Abstract
AbstractIn 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 bi...
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