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A Review of Flood Loss Models as Basis for Harmonization and Benchmarking
Risk-based approaches have been increasingly accepted and operationalized in flood risk management during recent decades. For instance, commercial flood risk models are used by the insurance industry to assess potential losses, establish the pricing of policies and determine reinsurance needs. Despi...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4959727/ https://www.ncbi.nlm.nih.gov/pubmed/27454604 http://dx.doi.org/10.1371/journal.pone.0159791 |
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author | Gerl, Tina Kreibich, Heidi Franco, Guillermo Marechal, David Schröter, Kai |
author_facet | Gerl, Tina Kreibich, Heidi Franco, Guillermo Marechal, David Schröter, Kai |
author_sort | Gerl, Tina |
collection | PubMed |
description | Risk-based approaches have been increasingly accepted and operationalized in flood risk management during recent decades. For instance, commercial flood risk models are used by the insurance industry to assess potential losses, establish the pricing of policies and determine reinsurance needs. Despite considerable progress in the development of loss estimation tools since the 1980s, loss estimates still reflect high uncertainties and disparities that often lead to questioning their quality. This requires an assessment of the validity and robustness of loss models as it affects prioritization and investment decision in flood risk management as well as regulatory requirements and business decisions in the insurance industry. Hence, more effort is needed to quantify uncertainties and undertake validations. Due to a lack of detailed and reliable flood loss data, first order validations are difficult to accomplish, so that model comparisons in terms of benchmarking are essential. It is checked if the models are informed by existing data and knowledge and if the assumptions made in the models are aligned with the existing knowledge. When this alignment is confirmed through validation or benchmarking exercises, the user gains confidence in the models. Before these benchmarking exercises are feasible, however, a cohesive survey of existing knowledge needs to be undertaken. With that aim, this work presents a review of flood loss–or flood vulnerability–relationships collected from the public domain and some professional sources. Our survey analyses 61 sources consisting of publications or software packages, of which 47 are reviewed in detail. This exercise results in probably the most complete review of flood loss models to date containing nearly a thousand vulnerability functions. These functions are highly heterogeneous and only about half of the loss models are found to be accompanied by explicit validation at the time of their proposal. This paper exemplarily presents an approach for a quantitative comparison of disparate models via the reduction to the joint input variables of all models. Harmonization of models for benchmarking and comparison requires profound insight into the model structures, mechanisms and underlying assumptions. Possibilities and challenges are discussed that exist in model harmonization and the application of the inventory in a benchmarking framework. |
format | Online Article Text |
id | pubmed-4959727 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-49597272016-08-08 A Review of Flood Loss Models as Basis for Harmonization and Benchmarking Gerl, Tina Kreibich, Heidi Franco, Guillermo Marechal, David Schröter, Kai PLoS One Research Article Risk-based approaches have been increasingly accepted and operationalized in flood risk management during recent decades. For instance, commercial flood risk models are used by the insurance industry to assess potential losses, establish the pricing of policies and determine reinsurance needs. Despite considerable progress in the development of loss estimation tools since the 1980s, loss estimates still reflect high uncertainties and disparities that often lead to questioning their quality. This requires an assessment of the validity and robustness of loss models as it affects prioritization and investment decision in flood risk management as well as regulatory requirements and business decisions in the insurance industry. Hence, more effort is needed to quantify uncertainties and undertake validations. Due to a lack of detailed and reliable flood loss data, first order validations are difficult to accomplish, so that model comparisons in terms of benchmarking are essential. It is checked if the models are informed by existing data and knowledge and if the assumptions made in the models are aligned with the existing knowledge. When this alignment is confirmed through validation or benchmarking exercises, the user gains confidence in the models. Before these benchmarking exercises are feasible, however, a cohesive survey of existing knowledge needs to be undertaken. With that aim, this work presents a review of flood loss–or flood vulnerability–relationships collected from the public domain and some professional sources. Our survey analyses 61 sources consisting of publications or software packages, of which 47 are reviewed in detail. This exercise results in probably the most complete review of flood loss models to date containing nearly a thousand vulnerability functions. These functions are highly heterogeneous and only about half of the loss models are found to be accompanied by explicit validation at the time of their proposal. This paper exemplarily presents an approach for a quantitative comparison of disparate models via the reduction to the joint input variables of all models. Harmonization of models for benchmarking and comparison requires profound insight into the model structures, mechanisms and underlying assumptions. Possibilities and challenges are discussed that exist in model harmonization and the application of the inventory in a benchmarking framework. Public Library of Science 2016-07-25 /pmc/articles/PMC4959727/ /pubmed/27454604 http://dx.doi.org/10.1371/journal.pone.0159791 Text en © 2016 Gerl et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Gerl, Tina Kreibich, Heidi Franco, Guillermo Marechal, David Schröter, Kai A Review of Flood Loss Models as Basis for Harmonization and Benchmarking |
title | A Review of Flood Loss Models as Basis for Harmonization and Benchmarking |
title_full | A Review of Flood Loss Models as Basis for Harmonization and Benchmarking |
title_fullStr | A Review of Flood Loss Models as Basis for Harmonization and Benchmarking |
title_full_unstemmed | A Review of Flood Loss Models as Basis for Harmonization and Benchmarking |
title_short | A Review of Flood Loss Models as Basis for Harmonization and Benchmarking |
title_sort | review of flood loss models as basis for harmonization and benchmarking |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4959727/ https://www.ncbi.nlm.nih.gov/pubmed/27454604 http://dx.doi.org/10.1371/journal.pone.0159791 |
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