Flood susceptibility mapping using supervised machine learning models: insights into predictors’ significance and models’ performance

Flood susceptibility mapping using supervised machine learning models: insights into predictors’ significance and models’ performance

Eastern Hindu Kush (EHK) is one of the most flood-prone regions due to its diverse topographic features, complex climatic conditions, and fragile socioeconomic situations. Yet there are limited studies on robust assessment and prediction of flood susceptibility in this region. This study aims to pre...

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Bibliographic Details
Main Authors: Zahid Ur Rahman, Meimei Zhang, Fang Chen, Safi Ullah, Mansoor Ahmad, Aamir Feroz, Samir Shehu Danhassan, Abdullah Azzam
Format: Article
Language:English
Published: Taylor & Francis Group 2025-06-01
Series:Geomatics, Natural Hazards & Risk
Subjects:
Flood susceptibility
supervised machine learning
eXtreme gradient boost
Kabul river basin
Eastern Hindu Kush region
Online Access:https://www.tandfonline.com/doi/10.1080/19475705.2025.2516728
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