Articles | Volume 26, issue 6
https://doi.org/10.5194/nhess-26-2743-2026
https://doi.org/10.5194/nhess-26-2743-2026
Research article
 | 
11 Jun 2026
Research article |  | 11 Jun 2026

Multi-hazard susceptibility mapping in a karst context using a machine-learning method (MaxEnt)

Hedieh Soltanpour, Kamal Serrhini, Joel C. Gill, Sven Fuchs, and Solmaz Mohadjer

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Cited articles

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Short summary
We applied the Maximum Entropy model to characterise multi-hazard scenarios in a karst environment, focusing on flood-triggered sinkholes in Val d'Orléans, France. Karst terrains as multi-hazard forming areas, have received little attention in multi-hazard literature. Our study developed a multi-hazard susceptibility map to forecast the spatial distribution of these hazards. The findings improve understanding of hazard interactions and demonstrate the model's utility in multi-hazard analysis.
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