Journal of Water and Climate Change (May 2022)
Effect of climate change on streamflow in the Gelana watershed, Rift valley basin, Ethiopia
Abstract
Climate change is one of the current global threats and the topmost challenges. This study aims to investigate the climate change effect on streamflow in the Gelana watershed using the soil and water assessment tool (SWAT) model for three consecutive periods of 2031–2050, 2051–2070, and 2071–2090. Climate variables were downscaled from two regional climate models (RCMs) (RACMO22T and RCA4) from CORDEX-Africa under representative concentration pathway (RCP4.5 and RCP8.5) scenarios. RCMs were evaluated using four statistical indicators and performed very well. Power transformation and distribution mapping methods were used to correct biases of precipitation and temperatures, respectively. The 19 SWAT model-sensitive parameters were transferred from the gauged donor watersheds to the ungauged watershed outlet by using the principal component analysis coupled with the stepwise multiple linear regression. The ensemble mean of RCMs revealed that the maximum and minimum temperatures and potential evapotranspiration were predicted to increase up to 3.48 °C, 4.19 °C, and 17.85%, respectively, in the period of 2071–2090 under the RCP8.5 scenario. These changes translate to possible reductions in the mean annual rainfall and streamflow up to 15.12 and 44.14%, respectively, with a consequent higher decline of surface runoff by 22.23%, groundwater by 42.54%, and water yield by 35.89% in the period of 2051–2070 under the RCP4.5 scenario. The projected rainfall and streamflow are expected to face a higher decline in wet seasons. Detections of trends in hydro-climatic variables were performed by using the Mann–Kendall test. Hence, these projection scenarios should be of interest to river users and water resource managers in the Gelana watershed. HIGHLIGHTS The principal component analysis is used to evaluate and analyze the physical catchment characteristics that contribute to the SWAT model-sensitive parameters.; Climate variables, streamflow, surface runoff, groundwater, and water yield are integrated.; A higher shortage of rainfall in wet seasons than in dry seasons is expected.;
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