This study analyzed the performance of four (REgional MOdel (REMO2009), High-Resolution Hamburg Climate Model 5 (HIRAM5), Climate Limited-Area Modeling Community (CCLM4-8) and Rossby Centre Regional Atmospheric Model (RCA4)) Regional Climate Models (RCMs) simulations from Coordinated Regional Climate Downscaling Experiment (CORDEX) Africa program. The simulation period of 1985-2005 was evaluated considering how each RCM simulated the observed rainfall and air temperature over southwest Ethiopia. It was found that all the RCMs simulated the seasonal rainfall, but not the peak rainfall, with all models including their ensemble underestimating the peak rainfall. However, the ensemble was better than the individual RCMs in simulating both rainfall and air temperature. All models were slightly biased around a warm climate zone in simulating maximum air temperature when compared to the simulation of air minimum temperature. Of the four RCMs, REMO2009 performed well in simulating the maximum and minimum air temperatures. The interseasonal variation in rainfall was greater than the seasonal variation in air temperature. In terms of cumulative distribution, the HIRAM5 captured more extreme rainfall events and overestimated the return period. Overall, the differences in performance among the RCMs provided strong evidence for the use of regional-scale data at the local scale in climate impact assessments being controversial. In relation to the spatial pattern of the rainfall, most of the models simulated the observed minimum rainfall in the north and northeast, medium rainfall in the central region, and maximum rainfall in the south and southwest of the study area. The overall results indicate that choosing a reliable RCM is fundamentally necessary to delivering a strong basis for any climate-change impact study.
Surface runoff is a critical input in watershed management. Runoff is a driving force for soil erosion which causes sedimentation of reservoirs located at downstream of watersheds. The present study aimed to model surface runoff using the Soil and Water Assessment Tools (SWAT) model in Ketar watershed, Ethiopia. Ketar river crosses mountainous steep slope areas. High surface runoff from the Ketar watershed flows to Lake Ziway. The Ketar watershed was delineated into 35 subbasins and 147 Hydraulic Response Units (HRUs). In this work, surface runoff was simulated using 36 years meteorological data as input. The model was calibrated and validated for streamflow using sequential uncertainty fitting-2 (SUFI_2) of the SWAT Calibration and Uncertainty Programs (SWAT_CUP). The model calibrated using 12-year measured streamflow data (1988)(1989)(1990)(1991)(1992)(1993)(1994)(1995)(1996)(1997) and validated using 7-year streamflow data (1998)(1999)(2000)(2001)(2002)(2003)(2004). The coefficient of determination (R 2 ) and Nash-Sutcliffe (NSE) were used to measure the performance of the model. R 2 and NSE were 0.82 and 0.7 during calibration and 0.78 and 0.71 during validation, respectively. The results show that there was an excellent relation between monthly observed and simulated streamflow during both calibration and validation. Simulated average monthly surface runoff of the watershed was 112.82 mm per month. The southwest part of the watershed, which was characterized by highest annual surface runoff, covers 27% of the total area.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.