Disentangling aggregated uncertainty sources in peak flow projections under different climate scenarios

Abstract

Evaluation of peak flood magnitude and frequency in the future at a catchment scale under global warming is crucial for water resource management and flood risk management. Climate model outputs provide a leading source of information to quantify the effect of the foreseen natural and anthropogenic climate change on the environment and natural systems. However, modelling climate change impact on peak flow is subject to considerable uncertainties from the climate model discrepancies, bias correction methods, and hydrological model parameters. This study develops a framework to examine changes and disentangle uncertainties in peak flow, which is tested at five Awash catchments in Ethiopia, a region exposed to extreme flood risk. The results showed that projected extreme precipitation and peak flow magnitude could increase substantially in the coming decades by 30% to 55%. The uncertainty analysis confirms that the dominant factor in peak flood projection is climate models in catchments like Akaki (55%) and Awash H (51%), but the bias correction methods in Awash B (58%) and Kela (50%), respectively. The least important factor is the hydrological parameter set for flood projections. Moreover, the findings reveal that peak flood risks would noticeably increase in the near and far future in all catchments, in Awash located in the Tropical dry region. Therefore, various state water agencies from local to national scales must take certain non-structural/structural measures to mitigate flood risks in the future, and to adapt to future climate.