Effect of Climate Change on Runoff Generation: Application to Rift Valley Lakes Basin of Ethiopia

Abstract

In this paper, an attempt has been made to investigate the potential impact of climate change on runoff generation at two agricultural watersheds. Climate change and key future signals of its variability were assessed using general circulation models (GCMs). Given that GCMs are operating at coarser resolution, the statistical downscaling model was applied to reduce large-scale atmospheric variables into localized weather variables from the Bjerknes Center for Climate Research–Bergen Climate Model 2.0 and Commonwealth Scientific and Industrial Research Organization (CSIRO) Mark (MK) 3.0 GCM outputs. As precipitation variables are composed of biases, both linear and power transformation bias correction methods were applied to obtain bias-corrected daily precipitation. Bias-corrected daily precipitation and temperature variables were used to simulate runoff for current and future climate scenarios using the Soil and Water Assessment Tool (SWAT) model. The statistical downscaling model, followed by bias correction, effectively reproduced the current weather variables. Increased extreme daily precipitation and temperature events prevailed for future scenarios. Dry spell length increased during the driest months and remained stable during wet seasons. There was no defined future precipitation change pattern. At two watersheds in the Rift Valley Lakes Basin in Ethiopia, the simulated runoff varied from −4 to 18% and −4 and 14%, respectively. Simulated average annual runoff showed slight variation between the GCMs at both watersheds.