An XGBoost-SHAP framework for identifying key drivers of urban flooding and developing targeted mitigation strategies

An XGBoost-SHAP framework for identifying key drivers of urban flooding and developing targeted mitigation strategies

Urban flooding is a multifaceted and severe issue, exacerbated by global climate change and urban expansion. Hence, it is imperative to investigate effective strategies for mitigating the urban flooding risk. This research proposes an innovative framework to recognize the driving factors and evaluat...

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Bibliographic Details
Main Authors: Xiaoping Fu, Mo Wang, Dongqing Zhang, Furong Chen, Xiaotao Peng, Lie Wang, Soon Keat Tan
Format: Article
Language:English
Published: Elsevier 2025-06-01
Series:Ecological Indicators
Subjects:
Urban flooding
Green infrastructure
Machine learning
Scenario simulation
Online Access:http://www.sciencedirect.com/science/article/pii/S1470160X25005096
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