Evaluating the future total water storage change and hydrological drought under climate change over lake basins, East Africa

Ayalkibet M. Seka,Huadong Guo,Jiahua Zhang,Jiaqi Han, Eyale Bayable,Gebiaw T. Ayele, Habtamu T. Workneh, Olfa T. Bayouli,Fabien Muhirwa, Kidane W. Reda

JOURNAL OF CLEANER PRODUCTION(2024)

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摘要
Climate change led an increase in the frequency of severe droughts, the effects of which are exacerbated by a lack of water storage. Despite increasing research on global -scale total water storage (TWS) change and drought prediction, basin -scale long-term hydrological drought, TWS change, and El Nino-Southern Oscillation (ENSO) influence in East Africa (EA) remain unexplored. In this paper, we used multiple approaches, of ensemble machine learning (ML) and weighted averaging, to conduct a basin -scale exploratory analysis of future hydrological drought and TWS change for the period 2025-2099. Climate change will affect future hydrological conditions in the basins, with maximum severity values of -90.3, -726.6, and -2567.7 Gt in the Tana, Turkana, and Victoria basins, respectively, under RCP6.0. Similarly, we found maximum severities of -187.5 and -277.7 Gt in the Abaya-Chamo and Tanganyika basins, respectively, under RCP 2.6. The most severe El Nino drought and exceptional La Nina conditions in the basins were found under both RCP scenarios. To ensure future water security in EA, sustainable water resource management strategies that can mitigate the impacts of extreme climate events in the future are urgently needed.
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关键词
Total water storage change,Machine learning,El Nino -Southern oscillation,Climate change scenario,Hydrological drought
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