a functon of PET, vegetaton and ts growng stage, and mosture content n the cell ES ( t) = c [ c EP EI ( t) ED ( t) ] v v EP EI θ θ, ( t) θ θ ( t) ED ( t) for θ ( t) f, w, w for θ, w θ θ ( t), f p θ, f (2.18) where ES (t) s the actual sol evapotranspraton for the tme ncrement (mm), c v s a vegetaton coeffcent determned by land use classes varyng throughout the year, θ (t) s the cell average sol mosture content at tme t (m³/m³), θ,f s the sol mosture content at feld capacty (m³/m³), and θ,w s the sol mosture content at plant permanent wltng pont (m³/m³). It can be concluded from Eq. (2.18) that when the sum of ntercepton and depresson storage s greater than the PET, all evaporaton comes from the ntercepton and depresson storage wth a potental rate. When the sum of ntercepton and depresson storage s less than the amount of PET, all the remanng storage evaporates at ths tme step, and there s a part of evapotranspraton from the sol layer dependng on the sol mosture content. For the smulaton between storm events, actual evapotranspraton s manly from the sol and plant, whch vares lnearly between PET when sol mosture content s at or above feld capacty, and zero when sol mosture content s below the wltng pont. A graphcal presentaton of sol evapotranspraton s gven n Fgure 2.8, n 35

36 whch θ,s s the sol porosty (m³/m³). For the cell n urban areas, sol evapotranspraton s reduced by 70 % to account for mpervous surface covers the mpervous areas, and s calculated by cell evapotranspraton tmes the pervous percentage. ES(t)/cvEP 1 0 θ,w θ,f Mosture content θ,s Fg Graphcal presentaton of sol evapotranspraton 2.8 PERCOLATION AND INTERFLOW Percolaton or groundwater recharge refers to the natural process by whch water s added from sol water zone to the saturaton zone of the aqufer. Groundwater recharge s an mportant component n the root zone water balance, whch connects the sol water and the saturated groundwater. The man nfluencng factors to the groundwater recharge are the hydraulc conductvty, root depth, and water content of the sol. In WetSpa Extenson, percolaton out of root zone s assumed to pass drectly to the groundwater reservor, and estmated based on the Darcy s law, beng the product of hydraulc conductvty and the gradent of hydraulc potental. When an assumpton s made that the pressure potental only vares slghtly n the sol, ts gradent can be approxmated to zero, and the percolaton s controlled by gravty alone (Famglett and Wood, 1994). Based on ths assumpton, the percolaton amount out of root zone s smply specfed as the hydraulc conductvty correspondng to the average effectve saturaton n the respectve sol layer. The Brooks and Corey relatonshp between hydraulc conductvty and effectve saturaton s used to defne percolaton, whch s smply (Brooks and Corey, 1966) 36

37 RG ( t) = K [ θ ( t) ] t = K, s θ θ ( t), s A θ, r t θ, r (2.19) where RG (t) s the percolaton out of root zone over the tme nterval (mm), K [θ (t)] s the effectve hydraulc conductvty correspondng to the average sol mosture content at tme t (mm/h), t s the tme nterval (h), K,s s the cell saturaton hydraulc conductvty (mm/h), θ,s s the sol porosty (m³/m³), θ,r s the cell resdual mosture content (m³/m³), and A s the pore dsconnectedness ndex, calculated by the equaton A = (2+3B)/B, n whch B s the cell pore sze dstrbuton ndex. 1.0 K[θ(t)]/K k(/k s,s 0.5 Sand Loam Clay [θ(t)-θ,r]/(θ,s-θ,r) (st-sr)/(ss/sr) Fg Effectve hydraulc conductvty as a functon of mosture content Fgure 2.9 gves a graphcal presentaton for the effectve hydraulc conductvty as a functon of mosture content for three dfferent sol types: sand, loam and clay. It can be seen that the effectve hydraulc conductvty vares wth mosture content exponentally, reachng a maxmum, the saturated conductvty, when sol s completely saturated, and zero when sol becomes dry. Interflow, or shallow subsurface lateral flow, s also a key component n the sol water balance. It s defned as the water whch nfltrates the sol surface and moves laterally through the upper sol layers untl t enters a channel, whch ncludes ltter flow, return flow, unsaturated through flow, saturated through flow and so on, but excludes the saturated groundwater flow. Due to the delayed flow tme, nterflow usually contrbutes to the fallng lmb of a flood hydrograph, but t may also be a part of peak dscharge at the 37

38 basn outlet, partcularly for the areas wth steep slope and forest cover n humd or template regons. Factors that nfluence the amount of nterflow nclude: (1) physcal propertes and depth of the sol, for whch coarse texture leads to more vertcal flow, whle fne texture or layered sol results n resstance to vertcal flow and nterflow may some tme occur quckly; (2) vegetaton cover and land use, whch are drectly related to the mantenance of nfltraton capacty and the condtonng effect of organc materal on sol structure, bulk densty and porosty; (3) topography, for whch the slope gradent s a major factor determnng the amount and the velocty of nterflow; (4) sol mosture content, for whch hgher mosture content tends to generate more nterflow; and (5) lthology and clmate of the study area. In WetSpa Extenson, nterflow s assumed to occur after percolaton and cease when sol mosture s lower than feld capacty. The quantty of nterflow out of each cell s calculated from Darcy's Law and the knematc approxmaton;.e. the hydraulc gradent s equal to the land slope at each cell ( ) θ ( ) RI t = kd SK t t W (2.20) n whch RI (t) (mm) s the amount of nterflow out of the cell over the tme nterval t (h), D s the root depth (m), S s the cell slope (m/m), K[θ I (t)] (mm/h) s the cell effectve hydraulc conductvty at mosture content θ (t) (m³/m³), W s the cell wdth (m), and k (-) s a scalng factor dependng on land use, used to consder stream densty and the effects of organc matter and root system on horzontal hydraulc conductvty n the top sol layer. Apparently, rapd nterflow may generate n areas wth hgh mosture, steep slope and well vegetaton, whle lttle s produced for other areas wth Eq. (2.20). For modellng smplfcaton, nterflow s assumed to jon the surface runoff at the nearest channels or gulles servng as a supplementary dscharge to the stream flow durng and after storm event wthout further dvsons among down slope neghbours. Sol hydraulc characterstcs, such as porosty, feld capacty, resdual saturaton, hydraulc conductvty, and so on, are collected from the lterature, and used as default values n the WetSpa Extenson (Table 3.1). 38

39 2.9 GROUNDWATER STORAGE AND BASEFLOW Groundwater storage s defned as the quantty of water n the zone of saturaton ncludng that part of such stage when water s enterng and leavng storage. Groundwater storage capacty refers to the volume of saturated groundwater that can be alternatvely extracted and replaced n the depost under natural condtons. Normally, the groundwater dscharge forms a base flow to the hydrograph at basn outlet. Groundwater storage capacty s governed by the thckness and extent of the aqufer and ts porosty, whle the movement of groundwater s governed by the hydraulc gradent and the hydraulc conductvty of the aqufer. For the purpose of streamflow predcton, an estmate must be made of flow from the groundwater storage nto the stream for each tme step. Snce lttle s known about the bedrock, the smple concept of a lnear reservor s used to estmate groundwater dscharge on a small subcatchment scale, whle a non-lnear reservor method s optonal n the model wth storage exponent of 2 (Wttenberg and Svapalan, 1999). The groundwater outflow s added to any runoff generated to produce the total streamflow at the subcatchment outlet. The general groundwater flow equaton can be expressed as s ( t) = c [ SG ( t) ] m QG 1000 g s (2.21) where QG s (t) s the average groundwater flow at the subcatchment outlet (m 3 /s), SG s (t) s the groundwater storage of the subcatchment at tme t (mm), m (-) s an exponent, m = 1 for lnear reservor,and m = 2 for non-lnear reservor, c g s a groundwater recesson coeffcent takng the subcatchment area nto account, has a dmenson of (m 2 /s) for lnear reservor and (m -1 s -1 ) for non-lnear reservor, whch s dependent upon area, shape, pore volume and transmssvty of the subcatchment, and can be estmated from recesson portons of streamflow hydrographs f measurement data at the subcatchment outlet are avalable. For each subcatchment, the groundwater balance can be expressed as SG ( t) = SG s s ( t 1) + Ns [ RG ( t) A ] ( t) = 1 QGs EGs ( t) As 1000A s t (2.22) where SG s (t) and SG s (t-1) are groundwater storage of the subcatchment at tme step t and t-1 (mm), N s s the number of cells n the subwatershed, A s the cell area (m 2 ), A s s the 39

40 subcatchment area (m 2 ), EG s (t) s the average evapotranspraton from groundwater storage of the subcatchment (mm), and QG (t) s the groundwater dscharge (m³/s). The component of evapotranspraton from groundwater storage s consdered n the WetSpa Extenson, whch may be produced by deep root system or by capllary drve n the areas wth shallow groundwater table. It happens only when sol mosture s less than feld capacty from Eq. (2.18) and has a greater mpact durng the summer than the wnter, gvng the effect of a steeper recesson durng dry perod. A smple lnear equaton s used n the model relatng deep evapotranspraton wth PET and groundwater storage as EG ( t) = c [ c EP EI ( t) ED ( t) ES (t)] d v (2.23) where EG (t) s average evapotranspraton from groundwater storage (mm), EP s PET (mm), and c d (-) s a varable, calculated by SG (t)/sg s,0, n whch SG (t) s the groundwater storage of the subwatershed at tme t (mm), and SG s,0 s the groundwater storage capacty of the subwatershed (mm). Usng the method of groundwater reservor, there are only two groundwater parameters, the groundwater recesson coeffcent and the storage capacty, whch can be determned by calbraton aganst baseflow separated from the observed hydrograph OVERLAND FLOW AND CHANNEL FLOW ROUTING Flow response at a cell level The routng of overland flow and channel flow n WetSpa Extenson s mplemented by the method of a lnear dffusve wave approxmaton. Ths method s sutable for smulatng sheet flow and channel flow at a certan degree, and one of the mportant advantages s that t can be solved analytcally, avodng numercal calculaton and dentfcaton of the exact boundary condtons. Assumng the cell as a reach wth 1-D unsteady flow and neglectng the nertal terms n the St. Venant momentum equaton, the flow process n the cell can be modelled by the dffusve wave equaton as (Mller and Cunge, 1975) Q + c t Q d x 2 Q = 0 2 x (2.24) where Q (m³/s) s the flow dscharge at tme t (s) and locaton x (m), c s the knematc wave celerty at cell (m/s), d s the dsperson coeffcent at cell (m²/s). Consderng a 40

41 system bounded by a transmttng barrer upstream and an adsorbng barrer downstream, the soluton to Eq. (2.24) at the cell outlet, when the flow velocty and dffuson coeffcent are constant, can be obtaned by the frst passage tme densty dstrbuton of a Brownan moton and expressed as (Eagleson, 1970) u ( t) = 2 l πd t 3 exp 2 ( c t l ) 4d t (2.25) where u (t) s the cell mpulse response functon (1/s), and l s cell sze (m). Two parameters c and d are needed to defne the cell response functon, whch can be estmated usng the relaton of Mannng as (Henderson, 1966) 5 c = v 3 (2.26 ) and d v R = 2S (2.27) where R s the average hydraulc radus of cell (m), S s the cell slope (m/m), and v s the flow velocty of the cell (m/s). The hydraulc radus s determned by a power law relatonshp wth an exceedng probablty (Molnar and Ramrez, 1998), whch relates hydraulc radus to the controllng area and s seen as a representaton of the average behavour of the cell and the channel geometry R = a p b ( A ) p (2.28) where A s the draned area upstream of the cell (km²), whch can be easly determned by the flow accumulaton routne n ArcVew GIS, a p (-) s a network constant and b p (-) a geometry scalng exponent, both dependng on the dscharge frequency. The flow velocty s calculated by the Mannng s equaton as 1 v = R n 2 3 S 1 2 (2.29) where n s the Mannng s roughness coeffcent (m -1/3 s), whch depends upon land use categores and the channel characterstcs. Default Mannng s roughness coeffcents can be collected from lterature (Table 3.2). The velocty calculated by Eq. (2.29) may be very large or even zero due to varatons n land surface slope. Therefore t s bounded between 41

42 predetermned lmts v mn and v max durng model calculaton. Flow velocty s a tme-dependent, dscharge-related and locaton-related hydrologcal varable. But to be applcable of the dffusve wave approxmaton method for hydrologcal analyss, the flow must be only locaton-related. In realty, water depth usually ncreases as water goes downstream. As water deepens, the effectve resstance of the streambed and banks on the flow dmnshes because the hydraulc radus ncreases. To reflect ths property, the channel roughness coeffcent s set between predetermned lmts n max and n mn, dependng upon the GIS derved stream orders n the WetSpa Extenson. Thus, wth the supportng Equatons (2.26) to (2.29), the cell mpulse unt response functon u (t) can be calculated for each grd cell over the entre watershed, whch reflects the redstrbuton tendency n the flow element servng as a flow redstrbuton functon Flow response at a flow path level Under the assumpton of lnear routng system, the flow response at the end of a flow path, resultng from a unt mpulse nput to a sngle cell, can be calculated wthout the nterference of the nputs to the other cells. Determnng the flow-path response conssts n routng the mpulse through the correspondng sequence of cells down to the system outlet. Along the flow-path, the mpulse travels through many cells, each of them havng a dfferent unt-mpulse response functon. In ths routng process, the output of any cell becomes the nput to the recevng cell, and the orgnal nput dstrbuton s contnuously modfed by the flow dynamcs n the cells, whch are descrbed by ther mpulse response functons. The flow path response s found by successvely applyng the convoluton ntegral, gvng U ( t) = N j= 1 u ( t) j (2.30) where U(t) s flow path response functon (1/s), the subscrpt refers to the cell n whch the nput occurs, j s the cell sequence number, and N s the total number of cells along the flow path. The dffuson equaton model satsfes Eq. (2.30) wthn the cells, whch means that t allows for longtudnal decomposablty. Snce the cell unt mpulse response functons are tme-nvarant, the result of the convolutons of Eq. (2.30) s also tme-nvarant, and therefore, there s a lnear relaton between the flow path response and the mpulse nput. 42

43 Assumng that the flow path response U (t) s also a frst passage tme dstrbuton, De Smedt F. et al. (2000) proposed an approxmate numercal soluton to Eq. (2.30), relatng the dscharge at the end of a flow path to the avalable runoff at the start of the flow path 2 1 ( t t ) U ( t) = exp πσ 2 t t 2σ t / t (2.31) where t s the mean flow tme from the nput cell to the flow path end (s), and σ 2 s the varaton of the flow tme (s²). The parameters t and σ 2 are spatally dstrbuted, and can be obtaned by convoluton ntegral along the topographc determned flow paths as a functon of flow celerty and dsperson coeffcent and t = N j= 1 1 l c j N 2d 2 j σ = l j 3 j= 1 c j j (2.32) (2.33) The summatons presented n Eq. (2.32) and (2.33) can be calculated for each grd cell as a weghted flow length to the water outlet or any downstream convergng pont wth the routne FLOWLENGTH nvolved n the standard GIS tools. Examples of such flow path mpulse response functon are presented n Fgure 2.10 for dfferent mean flow tme and ts varaton. It s seen that the response functon s asymmetrc wth respect to tme caused by the wave attenuaton U(t) (1/s) Seres1 t = 1800, σ = Seres2 t = 3600, σ = Seres3 t = 7200, σ 2 = t (s) Fg Flow path response functons wth dfferent t and σ 2 43

44 The flow response at the end of a flow path, to an arbtrary nput at the start cell, can be calculated by convolvng the nput runoff volume by the flow path unt mpulse response functon. From a physcal pont of vew, ths s equvalent to decomposng the nput nto nfnte mpulses and addng all the responses nto a sngle response. Thus, the outflow hydrograph to an arbtrary nput can be determned as Q t τ = τ = ( t) V ( τ ) U ( t τ ) 0 (2.34) where Q (t) s the outflow at the end of a flow path produced by an arbtrary nput n cell (m³/s); U (t-τ) s the flow path response functon (1/s), beng equvalent to the nstantaneous unt hydrograph (IUH) used n the conventonal hydrology, and τ s the tme delay (s); V (τ) s the nput runoff volume at cell and at tme τ (m³), ncludng surface runoff and nterflow, as well as groundwater runoff f cell s located at the subcatcment outlet Flow response of the catchment Consderng the areal decomposablty n a lnear routng system, the catchment flow response can be determned as the sum of ts elements responses from all contrbutng cells. Thus, the catchment flow response can be calculated as Q( t) N = w = 1 ( ) Q t (2.35) where Q(t) s the total flow at the catchment outlet (m³/s), N w s the number of cells over the entre catchment. Hence, the flow routng conssts of trackng runoff along ts topographc determned flow path, and evaluatng groundwater flow out of the subcatchment. The total dscharge s the sum of the overland flow, nterflow and groundwater flow, and s obtaned by convoluton of the flow response from all grd cells. The advantage of ths approach s that t allows the spatally dstrbuted runoff and hydrologcal parameters of the terran to be used as nputs to the model, and can route runoff from a certan land use area to the catchment outlet or any downstream convergng pont. 44

45 2.11 SUBWATERSHED INTEGRATION In case of watershed modellng on medum or large scale, model parametersaton and computaton on small grd sze are tedous, costly and tme consumng. On the other hand, workng wth coarse spatal resoluton may ntroduce errors by aggregaton of spatal nput data and msrepresentaton of the true watershed characterstcs. To cope wth ths problem, WetSpa Extenson provdes a smplfed sem-dstrbuted opton workng on the scale of a small hydrologcal unt, so as to allow adequate smulaton and mappng of the areal dstrbuton of the hydrologcal processes. These unts correspond to very small subcatchments, bult up from hgh resoluton DEM data, rather than to large grd cells wth approxmately the same area as the subwatersheds. Ths has the advantage of allowng for the nternal dranage structure of the unts, whch would be mpossble by usng large grd cells. Model parameters, meteorologcal data nput, and state varables for each smulaton unt are obtaned by ntegraton of the values from all cells of that subcatchment. Meanwhle, the water and energy balance, as well as the process state varables, are computed on each unt durng model smulaton at each tme step. The subwatershed parameters calculated by WetSpa Extenson nclude area, slope, potental ranfall excess coeffcent, ntercepton capacty, depresson capacty, sol physcal propertes, etc. Flow hydrographs are frst calculated at the outlet of each subcatchment usng the subcatchment response functon, and thereafter, the flow s routed to the catchment outlet along the rver channel by means of channel flow response functon. Consderng the effect of cell characterstcs on the subwatershed IUH, the subcatchment response functon s computed by ntegraton of the flow path response functons for all cells n the subcatchment weghted by ther potental ranfall excess coeffcent. The equaton can be wrtten as U s N s N s ( t) = [ CU ( t) ] C = 1 = 1 (2.36) where U s (t) s the response functon or IUH of the subcatchment (1/s), C s the potental ranfall excess coeffcent at cell (-), U (t) s the flow path response functon at the subcatchment outlet wth runoff nput at cell (1/s), and N s s the number of cells n the 45

46 subcatchment. The flow hydrograph at subcatchment outlet s obtaned by summaton of ts surface runoff, nterflow and groundwater flow, and can be expressed as Q t s = τ s s + = ( t) V ( τ ) U ( t τ ) QG ( t) s τ 0 (2.37) where Q s (t) s the flow hydrograph at the subcatchment outlet (m³/s), V s (τ) s volume of readly avalable runoff of the subcatchment ncludng surface runoff and nterflow (m³), τ s the tme delay (s), and QG s (t) s the groundwater flow at the subcatchment outlet (m³/s). The total hydrograph at the watershed outlet s obtaned by ntegraton of the flow hydrographs produced from each subwatershed, and can be expressed as Q N = r ( t) Q s ( τ ) U r ( t τ ) s= 1 t (2.38) where Q(t) s the flow hydrograph at the catchment outlet (m³/s), U r (t) s the channel response functon from the subcatchment outlet to the catchment outlet calculated by Eq. (2.31) (1/s), t s the tme nterval (s), and N r s the number of subcatchment or the number of stream lnks n the catchment. Wth the unt response functons defned for each smulaton unt and the correspondng rver channel, water can be routed accumulatvely downstream up to the catchment outlet. However, the process of flow routng wthn each subcatchment can be omtted n case of hghly ntensve watershed dscretzaton, snce the water may flow out of the subwatershed wthn the frst tme step. In practce, dvson of the watershed should be performed accordng to the project purpose and the complexty of the terran. A few smulatons are necessary to decde the watershed dscretzaton to meet vares objectves of the project CATCHMENT WATER BALANCE Water balance for the entre catchment s used to keep track of water changes n the hydrologcal system, and also a measure of model performance by comparng the smulaton results wth the feld observatons. Among the consttuents n the system, sol 46

47 water content s an mportant state varable that nfluence fluxes nto and out of the root zone (nfltraton, evapotranspraton, percolaton and nterflow) and the energy balance on the land surface. The stores of ntercepton, depresson, sol mosture and groundwater are treated as separate control volume, but related subsequently. Precptaton s the nput to the system, whle drect runoff, nterflow, groundwater flow, and evapotranspraton are losses from the hydrologcal system. When modellng for a relatvely long tme perod, changes n the storage of ntercepton, depresson and channel can be neglected, and the general watershed water balance can be expressed as P = RT + ET + SS + SG (2.39) where P s the total precptaton n the watershed over the smulaton perod (mm), RT and ET are total runoff and total evapotranspraton (mm), SS s the change n sol mosture storage for the watershed between the start and the end of the smulaton perod (mm), and SG s the change n groundwater storage of the watershed (mm). For a gven smulaton perod T (s) and ntal mosture and groundwater storage condton, these components can be expressed as P = T N w t= = ( t) P 0 1 (2.40) RT = T N w [ RS ( t) + RI ( t) ] + t= 0 = 1 T Nr t= 0 s= 1 QGs ( t) t As (2.41) ET = N w T N w [ EI ( t) + ED ( t) + ES ( t) ] + [ EG ( t) ] T Nr t = 0 = 1 t= 0 s= 1 (2.42) θ ( ) θ ( 0) (2.43) SS = D T = 1 SG = N r [ SGs ( T ) SG s ( 0) ] s= 1 (2.44) where θ (T) and θ (0) are cell sol mosture content at the end and the start of the smulaton perod (m³/m³), SG s (T) and SG s (0) are subcatchment groundwater storage at the end and the start of the smulaton perod (mm), and the others have been descrbed n above 47

48 sectons. All of these components vary over tme. A change n any one component of the watershed water balance can result n changes n the other components n the system. Ths s partcularly useful for analysng the mpact of land use changes on the watershed hydrologcal processes. For nstance, deforestaton results n more surface runoff and less nfltraton, thus, decreasng the change n sol mosture storage and groundwater storage for a storm event, and the evapotranspraton s lmted by the mosture content as well. When the model performs on a very long tme seres, the changes n sol mosture and groundwater storage wll be less mportant, and the total precptaton s more or less equal to the sum of the runoff and the evapotranspraton. 3. PARAMETER IDENTIFICATION AND MODEL EVALUATION 3.1 DEFULT PARAMETERS Default parameters characterzng sol texture classes Sol textural classes are used to provde nformaton concernng sol physcal propertes, such as porosty, hydraulc conductvty, pore sze dstrbuton ndex, etc. Although other descrptors such as horzon and structural sze certanly nfluence the hydraulc parameters of sols, Cosby et al. (1984) perform a two-way analyss of varance of nne descrptors to conclude that sol texture alone can account for most of the dscernble patterns. Over the last two decades, a great deal of efforts has been made to the estmaton of sol hydraulc propertes from the nformaton on sol textures n the lterature (McCuen et al., 1981; Rawls et al., 1982; Cosby et al., 1984; Rawls & Brakensek, 1985; Carsel & Parrsh, 1988). In WetSpa Extenson, sol textures are classfed nto 12 USDA (U.S. Department of Agrculture) classes rangng from 1 to 12 based on the percentage of sand, slt and clay n the sol sample. Fne textured sols have a hgh percentage of clay and are very stcky when wet and hard when dry, whle coarse textured sols have a hgh percentage of sand and are loose and frable. A lookup table s then establshed as presented n Table 3.1 to estmate hydraulc propertes as a functon of sol texture classes usng mean values obtaned from the lterature. 48

49 Texture classes Table 3.1. Default parameters characterzng sol textural classes Hydraulc conductvty 1 (mm/h) Porosty 1 (m³/m³) Feld capacty 1 (m³/m³) Wltng pont 1 (m³/m³) Resdual mosture 1 (m³/m³) Pore sze dstrbuton ndex 2 (-) Sand Loamy sand Sandy loam Slt loam Slt Loam Sandy clay loam Slt clay loam Clay loam Sandy clay Slt clay Clay Obtaned by analyss of data presented n Rawls et al. (1982) 2 Obtaned from Cosby et al. (1984) Sol texture s a key varable n the coupled relatonshp between clmate, sol, and vegetaton. Under gven clmatc and vegetaton condtons the above sol-texture-dependent physcal propertes, through ther nfluence on sol water movement and the energy state of the water n the sol column, determne the sol wetness values whch n turn establsh the water condton of the vegetaton (Fernandez-Illescas et al., 2001). One advantage n favour of usng texture as the only dstngushng factor among components s that ths approach sgnfcantly smplfes model data management. When only a sngle dstngushng factor s used, components wth a common texture can be lumped together and the spatal sols nformaton passed from the GIS to the hydrology model s set at 12 dfferent specfcatons. Among the sol propertes lsted n Table 3.1, hydraulc conductvty has by far the largest coeffcent of varaton based on the analyss of Carsel & Parrsh (1988), and s more senstve than other sol related parameters. These parameters allow to be revsed durng model calbraton for refnng better ft as descrbed n Chapter Default parameters characterzng land use classes Land use or land cover s an mportant boundary condton, whch drectly or ndrectly nfluence many hydrologcal processes. The most obvous nfluence of land use on the 49

50 water balance of a catchment s on the evapotranspraton process. Dfferent land use types have dfferent evapotranspraton rates, due to ther dfferent vegetaton cover, leaf area ndces, root depths and albedo. Durng storms, ntercepton and depresson rates are dfferent for dfferent land use types. Land use also nfluences the nfltraton and sol water redstrbuton process, because especally the saturated hydraulc conductvty s nfluenced by plant roots and pores resultng from sol fauna (Ragab & Cooper, 1993). An extreme example s the nfluence of buld up areas and roads on overland flow. Moreover, land use nfluences surface roughness, whch controls overland flow velocty and floodplan flow rates. Therefore, the effect of land use should be taken nto account as much as possble n the smulaton calculatons. In WetSpa, the vegetaton type defnton s based on IGBP (Internatonal Geosphere-Bosphere Program) classfcaton system. The followng table shows the exact defnton: IGBP vegetaton type defnton ====================================================== Category 1 - Evergreen Needleleaf Forest Category 2 - Evergreen Broadleaf Forest Category 3 - Decduous Needleleaf Forest Category 4 - Decduous Broadleaf Forest Category 5 - Mxed Forest Category 6 - Closed Shrublands Category 7 - Open Shrublands Category 8 - Woody Savannah Category 9 - Savannahs Category 10 - Grasslands Category 11 - Permanent Wetlands Category 12 - Croplands Category 13 - Urban and Bult-Up Category 14 - Cropland / Natural Vegetaton Mosac Category 15 - Snow and Ice Category 16 - Barren or Sparsely Vegetated Category 17 - Water Bodes ====================================================== Reference: Edenshnk, J.C., Faundeen, J.L., 1994, The 1-km AVHRR global land data set: frst stages n mplementaton, nternatonal Journal of Remote Sensng,15:3443:3462 Therefore, 17 basc land use classes are specfed n the WetSpa Extenson, based on the observed physcal and bophyscal cover of the land surface, as well as the functon and the actual purpose for whch the land s currently beng used. Such nformaton s obtaned 50

51 from ground surveys or remote sensng mages. For each land use type, several vegetaton parameters are defned takng the reference of prevous studes as shown n Table 3.2. In order to more correctly smulate the effect of vegetaton on ntercepton and evapotranspraton, a range of leaf area ndex and ntercepton capacty s gven n the table correspondng to the mnmum and maxmum values n a year for each vegetaton class. Calculaton of the temporal varaton s descrbed n Chapter 2. Moreover, some of the parameters, such as root depth, roughness coeffcent, etc., should be determned as functons of both sol type and land use. However, for the present mplementaton, these parameters reman a functon of land use type only. Values of Mannng s roughness coeffcent shown n Table 3.2 are typcal values obtaned from experments reported n the lterature. These values are generally representatves of very small areas when correspondence exsts between realty and the mathematcal model of one-dmensonal flow over a plane. Therefore, f a larger grd sze, e.g. larger than 100 m, s used n the model, these values should be adjusted downward to reflect the greater number of rlls on long slopes (Wu et al., 1982; Harsne & Parlange, 1986; Veux & Farajalla, 1994). Table 3.2. Default parameters characterzng land use classes Category Cover Intercepton capacty(mm) Root Mannng's Vegetated Leaf area ndex(-) Maxmum Mnmum depth(m) Coeffcent fracton(%) Maxmum Mnmum 1 Evergreen Needleleaf Forest Evergreen Broadleaf Forest Decduous Needleleaf Forest Decduous Broadleaf Forest Mxed Forest Closed Shrublands Open Shrublands Woody Savannah Savannahs Grasslands Permanent Wetlands Croplands Urban and Bult-Up Cropland / Natural Vegetaton Snow and Ice Barren or Sparsely Vegetaton Water Bodes Obtaned and Adapted from Dcknson et al. (1993), Lull (1964), Znke (1967), Rowe (1983), Chow (1964), Haan (1982), Yen (1992) and Ferguson (1998). 51

52 In case the model s appled to a medum or large watershed, the parameter of channel roughness coeffcent, whch s governed manly by bed materal and channel cross secton, wll have a great nfluence to the predcted hydrograph. In natural rvers wthout overbank flow, the roughness coeffcent s generally small for downstream channels due to ther fne bed materals, and s large for upstream channels n contrast. To account for these effects, a lnear relatonshp s assumed n the model relatng Mannng s roughness coeffcent to the stream order descrbed as n r = n O O ( n n ) mn r, max r,max r,mn Omax O mn (3.1) where n r s the Mannng s coeffcent (m -1/3 s) for stream order O, O max and O mn are maxmum and mnmum stream order derved from ArcVew GIS, and n r,max and n r, mn are maxmum and mnmum Mannng s coeffcents correspondng to O max and O mn (m -1/3 s). Clearly, the Mannng s coeffcent has largest value for the channel wth mnmum order and smallest value for the channel wth maxmum order wth Equaton 3.1. The value of n r,max and n r, mn can be defned n the scrpt accordng to the channel characterstcs Potental runoff coeffcent The runoff coeffcent of a grd or catchment s the rato of runoff volume to ranfall volume. A smple and practcal technque s developed n WetSpa Extenson to estmate the runoff coeffcent under varyng land use, sol type, slope, ranfall ntensty and antecedent sol mosture condton as descrbed n Chapter 2. Undoubtedly, these varables act ndependently but also nteract n ther effect on the runoff coeffcent. A table of potental runoff coeffcent s bult for deferent land use, slope and sol type combnatons and under the condton of near saturated sol mosture. Water lost from the sol surface s consdered to nfltrate nto the sol used for further vertcal percolaton, evapotranspraton and lateral nterflow. To smply the table, the orgnal land use classes are reclassfed nto 5 classes as forest, grass, crop, bare sol and mpervous area. 52

53 Table 3.3. Potental runoff coeffcent for dfferent land use, sol type and slope Land use Slope (%) Sand Loamy sand Sandy loam Loam Slt loam Slt Sandy clay loam Clay loam Slty clay loam Sandy clay Slty clay Clay Forest <0, , > Grass <0, , > Crop <0, , > Bare <0, sol 0, > IMP The potental runoff coeffcents for mpervous (ncludng open water surface) are set to 1. In addton, surface slope s dscrtzed nto 4 classes as shown n Table 3.3. Values n the table are takng the reference from lterature (Krkby 1978, Chow et al. 1988, Browne 1990, & Fetter 1980) and adjusted after Mallants and Feyen (1990). In order to estmate the potental runoff coeffcent on the bass of a contnuous slope, a smple lnear relatonshp between potental runoff coeffcent and surface slope s used, whch can be descrbed as C = C ( C ) 0 S S + S 0 (3.2) where C s the potental runoff coeffcent for a surface slope S (%), C 0 s the potental runoff coeffcent for a near zero slope correspondng to the values lsted on the frst row of each land use class n Table 3.4, and S 0 (%) s a slope constant for dfferent land use and sol type combnatons, as lsted n Table 3.4, whch s calbrated usng the data n Table 3.4. Fgure 3.1 gves a graphcal presentaton of the grd potental runoff coeffcent for a forest cover as a functon of slope and dfferent sol types. 53

54 Table 3.4. Slope constant S 0 for determnng potental runoff coeffcent Land use Sand Loamy sand Sandy loam Loam Slt loam Slt Sandy clay loam Clay loam Slty clay loam Sandy clay Slty clay Clay Forest Grass Crop Bare sol Potental runoff coeffcent Slope (%) Potental runoff coeffcent Slope (%) Sand Loamy sand Sandy loam Slt loam Slt Loam Sandy clay loam Slt clay loam Clay loam Sandy clay Slt clay Clay Fg Potental runoff coeffcent vs. slope for forest and dfferent sol types The left fgure of Fgure 3.1 shows the potental runoff coeffcent for a slope rangng from 0 to 20% and the supportng ponts, and the rght one shows the potental runoff coeffcent for a slope rangng from 0 to 300%. Clearly, the potental runoff coeffcent approaches to C 0 when slope s very small, and 1 when slope s nfnte. The fgure also shows that the changng magntude of potental runoff coeffcent s decreasng along wth the ncreasng of surface slope. Ths conforms that the runoff volume for a certan amount of ranfall s less or even not affected by slope beyond a crtcal slope (Sharma, 1986). The nfluence of urban areas to the storm runoff s self-evdent. Due to the grd sze, cells may not be 100% mpervous n realty. In WetSpa Extenson, the remanng area s assumed to be pervous and covered by grass, and therefore, the potental runoff coeffcent for urban areas s calculated as C u = IMP + 1 ( IMP) C grass (3.3) 54

55 where C u and C grass are potental runoff coeffcent for urban and grass grd, and IMP s the proporton of mpervous area. Table 3.5 s developed to assocate an mpervous cover percent wth several of the specfed land use categores. Impervous percent for resdental area, commercal and ndustral s estmated based on the nformaton n Chow et al. (1988). Other estmates are consdered reasonable guesses. Zero mpervous percent s assumed for land use categores not lsted (.e. agrculture, grass land, and forest land). Table 3.5. Impervous percentages assocated wth selected land use classes No. Land use descrpton Impervous percent (%) 1 Resdental area 30 2 Commercal and ndustral area 70 3 Mxed urban or bult-up land 50 4 Transportaton and communcaton utltes Streams, Canals, lakes and reservors Forest wetland Bare exposed rock 100 In case the model s appled to a medum or large watershed, drect flow generated from the flow surface becomes an essental part of the storm runoff. Due to the effect of grd sze, upstream channel cells may not be fully occuped by flow. Equaton 3.4 s then used to calculate the potental runoff coeffcent for these channel cells. C r = RP + ( 1 RP)C (3.4) where C r s the potental runoff coeffcent for a channel grd, C s the potental runoff coeffcent wthout consderng the channel effect, and RP s the percentage of channel area of the grd calculated by the estmated flow wdth dvded by the grd sze. The flow wdth s determned by a power law relatonshp wth an exceedng probablty (Molnar & Ramrez, 1998), whch relates flow wdth to the controllng area and s seen as a representaton of the average behavour of the cell and the channel geometry. W = a W b ( A ) W (3.5) where A s the draned area upstream of the cell (km²), a W (-) s a network constant and b W (-) a geometry scalng exponent both dependng on the flood frequency. 55

56 Researches have shown that the runoff effcency (volume of runoff per unt of area) ncreases wth the decreasng catchment area,.e. the larger the catchment area the smaller the runoff effcency (Boers & Ben-Asher, 1982; Brown et al., 1999). Analogously, The potental runoff coeffcent s affected by the grd sze, n whch more surface runoff s produced when modellng wth a small grd sze, and vce versa. Ths can be explaned by that spatal varablty n clmatc nputs such as ranfall and hydrometorologcal varables, n sol characterstcs such as hydraulc conductvty and porosty, n topography, and land use, ncrease wth spatal scale (Vjay & Woolhser, 2002). For nstance, the average saturated hydraulc conductvty and the surface retenton capacty are hgher when modellng n a coarser resoluton, causng more nfltraton and less surface runoff. These have been addressed n many of the lteratures (Loague, 1988; Mazon & Yen, 1994; Saghafan et al., 1995). Therefore, the grd sze should be chosen properly n order to adequately represent the spatal heterogenety of a watershed, and the values of potental runoff coeffcent are allowed to readjust durng calbraton Depresson storage capacty Depresson storage capacty s a value that s land use dependent and represents the total amount of water that can be stored n small surface depressons. Moreover, the sol type and the slope steepness also affect the depresson storage capacty for pondng water and thereby the condtons for surface runoff. Generally rougher surfaces store more surface water than smoother surfaces and steeper slopes store less surface water than gentle slopes (Moore and Larson, 1979; Ullah and Dcknson, 1979a, b; Onstad, 1984). After the depresson storage amount s met, runoff wthn a cell begns. A table of depresson storage capacty, as shown n Table 3.6, s bult n WetSpa Extenson for dfferent land use, sol type and slope combnatons, based on the analyss of data n ASCE (1969), SINCE (1972), Sheaffer et al., (1982), and Geger et al. (1987). The depresson storage capacty for mpervous areas s consdered as wettng loss, and set to 0.5 mm (Fronteau & Bauwens, 1995). In order to obtan a depresson storage capacty as a functon of a contnuous slope used n the WetSpa Extenson, a smple regresson equaton as n Hansen et al. (1999) s appled, n whch the depresson storage capacty s controlled by land use and sol type, and 56

57 decreases wth slope exponentally. Sd = Sd 0 exp( bs) (3.5) where Sd s the depresson storage capacty (mm), S s the slope (%), Sd 0 s the depresson storage capacty for a near zero slope and dfferent sol types (mm), correspondng to the values lsted on the frst row of each land use class n Table 3.6, and b = -9.5, calbrated usng the data n Table 3.6. Fgure 3.2 shows the depresson storage capacty for a grass cover as a functon of slope and dfferent sol types. Table 3.6. Depresson storage capacty for dfferent land use, sol type and slope Land use Slope (%) Sand Loamy sand Sandy loam Loam Slt loam Slt Sandy clay loam Clay loam Slty clay loam Sandy clay Slty clay Clay Forest <0, , > Grass <0, , > Crop <0, , > Bare <0, sol 0, > IMP The left fgure of Fgure 3.2 shows the depresson storage capacty for a slope rangng from 0 to 20% and the supportng ponts, and the rght one shows the depresson storage capacty for a slope rangng from 0 to 100%. Clearly, the depresson storage capacty approaches to Sd 0 for a very small slope, and 0 for a steep slope. Ths conforms that the effect of depresson storage s not mportant for a steep slope n controllng overland flow generaton (Hansen et al., 1999). 57

58 Depresson storage capacty (mm) Depresson storage capacty (mm) Sand Loamy sand Sandy loam Slt loam Slt Loam Sandy clay loam Slt clay loam Clay loam Sandy clay Slt clay Clay Slope (%) Slope (%) Fg Depresson storage capactes vs. slope for grass and dfferent sol types The computaton of depresson storage capacty for urban areas s the same lke the process n calculatng potental runoff coeffcent, whch s the weghted mean of the depresson storage capacty for mpervous area and grassland. The equaton can be expressed as Sd u = 0.5IMP+ 1 ( IMP) Sdgrass (3.6) where Sd u and Sd grass are the depresson storage capacty for an urban and grass grd respectvely (mm). As there s no depresson loss on water surface, the depresson storage capacty for a channel cell can be calculated as Sd r = ( 1 RP)Sd (3.7) where Sd r (mm)s the depresson storage capacty for a channel grd, and Sd (mm) s the depresson storage capacty wthout consderng the channel effect. The values of depresson storage capacty are also affected by the grd sze as dscussed n secton Therefore, cautons should be made wth regards to use these values for a large grd. These parameters are allowed to modfy durng the GIS preprocessng n order to get a better ft. 58

59 3.2 GLOBAL PARAMETERS For smplfyng the process of parameter calbraton, 12 global parameters are used n the WetSpa Extenson,.e. the correcton factor of PET, nterflow scalng factor, groundwater recesson coeffcent, ntal sol mosture, ntal groundwater storage, base temperature for snowmelt, temperature degree-day coeffcent, ranfall degree-day coeffcent, surface runoff exponent, and the ranfall ntensty correspondng surface runoff exponent of 1. These parameters have physcal nterpretatons and are mportant n controllng runoff producton and hydrographs at basn outlet, but dffcult to assgn properly on a grd scale. Therefore, calbraton of these global parameters aganst observed runoff data s preferable n addton to the adjustment of dstrbuted model parameters. 1) Correcton factor for potental evapotranspraton The PET data used n the model are obtaned from pan measurement or calculated by Pemman-Monteth or other equatons usng avalable weather data. These reference evapotranspraton rates refer to water surface or a grass cover n large felds. Actual reference or PET rates, however, may depend on local factors that are not addressed by these methods. For nstance, the land use, elevaton, as well as the mcro-meteorologcal condtons for the grd to be smulated may be dfferent from those prevalng at the ste of the meteorologcal staton whose data are beng used. To account for these effects, a correcton factor s requred n the computed PET. The correcton factor s normally close to 1, and can be calbrated by the model through a long-term water balance smulaton. Specfcally, when modellng n a mountanous catchment, the evapotranspraton statons are usually very sparse and are located n the rver valley. To account for the effect of elevaton, the correcton factor for PET may be much lower n ths case. 2) Scalng factor for nterflow computaton Interflow or subsurface runoff s an essental runoff component for the humd temperate regon especally for the areas wth slopng landscapes and well-vegetated cover. In WetSpa Extenson, nterflow s assumed to occur when sol mosture exceeds the feld capacty and there s suffcent hydraulc gradent to move the water. Darcy s law s then used for the smulaton of nterflow. Dngman (1994) ponted out that due to 59

60 the ansotropy of water content dependent hydraulc conductvty, sol water preferentally flows laterally gven greater lateral hydraulc conductvty than vertcal. Even though a unform sol matrx s consdered n the model, but n fact, the porosty and permeablty of sol tend to decrease wth depth gven the weght of overlyng sol and the translocaton of materal n percolatng water to lateral subsurface flow. Moreover, sol water passng quckly to a stream through root canals, anmal tunnels, or ppes produced by subsurface eroson may become a crtcal component of peak flow. To account for theses effects, a scalng factor for lateral hydraulc conductvty n computng nterflow s used n the model. Ths scalng factor s generally greater than 1, and can be calbrated by comparng the recesson part of computed flood hydrographs wth the observed hydrographs. 3) Groundwater recesson coeffcent Groundwater flows are estmated on subcatchment scale n WetSpa Extenson as descrbed n Chapter 2. The groundwater recesson coeffcent reflects the storage characterstcs of the subwatershed and, therefore, s the same for all hydrographs at a gven locaton. In accordance wth Equaton (2.21), the groundwater recesson coeffcent wll reman constant f storage and dscharge volumes are dvded by area and expressed as depth n mm (Wttenberg, 1999). Ths s under the condton that groundwater flow for each subcatchment has the same recesson constant, and total groundwater at the outlet of the rver s only a tme-shfted superposton of partal groundwater flow from each subcatchment. In real rver basns, baseflow recesson coeffcent for each subcatchment may not be the same, and may have a consderable devaton from the theoretcal constant. A great porton of the devaton s assocated wth varablty of subcatchment characterstcs. Others may be attrbuted to aqufer heterogenety and dvergence from the Duput-Forchhemer assumpton of essentally horzontal groundwater flow. For model smplfcaton, a general value of groundwater flow recesson coeffcent s determned at the basn outlet n the nput fle. A lnear correcton s then performed for each subcatchment based on ts dranage area and the average slope, for whch hgher values are assgned for the subcatchments wth large dranage area and steep slope, and lower values for the subcatchments wth small area and gentle slope. The shape and 60

61 stream densty of the subcatchment s not accounted for n the current verson. The equaton can be expressed as c = c g, s g Ss W S s (3.8) where c g,s and c g (m 2 /s) are groundwater recesson coeffcent of the subcatchment and the entre basn, S s and S are average slope of the subcatchment and the entre basn, and Ws s the areal weght of the subcatchment. c g can be derved by the analyss of flow records as descrbed n Martn (1973) and Wttenberg (1999). Calbraton of ths parameter s necessary by comparng the computed and observed low flow hydrographs. 4) Intal sol mosture Sol mosture content s a key element n the model controllng the hydrologcal processes of surface runoff producton, evapotranspraton, percolaton and nterflow. A proper ntal sol mosture condton may provde a much more realstc startng pont for predctons. However, for a long-term flow smulaton n a watershed, the ntal sol mosture condton s less mportant, as t affects the hydrologcal processes only n the ntal part of the smulaton. An assumpton of unform ntal mosture dstrbuton can be made n ths case wth modellng purpose of flood predcton under present condton. A rato aganst feld capacty s then defned n the nput parameter fle for settng up the ntal sol mosture condtons. Ths value can be adjusted durng calbraton by analyss of water balance output and comparson between the computed and observed hydrographs for the ntal phase. If the model s used for short-term flow smulaton or event-based flood predcton, the antecedent mosture condton becomes one of the most mportant factors n runoff producton as well as ts dstrbuton. The concept of topographc wetness ndex (TWI) adapted from Moore et al. (1993) can be ntroduced n the model to evaluate antecedent mosture condton of a watershed wth TWI = ln(a/s), where ln(.) s the natural logarthm, A s the upslope dranage area (m 2 ), and S s the local slope (-). The TWI dstrbuton can be easly obtaned from a hgh resoluton DEM. Those cells wth hgh TWI values have larger upslope contrbutng areas or smaller cell slopes or a combnaton of the two propertes that lead to accumulaton of sol mosture. Whle an 61

62 assumpton s made for maxmum and mnmum mosture content wthn the watershed, the antecedent mosture dstrbuton can be obtaned by smply relatng mosture content to the TWI values. Cells wth very hgh TWI values may consder to be saturated wth runoff coeffcent of one. These cells are normally dstrbuted along the man rver or n the depresson areas n a watershed. 5) Intal groundwater storage In WetSpa Extenson, groundwater balance s mantaned on subcatchment scale and for the actve groundwater storage, whch s that part of storage n perched or shallow aqufers that contrbute to the surface stream flow. Water percolatng from the root zone storage may flow to actve groundwater storage or may be lost by deep percolaton. Actve groundwater eventually reappears as baseflow, but deep percolaton s consdered lost from the smulated system. A value of ntal groundwater storage n depth (mm) s set up n the nput parameter fle for all subcatchment. Ths value can be adjusted durng calbraton by comparng the computed and observed low flows for the ntal phase. 6) Base temperature for snowmelt The precptaton s assumed to fall as snow f the temperature s below the base temperature. Snowmelt starts when the temperature s above the base temperature. The base temperature s typcally a value near 0 C, partcularly for short computaton perod usng average temperature as nput. The user may specfy ths value durng model calbraton. 7) Temperature degree-day coeffcent The range of the temperature degree-day coeffcent s typcally mm/ C/day for ran-free condtons (Anderson, 1973; Male and Gray, 1981). Ths value can be determned by comparson between computed and observed sprng flood hydrographs durng calbraton. In general, the temperature degree-day coeffcent s vared both n tme and space. For nstance, the albedo s very hgh for new, cold snow fallng n the begnnng of the accumulaton season and decreases wth the age of the snow, whch results n an ncrease of the degree-day coeffcent. Moreover, the temperature degree-day coeffcent s also land use dependent, for whch forest cover leads to a hgher value, whle bare sol leads to a smaller value. For smplcty purpose, these 62

63 nfluencng factors are not accounted for n the current model, and recommended to be coupled n the future verson. 8) Ranfall degree-day coeffcent The ranfall degree-day coeffcent determnes the rate of snow meltng caused by condensaton of humd ar on the snow surface and the advectve heat transferred to the snow pack by precptaton, and s used for calculaton of an addtonal snowmelt due to ranfall. The value of ranfall degree-day coeffcent s generally very small, typcally around 0.01 (mm/mm/ C/day), and can be determned durng model calbraton. If zero value s gven, the effect of ranfall on snowmelt wll not be consdered. 9) Surface runoff exponent for a near zero ranfall ntensty Ranfall ntensty has a bg nfluence n controllng the proporton of surface runoff and nfltraton. As ponted by Dunne (1991), nfltraton rate ncreases wth ranfall ntensty for two reasons: (1) Hgher ranfall ntensty tends to exceed the saturated hydraulc conductvty of larger proportons of the sol surface, and thereby to rase the spatally averaged hydraulc conductvty, and (2) Hgher ranfall ntensty gves more surface runoff rate and the nundated flow depth. To account for ths effect on the producton of surface runoff, an emprcal exponent s ntroduced n the model as descrbed n Eq. (2.7). The concept s that the proporton of surface runoff s very small, or even nl, under the condton of very small ranfall ntensty, and the proporton ncreases along wth the ncrease of ranfall ntensty up to a stage for whch a potental runoff coeffcent s acheved. In WetSpa Extenson, ths exponent s assumed to be a varable startng from a hgher value for a near zero ranfall ntensty, and changng lnearly up to 1 along wth the ranfall ntensty, when the predetermned maxmum ranfall ntensty s reached. Ths value s generally less than 3 accordng to the prevous applcatons. If an exponent value 1 s gven, the actual runoff coeffcent s then a lnear functon of the relatve sol mosture content, and the effect of ranfall ntensty on the runoff coeffcent s not taken nto account. 10) Ranfall ntensty correspondng to a surface runoff exponent of 1 Ths parameter corresponds to threshold ranfall ntensty n unt of mm/h or mm/d dependng upon the temporal resoluton of the model smulaton, over whch the surface runoff exponent equals 1, and the actual runoff coeffcent becomes a lnear 63

64 functon of the relatve sol mosture content. Calbraton of ths parameter can be performed by comparson of the observed and computed surface runoff volume and the peak dscharge for hgh floods. Ths parameter s n fact spatally dstrbuted, dependng upon the cell characterstcs, such as sol type, land use, and slope, etc. A constant value s assumed n the current model for smplfcaton. 3.3 MODEL EVALUATION In order to evaluate how well WetSpa Extenson reproduces an observed hydrograph, a seres of statstcs are used. In addton to the evaluaton based on a vsual comparson and an evaluaton of peak flow rate and tme to the peak, the bas, model confdence, and the model effcency are also taken nto account. These statstcal measures provde quanttatve estmates for the goodness of ft between observed and predcted values, and are used as ndcators of the extent at whch model predctons match observaton. Based on the results of these tests, model predctve capabltes are assessed. The goodness of ft n the peak dscharge and tme to the peak can be evaluated by ther relatve and absolute errors respectvely, whle other evaluaton crtera are descrbed as followng: 1) Model bas Model bas can be expressed as the relatve mean dfference between predcted and observed stream flows for a suffcently large smulaton sample, reflectng the ablty of reproducng water balance, and perhaps the most mportant crteron for comparng whether a model s workng well n practce. The crteron s gven by the equaton CR1 N ( Qs Qo ) = 1 = N = 1 Qo (3.9) where CR1 s the model bas, Qs and Qo are the smulated and observed stream flows at tme step (m 3 /s), and N s the number of tme steps over the smulaton perod. Model bas measures the systematc under or over predcton for a set of predctons. A lower CR1 value ndcates a better ft, and the value 0.0 represents the perfect smulaton of observed flow volume. 64

65 2) Model confdence Model confdence s one of the mportant crtera n assessment of contnuous model smulaton, and can be expressed by ts determnaton coeffcent, whch s calculated as the porton of the sum of the squares of the devatons of the smulated and observed dscharges from the average observed dscharge. CR 2 N = 1 = N = 1 ( Qs Qo ) 2 ( ) 2 Qo Qo (3.10) where CR2 s the model determnaton coeffcent, Qo s the mean observed stream flow over the smulaton perod. CR2 represents the proporton of the varance n the observed dscharges that are explaned by the smulated dscharges. It vares between 0 and 1, wth a value close to 1 ndcatng a hgh level of model confdence. 3) Nash-Sutclffe effcency The Nash-Sutclffe coeffcent (Nash and Sutclffe, 1970) descrbes how well the stream flows are smulated by the model. As ponted out by Kachroo and Natale (1992), ths effcency crteron s commonly used for model evaluaton, because t nvolves standardzaton of the resdual varance, and ts expected value does not change wth the length of the record or the scale of runoff. The equaton can be descrbed as CR 3 = 1 N ( Qs Qo ) = 1 N = 1 2 ( ) 2 Qo Qo (3.11) where CR3 s the Nash-Sutclffe effcency used for evaluatng the ablty of reproducng the tme evoluton of stream flows. The CR3 value can range from a negatve value to 1, wth 1 ndcatng a perfect ft between the smulated and observed hydrographs. CR3 below zero ndcates that average measured stream flow would have been as good a predctor as the modelled stream flow. A perfect model predcton has CR3 score equal to 1. 4) Logarthmc verson of Nash-Sutclffe effcency for low flow evaluaton A logarthmc transformed Nash-Sutclffe crteron s presented n Equaton 3.11, whch gves emphasze for evaluatng the qualty of low flow smulatons (Smakhtn et 65

66 al., 1998). CR4 N = 1 = 1 N [ ln( Qs + ε ) ln( Qo + ε )] [ ln( Qo + ε ) ln( QO + ε )] = (3.12) where CR4 s a logarthmc Nash-Sutclffe effcency for evaluatng the ablty of reproducng the tme evoluton of low flows, and ε s an arbtrary chosen small value ntroduced to avod problems wth nl observed or smulated dscharges. The value of ε should be suffcently low, and those observed dscharges lower than ε value are neglgble. Otherwse the CR3 crteron would present a bas. Smlar as CR3, a perfect value of CR4 s 1. 5) Adapted verson of Nash-Sutclffe effcency for hgh flow evaluaton where, An adapted verson of the Nash-Sutclffe crteron s proposed as n Equaton It s n fact a combnaton between the calbraton crtera used by Guex (2001) for the hydrologcal study on the Alzette rver basn and the HEC-1 objectve functon (USACE, 1998). CR 5 = 1 = 1 N N ( Qo + Qo )( Qs Qo ) ( Qo + Qo )( Qo Qo ) = (3.13) where CR5 s an adapted verson of Nash-Sutclffe crteron for evaluatng the ablty of reproducng the tme evoluton of hgh flows. As can be seen n the formula, more weght s gven on hgh dscharges than low ones. A perfect value of CR5 s 1. Other model performance ndces are descrbed as follows: Modfed Correlaton Coeffcent r mod, whch reflects dfferences both n hydrograph sze and n hydrograph shape (McCuen and Snyder, 1975): σ o and r mod mn = r max { σ } { } o, σ s σ o, σ s σ s are the standard devatons of observed and smulated dscharges respectvely, r s the correlaton coeffcent between observed and smulated hydrographs. The perfect value for ths crteron s 1. 66

67 The mean squared error ( MSE ) s: 1 MSE = n n = 1 ε 2 where ε s the resduals, or estmated errors, are the dfferences between the observed data and ftted model: ε = ( Qs Qo ) Mean absolute error the mean absolute error s a quantty used to measure how close forecasts or predctons are to the eventual outcomes. The mean absolute error (MAE) s gven by 1 MAE = n n = 1 ε Root Mean Squared Error The root mean squared error ( RMSE ) s evaluated by the equaton: RMSE = MSE where MSE s the mean squared error. For a perfect ft, RMSE = 0. so, the RMSE ndex ranges from 0 to nfnty, wth 0 correspondng to the deal. Model Volumetrc effcency ( MVE ) The volumetrc effcency ranges from 0 to 1 and represents the fracton of water delvered at the proper tme; ts complment represents the fractonal volumetrc msmatch. The MVE s most accurate when detaled dscharge tme seres are avalable. The MVE would be partcularly helpful n comparng the performance of smlarly scaled, ranfall-runoff transfer functons. A major advantage of the MVE ts physcal sgnfcance as t treats every cubc meter of water the same as any other cubc meter, whether t be delvered durng low recesson or durng peak flows (Crss and Wnston, 2008): MVE N = 1 = 1 N ( Qs Qo ) = 1 Qo where MVE s the volumetrc effcency. A perfect value of MVE s 1. 67

68 4. MODEL OPERATION 4.1 PROGRAM INSTALLATION Installaton of WetSpa requres a Wndows 98/ME/2000/XP or Wndows NT 4.0 operatng system. Also requred are lcensed versons of ESRI s ArcVew 3.2 GIS Applcaton and Spatal Analyst v2.0 Extenson. In addton, the software of Vsual FORTRAN 6.1 or other FORTRAN complers are requred f the user wants to edt and modfy the program source code. The mnmum drve space requred s 100MB. Addtonal space may be necessary dependng on the spatal and temporal scale of the project. By smple copy and paste operaton, the model can be nstalled and run on any computer drves and under any exstng drectores. Specfc folders are referenced from that drve locaton throughout the modellng process. Fgure 4.1 gves a schematc vew of the model s project folders. Project Document ArcVew Model DEM Sol type Land use Coverage Asc Data Help Scrpt Table Temp Project.apr Input Output Program Source Fg Schematc vew of the model s project folders Where Project s the general folder of the modellng project, and the others are: 1) Document: for storng model documents 2) ArcVew: for storng ArcVew GIS components 3) ASCII: for storng spatal parameter maps n ASCII format 4) Data: for storng spatal data of base maps 68

69 5) Help: for storng model help fles 6) Scrpt: for storng ArcVew Avenue scrpts 7) Table: for storng model lookup tables. 8) Temp: project workng drectory for storng ntermedate and temporary fles 9) Project.apr: ArcVew project of the model 10) DEM: dgtal elevaton model 11) Sol type: dgtal sol type map n grd format 12) Land use: dgtal land use map n grd format 13) Coverage: for storng coverage data ncludng statons, streams, boundares, etc. 14) Model: for storng model nputs, outputs and programs 15) Input: for storng model nput fles 16) Output: for storng model output fles 17) Program: for storng model executve programs 18) Source: for storng program source codes 4.2 PROGRAM DESCRIPTION Avenue scrpts and ther tasks 1) conductvty: creates a grd of saturated hydraulc conductvty 2) delta_h: calculates standard devaton of flow tme from cells to the basn outlet 3) delta_s: calculates standard devaton of flow tme from cells to the man rver 4) depresson: calculates depresson storage capacty for each cell 5) feldcapacty: creates a mosture grd at sol feld capacty 6) fllsnk: fll snks to remove small mperfectons from DEM 7) flowacc: creates an accumulated flow grd at each cell 8) flowdr: creates a flow drecton grd from each cell to ts steepest downslope neghbour 9) flowlen: calculates a downstream dstance grd along ts flow path 10) ntercepton: calculates mnmum and maxmum ntercepton storage capacty 11) la: creates a grd of leaf area ndex 69

70 12) mannng: calculates Mannng s roughness coeffcent for each cell 13) mask: creates a mask grd of the watershed 14) mosture: creates an ntal sol mosture grd based on the topographc ndex 15) porendex: creates a grd of sol pore sze dstrbuton ndex 16) porosty: creates a mosture grd at sol porosty 17) radus: calculates hydraulc radus for each cell accordng to flood frequency 18) resdual: creates a mosture grd at resdual sol mosture content 19) rootdepth: creates a grd of root depth 20) runoffco: creates a grd of potental runoff coeffcent 21) slope: creates a slope grd for both land surface and rver channel 22) streamlnk: assgns unque values to sectons of stream network 23) streamnet: creates a grd of stream network 24) streamorder: assgns a numerc order to branches of a rver network 25) streamtolne: converts stream grd to a lne coverage 26) t0_h: calculates flow tme from each cell to the basn outlet 27) t0_s: calculates flow tme from each cell to the man rver 28) thessen: creates a grd of Thessen polygons 29) velocty: creates a velocty grd for both overland flow and channel flow 30) v_fracton: creates a grd of maxmum fractonal vegetaton cover 31) watershed: determnes subwatersheds based on stream lnks 32) wltngpont: creates a mosture grd at permanent wltng pont Lookup tables 1) depresson.dbf: default values of depresson storage capacty for dfferent land use, sol texture, and near zero slopes 2) landuse_reclass.dbf: land use reclassfcaton table for dervng potental runoff coeffcent and depresson storage capacty of the 5 man land use classes 3) landuse_remap.dbf: default model parameters based on land use classes, ncludng root depth, mannng s roughness coeffcent, ntercepton capacty, vegetated fracton and leaf area ndex 4) radus: default parameters governng average hydraulc radus for a certan flood 70

71 frequency 5) runoff_coeffcent.dbf: default potental runoff coeffcent for dfferent land use, sol texture, and near zero slopes 6) sol_remap: default parameters based on sol texture categores, ncludng hydraulc conductvty, porosty, feld capacty, wltng pont, resdual mosture, pore sze dstrbuton ndex, etc Fortran programs and ther tasks 1) mean: calculates mean parameters of each subcatchment 2) uh: calculates the unt response functon of each cell to the catchment and subcatchment outlet, the unt hydrograph of each subcatchment to the catchment and subcatchment outlet, and the unt hydrographs of man rvers. 3) model1: sem-dstrbuted model on subcatchment scale 4) model2: fully dstrbuted model on cell scale 5) water_balance: calculates water balance on grd scale wthout flow routng 6) evaluaton: statstcs of smulaton results and model evaluaton 4.3 GIS PRE-PROCESSING The purpose of GIS pre-processng s to create all necessary spatal parameter maps used n the WetSpa Extenson. Open a new ArcVew project project (or other name) under the subdrectory \project\arcvew. Set the project s workng drectory to \project\arcvew\temp, n whch the ntermedate and temporary GIS fles are stored, and all other nput and output fles are transferred from or to ther subdrectory referencng to ths path. Before performng GIS pre-processng, be sure that the ArcVew Extensons: Spatal Analyst, GeoProcessng, WetSpa and Create Thessen Polygons, are added to the ArcVew project. Next, Load grd themes of elevaton, landuse and soltype from the subdrectory \project\arcve\data to the Vew Topography, Landuse and Soltype separately. Set the theme names as Elevaton, Landuse and Sol. Note that the extent of these three base maps must be the same n order to perform the model smulaton properly. 71

72 4.3.1 Surface grd preparaton Surface parameter grds based on a DEM are prepared n the vew Topography of the ArcVew project. The preparaton of a proper DEM employs many geo-processng schemes, and can be mplemented ndependently from the project usng more powerful GIS software, such as ArcInfo etc. From the avalable DEM, ts hydrologcal potental s calculated n ArcVew by performng the followng functons: fllng snks, determnng flow drecton and flow accumulaton, assgnng stream network, stream lnk and stream order, calculatng slope and hydraulc radus, and delneatng subcatchments, etc. Fgure 4.2 gves a screenshort of the surface grd menu. Fg Screenshort of surface menu 1) Fll Snks A snk s a cell or set of spatally connected cells whose flow drecton cannot be assgned one of the eght vald values n a flow drecton Grd. Ths can occur when all neghbourng cells are hgher than the processng cell. In ArcVew GIS, snks are consdered to have undefned flow drectons and are assgned a value that s the sum of ther possble drectons. To create an accurate representaton of flow drecton and therefore accumulated flow, t s requred to use a data set that s free of snks. The fll 72

73 snks request n the surface menu takes a grd theme Elevaton and flls all snks and areas of nternal dranage contaned wthn t. The process of fllng snks can create new snks, so a loopng process s used untl all snks are flled (ESRI, 1999). The output theme s named as Flled Elevaton dsplayed n the same vew, and the correspondng ASCII fle elevaton.asc s saved n the subdrectory /project/arcvew/asc used for estmaton of alttude-dstrbuted temperature. 2) Mask A mask grd defnes the study regon n the grd doman, whch can be used to extract catchment boundary, determne the extent of other grds, etc. The request takes the grd theme Flled Elevaton and assgns a unque value 1 for the cells wthn the study catchment wth output theme Mask dsplayed n the same vew. 3) Flow drecton The flow drecton request calculates the drecton of flow out of each cell nto one of ts eght neghbours. The drecton of flow s determned by fndng the drecton of steepest descent from each cell. If a cell s lower than ts 8 neghbours that cell s gven the value of ts lowest neghbour and flow s defned towards ths cell. If the descent to all adjacent cells s the same, the neghbourhood s enlarged untl the steepest descent s found (ESRI, 1999). The request takes the grd theme Flled Elevaton and calculates flow drecton for each cell wth output theme Flow Drecton dsplayed n the same vew. 4) Flow accumulaton The flow accumulaton request creates a grd of accumulated flow to each cell by accumulatng the weght for all cells that flow nto each downslope cell. Cells of undefned flow drecton can only receve flow; they wll not contrbute to any downstream flow. The accumulated flow s based upon the number of cells flowng nto each cell n the output grd. Output cells wth a hgh flow accumulaton are areas of concentrated flow, and therefore can be used to dentfy stream channels. Output cells wth a flow accumulaton of zero are local topographc hghs and can be used to dentfy rdges. The request takes the grd theme Flow Drecton and calculates flow accumulaton for each cell wth output Flow Accumulaton dsplayed n the same vew. 73

74 5) Stream network The results of the flow accumulaton are used to create a vector stream network by applyng a threshold value to subset cells wth a hgh-accumulated flow. All cells that have more than a user-defned number of cells flowng nto them are assgned a value of one; all other cells are assgned no data. The resultng stream network can be used as a predcted hydrography (ESRI, 1999). The stream network request takes the grd theme Flow Accumulaton and delneates a stream network grd Stream Network dsplayed n the same vew. 6) Stream lnk Lnks are the sectons of a stream channel connectng two successve junctons, a juncton and the outlet, or a juncton and the dranage dvde (ESRI, 1999). The stream lnk request takes the grd themes Flow Drecton and Stream Network, and assgns unque values to sectons of a stream network between ntersectons. The output theme s named as Stream Lnk dsplayed n the same vew, whch can be used as the source grd to create dranage basns that correspond the branches of a stream network. Meanwhle, the output grd data s wrtten to an ASCII fle lnk.asc used to calculate IUH of stream channels. 7) Stream order The stream order request takes the grd themes Flow Drecton and Stream Network, and assgns a numerc order to segments of the stream network. The Shreve method s used n the model, n whch all lnks wth no trbutares are assgned an order of 1 and the orders are addtve downslope. When two lnks ntersect, ther magntudes are added and assgned to the downslope lnk. The output theme s named as Stream Order dsplayed n the same vew, and used as a source grd n assgnng Mannng s n for stream channels. 8) Slope The process of slope dervaton calculates the rate of maxmum change for locatons on the elevaton grd theme and creates a new grd theme Slope as output. Each cell n the output theme contans a contnuous slope value represented as a percentage. Consderng that the stream network s n a vector style, and ts slope s determned by the elevaton dfference and dstance between the up and down cells along the 74

75 streamlne, the channel slope s calculated separately from the general slope usng DEM and the stream network nformaton. Ths avods the dsturbance n channel slopes for a rver, especally for stream channels wth asymmetrc sde slopes of the rverbank. The fnal slope grd s then obtaned usng the general slope grd overlad by the grd of channel slope. An ASCII fle slope.asc s saved n the subdrectory /project/arcvew/asc for use n calculatng nterflow from each cell. 9) Hydraulc radus The hydraulc radus request takes the grd theme Flow accumulaton, and calculates hydraulc radus for each grd cell. The hydraulc radus s determned by a power law relatonshp wth an exceedng probablty, whch relates hydraulc radus to the controllng area and s seen as a representaton of the average behavour of the cell and the channel geometry. Generally, a flood frequency wth 2-year return perod s chosen for normal floods. The two controllng parameters can be adjusted n the lookup table radus.dbf to meet the specfc characterstcs of catchment. The output grd theme s named as Radus (m), and s used for calculaton of flow velocty at each cell. 10) Watershed The watershed request takes the grd themes Flow Drecton and Stream Lnk, and determnes the subcatchment for each stream lnk. The output grd theme s named as Watershed dsplayed n the same vew, and s saved as an ASCII fle for sem-dstrbuted modellng and the smulaton of groundwater balance. If the subcatchment does not delneate as expected, delete the grd themes Stream Network, Stream Lnk and Watershed by nvokng the delete theme command n the edt dropdown menu, and rebuld the three grd themes by settng a new threshold value. Often t s necessary to closely zoom nto the area of nterest to ensure the outlet pont s locaton s postoned correctly Sol based grd preparaton To calculate the sol hydraulc propertes, actvate the vew Soltype, select the Parameter dropdown menu, and the commands related to sol types are hghlghted (Fg. 4.3), ncludng Conductvty, Porosty, Feld capacty, Resdual mosture, Pore dstrbuton ndex, and wltng pont, etc. The commands Maxmum saturaton, 75

76 Arthmetc mean of G and Geometrc mean of G are desgned for future model mprovement, where G s the capllary drve (mm). By clckng each of the command, the grd fles are created to redefne and dsplay the sol unts wth respect to ther hydrologcal propertes, and the correspondng ASCII fles are saved n the subdrectory /project/arcvew/asc. Fg Screenshort of parameter menu Another actvated functon under the dropdown menu s the Intal mosture. Ths functon creates an ntal relatve saturaton grd of the sol usng the method of the Topographcal Wetness Index. A mnmum rato reflectng the mosture condton of the drest cells s asked n a pop up wndow, whch can be selected from the provded lst. The output theme s named as Intal Mosture dsplayed n the same vew, and the ASCII fle mosture.asc s saved n the subdrectory /project/arcvew/asc. Note that ths operaton s optonal and desgned for event based flood modellng, for whch the ntal sol mosture condton s rather mportant Land use based grd preparaton To calculate the land use dependent modem parameters, actvate the vew Landuse, select the Parameter dropdown menu, and the commands related to land use grd are hghlghted, ncludng Root depth, Vegetated fracton, Intercepton capacty, 76