Articles | Volume 29, issue 21
https://doi.org/10.5194/hess-29-6043-2025
https://doi.org/10.5194/hess-29-6043-2025
Research article
 | 
06 Nov 2025
Research article |  | 06 Nov 2025

Decoding the architecture of drought: SHAP-enhanced insights into the climate forces reshaping the Sahel

Fabio Di Nunno, Mehmet Berkant Yıldız, and Francesco Granata

Cited articles

Allen, R. G., Pereira, L., Raes, D., and Smith, M.: Crop Evapotranspiration: Guidelines for Computing Crop Water Requirements, FAO Irrigation and Drainage Paper 56, Food and Agriculture Organisation, Rome, Italy, ISBN 92-5-104219-5, 1998. 
Azam, M., Park, H. K., Maeng, S. J., and Kim, H. S.: Regionalization of Drought across South Korea Using Multivariate Methods, Water, 10, 24, https://doi.org/10.3390/w10010024, 2018. 
Barton, Y., Giannakaki, P., Von Waldow, H., Chevalier, C., Pfahl, S., and Martius, O.: Clustering of regional-scale extreme precipitation events in southern Switzerland, Mon. Weather Rev., 144, 347–369, 2016. 
Cohen, J., Huan, X., and Ni, J.: Shapley-based explainable AI for clustering applications in fault diagnosis and prognosis, Journal of Intelligent Manufacturing, 35, 4071–4086, https://doi.org/10.1007/s10845-024-02468-2, 2024. 
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Short summary
Droughts in the Sahel are becoming more severe and unpredictable due to climate change. This study explores how large-scale climate patterns influence drought trends in the region. Using advanced data analysis and machine learning, we identified key climate factors driving droughts and mapped areas most at risk. Our findings provide a clearer understanding of regional drought dynamics, helping policymakers and communities develop effective strategies for water management and climate adaptation.
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