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Biases in national and continental flood risk assessments by ignoring spatial dependence
Recently, flood risk assessments have been extended to national and continental scales. Most of these assessments assume homogeneous scenarios, i.e. the regional risk estimate is obtained by summing up the local estimates, whereas each local damage value has the same probability of exceedance. This...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7653947/ https://www.ncbi.nlm.nih.gov/pubmed/33168927 http://dx.doi.org/10.1038/s41598-020-76523-2 |
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author | Nguyen, Viet Dung Metin, Ayse Duha Alfieri, Lorenzo Vorogushyn, Sergiy Merz, Bruno |
author_facet | Nguyen, Viet Dung Metin, Ayse Duha Alfieri, Lorenzo Vorogushyn, Sergiy Merz, Bruno |
author_sort | Nguyen, Viet Dung |
collection | PubMed |
description | Recently, flood risk assessments have been extended to national and continental scales. Most of these assessments assume homogeneous scenarios, i.e. the regional risk estimate is obtained by summing up the local estimates, whereas each local damage value has the same probability of exceedance. This homogeneity assumption ignores the spatial variability in the flood generation processes. Here, we develop a multi-site, extreme value statistical model for 379 catchments across Europe, generate synthetic flood time series which consider the spatial correlation between flood peaks in all catchments, and compute corresponding economic damages. We find that the homogeneity assumption overestimates the 200-year flood damage, a benchmark indicator for the insurance industry, by 139%, 188% and 246% for the United Kingdom (UK), Germany and Europe, respectively. Our study demonstrates the importance of considering the spatial dependence patterns, particularly of extremes, in large-scale risk assessments. |
format | Online Article Text |
id | pubmed-7653947 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-76539472020-11-12 Biases in national and continental flood risk assessments by ignoring spatial dependence Nguyen, Viet Dung Metin, Ayse Duha Alfieri, Lorenzo Vorogushyn, Sergiy Merz, Bruno Sci Rep Article Recently, flood risk assessments have been extended to national and continental scales. Most of these assessments assume homogeneous scenarios, i.e. the regional risk estimate is obtained by summing up the local estimates, whereas each local damage value has the same probability of exceedance. This homogeneity assumption ignores the spatial variability in the flood generation processes. Here, we develop a multi-site, extreme value statistical model for 379 catchments across Europe, generate synthetic flood time series which consider the spatial correlation between flood peaks in all catchments, and compute corresponding economic damages. We find that the homogeneity assumption overestimates the 200-year flood damage, a benchmark indicator for the insurance industry, by 139%, 188% and 246% for the United Kingdom (UK), Germany and Europe, respectively. Our study demonstrates the importance of considering the spatial dependence patterns, particularly of extremes, in large-scale risk assessments. Nature Publishing Group UK 2020-11-09 /pmc/articles/PMC7653947/ /pubmed/33168927 http://dx.doi.org/10.1038/s41598-020-76523-2 Text en © The Author(s) 2020 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/. |
spellingShingle | Article Nguyen, Viet Dung Metin, Ayse Duha Alfieri, Lorenzo Vorogushyn, Sergiy Merz, Bruno Biases in national and continental flood risk assessments by ignoring spatial dependence |
title | Biases in national and continental flood risk assessments by ignoring spatial dependence |
title_full | Biases in national and continental flood risk assessments by ignoring spatial dependence |
title_fullStr | Biases in national and continental flood risk assessments by ignoring spatial dependence |
title_full_unstemmed | Biases in national and continental flood risk assessments by ignoring spatial dependence |
title_short | Biases in national and continental flood risk assessments by ignoring spatial dependence |
title_sort | biases in national and continental flood risk assessments by ignoring spatial dependence |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7653947/ https://www.ncbi.nlm.nih.gov/pubmed/33168927 http://dx.doi.org/10.1038/s41598-020-76523-2 |
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