Modelling Future Climate Changes Impacts on Precipitation Pattern Using a Multi-Model Ensemble of CMIP6 Scenarios for the Abaya-Chamo Sub-Basin, Ethiopia.

Desalegn Laelago; Admasu Gebeyehu  Awoke

doi:10.59122/EJWST658

Desalegn Laelago Department of Hydraulics and Water Resources Engineering, Hawassa Institute of Technology, Hawassa University
Admasu Gebeyehu Awoke School of Civil and Environmental Engineering, Addis Ababa Institute of Technology(AAiT), Addis Ababa University, Post Office Box: 1176, Addis Ababa, Ethiopia

Abstract

Climate change disrupts the natural water cycle and agriculture, hindering the progress toward achieving sustainable development goals. Employing bias-corrected climate model simulations is crucial for future climate change patterns prediction and informing policy decisions. This research employs a multi-model ensemble from the Coupled Model Intercomparison Project Phase 6 to assess how climate change affects precipitation patterns in the Abaya-Chamo Sub-basin located in southern Ethiopia. Future predicted precipitation datasets were evaluated under Shared Socioeconomic Pathway scenarios. The Climate Data Operators (CDOs) tool was used to interpolate global climate model results. A power transformation method was utilized to address systematic biases in the outputs of the multi-model ensemble. Spatial patterns of precipitation maps in ArcMap were generated using the inverse distance weighting method. The findings revealed that the bias-corrected mean monthly and annual precipitations were lower than the observed precipitations. The SSP2-4.5 scenario forecasted a decrease in mean annual precipitation of 6.6% to 25.85% over the near periods (2021-2064) and a decrease of 2.25% to 20.24% in the long term future (2065-2100). The spring (MAM) season experienced the largest percentage reduction of all seasons. The spatial distribution of mean annual precipitation varied widely across watersheds, ranging from 450 to 1,140 millimeters. The multi-model ensemble projection for precipitation indicates a more significant decrease in the Gidabo watersheds during the summer (JJA) and spring (MAM) seasons, highlighting spatial variability. Projected future precipitation declines are expected to reduce the amount of water available to ecosystems. Therefore, developing comprehensive, effective water resource management strategies is extremely important to adapt to these changes.

Keywords: Abaya-Chamo, Bias Correction, CMIP6, Climate Change, Multi-Model Ensemble, Precipitation.

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