Implication of bias correction on climate change impact projection of surface water resources in the Gidabo sub-basin, Southern Ethiopia

Abstract

Climate change impact studies that evaluated the biases of climate models' simulations showed the presence of large systematic errors in their outputs. However, many studies continue to arbitrarily select bias correction methods for error reduction. This work evaluated the implications of bias correction methods on the projections of climate change impact on streamflow of the Gidabo sub-basin, Ethiopia. Climate outputs from four global climate model and regional climate model (GCM–RCM) combinations for the representative concentration pathway (RCP4.5) scenario were used. Five bias correction methods were used to reduce the systematic errors of the simulated rainfall data. The future changes in rainfall pattern, evapotranspiration, and streamflow were analyzed by using their relative percentage difference between the projected and the baseline period. The distribution mapping method provided better results in mean and extreme rainfall cases. This is also reflected in streamflow projections, as the daily interquartile range value indicates the lowest variability of the projected streamflow. The wet season streamflow will likely decrease in the future, whereas the short rainy season streamflow will increase. Our findings show that climate models and bias correction methods considerably limit the magnitude of future projections of streamflow. However, similar research should be conducted in other catchments to extend the conclusions of this study. HIGHLIGHTS COordinated Regional Climate Downscaling Experiment (CORDEX)-Africa domain climate model data were used for impact analysis.; Projected climate change impact on streamflow is affected both by climate models and bias correction methods.; The distribution mapping method provided better results in correcting the errors of mean and extreme rainfall projection.; Wet season streamflow of the study area will likely decrease in the future.;

Keywords

• bias correction
• climate change
• gidabo
• rift valley
• streamflow simulation
• water availability