Integrated socio-environmental vulnerability assessment of coastal hazards using data-driven and multi-criteria analysis approaches

Coastal hazard vulnerability assessment has been centered around the multi-variate analysis of geo-physical and hydroclimate data. The representation of coupled socio-environmental factors has often been ignored in vulnerability assessment. This study develops an integrated socio-environmental Coast...

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Autores principales: Tanim, Ahad Hasan, Goharian, Erfan, Moradkhani, Hamid
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9270473/
https://www.ncbi.nlm.nih.gov/pubmed/35803988
http://dx.doi.org/10.1038/s41598-022-15237-z
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author Tanim, Ahad Hasan
Goharian, Erfan
Moradkhani, Hamid
author_facet Tanim, Ahad Hasan
Goharian, Erfan
Moradkhani, Hamid
author_sort Tanim, Ahad Hasan
collection PubMed
description Coastal hazard vulnerability assessment has been centered around the multi-variate analysis of geo-physical and hydroclimate data. The representation of coupled socio-environmental factors has often been ignored in vulnerability assessment. This study develops an integrated socio-environmental Coastal Vulnerability Index (CVI), which simultaneously combines information from five vulnerability groups: biophysical, hydroclimate, socio-economic, ecological, and shoreline. Using the Multi-Criteria Decision Making (MCDM) approach, two CVI (CVI-50 and CVI-90) have been developed based on average and extreme conditions of the factors. Each CVI is then compared to a data-driven CVI, which is formed based on Probabilistic Principal Component Analysis (PPCA). Both MCDM and PPCA have been tied into geospatial analysis to assess the natural hazard vulnerability of six coastal counties in South Carolina. Despite traditional MCDM-based vulnerability assessments, where the final index is estimated based on subjective weighting methods or equal weights, this study employs an entropy weighting technique to reduce the individuals’ biases in weight assignment. Considering the multivariate nature of the coastal vulnerability, the validation results show both CVI-90 and PPCA preserve the vulnerability results from biophysical and socio-economic factors reasonably, while the CVI-50 methods underestimate the biophysical vulnerability of coastal hazards. Sensitivity analysis of CVIs shows that Charleston County is more sensitive to socio-economic factors, whereas in Horry County the physical factors contribute to a higher degree of vulnerability. Findings from this study suggest that the PPCA technique facilitates the high-dimensional vulnerability assessment, while the MCDM approach accounts more for decision-makers' opinions.
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spelling pubmed-92704732022-07-10 Integrated socio-environmental vulnerability assessment of coastal hazards using data-driven and multi-criteria analysis approaches Tanim, Ahad Hasan Goharian, Erfan Moradkhani, Hamid Sci Rep Article Coastal hazard vulnerability assessment has been centered around the multi-variate analysis of geo-physical and hydroclimate data. The representation of coupled socio-environmental factors has often been ignored in vulnerability assessment. This study develops an integrated socio-environmental Coastal Vulnerability Index (CVI), which simultaneously combines information from five vulnerability groups: biophysical, hydroclimate, socio-economic, ecological, and shoreline. Using the Multi-Criteria Decision Making (MCDM) approach, two CVI (CVI-50 and CVI-90) have been developed based on average and extreme conditions of the factors. Each CVI is then compared to a data-driven CVI, which is formed based on Probabilistic Principal Component Analysis (PPCA). Both MCDM and PPCA have been tied into geospatial analysis to assess the natural hazard vulnerability of six coastal counties in South Carolina. Despite traditional MCDM-based vulnerability assessments, where the final index is estimated based on subjective weighting methods or equal weights, this study employs an entropy weighting technique to reduce the individuals’ biases in weight assignment. Considering the multivariate nature of the coastal vulnerability, the validation results show both CVI-90 and PPCA preserve the vulnerability results from biophysical and socio-economic factors reasonably, while the CVI-50 methods underestimate the biophysical vulnerability of coastal hazards. Sensitivity analysis of CVIs shows that Charleston County is more sensitive to socio-economic factors, whereas in Horry County the physical factors contribute to a higher degree of vulnerability. Findings from this study suggest that the PPCA technique facilitates the high-dimensional vulnerability assessment, while the MCDM approach accounts more for decision-makers' opinions. Nature Publishing Group UK 2022-07-08 /pmc/articles/PMC9270473/ /pubmed/35803988 http://dx.doi.org/10.1038/s41598-022-15237-z Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Tanim, Ahad Hasan
Goharian, Erfan
Moradkhani, Hamid
Integrated socio-environmental vulnerability assessment of coastal hazards using data-driven and multi-criteria analysis approaches
title Integrated socio-environmental vulnerability assessment of coastal hazards using data-driven and multi-criteria analysis approaches
title_full Integrated socio-environmental vulnerability assessment of coastal hazards using data-driven and multi-criteria analysis approaches
title_fullStr Integrated socio-environmental vulnerability assessment of coastal hazards using data-driven and multi-criteria analysis approaches
title_full_unstemmed Integrated socio-environmental vulnerability assessment of coastal hazards using data-driven and multi-criteria analysis approaches
title_short Integrated socio-environmental vulnerability assessment of coastal hazards using data-driven and multi-criteria analysis approaches
title_sort integrated socio-environmental vulnerability assessment of coastal hazards using data-driven and multi-criteria analysis approaches
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9270473/
https://www.ncbi.nlm.nih.gov/pubmed/35803988
http://dx.doi.org/10.1038/s41598-022-15237-z
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