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1. i These values will be used to estimate BD BDref TopSoilBD BDRef1 4 three phases of top and subsoil water content saturated hydraulic conductivity field capacity and permanent wilting point proportionally to area fraction of soil type and soil depth per subcatchment and per year of land cover transition time Plant available water I PlantAvWatSub1 4 inaccessible water for plants PWPSub1 4 and capacity of soil quick flow I SoilSatMinFCSub1 4 for each subcatchment and per year of land cover transition time estimated from these three phase of top and subsoil water content Input Parameters Location in Excel BD BDref per year of land cover transition time Cells FA4 F47 BDref soil texture and soil carbon Cells B79 F88 Area of each soil type per subcatchment Cell AE8 AN27 Soil depth of each s oil type Cell AE35 Al44 Estimated Input Parameters Location in Excel SoilSatMinFCSub1 4 Cells AN101 AN120 AW101 AW120 BF101 BF120 BO101 BO120 PlantAvWatSub1 4 Cells AO101 AO120 AX101 AX120 BG101 BG120 BP101 BP120 PWPSub1 4 Cells AP101 AP120 AY101 AY120 BH101 BH120 BQ101 BQ120 TopSoilBD BDRef1 4 Cells B145 U145 B161 U161 B177 U177 B193 0193 Generic River and Flow Persistence Models Link to Stella sheet This sheet stores all input parameters linked to Stella No changes are allowed on this worksheet 2 1
2. C119 F100 F119 1100 1119 L100 L119 GWRelFrac1 4 Subcatchment Cells D100 D119 G100 G119 J100 J119 M100 M119 LandCoverData sheet The sheet LandCoverData Figure 2 7 is designed to help you initialize 1 land cover type of each subcatchment 2 year of land cover change 3 fraction of land cover change for each subcatchment and each transition year and 4 potential interception drought limitation BD BDRef per land cover type and multiplier of daily potential evapotranspiration 12 Generic River and Flow Persistence Models Year of land cover change GenRiver arranges changing of land cover type based on a given year of transition with linear interpolation for years in between This data links to Stella I InputDataYears BE le git vew pest Format Took Dua Window Hep Adobe PDF KA ni EBa0D1 ex APE _ ioe Oo ow s EBEN Ba Duc ab Em oe a amp r nis ue 05 Nan o5 ad n iud ir Land Cover Data This spreadsheet is built to help you to initialize The typology of land cover use types for your simulation Key hydrological properties of the land cover type potential interception drought limitation soil bulk density Year of land cover change land cover transtition time Land cover type of each subcathment Fraction of each land cover type per subcatchment per year of land cover transition time This spreadsheet is also helps you to estimate Da
3. Month Airport Station Research Station Average Min Average Max Min Average Max Min Average Max 1 3 13 3 47 3 74 2 38 329 415 2 76 3 38 3 95 2 4 15 4 45 4 62 3 66 4 87 5 76 3 91 4 66 5 19 3 4 88 5 46 5 93 4 73 5 51 6 64 4 81 5 49 6 29 4 5 65 6 24 6 91 4 64 5 64 6 62 5 15 5 94 6 77 5 5 20 5 89 6 74 2 79 4 11 5 20 4 00 5 00 5 97 6 4 07 4 56 5 07 1 63 2 65 4 07 2 85 3 61 4 57 7 3 83 4 12 4 52 0 99 2 24 3 83 2 41 3 18 4 18 8 4 01 4 30 4 97 1 33 222 4 11 267 3 26 4 54 9 3 80 4 32 4 81 1 94 2 61 3 80 2 87 3 47 4 31 10 3 84 4 18 4 34 2 37 2 88 3 84 3 11 3 53 4 09 11 3 56 3 72 3 78 2 06 3 00 4 72 2 81 3 36 4 25 12 3 07 3 31 3 47 1 99 2 56 3 18 2 53 2 94 3 33 52
4. Suriace run off pquick we outflow T al base ee flow percolation canopy water F evaporation y transpiration JJ surface A evaporation surface run on sub surface lateral Generic River and Flow Persistence Models interception Vegetation spongel Soil water store Groundwater discharge Riverflow GenRiver is a generic river model on river flow As is common in hydrology it start the accounting with rainfall or precipitation P and traces the subsequent flows and storage in the landscape that can lead to either evapotranspiration E river flow Q or change in storage AS Figure 1 3 P Q E AS Models differ in the relations between the different terms of the balance equation and in the way they account for the slow flows that derive from water that infiltrates into the soil but can take a range of pathways with various residence times to reach the streams and rivers depending on land form geology and extractions along the way The core of the GenRiver model is a patch level representation of a daily water balance driven by local rainfall and modified by the land cover and land cover change and soil properties of the patch The patch can contribute to three types of stream flow surface quick flow on the day of the rainfall event soil quick flow on the next day and base flow via the gradual release of groundwater A river is treated as a
5. wA A Gen River ara Meine van Noordwijk Rudy Harto Widodo Ai Farida Desi A Suyamto Betha Lusiana Lisa Tanika Ni matul Khasanah World Agroforestry Centre GenRiver and FlowPer Generic River and Flow Persistence Models User Manual version 2 0 Meine van Noordwijk Rudy Harto Widodo Ai Farida Desi A Suyamto Betha Lusiana Lisa Tanika Ni matul Khasanah World Agroforestry Centre 2011 Correct citation van Noordwijk M Widodo RH Farida A Suyamto D Lusiana B Tanika L Khasanah N 2011 GenRiver and FlowPer Generic River Flow Persistence Models User Manual Version 2 0 Bogor Indonesia World Agroforestry Centre ICRAF Southeast Asia Regional Program 117 p Disclaimer and Copyright This is version 2 0 of a model on river flow Although efforts have been made to incorporate relevant process knowledge on a range of interactions the model is no more and no less than a research tool Model predictions may help in developing specific hypotheses for research in exploring potential management options and extrapolation domains but they should not be used as authoritative statements Copy right but do not copy wrong The GenRiver model was developed on the basis of publicly funded research by the World Agroforestry Centre ICRAF and may be used for non commercial research purposes in the interests of the smallholder agroforesters of the world The STELLA modelling shell used is protected by international
6. 2 Familiarize yourself with GenRiver stm To familiarize yourself with GenRiver stm we suggest you try the following exercise e First view the model component by clicking model structure then go to each component of the model At the end return to the main menu e Second run the model using the default parameters looking at the simulation result e Third modify the input parameters try anew run and import the result In the following sections you will find descriptions on how to perform each of the above exercises View the model components On the Main Menu you will see something like in Figure 2 9 on your screen by clicking model sector button The model has the following components 7 oe LIE Lom m His Patch Water fee ra up anu ssl d SubcResDynamic u ELE __ Memamen eon 7 Working with the GenRiver model 1 an initialization sector dealing with input data related to rainfall data Rainfall river flow data I RivFlowData subcatchment condition SubcatchmParam daily evapotranpiration DailyEvapotranspiration and land cover type l_LandCover 2 dynamic sectors dealing with patch level water balance PatchWaterBalance stream and river flow StreamNetwork and the operational rules of reservoirs in the river network SubcResDynamic 3 two sectors for keeping track of all output parameters required Check amp Balance and Measurement Period and 4 in
7. compass direction of the rain front Dairaku et al 2000 The rainy season mostly occur May to October with average temperature range of 20 34 C Deciduous forest is still the largest amount of land cover 43 followed by evergreen forest 11 at higher elevations and a considerable range of other classes ranging from urban field crop shrub scrub crop mosaic rice field fallow orchard degraded forest and hill pine forest Thomas et al 2006 30 Kilometers ee 3 2 2 Data on input parameters Rainfall There are more than 20 rainfall stations in the Mae Chaem basin We chose six stations which had the same series of data to interpolate daily rainfall depth for all subcatchments Table 3 12 We used Thiessen interpolated rainfall data for the whole basin area Figure 3 11 Figure 3 12 and Table 3 13 as the basic rainfall data 48 Table 3 12 Rainfall stations and description data available in the area Rainfall station WRD55 MTD22 RYP48 RYP46 GMT13 WRD 52 Name Mae Chaem MAE Wat Chan WA Doi Inthanon DO Research Station RE Ban Kong Kan Ban Mae Mu X 434894 425936 445494 426124 432146 437312 2039919 2108176 2054637 2047327 2050808 2070460 Eleva tion m 454 960 2565 1100 446 660 Source Water Resource Dept Met Dept Royal Project Royal Project Game T data Rainfall Data 1989 2003 1989 2003 1989 2003 1989 2003 1989 20
8. field capacity permanent wilting point and saturated water content for 10 soil groups You should provide bulk density relative to its reference value BD BDref for each land cover type and for each year of land cover transition time Values of BD BDref for each land cover type are defined based on the range of BD BDref forest soil 0 7 agriculture soil 1 degraded soil 1 3 while BD BDref for each year of land cover transition time is the generic value within the range of BD BDref of forest to degraded soil Working with the GenRiver model W Er Ed yew poot Format Took Qua Window tp Adobe POF O Ps oe ge E Dsugu ad AA r tltl BR we D um ua ffo T Soil Properties own amp QM This spreadsheet is built to help you to initialize Soil physical bulk density and soil texture and chemical soil carbon properties B Area of each soil type 10 groups of soil type Soil depth of each soil type This spreadsheet is also built to help you to estimate Three phase of top and sub soil water content field capacity permanent wilting point and saturated water content per subcatchment and per year of landcover transition time Plant available water inaccessible water for plant and capacity of soilquick flow BACK TO READ ME Soil Physical amp Chemical Properties YOU CAN ONLY CHANGE VALUES IN BLUE FONT Soi Area and Depth rows You can not insert columns or BENISEREBN
9. for a patch or plot level water balance Figure 4 4 Overview of the GenRiver model the multiple subcatchments that make up the catchment as a whole can differ in basic soil properties land cover fractions that affect interception soil structure infiltration rate and seasonal pattern of water use by the vegetation The subcatchment will also typically differ in routing time or in the time it takes the streams and river to reach an observation point Figure 4 5 Models for watershed functions at catchment scale need to combine explicit rules for effects of land use on interception infiltration and transport to the stream network at patch scale with assemblage and filter rules that reflect the river network and the changes that this can cause to the overall flow Figure 4 6 Two alternative models for steady river flow the sponge and patchy rain versions that are likely to dominate research at plot left and landscape right levels Figure 4 7 Array of dimensions used in the model 50 52 53 56 57 60 61 61 63 65 68 70 71 72 74 76 xii Figure 4 8 Implementation process of daily rainfall at subcatchment level from long term records 78 Figure 4 9 Water balance at soil surface level 79 Figure 4 10 The soil water dynamic 81 Figure 4 11 Water balance in ground water 83 Figure 4 12 Interpolation of land cover fraction inside GenRiver Number 1 2 110nl Fracl 11 1 Frac2_11 Fra
10. require explanation see next section C Flow persistence Q versus Q plots may indicate gaps in the data or outliers that indicate errors see further in Chapter 5 Double Mass Curves of Cumulative Rainfall and River Flow We compared the cumulative river flow against the cumulative rainfall to visually inspect the relationship between rainfall toward simulated and observed river flow for discrepancies Double mass chart for 1989 3000 ___ River ET Delta Storage NR YA e e SurfaceFlow Base flow SoilQFlow SoilQFlow Base flow x o U gt E E 3 o ram U 2 rn Ki 5 23 Qo Baseflow 1000 2000 3000 Cumulative rainfall mm year 2 2 3 Analysis on indicators of watershed functions water quantity and quality The assessment of the hydrological situation of a watershed is determined by the criteria and indicators of water transmission total water yield per unit rainfall buffering capacity relationship of peak river flow and peak rainfall linked to flooding risk and gradual release of ground water in the dry season based on recharge in the rainy season Table 2 5 These indicators all relate the flows of water to the preceding rainfall and by doing so allow analysis of relatively small land use effects superimposed on substantial year to year variations in rainfall We provide a file IndicatorWatershed to help you make this analysis 32 Ge
11. simulation owing to time availability of land cover classification The observed data was adjusted to the whole basin area by calculating the fraction area of contributed area Table 3 14 Table 3 14 Annual river flow data recorded in P14 station mm year Year River flow Year River flow 1989 251 1997 223 1990 240 1998 126 1991 278 1999 324 1992 219 2000 319 1993 169 2001 252 1994 362 2002 342 1995 377 2003 33 1996 301 Evapotranspiration Evapotranspiration in the Mae Chaem basin was obtained from pan evaporation data recorded at Airport TM meteorology department and Mae Chaem Watershed Research Station RFD Table 3 15 The Airport Station was located outside the basin thus daily evapotranspiration data was taken from the average of both stations Table 3 16 The actual data of evapotranspiration per land cover type was provided by multiplying this average data to evapotranspiration multiplier per land cover type Table 3 17 Generic River and Flow Persistence Models Rainfall mm E E z u S 2 a 1997 Vou Rainfall mm River Flow mm Table 3 15 Locations of available weather station data Id Name Elevation X Y Source Available m Data MTD17 Airport CM 304 498946 3 2077423 4 Met Dept 1973 2003 RFD44 Research Station 1100 426123 7 2047326 7 RFD 1986 2002 Table 3 16 Monthly average of daily potential evapotranspiration pan evaporation record in Mae Chaem 1989 2003
12. summation of streams each originating in a subcatch ment with its own daily rainfall yearly land cover fractions and constant total area and distance to the river outflow or measurement point Interactions between streams in their contribution to the river are considered to be negligible that is there is no backflow problem Spatial patterns in daily rainfall events are translated into average daily rainfall in each subcatchment The subcatchment model represents interception infiltration into soil rapid General information percolation into subsoil surface flow of water and rapid lateral subsurface flow into streams with parameters that can vary between land cover classes This user s manual is designed to help people who work with the GenRiver model The text of the manual is organized as 1 general overview on GenRiver model and minimum system requirement to run it 2 guide on working with GenRiver model and evaluation on model output 3 number of examples of model application and 4 detail on model description and its component and appendices on description of model input and output parameter advice on dealing with data inputs parameter and advice on model calibration Subcatchments can differ in timing of rainfall vegetation inherent soils soil compaction and routing time for stream flow a Deen infiltration To ka ote Cos ms Ja E Routin Time LO amp AS Soil Di
13. 03 Water Dept 1989 2003 Examples of model application Weighting Area 0 30 0 18 0 04 0 18 0 05 0 26 Generic River and Flow Persistence Models Me Thiessen E S ac 0 L 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 Year Table 3 13 Annual rainfall 1989 2003 recorded in Mae Chaem basin Year Mae Wat Doi Research Ban Kong Ban Mae Average Chaem Chan Inthanon Station Kan Mu Thiessen MAE WA DO RE 1989 816 1267 1781 1245 809 1310 1137 1990 569 2224 492 1172 974 1357 1195 1991 891 1064 1793 1223 991 1119 1079 1992 765 861 1187 908 1097 957 1993 281 849 1243 1065 738 745 702 1994 383 1904 2097 1176 1180 1804 1271 1995 384 1176 2033 1344 1155 1701 1139 1996 487 922 2245 1322 1032 1404 1064 1997 808 927 1559 1086 790 956 948 1998 476 938 1916 855 781 939 816 1999 1033 1220 3648 1341 1473 1474 1377 2000 999 883 2796 1352 1076 1469 1266 2001 809 1191 2740 988 1027 1513 1177 2002 1026 63 3165 1627 1381 2003 877 670 2161 985 921 50 Examples of model application River flow data River flow data was obtained from the Royal Irrigation Department RID river gauge station P 14 in Ob Luang which has an area of about 3740 km The data was taken from ICHARM web site which publishes discharge data recorded 1954 2003 Figure 3 13 http www icharm pwri go jp html network pub dabase top files maecha m q txt We used data from 1 January 1989 to 30 March 2003 for the
14. 5 lt NSESO 75 Satisfactory 0 50 lt NSE lt Q 65 Unsatisfactory NSESO 5 Coefficient of correlation The coefficient of correlation representing the change direction of simulation data compared with the observation data gt x u X nean y u Yun where x is observation data y is simulation result x_ is mean observation data and y is mean simulation When applying the GenRiver model to landscapes where at least some riverflow data are available there is an opportunity to assess the lack of fit between model and measurements Lack of fit can be due to 1 inaccuracy or error in the data e g with incomplete representation of spatial variability on rainfall and or errors in the data records 2 suboptimal model parameterization 3 error and or oversimplification in the model process description Component 3 can only be assessed if components 1 and 2 can be quantified Tests of data consistency can be used to assess component 1 for example at seasonal aggregate level Steps can include A P Qgives an estimated top total evapotranspiration Values below 500 or above 1500 mm year are suspect These may indicate errors in P or Q registration error in the area or deviation from the closed catchment assumption for example subsurface flows out of or into the catchment are non negligible Working with the GenRiver model B Double Mass curves of cumulative Q versus P during the year large jumps will
15. 6 1998 PU2 Pusair Excel files Subcatchment Boundaries ICRAF Indonesia Shape files ESRI Hydrology River Network ICRAF Indonesia Shape files ESRI Bureau of Meteorological and Geophysics Public Work Department National Electricity Company World Agroforestry Centre ICRAF Indonesia RiverFlow mm Z amp Rainfall mm co e 2000 RiverFlow mm Rainfall mm 34 Examples of model application River flow data Daily river flow data are available for from 1976 to 1998 and 2005 and covering 90 of the total area For the years 1976 1998 the daily river flow data were obtained from the Department of Public Works in Kotabumi Lampung province local level and from PUSAIR Pusat Litbang Sumber Daya Air the Research Centre for Water Resources based in Bandung national level The daily river flow data were estimated based on continuous water level measurements using a drum recorder For the year 2005 the daily river flow data were obtained from the World Agroforestry Centre ICRAF Indonesia The daily river flow data were measured using automatic water level Data was extrapolated to hydropower inlet 414 4 km by calculating the fraction area Figure 3 1 Evapotranspiration Monthly average of potential evapotranspiration was calculated using the Thornwaite equation Air temperature data is one of its input parameters Figure 3 2 Daily pattern of potential evapotranspiration of each land c
16. 9443224 428931 5 9442640 42 6 16 Wlirikan 440783 9445875 435966 5 9440275 6 7 17 WB8 441281 9446547 431951 5 9433445 40 9 18 WPetai 442535 9445669 447846 5 9441005 13 8 19 WCengkaan 442046 9449398 435511 5 9445630 27 3 20 WDAM 442415 9449293 439381 5 9435155 15 1 Total 414 4 Table 3 6 Final input parameters BD BDref potential interception and relative drought threshold Land Cover Class Potential Interception Relative Drought BD BDref mm day Threshold Sun coffee 1 08 1 00 0 55 Shrub and grass 1 07 3 00 0 60 Forest 0 80 4 00 0 40 Simple shade 1 00 2 00 0 55 Multistrata 1 00 3 00 0 60 Horticulture 1 07 1 00 0 70 Rice field 1 10 1 00 0 90 Settlement 1 30 0 05 0 01 40 Generic River and Flow Persistence Models Table 3 7 Final input of non measured parameter of GenRiver Acronym Definition Value RainInterceptDripRt i Rain interception Drip Rate 10 mm RainMaxlntDripDur i Rain interception Drip Duration 0 5 mm InterceptEffectontrans i Rain Interception Effect on Transpiration 0 8 mm RainlntensMean Average rainfall intensity 30 mm day RainIntensCoefVar Coefficient of variation of rainfall intensity 0 3 MaxlnfRate i Maximum infiltration capacity per unit 720 mm day MaxlnfSubsoil i Maximum infiltration capacity per unit i 120 mm day PerFracMultiplier i Daily soil water drainage as fraction of 0 13 groundwater release fraction MaxDynGrWatStore i Dynamic groundwater storage capacity 300 mm GWReleaseFra
17. B hard disk space 16 bit color Thousands of colors 1 3 Installing GenRiver model You may copy and decompress the GenRiver model GenRiver stm and the MS Excel file GenRiver xls into any directory 2 Working with the GenRiver model 2 1 Starting the GenRiver model The GenRiver xls file contains a number of macros The default setting in most MS Windows and MS Excel installations is to not allow such macros and to not even ask whether the user wants them or not If your computer security settings don t allow any macro to run you may need to change the security level for macros If you are working with MS Excel 2003 to change the security level go to Tools and Macro and choose low then close and re open GenRiver xls It will give a warning that the file contains a macro Choose enable macro and then you will see something like Figure 2 1 If you working with MS Excel 2007 to change the security level for macros follow the diagram below This is to make sure the macro built to ease inputting parameters in the model is working properly Then run Stella and open GenRiver stm If you are working with Stella 7 or 8 to update the linked input from GenRiver xls into GenRiver stm click Yes when the question This model contain links Re establish link appears on your screen when you open GenRiver stm If you working with Stella 9 to update the linked input from GenRiver xls into GenRiver stm
18. D Pw E EH ae Es Dust a tee Erd me wow Gat amje AAAS D E F G H J k 2 GenRiver MODEL A Generic model on River flow 4 By Meine van Noordwijk Ai Farida Rudi H Widodo Desi Suyamto Betha Luslana Lisa Tanika and Ni matu Khasanah ICRAF South East Asia 5 This Excel file contains input parameters that are linked to the GenRiver model version 2 running in Stella EES CO Wise lela celery Tee 7 or higher Research or Regular Version The final sheet provides the links summarized from all sheets st The GenRiver model is based on rainfall and predicts river now or dabit The workaheets called RiverFlowData 11 RainData and RiverFlowData allow you to enter data on the primary driver of the water balance 12 and of data that can be used to check the validitry of the model and or tune model parameters to 13 get a better match As examples the sheets contain the rainfall and river flow data from M s Sumberjaya Way Besai watershed in Lampung Indonesia for the years 1976 2007 hCatchlnfe T The names of subeatchments their area oroundwaber storage and the routing distance from each Subeatchment to the final outlet debermine the routing times We can add observation points anywhere in 29 the basin to match the availability of data or points of specific Interest for flow prediction 16 The sheet SubCatchInfo provides the basic GIS description of the catchment and its subcatchments mmm Li
19. NSE r NSE 1976 365 14 87 0 64 0 8 satisfactory 1977 365 2 24 0 59 0 8 satisfactory 1978 365 2 73 0 60 0 8 satisfactory 1979 365 1 35 0 70 0 9 good 1980 365 1 07 0 63 0 8 satisfactory 1981 365 2 11 0 70 0 8 good 1982 365 9 92 0 64 0 8 satisfactory 1983 365 8 98 0 64 0 8 satisfactory 1984 365 11 30 0 55 0 8 satisfactory 1985 365 8 14 0 42 0 7 unsatisfactory 1986 365 15 69 0 37 0 7 unsatisfactory 1987 365 10 98 0 68 0 8 good 1988 365 14 86 0 59 0 8 satisfactory 1989 365 5 44 0 42 0 7 unsatisfactory 1990 365 0 88 0 32 0 7 unsatisfactory 1991 365 3 17 0 59 0 8 satisfactory 1992 365 1 24 0 61 0 8 satisfactory 1993 365 0 12 0 76 0 9 very good 1994 365 0 07 0 75 0 9 very good 1995 365 27 07 0 34 0 7 unsatisfactory 1996 365 28 23 0 02 0 5 unsatisfactory 1997 365 39 26 0 29 0 8 unsatisfactory 1999 365 40524 54 542 45 0 1 unsatisfactory 2005 365 221 31 3 31 0 2 unsatisfactory 2006 365 5 87 0 76 0 9 very good Generic River and Flow Persistence Models RiverFlow mm o S e Ai nla pem 1980 1988 1992 1996 2000 2004 2008 Year Measured Debit mm Simulated Debit cu 1000 1500 2000 2500 3000 3500 0 1000 1500 2000 2500 3000 3500 Cumulative Rainfall mm er Cumulative RiverFlow mm 42 Examples of model application PI tn f 3 Ba e 100 150 200 250 300 350 Measured Debit Simulated Debit Water balance of Way Besai The average water balance of Way Besay during 31 ye
20. River flow is the flow of water in the river channel Storage capacity is the total amount of water that can be stored in a reservoir before overflow occurs Stream flow is the flow of water in streams rivers and other channels Surface runoff or Overland flow is the flow across the land surface of water when rainfall rate exceeds the infiltration capacity of the soil The rate of infiltration and therefore the possibility of surface runoff is determined by such factors as soil type vegetation and the presence of shallow relatively impermeable soil horizons Saturated overland flow can occur when a temporary rise of the watertable inhibits infiltration and causes flow over the surface Total discharge fraction is total water yield discharge per unit rainfall usually on an annual basis Water balance is the comparison over a certain time period for example month or year of inflow of water precipitation and outflows by evapotranspiration stream flow and subsurface flows Water quality is the chemical physical and biological characteristics of water with respect to its suitability for a particular use Water storage is the volume of water that can be temporarily withheld from evapotranspiration stream flow or subsurface flows either above ground in lakes rivers and other waterways or below ground as ground water Water transmission is the fraction of incoming precipitation that is converted into stream flow Prefac
21. apacity is the ability of a system to reduce the impact of external variation on internal properties for example reducing the variation in stream flow relative to variation in rainfall Buffering indicator is derived from the ratio of above average stream flow and above average rainfall Buffering for peak events is the buffer function demonstrated at peak rainfall events C Cref is the organic soil carbon content of a soil relative to the reference soil Corg concentration that can be expected for a soil of similar texture pH and mineralogy under natural forest conditions at the given elevation temperature regime Discharge or Outflow of a river is the volume of water transported by it in a certain amount of time The unit used is usually m s cubic meters per second Evapotranspiration is a term used to describe the sum of evaporation and plant transpiration from the earth s land surface to atmosphere Evaporation accounts for the movement of water to the air from sources such as the soil canopy interception and waterbodies Transpiration accounts for the movement of water within a plant and the subsequent loss of water as vapor through stomata in its leaves Field capacity is the volumetric soil water content measured one day after a saturating rainfall event when rapid drainage and interflow have removed excess water to streams or groundwater Flash floods is floods caused by heavy or excessive rainfall in a short pe
22. ars of simulation excluding the unsatisfactory output and unavailable data is presented in Table 3 9 The result showed that evapotranspiration in the area was about 3496 of annual rainfall and base flow was 3696 of annual rainfall Runoff in the whole catchment area was about 2696 of annual rainfall while soil quick flow is 496 of annual rainfall Table 3 9 Average water balance of Way Besai during 10 years simulation No Bunamicot Water Observed Simulated Average Average 1 Precipitation mm 2515 2515 2 Evapotranspiration mm 858 34 3 River flow mm 1648 66 1658 66 gt Runoff mm 645 26 x Soil Quick Flow mm 101 4 gt Base Flow mm 911 36 NB Values in parentheses are percentages Aa Generic River and Flow Persistence Models Analysis of indicators of watershed functions water quantity due to land cover change The assessment of the hydrological situation of a watershed is determined by the criteria and indicators of water transmission total water yield per unit rainfall buffering capacity relationship of peak river flow and peak rainfall linked to flooding risk and gradual release of ground water in the dry season based on recharge in the rainy season Table 3 9 These indicators all relate the flows of water to the preceding rainfall and by doing so allow the analysis of relatively small land use effects superimposed on substantial year to year variation in rainfall The watershed f
23. both forest cover and land use patterns outside of the forest have been well documented and are subject to considerable interest from downstream water users We used this basin as a test of the robustness of GenRiver and of the reliability of the model predictions Table 3 11 Data available in Mae Chaem basin Data Timeseries Sources Files WRD55 MTD22 MS Excel chia Daily Rainfall 1989 2002 RYP48 RYP46 GMT13 WRD 52 Pan Evaporation 1989 2002 RFD Airport MS Excel DEM DEM 1989 2002 ICRAF SEA Asc Land Cover Landsat TM5 BSQ 30 1989 ICRAF Chiang Mai GRID Landsat TM7 HDF 15 2000 Spatial Data Geology TRFIC MSU EDU Vector shp Soil TRFIC MSU EDU Vector shp Subcatchment Boundaries TRFIC MSU EDU Vector shp River Network TRFIC MSU EDU Vector shp Discharge Daily discharge P 14 1954 2003 ICHARM MS Excel 1 World Agroforestry Centre ICRAF Southeast Asia Program 2 World Agroforestry Centre ICRAF Thailand office 3 2 1 Area description Mae Chaem watershed is geographically positioned at 18 06 19 10 North and 98 04 98 34 East The basin area is about 3890 km The elevation varies from 475 to 2560 m above sea level and slopes range from 0 to 78 Generic River and Flow Persistence Models The climate of this basin has seasonal variations influenced by Pacific born typhoons which superimposed on the south west monsoon orographic effect induces an increase of rainfall with elevation depending on the dominant
24. cVar i An option to have a constant groundwater 0 1 release fraction for each subcatchment or using single value for the whole catchment Tortuosity i Stream shape Factor 0 4 Dispersal Factor i Drainage density 0 3 River Velocity i River Flow velocity 0 4 ms 3 1 4 Modelling result Model performance The model was simulated by using rainfall data from 1 January 1976 to February 2007 The periods where there were no measured data available were discarded and the remaining periods were used for performance analysis We obtained the result that 16 of the 25 years of the simulation period showed satisfactory to good performance NSE 0 5 0 75 The bias is less than 20 and the minimum coefficient of correlation r is 0 55 Table 3 8 The model simulation could capture most of the observed pattern across 31 years Figure 3 5 and Figure 3 6 As shown in Figure 3 5 and Figure 3 6 observed and simulated flows for the first year 1976 tenth year 1986 16th year 1992 and the last year of simulation 2006 with daily correlation coefficient respectively with daily correlation coefficient are 0 78 0 73 0 84 and 0 83 However the model still has underestimation prediction if compared to observation data particularly in the second and at the end of the simulation period Examples of model application Table 3 8 Performance of GenRiver based on Nash Sutcliffe Efficiency NSE criteria of Moriasi et al 2007 Year n Biased
25. chment downstream of the observation point Estimated values of the differential storage in active groundwater as well as a groundwater release fraction were tuned to the recession phase of Working with the GenRiver model actual river flow during periods without rainfall In the absence of such data we need to guesstimate If data on the seasonal variation in depth of ground water table are available we can use those Wt t3 gem Feet Kamati Took Quo aiw tip Ak POF te E MWe BF u EES ex 2 Se A a Ow oe mm He ms Osea a tee go amp r Hi BI woe Oo 49 9 G Gu sm 2n Axas Subcatchment Information This spreadsheet is built to help you to initialize Subcatchment wv oc oO UC b rm area Routing distance for each subcatchment to either the final outlet or observation point Maximum ground water storage and its release fraction per subcatchment and per year of landcover transition time Relative River Flow Velocity per subcatchment and per year of landcover transition time Type Ctri t to update all subcatchment and soil YOU CAN ONLY CHANGE VALUES IN BLUE FONT You can not insert columns or rows ERBEEBFNIERLENTB i i Input parameters Location in Excel file Area Cells B52 B71 RoutingDistance Cells D52 J71 RivFlowTime1 4 Subcatchment Cells B100 B119 E100 E119 H100 H119 K100 K119 MaxDynGWSub1 A Subcatchment Cells C100
26. ci1 4 the first number land cover type the second number the transition year FracVegClass1 FracVegClass2 FracVegClass3 and FracVegClass4 is land cover fraction for start simulation first transition second transition and end transition 85 Figure 5 1 Effect of changing the test Fp value on the frequency distribution of Q estimates showing the decrease of mean and increase of the fraction of negative Q estimates with increase in test Fp value the algorithm selects the test Fp value that minimizes the standard deviation of the Q estimates frequency distributions 90 Figure 5 2 The main interface of the FlowPer Model 92 Figure 5 3 The interface of the FlowPer model 93 Figure 5 4 Example of the type of fit that can be achieved for the six parameter FlowPer model 94 Figure 5 5 Jangkok sub watershed 95 Figure 5 6 Flow persistence value of Jangkok sub watershed 96 Table 2 1 Five buttons which control the simulation run Table 2 2 Summary of available output Table 2 3 Minimum data requirements to be able to run the GenRiver model Table 2 4 Reference stream flow model performance Moriasi et al 2007 Table 2 5 Criteria and indicators of watershed hydrological functions relevant to downstream stakeholders Van Noordwijk et a 2006 Table 3 1 List data available in Sumberjaya watershed Table 3 2 Monthly multipliers of evapotranspiration per land cover type Table 3 3 Soil BD BDref derive from soil physical measur
27. click on the working area After a numeric display box appears double click on it Now you will see a box emerge with two small boxes in the upper section e Toload a parameter into this numeric display highlight the parameter in the allowable box then click an adjacent arrow pointing to the selected box Locking graphs or tables to speed your simulation You can lock pages in your graphs and tables that you do not need Locked graphs or tables will not be updated in the next simulation run This saves a lot of time needed to run the model To lock a graph or table click on the lock icon It is in the bottom left corner of your graph or on the top right corner of your table Importing output results You can save your table as a text file and your graph as a pct file You can open the table saved as a text file in MS Excel You can also use copy Ctrl C and paste Ctrl V your output table For graphs or summary output you can use screen dump Shift Print then paste to your favourite software Working with the GenRiver model Graph Type f Time Series Scatter C Bar Sketchable Comparative Gonnect Dots Benchmark Allowable Selected C C Stocking ate D CumEvapLake D CumEvapTranspClass D CumHEPPUse D CumlnflowtoLake Title Untitled Wo Show Numbers On Plots Hide Detail Make 5 Grid Segments M Show Grid v Thick Lines Min Max Scale Gel Page From To Display Jo 3650 Cancel B
28. copyright Copies of the software are available from http www worldagroforestry org sea genriver ISBN 978 979 3198 50 7 For further information please contact Dr Meine van Noordwijk World Agroforestry Centre ICRAF Southeast Asia Program PO Box 161 Bogor 16001 Indonesia E mail m van noordwijk cgiar org Design and layout Tikah Atikah Photographs Ni matul Khasanah Rudy Harto Widodo and Degi Harja 2011 Water flow in rivers is generated by rainfall and modified by landscape topography vegetation and soil and also by human engineering to enhance drainage and or retention of water The degree to which river flow is influenced by land cover change deforestation reforestation agroforestation and other such practices is hotly debated as is the influence of climate change A simple tool that relates plot level to river level consequences was deemed relevant to assist in the analysis of catchment data Existing models were either too complex and data hungry or left out important processes such as the impact of land use change on the soil and its physical condition GenRiver is a generic river flow model that responds to spatially explicit rainfall and keeps track of a plot level water balance that responds to changes in vegetation and soil The model treats a river as a summation of streams each originating in a subcatchment with its own daily rainfall yearly land cover fractions and routing time based on distance to the
29. d from open pan evaporation measurements or from equations such as Penman s that is calibrated on such data e Rainfall spatial correlation optional An indication of the degree of spatial correlation in rainfall correlation 28 Generic River and Flow Persistence Models coefficient of daily rainfall as function of distance between stations or of the generic nature of rainfall frontal rains with high spatial correlation or convective storms that are patchy and show low correlation 2 Actual river discharge If available river debit data for any period of time expressed in m s in the river or mm day over the whole contributing subcatchments will be valuable in constraining the simulations If not available we will simply have to believe the model predictions as such 3 Vegetation and Land Cover e Year of transition of land cover change e Fractions of total land covers an example Deciduous reducing LAI in dry season to near 0 Semi deciduous reducing LAI in dry season to less than 0 5 of value in wet season Evergreen maintaining LAI at over 0 5 of the maximum value Bare soil or built up areas Open surface water Other land cover classification Interception storage capacity per land cover class Drought limitation to transpiration per land cover class relative to field Capacity 9 9 9 4 Soils e Average texture or soil type in a way that allows texture to be estimated as input to
30. de ETT i C Hours Normal Days Dycle time To 3650 Weeks C Months Interaction Mode DT 1 00 C Quarters Normal C Years C Flight Sim DT as fraction C Other Pause interval INF Integration Method Sim Speed Euler s Method ae o real secs 1 unit time C Runge Kutta 2 C Runge Kutta 4 Min run length O secs Analyze Mode stores run results in memory 395 9 MB required Cancel _ Working with the GenRiver model oh amp River Flow P 4 RFlowdata mmday 2 LinFlowtoLake 1048 25 1365 50 1682 75 2000 00 Days 2 34 FM Wed Nov 24 2010 River Flow Output result The type of output produced by GenRiver is river flow and water balance There are three types of output presented 1 Tables 2 Graphs and 3 Output summary To view output simulation results in a graph or table double click on the graph or table icon What you will see is actually a stack of graphs or tables Figure 2 14 and Figure 2 15 To view the rest of the graphs or tables click on the folded page at the bottom left corner When you look at the graphs notice that the scale on Y axis between parameters on the same graph can be different Match the index number of parameters with index number of scales in the Y axis To view output simulation result in output summary Figure 2 16 click on each button below the graphs and tables You will see a box displaying output parameters 22 Generic Riv
31. e Glossary List of Figures List of Tables 1 General information 1 1 GenRiver model overview 1 2 Minimum system requirements 1 3 Installing GenRiver model 2 Working with the GenRiver model 2 1 Starting the GenRiver model 2 1 1 Familiarize yourself with GenRiver xls 2 1 2 Familiarize yourself with GenRiver stm 2 2 Simulation with your own scenario 2 2 1 Minimum data requirements 2 2 2 Evaluation of model performance 2 2 3 Analysis on indicators of watershed functions water quantity and quality 3 Examples of model application 3 1 Simulation based on default parameter setting Sumberjaya 3 1 1 Area description 3 1 2 Raw data available 3 1 3 Data of input parameters 3 1 4 Modelling result 3 1 5 Discussion and conclusion 3 2 Simulation based on other sites Mae Chaem Basin North Thailand 3 2 1 Area description 3 2 2 Data on input parameters 3 2 3 Model output 3 2 4 Discussion and conclusions 4 Description of model sectors 4 1 Why a river flow model 4 2 GenRiver Model 4 2 1 Two alternative explanations for steady river flow lii ix xiii KR KR RS 31 33 33 33 33 33 40 46 47 47 48 59 64 65 65 70 72 Vil viii 4 2 2 Quantification of buffering of river flow by watershed areas 4 2 3 Target properties of the model 4 3 Description of GenRiver components and processes 4 3 1 Water balance 4 3 2 Stream network 4 3 3 Land cover 4 3 4 Subcatchment parameter 5 Flow Pe
32. e similar or e any rainfall simulator equation with the appropriate parameters that can be used to generate a 30 year dataset for the site for example MarkSim Working with the GenRiver model Table 2 3 Minimum data requirements to be able to run the GenRiver model Input Parameters Climate Rainfall i gt Average rainfall intensity gt Monthly or daily potential evapotranspiration Actual river discharge Vegetation and land cover gt Fraction of land cover i t gt Year of land cover change gt Potential interception j gt Drought limitation j Soil Soil texture and soil carbon gt BD BDref i t gt Fraction soil area s Soil depth t s gt Average of infiltration rate of top and sub soil Geology gt Percolation gt Ground water release fraction Subcatchment and river behaviour gt Area of subcatchment i gt Routing Distance i gt Tortuosity i gt Dispersal Factor i gt River Velocity i Dimension 1 mm day 1 mm day Mm 3 1 ms mm Mm km 1 ms Note index t refers to time dependent input i to subcatchment s to soil type and j to land cover classes e Rainfall intensity Data on rain duration and amount for a sampling period that is deemed representative to estimate the mean and coefficient of variation of rainfall depth per hour e Potential evapotranspiration Average values per month or daily data derive
33. e GenRiver model step in Stella special care is needed to obtain same day flows A similar issue holds for the soil quick flow that can reach the observation point at the earliest one day after the rainfall Run the model using default parameters To run or to see simulation results from Main Menu click To Run amp Output You will see something like Figure 2 12 on your screen Running GenRiver On the Run amp Output Section screen you will find five buttons see Figure 2 12 which control the simulation run as listed in Table 2 1 The model will run using default parameters by clicking Run Button The default setting will run for 12410 days with incremental time of simulation as one day By clicking Time Specs Button you will see something like Figure 2 13 allowing you to change the beginning and ending times of the simulation also DT which is incremental time of simulation We strongly advise you to keep DT value at 1 Generic River and Flow Persistence Models Click on Graph Table or Button to see the simulation results ga gE Er Model Petar B HEFF HEFP Back sans Vater funt koe aro Table 2 1 Five buttons which control the simulation run Buttons Purpose Run To start simulation Pause To pause during simulation run Stop To stop simulation Resume To resume simulation after pausing Run Spec To specify length of simulation time RUN SPECS Length of simulation Unit of time Hun Mo
34. ed to run the GenRiver model Changing input parameters that link to GenRiver model should not be done once you run the GenRiver stm and GenRiver xls simultaneously In all sheets you can only change values in blue font Below are explanations of each sheet Definition of each acronym of input parameter refers to appendix 1 Generic River and Flow Persistence Models RainData sheet The sheet RainData stores rainfall data and is implemented as daily amounts mm day from long term records This sheet also stores monthly evapotranspiration data Figure 2 3 The rainfall data can be derived from actual daily rainfall data records or from a random generator that takes temporal patterns as done in Markov chain models such as was used by Jones et al 2001 for temporal autocorrelation into account as well as the spatial correlation of rainfall at any point in time IM Be Edt Yew met Format Tock Data Window Bep AdobePDF nzu ESI s JA ERO Aa Daremu He Digu dt i bmo A r Hi ME woe 8 Rainfall amp Monthly Potential Evapotranspiration To Monthly Potensial Daily Rainfall Data mm day Evapotranspiration a Clr te update all rain and river parameters Data used here is Thiessen interpalated from 8 station of Way Besai m E Watershed 1975 1998 West Lampung Sumatera Indonesia 29 020 SANA LIZmua i545 Ni e t5 A WOOOk how RES ZSLSReeee ore gcn te Cm amp SE P inm p tbi e hi
35. een in Stella the user can modify input values Figure 2 19 Example of a double mass chart of cumulative river flow components against cumulative rainfall the change in slope at about 1500 mm indicates start of a relatively dry period Figure 3 1 Rainfall and river flow in Way Besai Sumberjaya West Lampung for period August 1976 May 2007 There is a gap due to no river flow data available in 1983 1998 to 2005 Figure 3 2 Monthly average of potential evapotranspiration calculation using Thornwaite method This ranged between 97 to 104 mm Figure 3 3 Catchment and subcatchment boundaries of Way Besai Figure 3 4 Soil map derived from soil survey conducted by CSAR Kasdi et al 2005 legend shows the derivation type of soil order 1 andisol 2 inceptisol and 3 ultisol Figure 3 5 Plot of simulation against observation for 1 January 1976 13 February 2007 Figure 3 6 Plot of cumulative of simulated and observed rainfall and river flow during 31 year simulation period Figure 3 7 Hydrograph of simulated and observed of rainfall and river flow over 31 years Figure 3 8 Discharge Fraction during 31 year simulation top left and Gradual water release function bottom left The water transmission function top right and Buffering capacity function bottom right Figure 3 9 Indicators of watershed function of Way Besai Sumberjaya expressed in relationship to the total discharge fraction which is positively correlated with annual rai
36. ement Kasdi et al 2004 Table 3 4 Land cover classification of Way Besai Sumberjaya ICRAF Indonesia database Table 3 5 Subcatchment area and stream length Table 3 6 Final input parameters BD BDref potential interception and relative drought threshold Table 3 7 Final input of non measured parameter of GenRiver Table 3 8 Performance of GenRiver based on Nash Sutcliffe Efficiency NSE criteria of Moriasi et al 2007 Table 3 9 Average water balance of Way Besai during 10 years simulation Table 3 10 Average of indicators of watershed functions Table 3 11 Data available in Mae Chaem basin Table 3 12 Rainfall stations and description data available in the area Table 3 13 Annual rainfall 1989 2003 recorded in Mae Chaem basin Table 3 14 Annual river flow data recorded in P14 station mm year Table 3 15 Locations of available weather station data Table 3 16 Monthly average of daily potential evapotranspiration pan evaporation record in Mae Chaem 1989 2003 Table 3 17 Monthly multiplier used for evapotranspiration per land cover type Table 3 18 Main soil order of Mae Chaem subcatchments Table 3 19 Land unit in Mae Chaem basin Merrit 2005 Table 3 20 Infiltration base of reference basic infiltration rates for various soil types Brouwer 1990 20 23 27 30 32 34 36 37 38 39 49 40 41 43 45 47 49 50 51 52 52 53 54 55 55 xiii XIV Table 3 21 BD BDref Unpublished survey r
37. er and Flow Persistence Models Z Daily Water Balance X 5 6 2011 Water Balance p1 Daily Water Balance jed Days ORainAcc ointereace O EvapoTransAO SollQFlowAclO Infacce OPercAcc O Deepinf cc O Baserlowacdo 1579 476 ago 3 05 ooa 9 283 35 000 351 15800 390 178 00 212 353 ooo 352 058 049 274 X 000 009 349 00 352 1581 1582 1583 1585 1586 1589 1590 1891 1592 1593 1594 1595 1596 1598 1599 N lt i 5 Ger Heri OSTA B i Subcatchment Balance D Camote 17734 cc 00 Working with the GenRiver model Table 2 2 is summary of available output on display See more detailed definition on each output parameter presented in Appendix 2 Table 2 2 Summary of available output Graph amp Table Graph Content Page Table Page 1 WaterBalance HEPP Output Parameters RFlowData mmday L_InflowtoLake O RainAcc O IntercAcc O EvapotransAcc O SurfQFlo O InfAcc O RainAcc O DeepinfAcc O PercAcc O SoilQFlowAcc O BaseFlowAcc O CumhRain O Cumilnterc O CumEvapot O_CumSurfQFlow O Cuminf O CumRain O CumDeepinf O CumPerc O CumSoilQFlow O CumBaseFlow RFlowData mmday L InflowtoLake L HEPPWatUseFlow L HEPPkwh L LakeVol L LakeLevel O BestYHEPP O WorstYHEPP L CumHEPPUse O FrBaseFlow O FrSoilQuickflow O FrSurfQuickFlow Graph Table Type Time series Time series Time series Time ser
38. er flow in two catchments in SE Asia the Way Besai Sumberjaya watershed in Lampung Indonesian and Mae Chaem in Northern Thailand default input parameters are based on the Sumberjaya case The model treats a river as a summation of streams each originating in a subcatchment with its own daily rainfall yearly landcover fractions and constant total area and distance to the river outflow or measurement point Interactions between streams in their contribution to the river are considered to be negligible i e there is no backflow problem Spatial patterns in daily rainfall events are translated into average daily rainfall in each subcatchment in a separate module The subcatchment model represents interception infiltration into soil rapid percolation into subsoil surface flow of water and rapid lateral subsurface flow into streams with parameters that can vary between land cover classes 20 subcatchments can be simulated in this model The number of land cover classes is 11 2 1 1 Familiarize yourself with GenRiver xls GenRiver xls is organized into nine sheets labeled READ ME RainData RiverFlowData SubCatchInfo LandCoverData Fallow OUT SoilProperties LinktoStella and LinktoStella9 The last two sheets provide two alternative formats for linking the input parameters the GenRiver stm model depending on the version of Stella used The basic purpose of this Excel file is to help with organizing and modifying input parameters need
39. er of daily potential evapotranspiration I MultiplierEvapoTrans LandCoverType These multiplier values follow seasonal patterns of crop tree and paddy The highest value 1 rice field pine and the lowest 0 1 houses All these data are linked to Stella 14 Generic River and Flow Persistence Models Input parameters Location in Excel file InterceptClass LandCoverType Cells B105 B115 RelDroughtFact LandCoverType Cells C105 C115 MultiplierEvapoTrans LandCoverType Cells E105 P115 DailyE TYear to Cells AZ11 BG1470 BD BDref per land cover type Cells D105 D115 SoilProperties sheet The SoilProperties sheet Figure 2 8 is designed to help you initialize 1 soil physical bulk density and soil texture and chemical soil carbon properties of 10 groups of soil type 2 area of each soil type 10 groups of soil type and 3 soil depth of each soil type This spreadsheet also provides basic estimates of 1 three phases of top and subsoil water content i field capacity ii permanent wilting point and iii saturated water content per subcatchment and per year of land cover transition time and 2 plant available water inaccessible water for plants and the capacity of soil quick flow Soil physical bulk density reference and soil texture and chemical soil carbon properties of 10 groups of soil type are derived from the soil database They are used to generate generic values of
40. esults from ICRAF Thailand 2002 LUT BD BDref Table 3 22 Satellite data for Mae Chaem area Saipothong et al 2007 Table 3 23 Land use types in Mae Chaem basin based on Landsat image classifications Classified by ICRAF Thailand Table 3 24 Routing distance from centroid point to the outlet Table 3 25 Final input parameter BD Bdref potential interception and relative drought Table 3 26 Final input parameters GenRiver Table 3 27 Performance of GenRiver based on Nash Sutcliffe efficiency NSE criteria of Moriasi et al 2007 Table 3 28 Water balance during 10 year simulation excluding the hydrological years 1998 1999 and 1999 2000 Table 3 29 Average of indicators of watershed functions for Mae Chaem basin for 1992 2002 Table 4 1 Models concepts of river flow Table 4 2 The overall water balance of the model summed over space and time Table 4 3 Well documented impacts of land use change by basin size Kiersch and Tognetti 2002 x Measured impact No well documented impact Table 4 4 Rainfall input table in MS Excel spreadsheet Table 5 1 Multiple influences on process and pattern of river flow and the downstream perceptions of ecosystem services modified from van Noordwijk et al 2006 Table 5 2 Standard deviation of the Q estimate distributions for a range of Test F values on a data set labelled Standard and two data sets that achieve a doubling of mean flow either through addition of the mean val
41. fe Efficiency as criteria Moriasi et al 2007 The similarity pattern was determined from the coefficient of correlation Parameters that were used for this calibration included the potential canopy interception and relative drought threshold per land cover type Table 3 6 and a number of the catchment response parameters Table 3 7 Model calibration was only carried out across the years for which data were available and no year specific ad hoc adjustments were made Model calibration was not pursued beyond coarse tuning of round numbers A key parameter for the dry season recession rate GWreleaseFracVar was tuned to the overall pattern in dry periods Examples of model application Table 3 5 Subcatchment area and stream length Outlet Centroid 2 No Subcatchment X Y X Y Area km 1 WTebu 447790 9441713 450951 5 9443950 7 7 2 WB1 449860 9443057 451731 5 9442500 3 2 3 WB2 451121 9440860 441626 5 9432780 2 7 4 WB3 446839 9437697 438026 5 9442660 38 7 5 Air Ringkih 443369 9435719 441146 5 9443460 6 1 6 WB4 442207 9434911 442916 5 9438090 25 7 7 Air Lingkar 442146 9434909 432941 5 9438950 5 7 8 WB5 438965 9436841 446051 5 9443450 42 8 9 WB6 435686 9438712 443086 5 9442990 16 8 10 Air Hitam 434952 9437048 437671 5 9438755 55 0 11 Air Napalan 434589 9440836 441386 5 9447405 6 0 12 WKabul 434562 9440872 445366 5 9435795 30 4 13 WRingkih 436110 9443545 429566 5 9439140 7 4 14 WB7 436032 9444430 437326 5 9450300 19 7 15 WCampang 434060
42. fluence of existing cattle and grass on the dynamics of soil structure Catle Grass and SoilStrucDyn You will see how the model is constructed by clicking the triangle on the right top corner of each component An example view of the constructed model component is shown in Figure 2 10A and 2 10B To return to the model sector menu click the small up triangle on the left top corner then click To Main Menu Below are brief descriptions of each of the model components Figure 2 10A Diagram of the patch level water balance in Stella with the stocks represented by rectangles parameters by circles water flows by double lined arrows and information flows by single lines Patch Water Balance DailyRainAmount a D D ActEvapTransp D D CumEvapTranspClass m InterceptEffectonTransp zi A I PotEvapTransp ec LT RelDroughtF act sd CanintercAreaClass SoilSatClass b l MaxinfArea Dr t RainTimeAvForlnf T RainDuration AD RainintercDelay ie RainIntercDripRt RainMaxIntDripDur D Raininiere 42 ED InterceptEvap H ReiArea eb SoilDischarge 2 Ed 2 iTA 3 SWRelRt Nec vaplrrigation CY Soil flowF rac Son N M D SoilQflowRelFrac D GWabDisch A CY B GWUsdFar pr DAftrigEfficiency WA D GW Utilization fractio 7 D Irrigation D EvapTranspClass 18 Generic River and Flow Persistence Models Rainfall p Evapo
43. heet Figure 2 8 View of Soil Properties sheet Figure 2 9 Components of GenRiver Model implemented in Stella Figure 2 10A Diagram of the patch level water balance in Stella with the stocks represented by rectangles parameters by circles water flows by double lined arrows and information flows by single lines Figure 2 10B Diagram of the patch level water balance overland flow and soil quick flow calculated at land use subcatchment array elements and groundwater relations at the subcatchment level Figure 2 11 Diagram of the stream network model sector The incoming flows surface flow soil discharge and groundwater discharge are delayed according to travel distance and flow velocity on their way to reach the various measuring points Figure 2 12 View of Run amp Output Section Figure 2 13 View of Time Specification screen Figure 2 14 Example of river flow prediction blue and river flow data red as one of the output parameters We can compare measured CN D A W 10 11 12 15 16 17 18 19 20 20 and simulated river flow over time in this example no specific effort to fit the model was made Figure 2 15 Example of output parameters in Table Figure 2 16 An example of cumulative table as output The balance per user defined measuring period allow us to check sensitivity of the water balance parameters Figure 2 17 View of box in working graph or table to load output parameters Figure 2 18 Input scr
44. hosen and you use output from the FALLOW model you have to copy genriver1 genriver2 genriver 25 file from the FALLOW model to the FALLOW Out sheet Input parameters Location in Excel file Land Cover Type Cells A105 A115 Cells BR15 BR325 Cells BS15 BS325 Cells BT15 BT325 Cells BU15 BU325 Frac1_1 11_4 Subcatchment Potential interception drought limitation and potential evapotranspiration You should provide storage capacity for intercepted water I InterceptClass of each land cover type mm day It is treated as a linear function of leaf branch area index of the land cover with the option of modifiers for surface properties that determine the thickness of the water film forest 4 young secondary forest young agroforestry 3 You should also provide drought limitation to transpiration per land cover class relative to field capacity I RelDroughtFact The values depend on drought resistance highest resistance 1 teak lowest resistance 0 1 durian The sheet LandCoverData also will contain potential evapotranspiration mm day data These can be either daily I DailyETYear to or monthly data Evapotrans These values can be derived from open pan evaporation measurements or from equations such as Penman s that calibrate such data The monthly pattern of potential evapotranspiration for each land cover type is calculated by multiplying these monthly values by a multipli
45. ies Time series Time series Time series Time series Time series Time series Time series Time series Time series Time series Time series Time series Time series Time series Time series Time series Time series Time series Scatter Scatter Time series Time series Time series Time series Time series Time series Time series Time series Time series Time series 24 Generic River and Flow Persistence Models Adding additional output parameters e To add more parameters to your tables or graphs do the following e Double click on your graph or table After a graph table appears double click again on it You will see a box emerge with two small boxes in the upper section Figure 2 17 The left box allowable box contains parameters that can be loaded into the graph or table The right box selected box contains parameters already in the graph or table A graph can contain up to five parameters while a table can contain more than 40 e Toload a parameter into the graph or table highlight the parameter in allowable box then click an adjacent arrow pointing to the selected box e If you want to load a parameter to a new clean page prior to the above you need to click an arrow pointing upward at the bottom left corner adjacent to Page Keep on clicking until you see NEW as page number e o add more parameters in box as in output summary do the following e Click on icon numeric display in the menu bar then
46. ily values of potential evapotranspiration based on monthly data The land cover data used for the default come from the Way Besai Watershed West Lampung Indonesia You can redefine and change the names of the land cover types to adjust to your situation YOU CAN ONLY CHANGE VALUES IN BLUE FONT H You can not Insert columns or rows Type Ciri to update all land cover BREEBSSSHERR i i Input parameters Location in Excel file InputDataYears Cells C51 C54 Land cover type and fraction of land cover change Default land cover types are of Way Besai watershed West Lampung Indonesia You can change the names of the land cover types to adjust to the local situation There are two options to initialize fraction of land cover of each subcatchment it can be either uniform for all the subcatchments land cover identification 1 or different for each subcatchment land cover identification 0 The different land cover for each subcatchment can be either generated from spatial data or using output data from the FALLOW model land cover identification 2 To specify this option fill in cell BS11 in the Excel file Working with the GenRiver model If the second option is chosen and you are using spatial data you need to enter the fraction of land cover change for each subcatchment that corresponds to the year of land cover change These data link to Stella Fraci_1 11 A Subcatchment If the second option is c
47. lso be checked using coefficient correlation or double mass cumulative rainfall river flow curve PerformanceTestGenRiver is a file that consists of an explanation on the process of this evaluation Nash Sutcliffe Efficiency The Nash Sutcliffe Efficiency NSE is a normalized statistic that determines the relative magnitude of the residual variance noise compared to the measured data variance Nash and Sutcliffe 1970 NSE indicates how well the plot of observed versus simulated data fits the 1 1 line Y y ymy NSE 1 gt gt Lymeny I t where Yi is the observation for the constituent being evaluated Yi is the simulated value for the constituent being evaluated Y is the mean of observed data for the constituent being evaluated and n is the total number of observations NSE ranges between and 1 0 1 inclusive with NSE 1 being the optimal value Values between 0 0 and 1 0 are generally viewed as acceptable levels of performance whereas values lt 0 0 indicates that the mean observed value is a better predictor than the simulated value which indicates unacceptable performance Performance of the model result will be evaluated annually and will be accepted when performed NSE criteria are more than 0 50 Table 2 4 30 Generic River and Flow Persistence Models Table 2 4 Reference stream flow model performance Moriasi et al 2007 Performance Rating NSE Very Good 0 75 lt NSEX1 00 Good 0 6
48. n Average Max Total discharge fraction 0 5 0 7 0 9 0 5 0 7 0 8 Buffering indicator 0 5 0 7 0 8 05 0 7 0 8 Relative buffering indicator 0 2 0 4 0 6 03 0 6 0 7 Buffering peak events 0 4 0 7 0 9 0 7 0 8 0 9 Highest monthly discharge relative 1 4 2 3 30 13 1 9 2 8 to mean rainfall Overland flow fraction 0 2 0 3 0 4 Soil quick flow fraction 0 0 0 0 0 1 Slow flow fraction 0 3 0 4 0 5 Lowest monthly discharge relative 0 0 0 4 0 8 to mean rainfall 46 Generic River and Flow Persistence Models 1 0 SoilQFlow Fraction 0 8 Overland Flow Fraction 0 4 0 2 0 0 35 3 0 2 5 2 0 1 5 1 0 0 5 0 0 0 0 0 50 0 55 060 065 070 0 75 080 0 50 05 0 60 O88 070 07 0 80 E Highest Month Fraction m Slow Flow Fraction Buffering Peak Total Discharge Fraction Lowest Month Fraction 3 1 5 Discussion and conclusion Using existing data and current hydrological studies of Way Besai to parameterize input of the GenRiver model can increase the model performance Through several tests over a 25 year simulation GenRiver produced daily hydrographs close to the observation data The model could simulate more than 6096 of the simulation year with satisfactory to very good performance NSE 0 5 0 75 while bias is less than 2096 and the coefficient of correlation r is more than 0 72 Table 3 10 NSE more than 0 5 The water balance in Sumberjaya indicated that around 6696 of rainfall flo
49. nated by clay and silty clay soil with the average of soil BD BDref per land cover being quite low 0 67 0 92 Table 3 3 Table 3 3 Soil BD BDref derive from soil physical measurement Kasdi et al 2004 Class Number of Min of Average of Max of samples BD BDref BD BDref BD BDref Sun coffee 14 0 54 0 88 1 08 Shrub and grass 5 0 74 0 86 1 07 Forest 5 0 51 0 67 0 80 Multistrata 72 0 51 0 87 1 14 Horticulture 7 0 78 0 92 1 07 Rice field 13 0 58 0 85 1 10 Settlement 1 1 1 30 38 Generic River and Flow Persistence Models Land cover The various coffee systems increased for 30 years Forest and shrub cover declined from 60 to 14 with forest mainly being converted into coffee based systems Table 3 4 Table 3 4 Land cover classification of Way Besai Sumberjaya ICRAF Indonesia database Land cover type Land cover change ALL subcatchments 1976 1986 2000 2007 Forest 0 43 0 18 0 11 0 1 Simple shade 0 0 0 06 0 13 Multistrata 0 12 0 36 0 44 0 48 Shrub and grass 0 27 0 13 0 14 0 04 Horticulture 0 01 0 01 0 01 0 03 Sun coffee 0 16 0 19 0 2 0 09 Rice field 0 004 0 08 0 01 0 1 Settlement 0 01 0 03 0 02 0 03 Stream routing The routing distance was calculated by measuring the stream length from the stream segment closest to subcatchment centroid to the targeted outlet Table 3 5 Non measured input parameter A number of non measured parameters were used in a model calibration exercise using the Nash Sutclif
50. neric River and Flow Persistence Models Table 2 5 Criteria and indicators of watershed hydrological functions relevant to downstream stakeholders van Noordwijk et al 2006 Criteria Indicator Quantitative Indicator Site Relevant for Characteristics Water Total water yield Q Annual rainfall Downstream transmition discharge per WY Asp mm year water user unit rainfall TWY Q annual river flow A total watershed area P annual precipitation Buffering Buffering indicator Or Avg Geomorphology Communities BI 1 where E peak rain for peak flows Ax P living along P abs Avg event given peak rain the river and even BI Pits Ave gt max P P 0 in flood plains Q 4 7 2 max Q Q noan0 Relative buffering indicator adjusted RBI 1 u m X C dis ag for relative water mean abs Avg yield RBI Buffering peak BPE _Max Daily_O Open event BPE Ax max Daily _ P P can Fraction of total Direct output from model river discharge derived from surface quick flow run off Fraction of total Direct output from model river discharge derived from soil quick flow Gradual water Lowest of monthly river discharge totals relative to mean Soil type and Communities who release water monthly rainfall characteristics do not own water availability harvesting storing during dry systems lake season embung Fraction of dish Direct output from model charge drived from slow flow 1 day after
51. nfall over a 31 year period Figure 3 10 Mae Chaem Watershed as part of the upper Ping Basin contributing to the Chao Phraya Figure 3 11 Thiessen polygon to determine the area rainfall map 21 22 22 25 26 31 34 35 36 37 42 42 43 45 46 48 49 Figure 3 12 Annual rainfall in Mae Chaem basin Figure 3 13 Temporal pattern of observed rainfall spatially averaged over the Mae Chaem catchment and river flow at the P14 station Figure 3 14 Soil map in Mae Chaem basin Figure 3 15 Land cover in Mae Chaem basin Figure 3 16 Subcatchments of Mae Chaem basin Figure 3 17 Plot of simulation against the observed flow for 1 January 1989 28 February 2003 Figure 3 18 Hydrographic simulation result of land cover change Figure 3 19 Annual cumulative rainfall vs cumulative river flow Figure 3 20 Indicators of watershed function of Mae Chaem expressed in relationship to the total discharge fraction which is positively correlated with annual rainfall over a 11 year period Figure 4 1 The biophysical relations between rainfall land use in upper catchments and river flow to downstream Figure 4 2 The biophysical relations between rainfall land use in upper catchments and river flow to downstream areas are subject to discussions between downstream and upland people whose perceptions on the cause effect relations are reflected in policies that may aggravate poverty and conflict Figure 4 3 The basic framework
52. nktoStella 7 za The sheet LandCoverData defines the names and key properties of 11 land cover types that Influence 23 the water balance of the subcatchments It also specifies the way the land cover fractions change with time 24 for each subcatchment LinktoStella 9 25 The sheet SoilProperties contains properties of 10 groups of soll type soll physical bulk density Type Cirl r to update all raln and cher parammtors 27 and soil texture and chemical soil carbon properties area and soil depth of each soil type Type e to update taten dated 22 The sheet also provides basic estimation of three phase of top and sub soll water content eae NL er field capacity permanent wilting point and saturated water content 31 32 IN ALL SHEETS YOU SHOULD ONLY CHANGE VALUES TEXT IN BLUE FONT IN en t W README RanDate RiverFlowData SubCatchinfo LandCoverfata FALLOW Out SclFroperties LINKTOSTELLA Lrktostellas jal Working with the GenRiver model GenRiver Model 2 0 By Meine van Noordwijk Ai Farida Rudy Harto Widodo Desi Suyamto Betha Lusiana Lisa Tanika and Ni matul Khasanah ICRAF Southeast Asia Bogor GenRiver model is a generic model of river flow in a catchment that is subdivided in subcatchments up to 20 in the current version with separate dynamics of land cover change and rainfall and different properties for soil parameters and routing distance if desired The model was developed as a tool to analyze riv
53. over type was calculated by multiplying this monthly value to multiplier of each land cover type Table 3 2 5 g E a 5 j lt Evapotranspiration mm Air Temperature C Evapotranspiration mm Generic River and Flow Persistence Models Table 3 2 Monthly multipliers of evapotranspiration per land cover type Month Sun Shruband Forest Simple Multi Horti Rice Settlement coffee Grass Shade strata culture field 1 0 5 0 6 0 8 0 6 0 7 1 0 1 0 0 01 2 0 5 0 6 0 8 0 6 0 7 1 0 1 0 0 01 3 0 5 0 6 0 8 0 6 0 7 1 0 1 0 0 01 4 0 5 0 6 0 8 0 6 0 7 1 0 1 0 0 01 5 0 5 0 6 0 8 0 6 0 7 1 0 1 0 0 01 6 0 5 0 6 0 8 0 6 0 7 1 0 1 0 0 01 7 0 5 0 6 0 8 0 6 0 7 0 7 1 0 0 01 8 0 5 0 6 0 8 0 6 0 7 0 3 1 0 0 01 9 0 5 0 6 0 8 0 6 0 7 0 5 1 0 0 01 10 0 5 0 6 0 8 0 6 0 7 0 5 1 0 0 01 11 0 5 0 6 0 8 0 6 0 7 0 5 1 0 0 01 12 0 5 0 6 0 8 0 6 0 7 0 8 1 0 0 01 Catchment boundaries A digital elevation model DEM was derived from 1 50 000 scale topographic map to delineate the catchment boundaries Way Besai catchmentis about 414 4 km and consists of 20 subcatchments Figure 3 3 Subcat_finsbj shp L1 Centro riv subca shp Examples of model application Soil types Soil types in Way Besai are dominated by andisol 48 inceptisol 30 and ultisol 22 Figure 3 4 Infiltration Infiltration capacity in Way Besai was estimated based on soil physical properties Generally the topsoil of Way Besai catchment is domi
54. pedotransfer functions to estimate soil water retention curve saturation field capacity wilting point e Estimated bulk density relative to the reference value for soils under agricultural use to estimate saturated hydraulic conductivity and potential infiltration e Fraction of soil area of each soil type per subcatchment e Mean soil depth till major restriction for root development e Maximum infiltration rate of top and subsoil 5 Geology We need to estimate the differential storage in active groundwater as well as a groundwater release fraction So far these parameters were tuned to the recession phase of actual river flow during periods without rainfall In the _ Working with the GenRiver model absence of such data we will need to guesstimate If data on the seasonal variation in depth of ground water table are available we can use those 6 Subcatchment and river behaviour Coarse DEM that allows for derivation of overall difference in elevation within the subcatchment and a delineation of sub subcatchments If there is a generic language for the shape of the subcatchments relative to the main channel we may use this 2 2 2 Evaluation of model performance Evaluation of model performance can be done by comparing simulation results to measurement data Statistical indicators proposed by Nash and Sutcliffe 1970 are used for checking the performance of the model The performance of the model can a
55. r ae sse SRpERES 78 18 46 98 98 FB8 0E 64 I5 AB 33 i 5 1 2 mp ide 6 86 E ai ee C t CEE EE S MEC n n 7 wee Bt Input parameters Location in Excel file Location in Stella DailyRainYear to Subcatchment Cells B15 11474 Input Section Rainfall SpatRain1 7 Subcatchment Input Section Rainfall Evapotrans RainData Sheet Cells T15 T26 Input Section Subcatchment Parameter This option is activated by switching on or off the slider UseSpatVarRain in GenRiver stm Input Section Rainfall Value 1 means using spatial rainfall distribution generated from SpatRain model and O means using actual daily rainfall data records Working with the GenRiver model Default values are based on the actual daily rainfall data from Sumberjaya Way Besai watershed in Lampung Indonesia for 32 years 1976 2007 The data are arranged in eight columns containing data for four years for each column as this is the maximum length that can be copied to Stella and it is linked to Stella DailyRainYear to Subcatchment Figure 2 4 You can adjust the daily rainfall data records for a station representing the area or multiple stations if these are supposed to be similar or using generated daily rainfall data using SpatRain model For generated data using SpatRain model you should manually copy the data to GenRiver stm input parameters SpatRain1 7 Subcatchm ent Fig
56. r 25 28 ear29 32 1976 1979 1980 1983 1984 1987 1988 1991 1992 1995 1996 1999 2000 2003 2004 2007 244 26 1 31 7 19 3 31 1 19 3 28 4 18 8 27 9 27 2 20 0 21 8 27 2 17 5 17 5 S C cA ow eo 1 2 3 4 5 6 7 8 9 SESBB5E EB oe o oo no oonsboo obeo oo2a a S888888888888888 888 MNioto oU 0B RObmMR O RiBRMOYHAB A LOUbDOO Ssssssssssssssss 2228 NRSSRBASSLRNSSOAA 1C OWoW aownoodnh cn iSSEESKSSSESSSS nN WSSSERS imSSSOPRSSELSSELS BOBNZSSSI IER N O Ur OO CO Un 74 D Ch O CO I 0o Un IJIOOOOOoOoooooooooooooococzco 1909090959995 909090990909 5900 I5 amp M Input parameters Location in Excel file Location in Stella DebitDataYear to Cells B11 11470 Model Sector I RivFlowData SubCatchinfo sheet The sheet SubCatchlnfo is designed to help you initialize the subcatchment area I Area and its routing distance I RoutingDistance to the outlet Figure 2 6 This sheet is also designed to initialize maximum ground water storage MaxDynGWSub1 4 and its release fraction I GWRelFrac1 4 and relative time of river flow velocity I RivFlowTime1 4 per subcatchment and per year of land cover transition time Routing distance is the distance from the midpoint of each subcatchment to any number of observation points This parameter will derive the routing time for each subcatchment to each of the observation points while excluding subcat
57. rain event Note Q mm day m sec x 24 hour x 3600 sec hour A km2 x 10 m km x 10 mm m If there is a shortage of reliable data on river flow you can first calibrate and validate a water balance model for the area and then use this for further exploration of scenarios If no continuous data on sedimentation or erosion exist you can assess the risk to erosion through level of runoff This is with an underlying assumption that high run off would lead to high risk of erosion or you can use the runoff output as the input for other erosion models at the catchment level 3 Examples of model application GenRiver model was initially developed to analyze river flow in Way Besai watershed in Sumberjaya Lampung Indonesia where coffee plantation is the dominant land cover Since then it has been applied at various sites with specific land cover and characteristics GenRiver Database is a file consisting of data input parameters from all sites that have ever been simulated This chapter discusses examples of model application based on current default input parameters Sumberjaya as well as other sites Mae Chaem basin North Thailand 3 1 Simulation based on default parameter setting Sumberjaya 3 1 1 Area description The Sumberjaya subdistrict is situated between 4 56 6 and 5 11 25 South and 104 17 52 and 103 33 51 East The elevation ranges between 720 m and 1831 m above
58. riod of time generally under six hours leading to stream flow and water levels that rise and fall quite rapidly Flow persistence is the fraction of flow on the previous day that can be expected as minimum volume of river flow ona given day Gradual water release is gradual release of ground water during periods without rainfall dry season Ground water discharge is the release of groundwater to streams or subsurface flows Interflow see Quickflow Low flow is flow through a watercourse after prolonged absence of rainfall Overland flow see surface runoff Overflow or Bank overflow is flow of water outside of the regular river bed during conditions where recent inflow minus outflow has exceeded the storage Capacity Peak flows is maximum flows through a watercourse Precipitation is all forms of water particles whether liquid or solid that fall from the atmosphere to the ground Distinguished from cloud fog dew and frost precipitation includes rain drizzle snow and hail Quickflow or Interflow is the part of a storm rainfall which moves laterally through hill slope soils to a stream channel it infiltrates the soil but cannot be retained by the soil at its field capacity shallow groundwater or interflow may emerge at the surface at the bottom of slopes and flow across the ground surface to the stream Relative buffering indicator is the buffer function adjusted for relative annual water yield
59. river outflow or measurement point Interactions between streams in their contribution to the river are considered to be negligible that is there is no backflow problem Spatial patterns in daily rainfall events are translated into average daily rainfall in each subcatchment in a separate module SpatRain The subcatchment model represents interception infiltration into soil rapid percolation into subsoil surface flow of water and rapid lateral subsurface flow into streams with parameters that can vary between land cover classes GenRiver was first developed as part of an Australian Centre for International Agricultural Research funded project on watershed functions in landscape mosaics This manual is reproduced through the TUL SEA Trees in Multi Use Landscapes in Southeast Asia project funded by the German Federal Ministry of Economic Cooperation and Development BMZ and Deutsche Gesellschaft f r Technische Zusammenarbeit GTZ However these sponsors are not responsible for any of the information provided in this manual The authors wish to acknowledge many colleagues and users for their valuable contributions and advice Base flow is the portion of stream flow that derives from groundwater and is not related to current or recent rainfall BD BDref is the bulk density of a soil layer relative to the reference bulk density that can be expected for a soil of similar texture under natural forest conditions Buffering c
60. rsistence and the FlowPer model 5 1 Background temporal autocorrelation of river flow 5 2 FlowPer model overview 5 3 Background of the FlowPer algorithm 5 4 Starting and running the FlowPer model 5 4 1 Input parameterization 5 4 2 Running the model 5 4 3 FlowPer model output 5 5 Case Study Jangkok sub watershed Lombok Indonesia References Appendices 5 5 76 77 83 84 86 87 87 87 90 91 91 92 94 95 97 99 Figure 1 1 Multiple influences of tree cover and forest soil condition on the water balance Figure 1 2 Landscape scale processes that relate the spatial and temporal aspects of rainfall to river flow Figure 1 3 Overview of the GenRiver model the multiple subcatchments that make up the catchment as a whole can differ in basic soil properties land cover fractions that affect interception soil structure infiltration rate and seasonal pattern of water use by the vegetation The subcatchment will also typically differ in routing time or in the time it takes the streams and river to reach the observation point Figure 1 4 GenRiver model key types of input and main output Figure 2 1 Main Menu of MS Excel file accompanying GenRiver model Figure 2 2 Main menu of GenRiver model Figure 2 3 View of RainData sheet Figure 2 4 View of converter to copy Rainfall data in _ Rainfall model sector Figure 2 5 View of RiverFlowData sheet Figure 2 6 View of SubCatchlInfo sheet Figure 2 7 View of LandCoverData s
61. scharge SoilQFlow ll al Figure 1 3 Overview of the GenRiver model the multiple subcatchments that make up the catchment as a whole can differ in basic soil properties land cover fractions that affect interception soil structure infiltration rate and seasonal pattern of water use by the vegetation The subcatchment will also typically differ in routing time or in the time it takes the streams and river to reach the observation point Generic River and Flow Persistence Models Climate change 0 Land use change GIS preprocessing of spatial data Daily water balance and ETact ETpot per Land Use per subcatchment Networked streamflow data and storage in lakes Figure 1 4 GenRiver model key types of input and main output 1 2 Minimum system requirements GenRiver was developed in the Stella modelling platform The GenRiver model is accompanied by an MS Excel file GenRiver xls GenRiver xls is to help users initialize and estimate some input parameters Before you run the model you must have the Stella program in your PC A free demonstration version a save disabled of Stella can be downloaded through http www iseesystems com Minimum system requirements to run GenRiver model Windows Macintosh 233 MHz Pentium 120 MHz PowerPC Microsoft Windows 2000 XP Any Intel based Mac English Version Mac OS 10 2 8 or higher English Version 128 MB RAM 128 MB RAM 70 MB hard disk space 70 M
62. sea level The subdistrict is 415 km The upper part of Way Besai watershed is a large caldera with the Bukit Rigis hill as a distinct remnant of the former volcano The major soils are inceptisols Dystropepts Dystrandepts and Humitropepts with some entisols Troporthent Land use in the area is mostly coffee plantation 70 3 1 2 Raw data available Secondary data available in Sumberjaya is presented in Table 3 1 3 1 3 Data of input parameters Rainfall data There are 17 rainfall stations in Way Besai watershed eight stations with manual and automatic rainfall gauges in the upper part of the watershed and nine stations outside the watershed within a radius of 60 km We chose eight stations which have high spatial correlation to interpolate daily rainfall depth for all subcatchments using Thiessen polygons The daily rainfall data are available for 32 years 1976 2007 Figure 3 1 Generic River and Flow Persistence Models Table 3 1 List data available in Sumberjaya watershed Data Timeseries Sources Type of Files Daily Rainfall 1976 2007 BMG Pu PLN Excel files Climate Daily temperature BMG 1976 2007 BMG1 Excel files DEM DEM Topographic map 10 m ICRAF Indonesia ASC Vegetation and Land Landsat MSS amp ETM 1973 2002 ICRAF Indonesia Shape files ESRI Cover Geology Geology 1 250000 ICRAF Indonesia Shape files ESRI Soil Land Unit Map 1 250 000 2003 CSAR Shape files ESRI Daily discharge Petai station 197
63. trans piration Et Overland flow Q 0 1 wa p E J Soil water mE 4 balance per land Soilquickflow Q LI 1 use das in sub ENS catchment i Option for use of GW for irrigation Groundwaterflow Q bis den alance per sub catchment i Initialization The model has a number of parameters that require initialization Some of the input parameters to initialize the model are organized in the MS Excel file and some are stored in the model GenRiver stm in Input Section and will be explored in the third part modify input parameters Patch level water balance The amount of rainfall for each land cover type within each subcatchment is calculated from the rate per unit area and the respective area fractions In order to implement the flows of this rainfall at the same day to either of the pools of soil water ground water cumulative evapotranspiration or the surface runoff the equations for the respective flows are linked and prioritized with interception having priority and surface runoff being the residue of potential infiltration and rainfall minus interception Stream and river flow network The implementation of the stream and river flow Figure 2 11 sector distinguishes between the part of the surface flow that can reach the observation points on the day of rainfall and the part that has one or more days of delay before reaching them As each calculation step takes one time Working with th
64. u Br Modify input parameters and try new run Click on To Input in Main Menu You will see some categories of input parameter organized in buttons as shown in Figure 2 18 You can see the input parameters by clicking each button See Appendix 1 for more detailed definition on these input parameters Many of the input parameters both organized in the MS Excel file and this input section are processed in the initialization component to convert units and apply the area fractions of the various subcatchments and land cover fractions in fact these land cover fractions can be dynamic You can start make you own simulation scenario by changing the input parameters in the MS Excel file and modifying the input values in this input section write over the current value 26 Generic River and Flow Persistence Models BOM oo DA INPUT SECTION 2 2 Simulation with your own scenario 2 2 1 Minimum data reguirements In order to make a new GenRiver application for a different watershed you need to prepare the following minimum data inputs Table 2 3 Some advice on dealing with data input parameter is presented in Appendix 3 1 Climate e Rainfall A number of formats are possible as long as they allow a reconstruction of monthly exceedance curves of daily rainfall intensity e 30 or at least 20 years of daily rainfall records for a station that can represent the area or multiple stations if these are supposed to b
65. ue A or through doubling of individual Table 5 3 Input parameters of the FlowPer model 55 56 56 58 58 59 60 62 63 70 71 74 77 89 91 93 1 General information 1 1 GenRiver model overview Land cover change can significantly affect watershed functions through a changes in the fraction of rainfall that reaches the ground b the subsequent pathways of water flow over and through the soil as related to surface and subsurface structure of the soil surface roughness and landscape drainage and c the rate of water use by plants Figure 1 1 Simple characteristics of vegetation monthly pattern of leaf biomass influencing canopy interception and transpiration and ability to extract water from deeper soil layers and soil especially compaction of the macro pores in the soil that store water between saturation and field Capacity can probably explain a major part of the impacts on river flow Empirical assessment of the dynamics of water flows as a function of land cover change and soil properties takes time and resources and needs to take temporal and spatial variation of rainfall into account A model based on first principles that integrates land cover change and change in soil properties as driving factors of changes in river flow can be used as a tool to explore scenarios of land use change if it passes a validation test against observed data Forest MEN oe Pd
66. unction of Way Besai Sumberjaya was assessed using criteria and indicators of water transmission total water yield per unit rainfall buffering capacity peak flow or peak rainfall and gradual release of ground water dry season flow Table 3 10 To capture the impact of land use change the indicators are scattered over the 30 year simulation period Figure 3 8 The main effect of land cover change seems to increase the total water yield as a fraction of total rainfall as well as the runoff overflowfraction tends to increase Gradual water release function slow flow soil quick flow and lowest monthly fraction tend to decrease over the years The buffering capacity buffering indicator buffering relative and buffering peak events tends to decrease before year 1998 and then tends to increase after year 2005 The effect of rainfall variation over the year could be evaluated when the indicator was expressed to the discharge fraction The runoff overlandflow has positive correlation The slow flow indicator has a negative correlation as well as the buffering indicator or buffering relative while the other indicators tended to be quite stable to the discharge fraction over the year Figure 3 9 Examples of model application 0 4 0 24 0 0 1975 1980 1985 1990 1995 u Slow Flow Fraction Lowest Month Fraction Soil Flow Table 3 10 Average of indicators of watershed functions mdi Observed Simulated Min Average Max Mi
67. ure 2 4 RiverFlowData sheet min Rainfall DailyRainYear 1 to af DailyRainYear 5 to 8 j a RainDoY To Rainfall Rainfall RainYear 9 t012 Mis O DailyRainYear 13 to 16 DailyRai ar 17 to 20 2 ilies ae Time aa FI RelArea DailyRainYear 29 to 32 RainPerDay Ji DailyRain Kaa UseSpatVarRain waa Q o mm Rain IntensMean J T uU Rain GenSeed SpatRain3 e Rain IntensCoefVar SpatRain4 5 Drs m iR 3 ei yy s RainDoY RainMultiplier SpatRain5 L Ks te RainCycle SpatRain6 Que Simulation Time x WUcorrectio WarmUpTime The sheet RiverFlowData contains the daily river flow data m s Figure 2 5 Default values are the river flow data from Sumberjaya Way Besai watershed in Lampung Indonesia for 32 years 1976 2007 You can adjust the river flow data to the local situation and at the same period with rainfall data This data links to Stella DebitDataYear to This data will be valuable in constraining the simulations 10 Generic River and Flow Persistence Models MW Ge Edt Yew poet format Toot Data window tp Adobe POF 0 e B U ESIa Ex e 6 BE ge Daguu2Uudi r umm SBr 0i OH wow g River Flow Data m sec Station HEPP 415 km2 Type Ctrier to update all rain and river BACK TO READ ME Series Record 1976 2007 Year1 4 Year5 8 Year9 12 ear13 16 fear17 20 ear21 24 Yea
68. use the ImportData option under the Edit menu How to allow for Macro s in Excel2007 Pops 005 formulas Proofing Save 4 ja k Ca L zi Advanced s Hon Customize m Gac Add Ins Paste B Trust Center Resources Microsoft Office Excel Trust Center The Trust Center contains security and privacy settings These settings help keep your computer secu change these settings RAPS war KIINI WI WALIA Cree Disable all macros except digitally signed macros Generic River and Flow Persistence Models There are two types of importing data the first one is import data one time meaning the data is imported without establishing a link the second is oersistent data import meaning the data is imported and a link established To cross check whether input parameters were updated both in MS Excel and Stella open a table in Stella tabulate input parameters and compare them with the MS Excel file You are now inside the main menu of GenRiver and ready to work On your screen you will see something like Figure 2 2 The active link between the MS Excel file GenRiver xls and the Stella file GenRiver stm requires that the filename for the Excel file remains the same If you want to differentiate multiple versions of the input parameters please make separate copies in different subdirectories folders otherwise the links are lost i Ee Ede yew Inset Format Teck Data window pep Adobe roe ao
69. ws into the river while 3496 of annual rainfall is used by the vegetation and lost as evaporation According to the model 2696 of rainfall comes as surface runoff and 3696 as ground water flow with the amount of soil quick flow around 496 of annual rainfall The estimated water balance of Way Besai watershed did not show the differentiation between the dry and rainy seasons Almost all of the hydrological years are in saturated condition The hydrological function of Way Besai indicator showed an increase of water transmission indicators and a decline of gradual release of water Average discharge expressed as a fraction of rainfall has increased while the slow flow Examples of model application fraction relative to the rainfall tends to be decreasing This is likely due to reduced canopy interception and evapotranspiration of coffee gardens However even though the buffering indicator of the overall hydrological years is not indicative of a change of direction the Way Besai as reflected in quantitative indicators is entering a degraded phase 3 2 Simulation based on other sites Mae Chaem Basin North Thailand The Mae Chaem basin in Northern Thailand has been the focus of a number of watershed studies Croke et al 2004 Thanapakpawin et al 2005 It has physically clear delineation good land cover and land use change data long term record of river flow at the outlet of the catchment and a number of rainfall stations Changes in

figures - World Agroforestry Centre

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