Projecting climate and socioeconomic contributions to global flood-induced displacements using a data-driven approach

Lenin Del Rio Amador (), Mathieu Boudreault () and David A. Carozza ()
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Lenin Del Rio Amador: Université du Québec à Montréal
Mathieu Boudreault: Université du Québec à Montréal
David A. Carozza: Université du Québec à Montréal

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2025, vol. 121, issue 14, No 31, 16935-16973

Abstract: Abstract The increasing frequency and severity of floods underscore the urgent need for effective risk assessment and management, especially in the face of climate change. Although global warming is expected to intensify flood hazards, projecting their socioeconomic impacts—particularly human displacement—remains a complex challenge. This study presents a direct and interpretable modeling approach that integrates climatic, environmental, demographic, and economic variables to estimate global flood frequency and displacement risk. Using a data-driven framework forced with bias-corrected outputs from the NCAR CESM Large Ensemble, we simulate flood impacts for 4734 basins worldwide from 1981 to 2060. Unlike approaches focused solely on population exposure, our model incorporates economic growth as a proxy for changes in vulnerability. Historical patterns suggest that adaptation, often linked to economic development, has reduced displacement rates, but our projections indicate that this effect may not continue under accelerating climate change. If the share of economic growth devoted to adaptation remains constant, its mitigating effect on displacement risk could diminish. These findings emphasize the need for intensified and targeted adaptation efforts, in addition to emission reductions, to address the rising challenges of flood-induced displacements in a warming world.

Keywords: Flood-induced displacements; Statistical learning; Risk modeling; Data-driven model; Flood risk; Machine learning (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11069-025-07457-z

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