Peak Flow Projections Under the Influence of Climate Change Impact and Uncertainty Evaluation in the Upper Awash River Basin Ethiopia
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Date
2021-09-17
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Addis Ababa University
Abstract
Modelling climate change impact on peak flood is subject to considerable uncertainty that comes from the climate model discrepancies, climate bias correction methods, and hydrological model parameters. These factors play a crucial role in flood risk planning and extreme event management. With the advent of the Coupled Model Inter comparison Project Phase 6 (CMIP6), flood managers and water resource planners are interested to know changes in catchment flood risk are expected to alter relative to previous assessments. A catchment-based projected change in peak flood quantiles for Upper Awash catchment was quantified. Conceptual hydrological model, three downscaling techniques, and an ensemble of hydrological parameter sets were used to examine changes in peak flood quantile magnitude and frequency under climate change in the mid and end of the 21st century. The results show that projected annual extreme precipitation and peak flood quantiles could increase substantially in the coming decades by 30%-55% in all the selected catchments. The associated uncertainty in future peak flood quantiles was quantified using aggregated variance decomposition and the result confirms that climate change is the dominant factor in Akaki (55%) and Awash H (51%) catchments, whereas the bias correction approaches in Awash B (58%) and Kela (50%) catchments. In Awash catchment both climate models and bias correction methods (45% and 49%, respectively) are the most dominate factors in projected peak flood magnitude. The hydrological parameter sets are identified as least important factor in the flood projections. Moreover, these results may add some significant information in the range of plausible changes expected for policy-relevant flood indices, and the tailoring of adaptation plans to account for the new generation climate model outputs.
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Keywords
CMIP6, HBV, Bias Correction, Hydrology, Extremes