Impact of Climate Change on Drought Dynamics in the Ganale Dawa River Basin, Ethiopia

Understanding how climate change will reshape drought dynamics is essential for planning sustainable water and agricultural systems in tropical regions. However, large uncertainties in existing projections limit effective adaptation. To address this, we applied machine learning-enhanced climate projections and satellite-based drought indices to assess drought dynamics in Ethiopia’s Ganale Dawa Basin as a case study. Agricultural and hydrological droughts were analyzed for a historical baseline (1982–2014) and three future periods (2015–2040, 2041–2070, 2071–2100) under SSP2-4.5 (a moderate-emission pathway) and SSP5-8.5 (a high-emission pathway) scenarios. Results show that agricultural droughts occurred 34 times during the historical baseline. Under SSP2-4.5, their frequency declined to 10 in the mid-future, before rising to 16 events in the far future. In contrast, SSP5-8.5 projected increased variability with 33 events in the near future, dropping to 2 in the mid-future, and increasing again to 19 in the far future. Hydrological droughts were more persistent, with a baseline frequency of 31 events, and 26–36 events over future periods under both scenarios. These findings reveal increasing variability in agricultural drought and continued recurrence of hydrological drought. The findings emphasize a dual adaptation approach combining immediate agricultural responses with sustained water management and climate mitigation.

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Publication Details

Journal
Climate
Published
2025-11-11
DOI
https://doi.org/10.3390/cli13110231
Primary Topic
Hydrology and Drought Analysis
Type
article
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article

Impact of Climate Change on Drought Dynamics in the Ganale Dawa River Basin, Ethiopia

Mohammed Mussa Abdulahi, Pascal Egli, Sintayehu W. Dejene, Yazidhi Bamutaze et al.
Climate
Hydrology and Drought Analysis
article

Impact of Climate Change on Drought Dynamics in the Ganale Dawa River Basin, Ethiopia

Mohammed Mussa Abdulahi, Pascal Egli, Sintayehu W. Dejene, Yazidhi Bamutaze, Anteneh Belayneh Desta
article en

Abstract

Understanding how climate change will reshape drought dynamics is essential for planning sustainable water and agricultural systems in tropical regions. However, large uncertainties in existing projections limit effective adaptation. To address this, we applied machine learning-enhanced climate projections and satellite-based drought indices to assess drought dynamics in Ethiopia’s Ganale Dawa Basin as a case study. Agricultural and hydrological droughts were analyzed for a historical baseline (1982–2014) and three future periods (2015–2040, 2041–2070, 2071–2100) under SSP2-4.5 (a moderate-emission pathway) and SSP5-8.5 (a high-emission pathway) scenarios. Results show that agricultural droughts occurred 34 times during the historical baseline. Under SSP2-4.5, their frequency declined to 10 in the mid-future, before rising to 16 events in the far future. In contrast, SSP5-8.5 projected increased variability with 33 events in the near future, dropping to 2 in the mid-future, and increasing again to 19 in the far future. Hydrological droughts were more persistent, with a baseline frequency of 31 events, and 26–36 events over future periods under both scenarios. These findings reveal increasing variability in agricultural drought and continued recurrence of hydrological drought. The findings emphasize a dual adaptation approach combining immediate agricultural responses with sustained water management and climate mitigation.

ClimateVol. 13(11)
Haramaya University (ET), Norwegian University of Science and Technology (NO), Makerere University (UG)
Openalex Percentile: Top 69%
Hydrology and Drought Analysis
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