Articles | Volume 25, issue 4
https://doi.org/10.5194/nhess-25-1353-2025
https://doi.org/10.5194/nhess-25-1353-2025
Research article
 | 
09 Apr 2025
Research article |  | 09 Apr 2025

Accelerating compound flood risk assessments through active learning: A case study of Charleston County (USA)

Lucas Terlinden-Ruhl, Anaïs Couasnon, Dirk Eilander, Gijs G. Hendrickx, Patricia Mares-Nasarre, and José A. Á. Antolínez

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Short summary
This study develops a conceptual framework that uses active learning to accelerate compound flood risk assessments. A case study of Charleston County shows that the framework achieves faster and more accurate risk quantification compared to the state-of-the-art. This win–win allows for an increase in the number of flooding parameters, which results in an 11.6 % difference in the expected annual damages. Therefore, this framework allows for more comprehensive compound flood risk assessments.
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