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Purpose The purpose of this paper is to prepare flood hazard map and show the extent of flood hazard under climate change scenarios in Woybo River catchment. The hydraulic model, Hydrologic Engineering Center - River Analysis System (HEC-RAS) was used to simulate the floods under future climate scenarios. The impact of climate changes on severity of flooding was evaluated for the mid-term (2041–2070) and long-term (2071–2100) with relative to a baseline period (1971–2000). Design/methodology/approach Future climate scenarios were constructed from the bias corrected outputs of five regional climate models and the inflow hydrographs for 10, 25, 50 and 100 years design floods were derived from the flow which generated from HEC-hydrological modeling system; that was an input for the HEC-RAS model to generate the flood hazard maps in the catchment. Findings The results of this research show that 25.68% of the study area can be classified as very high hazard class while 28.56% of the area is under high hazard. It was also found that 20.20% is under moderate hazard and about 25.56% is under low hazard class in future under high emission scenario. The projected area to be flooded in far future relative to the baseline period is 66.3 ha of land which accounts for 62.82% from the total area. This study suggested that agricultural/crop land located at the right side of the Woybo River near the flood plain would be affected more with the 25, 50 and 100 years design floods. Originality/value Multiple climate models were assessed properly and the ensemble mean was used to prepare flood hazard map using HEC-RAS modeling.

Climate changes significantly cause the precipitation deficiency and in turn reduce the inflow amount in reservoir affecting hydroelectric power generation. The primary objective of this study was to evaluate hydropower generation and reservoir operation under climate change from Kesem reservoir. Recent Representative Pathway (RCP) scenarios were used to evaluate the impact of climate change on power generation. Power transformation equation and variance scaling approach were amalgamated to adjust the bias correction of precipitation and temperature, respectively. Bias, root mean square error, and coefficient of variation were used to check the accuracy of projected rainfall. The base and future precipitation, temperature, and evaporation trend was analysed using the Mann–Kendall test. The flow calibration and validation were carried out by the Hydrologic Engineering Center-Hydrologic Modelling System (HEC-HMS), and hydropower generation was evaluated with reservoir simulation model (MODSIM 8.1) under climate scenarios. The performance of the model was found good with Nash–Sutcliffe coefficient (NSE) of 0.72 and coefficient of determination (R2) of 0.73 for calibration and NSE of 0.74 and R2 of 0.75 for validation. Projected future climate scenarios predicted increasing and decreasing trend of temperature and precipitation, respectively. For RCP4.5 climate scenario, the average energy generation is likely to decrease by 0.64% and 0.82% in both short-term (2021–2050) and long-term (2051–2080), respectively. In case of RCP8.5 climate scenario, the average energy generation will be decreased by 1.06% and 1.35% for short-term and long-term, respectively. Remarkable reduction of energy generation was revealed in RCP8.5 with relation to RCP4.5 scenario. This indicates that there will be high energy fluctuation and decreasing trend in the future energy generation. The research finding is crucial for decision-makers, power authorities, governmental and nongovernmental organizations, and watershed management agencies to take care for sustainability in the future hydropower generation in the Kesem reservoir.

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This research aims to map flood inundated areas under changing climate in the Boyo watershed of Southern Ethiopia. A semi-distributed physically based Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) and Hydrologic Engineering Center-River Analysis System (HEC-RAS) were used to simulate the flood events and maps, respectively, for climate scenarios. The bias-corrected data of four climate models were used for the baseline (1976–2005), mid-term (2041–2070) and long-term (2071–2100) cycles under RCP4.5 and RCP8.5 scenarios. The 50- and 100-year return period flood events were generated from the baseline and future period streamflow data. The HEC-RAS model was used to simulate the inundation areas and depths from the flood events. The result exhibited that the average annual rainfall and maximum and minimum temperatures of the catchment will increase in the future with an increase in annual runoff. The severity of annual floods would increase in the future under RCP4.5 and RCP8.5 scenarios. Approximately, 193 ha of the study may be flooded with flood events having a return period of 100 years under the RCP8.5 scenario in the long-term period, which is an extreme case. The result is a benchmark to reduce the flood risk and management of floodplains in this watershed.