Articles | Volume 16, issue 9
Hydrol. Earth Syst. Sci., 16, 3083–3099, 2012
Hydrol. Earth Syst. Sci., 16, 3083–3099, 2012

Research article 03 Sep 2012

Research article | 03 Sep 2012

Calibration and evaluation of a semi-distributed watershed model of Sub-Saharan Africa using GRACE data

H. Xie1, L. Longuevergne2, C. Ringler1, and B. R. Scanlon3 H. Xie et al.
  • 1International Food Policy Research Institute, 2033 K Street NW, Washington D.C. 20006, USA
  • 2CNRS – UMR 6118, Géosciences Rennes Université Rennes 1, 35042 Rennes, France
  • 3Bureau of Economic Geology, Jackson School of Geosciences, University of Texas, Austin, TX 78713-8926, USA

Abstract. Irrigation development is rapidly expanding in mostly rainfed Sub-Saharan Africa. This expansion underscores the need for a more comprehensive understanding of water resources beyond surface water. Gravity Recovery and Climate Experiment (GRACE) satellites provide valuable information on spatio-temporal variability in water storage. The objective of this study was to calibrate and evaluate a semi-distributed regional-scale hydrologic model based on the Soil and Water Assessment Tool (SWAT) code for basins in Sub-Saharan Africa using seven-year (July 2002–April 2009) 10-day GRACE data and multi-site river discharge data. The analysis was conducted in a multi-criteria framework. In spite of the uncertainty arising from the tradeoff in optimising model parameters with respect to two non-commensurable criteria defined for two fluxes, SWAT was found to perform well in simulating total water storage variability in most areas of Sub-Saharan Africa, which have semi-arid and sub-humid climates, and that among various water storages represented in SWAT, water storage variations in soil, vadose zone and groundwater are dominant. The study also showed that the simulated total water storage variations tend to have less agreement with GRACE data in arid and equatorial humid regions, and model-based partitioning of total water storage variations into different water storage compartments may be highly uncertain. Thus, future work will be needed for model enhancement in these areas with inferior model fit and for uncertainty reduction in component-wise estimation of water storage variations.