Procedure of hydrological modeling in a semi-arid river basin with SWAT. By: Ammar Rafiei

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1 Procedure of hydrological modeling in a semi-arid river basin with SWAT By: Ammar Rafiei

2 outline Objective Introduction Study area Preparation of data sets Model parameterization Uncertainty analysis Sensitivity analysis results

3 Objectives: 1- Building and calibrating a hydrological model in a semi arid river basin of Iran 2- Quantifying the water resources availability in the study area

4 Introduction Water scarcity in arid and semi arid area has negative impact on planning and management of this regions. Low precipitation, low water availability weakness of management Groundwater usage More than 90 % of water are using for agriculture with WUE less than 35 %

5 Study area

6 Razan-Ghavand watershed Watershed Area: 3100 Km 2 Max altitude 2842 m Min altitude: 1577 m Climate: semi arid Mean annual rainfall: 290 mm Mean annual temperature: 11⁰C Aquifer area: 1750 Km 2 Mean water level: 30 m

7 Study area: Razan-Ghavand Major river: Gharehchay river with mean annual discharge at the outlet: 6.68 m 3 s -1

8 q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ q_1_ Q (m3s-1) Study area: Razan-Ghavand Major river: Gharehchay river with mean annual discharge at the outlet: 6.68 m 3 s River Discharge

9 Study area: Razan-Ghavand Major river: Gharehchay river with mean annual discharge at the outlet: 6.68 m 3 s -1 Zehtaran river with mean annual discharge at the outlet: 0.66 m 3 s -1

10 10_1977 6_1978 2_ _1979 6_1980 2_ _1981 6_1982 2_ _1983 6_1984 2_ _1985 6_1986 2_ _1987 6_1988 2_ _1989 6_1990 2_ _1991 6_1992 2_ _1993 6_1994 2_ _1995 6_1996 2_ _1997 6_1998 2_ _1999 6_2000 2_ _2001 6_2002 2_ _2003 6_2004 2_ _2005 6_2006 2_ _2007 6_2008 Q(m3/s) Study area: Razan-Ghavand Major river: Gharehchay river with mean annual discharge at the outlet: 6.68 m 3 s -1 Zehtran river with mean annual discharge at the outlet: 0.66 m 3 s Discharge

11 Study area: Razan-Ghavand Major river: Gharehchay river with mean annual discharge at the outlet: 6.68 m 3 s -1 Zehtaran river with mean annual discharge at the outlet: 0.66 m 3 s -1 Sirab-khomigan river with mean annual discharge at the outlet: 0.33 m 3 s -1

12 10_1977 6_1978 2_ _1979 6_1980 2_ _1981 6_1982 2_ _1983 6_1984 2_ _1985 6_1986 2_ _1987 6_1988 2_ _1989 6_1990 2_ _1991 6_1992 2_ _1993 6_1994 2_ _1995 6_1996 2_ _1997 6_1998 2_ _1999 6_2000 2_ _2001 6_2002 2_ _2003 6_2004 2_ _2005 6_2006 2_ _2007 6_2008 Q (m3s-1) Study area: Razan-Ghavand Discharge Major river: Gharehchay river with mean annual discharge at the outlet: 6.68 m 3 s -1 Zehtaran river with mean annual discharge at the outlet: 0.66 m 3 s -1 Sirab-khomigan river with mean annual discharge at the outlet: 0.33 m 3 s -1

13 Study area: Razan-Ghavand Major river: Gharehchay river with mean annual discharge at the outlet: 6.68 m 3 s -1 Zehtaran river with mean annual discharge at the outlet: 0.66 m 3 s -1 Sirab-khomigan river with mean annual discharge at the outlet: 0.33 m 3 s -1 Koshabad river station, outside the watershed, with mean annual discharge at the outlet: 2.25 m 3 s -1

14 Land types

15 Material and method

16 SWAT input/output Input: DEM Landuse Soil Climate data Daily precipitation Daily temperature Agriculture management & practice data Output: Hydrological component Groundwater recharge Soil moisture Actual evapotranspiration Other Components: Crop yield Water quality Sediment

17 Digital elevation model Resolution : 25 m Source: topographical map 1:25000 Input: Output: DEM Landuse Soil Climate data Daily precipitation Daily temperature Agriculture management & practice data Hydrological component Groundwater recharge Soil moisture Actual evapotranspiration Other Components: Crop yield Water quality Sediment

18 Land use map Landsat 2009 Supervised classification Overall Accuracy = % Kappa Coefficient = Input: Output: DEM Landuse Soil Climate data Daily precipitation Daily temperature Agriculture management & practice data Hydrological component Groundwater recharge Soil moisture Actual evapotranspiration Other Components: Crop yield Water quality Sediment

19 Soil map Soil layers up to 5 layers Input: Output: DEM Landuse Soil Climate data Daily precipitation Daily temperature Agriculture management & practice data Hydrological component Groundwater recharge Soil moisture Actual evapotranspiration Other Components: Crop yield Water quality Sediment

20 Climate data No of rain gage selected: 8 ( 2 outside + 6 inside) Input: Output: No of rain gage stations= 21 No of Synoptic stations=4 No. of hydrometric stations =3 DEM Landuse Soil Climate data Daily precipitation Daily temperature Agriculture management & practice data Hydrological component Groundwater recharge Soil moisture Actual evapotranspiration Other Components: Crop yield Water quality Sediment

21 Agriculture management & practice Agricultural schedule both for rainfed and irrigated lands Input: DEM Landuse Soil Climate data Daily precipitation Daily temperature Agriculture management & practice data Output: Hydrological component Groundwater recharge Soil moisture Actual evapotranspiration Other Components: Crop yield Water quality Sediment

22 Model setup DEM m Landsat Derived m Soil Map 1: HRU No of sub basin with inlet: 138, No. of HRU with HRU: 831

23 Model set up Model was set up with inlet with non dominate HRU, Type of crop : winter wheat Auto-irrigation and fertilization operation options were used to simulate crop growth. evapotranspiration method : Hargreaves method curve number (CN) was adjusted based on the slop

24 Uncertainty analysis SUFI-2 was used to calibration and validation, uncertainty and sensitivity analysis, Duration of calibration: Duration of validation: Warm up duration: 2 years 28 Parameters was used for optimization

25 optimization Parameter CN2(.mgt) GW_DELAY(.gw) ALPHA_BF(.gw) REVAPMN(.gw) GW_REVAP(.gw) RCHRG_DP(.gw) GWQMN(.gw) SOL_AWC(.sol) SOL_K(.sol) SOL_BD(.sol) SOL_ALB(.sol) EPCO(.hru) SLSUBBSN(.hru) OV_N(.hru) CH_N2(.rte) CH_K2(.rte) ALPHA_BNK(.rte) SFTMP(.bsn) SMTMP(.bsn) SMFMX(.bsn) SMFMN(.bsn) TIMP(.bsn) SURLAG(.bsn) ESCO(.hru) HEAT_UNITS HI_TARG AUTO_WSTRS BIO_TARG Definition SCS runoff curve number for moisture condition II Groundwater delay time (days) Baseflow alpha factor (days) Threshold water in shallow aquifer Revap coefficient Aquifer percolation coefficient Threshold water level in shallow aq. for baseflow Available water capacity factor Saturated hydraulic conductivity Soil bulk density Moist soil albedo plant uptake compensation factor Average slope length (m) Manning's n value for overland flow Manning's n value for main channel Effective hydraulic conductivity in main channel alluvium Base flow alpha factor for bank storage (days) Snowfall temperature Snow melt base temperature (ºC) Melt factor for snow on 21 Jun Melt factor for snow on 21 Dec Snow pack temperature lag factor Surface runoff lag coefficient Soil evaporation compensation factor heat unit harvest index Water stress bio target

26 Results & Discussion

27 Discharge (m3s-1) discharge (m3s-1) 1_1978 9_1978 5_1979 1_1980 9_1980 5_1981 1_1982 9_1982 5_1983 1_1984 9_1984 5_1985 1_1986 9_1986 5_1987 1_1988 9_1988 5_1989 1_1990 9_1990 5_1991 1_1992 9_1992 5_1993 1_1994 9_1994 5_1995 1_1996 9_1996 5_1997 1_1998 9_1998 5_1999 1_2000 9_2000 5_2001 1_2002 9_2002 5_2003 1_2004 9_2004 5_2005 1_2006 9_2006 5_2007 1_2008 9_2008 1_ _1978 7_1979 4_1980 1_ _1981 7_1982 4_1983 1_ _1984 7_1985 4_1986 1_ _1987 7_1988 4_1989 1_ _1990 7_1991 4_1992 1_ _1993 7_1994 4_1995 1_ _1996 7_1997 4_1998 1_ _1999 7_2000 4_2001 1_ _2002 7_2003 4_2004 1_ _2005 7_2006 4_2007 1_ _2008 Time (monthly) Results of SWAT output NS: -0.76, PBIAS:0.12, RMSE:14.20 Omarabad Observated data simulated data Time (monthly) Zehtaran NS: -15.9, PBIAS:2.9, RMSE:1.5 observated data simulated data

28 Choose the duration for calibration and validation - Sirab-khomigan discharge-shows different hydrological condition in I and II periods. II I

29 Sub basins affected to flow in each station Stations Sub basins Area(km 2 ) 14 (Sirab khomigan) 1,2,3,4,5,6,12,13, (Zehtaran) 23,26, 27,28,29,32, 33, 34, ,38,41 71(Omarabad) All subbasin 3100

30 Sensitivity analysis Global sensitivity One at a time method

31 Global sensitivity Sensitivity analysis One at a time method Parameter Name t-stat P-Value r CN2.mgt 23,26,27,28,29,32,33,34,37,38, r CN2.mgt 1,2,3,4,5,6,12,13, v SMFMN.bsn v ALPHA_BNK.rte 1,2,3,4,5,6,12,13, v ALPHA_BNK.rte 23,26,27,28,29,32,33,34,37,38,41 r SOL_AWC().sol 23,26,27,28,29,32,33,34,37, 38, v SMFMX.bsn v TIMP.bsn v GWQMN.gw 23,26,27,28,29,32,33,34,37,38, V GW_DELAY.gw 1,2,3,4,5,6,12,13, v CH_K2.rte 23,26,27,28,29,32,33,34,37,38, r SOL_AWC().sol 1,2,3,4,5,6,12,13, v GW_REVAP.gw 23,26,27,28,29,32,33,34,37, 38,41 V GW_DELAY.gw 7-11,

32 Sensitivity analysis Global sensitivity One at a time method

33 Calibration and validation of outlet No.71 calibration validation P-factor=0.38 R-factor=0.78 R2 = 0.57 NS= 0.56 P-factor= 0.45 R-factor= 1.02 R2 = 0.69 NS= 0.66

34 Calibration and validation of outlet No.41 calibration validation P-factor= 0.49 R-factor= 1.76 R2 = 0.71 NS= 0.59 P-factor= 0.51 R-factor= 1.33 R2 = 0.78 NS= 0.42

35 Calibration and validation of outlet No.14 calibration validation P-factor= 0.51 R-factor= 1.26 R2 = 0.48 NS= 0.35 P-factor= 0.44 R-factor= 0.36 R2 = 0.91 NS= 0.72

36 CROP calibration Calibration winter wheat Validation winter wheat Irrigated: p-factor= 0.67 r-factor= 0.70 MSE = 1.08 t/ha Rainfed: p-factor= 0.83 r-factor= 0.77 MSE = 0.07 t/ha Irrigated: p-factor= 0.92 r-factor= 1.25 MSE = 0.19 t/ha Rainfed: p-factor= 0.70 r-factor= 0.54 MSE = 0.25 t/ha

37 -Average ( ) monthly 95PPU ranges of a: actual evapotranspiration b: soil water content c:perculation d:surface runoff

38 Water components spatial distribution Precipitation ET Percolation

39 Surface runoff Soil water

40 Conclusion Low data availability, especially amount of water use, is one of the main problem to calibrate the model. In semi arid regions because of low river discharge, the calibration process is pretty difficult. hence, the crop calibration can increase the precision of model.

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