Abstract
Quantifying the impact of climate change on the spatial and temporal hydrological processes is important for integrated water resource management. This study aimed to investigate the impacts of climate variability on streamflow and evapotranspiration in the Lake Tana basin, Ethiopia. Climate data was simulated using the Weather Research and Forecasting (WRF) model, with a 4-km horizontal resolution. Dynamically downscaled climate data for the baseline (2005–2015) and future period (2045–2055) under two Representative Concentration Pathways (RCP4.5 and RCP8.5) were analyzed. The SWAT hydrological model was calibrated and validated using observed streamflow data. The SWAT model was used to estimate the baseline and future hydrology using the bias-corrected climate data. On average, the annual rainfall may increase by 7.9% and 21.2% under RCP4.5 and RCP8.5 scenarios, respectively. The average temperature may rise by 1.4 °C under RCP4.5 and 2.2 °C under RCP8.5. Climate change under RCP4.5 and RCP8.5 scenarios may cause streamflow increase by 7.2% and 33% and evapotranspiration increase by 11.2% and 15.2%, respectively. The findings provide valuable insights to implement appropriate water management strategies to mitigate and adapt to the negative impacts of climate change and variability on the Lake Tana basin and other regions which have similar agro-ecology.
Highlights
Hydrologic systems have been changing due to the impact of climate change and climate variability
Annual rainfall may increase by 9.8% and 21.2% under RCP4.5 and RCP8.5 scenarios, respectively
Minimum temperature may rise by 1.68 °C and 2.26 °C while maximum temperature may increase by 1.65 °C and 2.75 °C under RCP4.5 and RCP8.5 scenarios, respectively
Summary
Hydrologic systems have been changing due to the impact of climate change and climate variability. Dile et al (2013) estimated the impact of climate change on streamflow of Gilgel Abay watershed using the SWAT model and downscaled climate data from HadCM3 A2 and B2 scenarios with Statistical Downscaling Tool (SDSM). They found that the mean monthly flow may decrease during the 2010-2040 period and increase during 2070-2100. Melke and Abegaz (2017) estimated the impact of climate change on streamflow in Gumara watershed using SDSM downscaled HadCM3A2a and HadCM3B2a climate outputs in which they found different trends of streamflow between the studied GCMs. the studies used different emission scenarios, GCMs, downscaling techniques, and hydrological models, the findings attest that climate change may unequivocally affect the water availability in Africa
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
