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      Hurricane risk assessment in a multi-hazard context for Dominica in the Caribbean

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          Abstract

          Hurricanes can trigger widespread landslides and flooding creating compound hazards and multiple risks for vulnerable populations. An example is the island of Dominica in the Caribbean, where the population lives predominantly along the coast close to sea level and is subject to storm surge, with steep topography rising behind, with a propensity for landslides and flash river flooding. The simultaneous occurrence of the multiple hazards amplifies their impacts and couples with physical and social vulnerabilities to threaten lives, livelihoods, and the environment. Neglecting compound hazards underestimates overall risk. Using a whole island macroscale, (level-I) analysis, susceptibility scenarios for hurricanes, triggered landslides, and floods were developed by incorporating physical process parameters. The susceptibilities were combined with vulnerability indicators to map spatial patterns of hurricane multi-risks in Dominica. The analysis adopted a coupled approach involving the frequency ratio (FR), analytic hierarchy process (AHP), and geographic information system (GIS). Detailed hazard modelling was done at selected sites (level-II), incorporating storm surge estimates, landslide runout simulations, and steady flow analysis for floods. High-resolution terrain data and simulation models, the Rapid Mass Movement Simulation (RAMMS) and the hydrologic engineering center’s river analysis system (HEC-RAS), were employed. Ground validation confirmed reasonable agreement between projected and observed scenarios across different spatial scales. Following the United Nations Office for disaster risk reduction (UNDRR) call for the inclusion of local, traditional, and indigenous knowledge, feedback, and expert opinion to improve understanding of disaster risk, 17 interviews with local experts and 4 participatory workshops with residents were conducted, and findings were incorporated into the analysis, so as to gain insights into risk perceptions. The study’s outcomes encompass projections and quantification of hurricane compound hazards, vulnerabilities, accumulated risks, and an understanding of local priorities. These findings will inform decision-making processes for risk mitigation choices and community actions by providing a new framework for multi-hazard risk assessment that is easy to implement in combining different data forms.

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          A physically based, variable contributing area model of basin hydrology / Un modèle à base physique de zone d'appel variable de l'hydrologie du bassin versant

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            Decision making with the analytic hierarchy process

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                Author and article information

                Contributors
                alamakhtar@uok.edu.in
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                23 November 2023
                23 November 2023
                2023
                : 13
                : 20565
                Affiliations
                [1 ]Institute for Risk and Disaster Reduction (IRDR), University College London (UCL), ( https://ror.org/02jx3x895) Gower Street, London, WC1E 6BT UK
                [2 ]Department of Geography and Disaster Management, University of Kashmir, ( https://ror.org/032xfst36) Srinagar, 190006 India
                [3 ]Department of Statistical Science, University College London (UCL), ( https://ror.org/02jx3x895) 1-19 Torrington Place, London, WC1E 7HB UK
                [4 ]Institute for Global Health, University College London (UCL), ( https://ror.org/02jx3x895) Gower Street, London, WC1E 6BT UK
                [5 ]University of Agder, ( https://ror.org/03x297z98) Kristiansand, Norway
                Author information
                http://orcid.org/0000-0002-0813-2783
                Article
                47527
                10.1038/s41598-023-47527-5
                10667232
                37996552
                1b743566-e40a-4ec3-b526-4f3aa457b9cd
                © The Author(s) 2023

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 13 June 2023
                : 14 November 2023
                Funding
                Funded by: Research England Global Challenges Research Fund (GCRF)
                Categories
                Article
                Custom metadata
                © Springer Nature Limited 2023

                Uncategorized
                natural hazards,environmental impact,climate-change adaptation
                Uncategorized
                natural hazards, environmental impact, climate-change adaptation

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