Climate change in the upper Awash subbasin and its possible impacts on the stream flow, Oromiyaa, Ethiopia

Abstract

ABSTRACTModelling climate change impact is very important to reduce the crisis behind food security, drought, and loss of energy sectors. The impact on streamflow and hydrological components due to climate change was aimed to investigate by the SWAT model for this study. Two regional climate models (RCM) were selected according to their performance to calibrate and validate the streamflow. The Regional Climate Models’ performance in simulation of flow and the hydrological cycle was evaluated by statistical performance criteria. Digital elevation model (DEM), land use land cover and soil map, and streamflow data were collected and used as raw input for the model. Bias correction was made by using power transformation and variance scaling method for RCM against observed data. The result simulated with RACMO22T was best with (PBIAS = 0.23, NSE = 0.84, R2 = 0.79) for calibration, (PBIAS = 0.11, NSE = 0.88, R2 = 0.81) for validation. RCA4 model underperformed in simulating streamflow compared to RACMO22T with (PBIAS = 0.28, NSE = 0.78, R2 = 0.74) and (PBIAS = 0.18, NSE = 0.85, R2 = 0.78) for calibration and validation of the models respectively. The streamflow was projected and shows a slightly increasing trend respectively with 13.8 and 21.3 % for the 2030s and 2050s simulation years. But in the 2080s simulation periods, the simulated streamflow indicates a decreasing trend under representative concentration pathways (RCP4.5) by 12.5%. The overall result indicates both streamflow and runoff show a decreasing pattern in the end of this century under both scenarios. The spatial variability of hydrological components which contributes to streamflow was dependent on the subbasin characteristics. Furthermore, the simulated groundwater recharge (GW_Q), rainfall, water yields (WYLD), surface runoff (SUR_Q) and evapotranspiration (ET) were decreased by 4%, 17.7%, 20.8%, 27.7%, and 8.6% respectively for the baseline period.

Keywords

• Bias correction
• climate change
• RCM
• spatial variability
• SWAT model