Hydrology and Earth System Sciences www.hydrol-earth-syst-sci.net 1027-5606 1607-7938 13 10 2009 10.5194/hess-13-2003-2009 http://www.hydrol-earth-syst-sci.net/13/2003/2009/ http://www.hydrol-earth-syst-sci.net/13/2003/2009/hess-13-2003-2009.html http://www.hydrol-earth-syst-sci.net/13/2003/2009/hess-13-2003-2009.pdf 2003 2021 2009-10-29 Modelling water-harvesting systems in the arid south of Tunisia using SWAT M. Ouessar med.ouessar@ira.agrinet.tn A. Bruggeman F. Abdelli R. H. Mohtar D. Gabriels W. M. Cornelis Institut des Régions Arides (IRA), Route de Jorf, 4119 Medenine, Tunisia International Center for Agricultural Research in the Dry Areas (ICARDA), P.O. Box 5466, Aleppo, Syria Department of Agricultural and Biological Engineering, Purdue University, West Lafayette, IN 47907, USA Department of Soil Management – International Centre for Eremology, Ghent University, Coupure links 653, 9000 Ghent, Belgium In many arid countries, runoff water-harvesting systems support the livelihood of the rural population. Little is known, however, about the effect of these systems on the water balance components of arid watersheds. The objective of this study was to adapt and evaluate the GIS-based watershed model SWAT (Soil Water Assessment Tool) for simulating the main hydrologic processes in arid environments. The model was applied to the 270-km² watershed of wadi Koutine in southeast Tunisia, which receives about 200 mm annual rain. The main adjustment for adapting the model to this dry Mediterranean environment was the inclusion of water-harvesting systems, which capture and use surface runoff for crop production in upstream subbasins, and a modification of the crop growth processes. The adjusted version of the model was named SWAT-WH. Model evaluation was performed based on 38 runoff events recorded at the Koutine station between 1973 and 1985. The model predicted that the average annual watershed rainfall of the 12-year evaluation period (209 mm) was split into ET (72%), groundwater recharge (22%) and outflow (6%). The evaluation coefficients for calibration and validation were, respectively, <i>R</i>² (coefficient of determination) 0.77 and 0.44; <i>E</i> (Nash-Sutcliffe coefficient) 0.73 and 0.43; and MAE (Mean Absolute Error) 2.6 mm and 3.0 mm, indicating that the model could reproduce the observed events reasonably well. 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