Modeling of a River Basin Using SWAT Model and SUFI-2 NINA OMANI MASOUD TAJRISHY AHMAD ABRISHAMCHI Sharif University of Technology, Tehran, Iran Karkheh Dam, Iran 1
Area of Gharasu Sub-basin : 5793 km2 Gharasu Karkheh Dam Location of Karkheh river basin in Iran Location of Gharasu sub-basin in Karkheh River Basin 2
The main problem of Gharasu sub-basin is conversion of rangelands to rain-fed crop in hilly lands without any conservation practices. This cause high erosion because most of the fields are located on steep slope. 3
Data Files Daily maximum and minimum temperature (1988-2000) Daily rainfall (1988-2000) Location and elevation of climate stations Simulated Required Input Data 6 2 8 Gauge Weather station Relative humidity 1 3 Wind speed Potential evapotranspiration 7 5 4 Solar radiation 4
Information Layers DEM Land use Soil Hydrography 5
Watershed Delineation 66 Sub-basins 6
Land Use Soil 437 HRU s 7
Management Data and Water Consumption Planting Operation Harvest and Kill Operation Tillage Operation Irrigation Operation Grazing Operation 8
DEM Soil Land Use SWAT Model Climate Land and Agriculture Management 9
Plains Rivers Sanjabi Kamiaran- Bilvare Kamiaran Gerdab Bilvar Koutab Razavar Mahidasht Kermanshah Zardab Gharasu Gharasu River Merek Merek River Main Outlet Merek River Main River 10
Location of stream gauges and climate stations Warm-up period : 1987-1990 Calibration : 1991-1996 Validation : 1997-2000 Ravansar Hojat Abad Jelogireh Doab Merek Khers Abad Kermanshah Gharabaghestan (Main outlet) Mahidasht 11
Initial and final values of SWAT calibration parameters for stream flow and TSS. Parameter ESCO SMFMN SMFMX GW_REVAP SMTMP ALPHA_BF CH_K2 GW_DELAY GWQMN OV_N SFTMP REVAPMN PRF SPEXP SPCON CH_EROD CH_COV Soil evaporation compensation factor Melt factor for snow on December 21 Melt factor for snow on June 21 Groundwater "revap" coefficient Snow melt base temperature (ºC) Base flow alpha factor (days) Effective hydraulic conductivity in the main channel (mm/hr) Groundwater delay time (days) Threshold depth of water in the shallow aquifer required for return flow to occur. Manning's n value for the over land flow Snow fall temperature ( 0 C) Threshold depth of water in the shallow aquifer for "revap". peak rate adjustment factor for sediment routing in the main channel channel re-entrained exponent parameter channel re-entrained linear parameter channel erodability factor channel cover factor SWAT variable name SUFI-2 calibration 0.48 (a),0.61 (b),0.56 (c) 2.77 (a), 1.95 (b),2.34 (c) 2.82 (a), 1.98 (b),2.45 (c) 0.06 (a),(b),0.04 (c) +3.55 [0.08, 0.23] 45,71 [43, 100] [-20, 171] [-0.13, 0.24] 1.91 [-33, 118] 0.38 1.04 0.0016 0.32 0.49 Final value SWAT calibration 0.40 2.5 2.6 0.04 (a),0.06 (b),0.02 (c) +4 0.118 (a), 0.098 (b), 0.05 (c) 40 (a), 60 (b),(c) Varied by HRU 40 (a),(b), 20 (c) 0.29 (a), 0.3 (b),(c) 2.0 20 (a),(b), 10 (c) 0.5 1.05 0.002 0.0 0.0 12
60 50 40 30 20 10 0 13 Oct-94 Mar-95 Aug-95 Jan-96 Jun-96 Nov-96 measured data bracketed by the 95PPU=83% d-factor=1.47 Xl=2.5% Xu=97.5% Jan-91 Jun-91 Nov-91 Apr-92 Sep-92 Feb-93 Jul-93 Dec-93 May-94 Date 95PPU observation Discharge (m 3 /s)
Jul-00 200 150 100 50 0 14 Discharge(m 3 /s) Jan-97 Jul-97 Jan-98 Jul-98 Jan-99 Jul-99 Jan-00 50 40 30 20 10 0 measured data bracketed by the 95PPU=80% d-factor=0.55 Date 95PPU observation 00/05/31 00/10/31 Figure 1 : Monthly stream flow at main outlet 250 (a) Model calibration (b) Model validation measured data bracketed by the 95PPU=76% d-factor=0.52 Apr-92 Sep-92 Feb-93 Jul-93 Dec-93 May-94 Oct-94 Mar-95 Aug-95 Jan-96 Jun-96 Nov-96 Jan-91 Jun-91 Nov-91 Date 95PPU observation 700 600 500 400 300 200 100 0 measured data bracketed by the 95PPU=95% d-factor=0.39 97/01/31 97/06/30 97/11/30 98/04/30 98/09/30 99/02/28 99/07/31 99/12/31 Date 95PPU observation TSS (10 3 ton/mon) TSS (10 3 ton/mon) 60 50 40 30 20 10 0 measured data bracketed by the 95PPU=83% d-factor=1.47 Apr-92 Sep-92 Feb-93 Jul-93 Dec-93 May-94 Oct-94 Mar-95 Aug-95 Jan-96 Jun-96 Nov-96 Jan-91 Jun-91 Nov-91 Date 95PPU observation Figure 2 : Monthly TSS at main outlet (a) Model calibration (b) Model validation Discharge (m 3 /s)
SWAT Sensitive model sub-basins predicted sediment to erosion yield per hectare of sub-basin from 1991-1996 15
Main factors of erosion in critical sub-basins DEM Slope 16
Management Scenarios for Soil Conservation 1- Support practices such as contouring and terracing. 2- Land cover change in hilly and mountainous areas of basin with consideration of land capability. 17
1- Summary of support practices results on sediment yield Sub-basin 16 17 19 37 39 Area of HRU (%) Predicted sediment yield (ton/ha) Contouring (Reduction %) Contouring and Terracing (Reduction %) Sediment yield reduction of Sub-basins (%) 9 25.0 19.5 (22) 15.1 (40) 5 3 3 4 3 4 1.5 0.6 29.0 13.8 42.1 22.6 1.3 0.28 (53) 25.1 (13) 9.8 (29) 34.3 (19) 20.3 (10) 0.0 (100) 0.28 (53) 18.8 (35) 7.5 (46) 16.8 (60) 13.7 (39) 0.65 (50) 5 28.0 22.9 (18) 17.7 (37) 5 6 Initial sediment yield (ton/ha) 7.8 5.1 (35) 3.2 (59) 1 2 4 18
2- Summary of land use conversion results on sediment yield Sub-basin Initial sediment yield (ton/ha) Predicted sediment Yield after land cover changing (ton/ha) Sediment yield Reduction of sub-basins (%) 3 6.83 0.42 94 19 4.12 0.25 94 8 4.63 0.33 93 17 7.52 2.98 60 1 5.12 2.13 58 18 4.63 2.05 56 2 10.21 6.94 32 58 6.32 4.73 25 21 6.15 5.24 15 37 8.75 8.85 0.03 39 7.93 7.83 0.03 10 6.71 6.52 0.01 16 3.42 3.51 0.01 19
conclusions Contouring and terracing will effectively reduce sediment loading of rain fed lands in hillsides. Changing agricultural practices such as increasing forest, conversion of rain-fed area in steep slope land to orchards and woods will reduce erosion about 50 percent within hilly and mountainous sub-basins. SWAT model is a capable tool for simulating hydrologic components and erosion in Gharasu river basin. Large amount of measured data at the outlet of the basin are necessary for calibration by using SUFI-2 but the more number of parameter can be determined in short time. 20
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