Investigation of climate change impact on the optimal operation of koka reservoir, upper awash watershed, Ethiopia

The objectives of this study were to predict the inflow and optimal operation of the Koka reservoir under the impact of climate change for the 2020s (2011–2040), 2050s (2041–2070), and 2080s (2071–2100) with respect to the reference period (1981–2010). The optimal elevation, storage, and hydropower capacity were modeled using the HEC-ResPRM, whereas the inflow to Koka reservoir was simulated using the calibrated SWAT model. Based on the result, the average annual inflow of the reference period was 139.675 Million Cubic Meter (MCM). However, from 2011 to 2100 an increase of +4.179% to +11.694 is expected. The inflow analysis at different flow regimes shows that the high flow may decline by (−28.528%) to (−22.856%) due to climate change. On the other hand, the low flow is projected to increase by (+78.407%) to (+90.401%) as compared to the low flow of the reference period. Therefore, the impact of climate change on the inflow to the Koka reservoir is positive. The study also indicates that the optimum values of elevation and storage capacity of the Koka reservoir during the reference period were 1590.771 m above mean sea level (a.m.s.l) and 1860.818 MCM, respectively. However, the optimum level and storage capacity are expected to change by (−0.016%) to (−0.039%) and (−2.677%) to (+6.164%), respectively from 2020s to 2080s as compared with their corresponding values during the reference period. On the other hand, the optimum power capacity during the reference period was 16.489 MCM, while it will likely fluctuates between (−0.948%) - (+0.386%) in the face of climate change. The study shows that the optimum elevation, storage, and power capacity were all higher than the corresponding observed values. However, the occurrence month of their peak value will likely shift due to climate change. The study can be used as a first-hand information for the development of reservoir operation guidelines that can account for the uncertainty caused by the impacts of climate change.