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Assessing coastline recession for adaptation planning: sea level rise versus storm erosion

The Sixth Assessment report (AR6) of the Intergovernmental Panel on Climate Change (IPCC) states with high confidence that most sandy coasts around the world will experience an increase in coastal erosion over the twenty-first century. An increase in long term coastal erosion (coastline recession) a...

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Autores principales: Ranasinghe, Roshanka, Callaghan, David P., Li, Fan, Wainwright, David J., Duong, Trang Minh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10203099/
https://www.ncbi.nlm.nih.gov/pubmed/37217579
http://dx.doi.org/10.1038/s41598-023-35523-8
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author Ranasinghe, Roshanka
Callaghan, David P.
Li, Fan
Wainwright, David J.
Duong, Trang Minh
author_facet Ranasinghe, Roshanka
Callaghan, David P.
Li, Fan
Wainwright, David J.
Duong, Trang Minh
author_sort Ranasinghe, Roshanka
collection PubMed
description The Sixth Assessment report (AR6) of the Intergovernmental Panel on Climate Change (IPCC) states with high confidence that most sandy coasts around the world will experience an increase in coastal erosion over the twenty-first century. An increase in long term coastal erosion (coastline recession) along sandy coasts can translate into massive socio-economic impacts, unless appropriate adaptation measures are implemented in the next few decades. To adequately inform adaptation measures, it is necessary to have a good understanding of the relative importance of the physical processes driving coastline recession, as well as of linkages between consideration (or not) of certain processes and the level of risk tolerance; understandings that are hitherto lacking. Here, we apply the multi-scale Probabilistic Coastline Recession (PCR) model to two end-member sandy coastal types (swell dominated and storm dominated), to investigate where and when coastline recession projections are dominated by the differential contributions from Sea Level Rise (SLR) and storm erosion. Results show that SLR substantially increases the projected end-century recession at both types of coasts and that projected changes in the wave climate have only a marginal impact. An analysis of the Process Dominance Ratio (PDR), introduced here, shows that the dominance of storm erosion over SLR (and vice versa) on total recession by 2100 depends on both the type of the beach and the risk tolerance levels. For moderately risk-averse decisions (i.e. decisions accounting only for high exceedance probability recessions and hence do not account for very high amounts of potential recession—for example, the placement of temporary summer beach cabins), additional erosion due to SLR can be considered as the dominant driver of end-century recession at both types of beaches. However, for more risk-averse decisions that would typically account for higher potential recession (i.e. lower exceedance probability recessions), such as the placement of coastal infrastructure, multi-storey apartment buildings etc., storm erosion becomes the dominant process. The results of this study provide new insights on which physical processes need to be considered when and where in terms of numerical modelling efforts needed for supporting different management decisions, potentially enabling more streamlined and comprehensive assessments of the efficacy of coastal adaptation measures.
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spelling pubmed-102030992023-05-24 Assessing coastline recession for adaptation planning: sea level rise versus storm erosion Ranasinghe, Roshanka Callaghan, David P. Li, Fan Wainwright, David J. Duong, Trang Minh Sci Rep Article The Sixth Assessment report (AR6) of the Intergovernmental Panel on Climate Change (IPCC) states with high confidence that most sandy coasts around the world will experience an increase in coastal erosion over the twenty-first century. An increase in long term coastal erosion (coastline recession) along sandy coasts can translate into massive socio-economic impacts, unless appropriate adaptation measures are implemented in the next few decades. To adequately inform adaptation measures, it is necessary to have a good understanding of the relative importance of the physical processes driving coastline recession, as well as of linkages between consideration (or not) of certain processes and the level of risk tolerance; understandings that are hitherto lacking. Here, we apply the multi-scale Probabilistic Coastline Recession (PCR) model to two end-member sandy coastal types (swell dominated and storm dominated), to investigate where and when coastline recession projections are dominated by the differential contributions from Sea Level Rise (SLR) and storm erosion. Results show that SLR substantially increases the projected end-century recession at both types of coasts and that projected changes in the wave climate have only a marginal impact. An analysis of the Process Dominance Ratio (PDR), introduced here, shows that the dominance of storm erosion over SLR (and vice versa) on total recession by 2100 depends on both the type of the beach and the risk tolerance levels. For moderately risk-averse decisions (i.e. decisions accounting only for high exceedance probability recessions and hence do not account for very high amounts of potential recession—for example, the placement of temporary summer beach cabins), additional erosion due to SLR can be considered as the dominant driver of end-century recession at both types of beaches. However, for more risk-averse decisions that would typically account for higher potential recession (i.e. lower exceedance probability recessions), such as the placement of coastal infrastructure, multi-storey apartment buildings etc., storm erosion becomes the dominant process. The results of this study provide new insights on which physical processes need to be considered when and where in terms of numerical modelling efforts needed for supporting different management decisions, potentially enabling more streamlined and comprehensive assessments of the efficacy of coastal adaptation measures. Nature Publishing Group UK 2023-05-22 /pmc/articles/PMC10203099/ /pubmed/37217579 http://dx.doi.org/10.1038/s41598-023-35523-8 Text en © The Author(s) 2023 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
Ranasinghe, Roshanka
Callaghan, David P.
Li, Fan
Wainwright, David J.
Duong, Trang Minh
Assessing coastline recession for adaptation planning: sea level rise versus storm erosion
title Assessing coastline recession for adaptation planning: sea level rise versus storm erosion
title_full Assessing coastline recession for adaptation planning: sea level rise versus storm erosion
title_fullStr Assessing coastline recession for adaptation planning: sea level rise versus storm erosion
title_full_unstemmed Assessing coastline recession for adaptation planning: sea level rise versus storm erosion
title_short Assessing coastline recession for adaptation planning: sea level rise versus storm erosion
title_sort assessing coastline recession for adaptation planning: sea level rise versus storm erosion
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10203099/
https://www.ncbi.nlm.nih.gov/pubmed/37217579
http://dx.doi.org/10.1038/s41598-023-35523-8
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