Understanding the evolutionary processes and causes of groundwater drought using an interpretable machine learning model

Abstract Drought is a widespread natural disaster, and rapid assessment of groundwater drought has become a challenge due to the lack of direct spatiotemporal observation of groundwater. We employed machine learning models and the Shapley Additive Explanation (SHAP), a game theory-based interpretabi...

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Bibliographic Details

Published in:	Scientific Reports
Main Authors:	Zhiyuan Gan, Xianjun Xie, Chunli Su, Weili Ge, Hongjie Pan, Liangping Yang
Format:	Article
Language:	English
Published:	Nature Portfolio 2025-07-01
Subjects:	Groundwater Machine learning Meteorological drought Climate Change SHAP XGBoost
Online Access:	https://doi.org/10.1038/s41598-025-05316-2