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Quantifying uncertainties of sandy shoreline change projections as sea level rises

Sandy shorelines are constantly evolving, threatening frequently human assets such as buildings or transport infrastructure. In these environments, sea-level rise will exacerbate coastal erosion to an amount which remains uncertain. Sandy shoreline change projections inherit the uncertainties of fut...

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Autores principales: Le Cozannet, Gonéri, Bulteau, Thomas, Castelle, Bruno, Ranasinghe, Roshanka, Wöppelmann, Guy, Rohmer, Jeremy, Bernon, Nicolas, Idier, Déborah, Louisor, Jessie, Salas-y-Mélia, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6328552/
https://www.ncbi.nlm.nih.gov/pubmed/30631107
http://dx.doi.org/10.1038/s41598-018-37017-4
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author Le Cozannet, Gonéri
Bulteau, Thomas
Castelle, Bruno
Ranasinghe, Roshanka
Wöppelmann, Guy
Rohmer, Jeremy
Bernon, Nicolas
Idier, Déborah
Louisor, Jessie
Salas-y-Mélia, David
author_facet Le Cozannet, Gonéri
Bulteau, Thomas
Castelle, Bruno
Ranasinghe, Roshanka
Wöppelmann, Guy
Rohmer, Jeremy
Bernon, Nicolas
Idier, Déborah
Louisor, Jessie
Salas-y-Mélia, David
author_sort Le Cozannet, Gonéri
collection PubMed
description Sandy shorelines are constantly evolving, threatening frequently human assets such as buildings or transport infrastructure. In these environments, sea-level rise will exacerbate coastal erosion to an amount which remains uncertain. Sandy shoreline change projections inherit the uncertainties of future mean sea-level changes, of vertical ground motions, and of other natural and anthropogenic processes affecting shoreline change variability and trends. Furthermore, the erosive impact of sea-level rise itself can be quantified using two fundamentally different models. Here, we show that this latter source of uncertainty, which has been little quantified so far, can account for 20 to 40% of the variance of shoreline projections by 2100 and beyond. This is demonstrated for four contrasting sandy beaches that are relatively unaffected by human interventions in southwestern France, where a variance-based global sensitivity analysis of shoreline projection uncertainties can be performed owing to previous observations of beach profile and shoreline changes. This means that sustained coastal observations and efforts to develop sea-level rise impact models are needed to understand and eventually reduce uncertainties of shoreline change projections, in order to ultimately support coastal land-use planning and adaptation.
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spelling pubmed-63285522019-01-14 Quantifying uncertainties of sandy shoreline change projections as sea level rises Le Cozannet, Gonéri Bulteau, Thomas Castelle, Bruno Ranasinghe, Roshanka Wöppelmann, Guy Rohmer, Jeremy Bernon, Nicolas Idier, Déborah Louisor, Jessie Salas-y-Mélia, David Sci Rep Article Sandy shorelines are constantly evolving, threatening frequently human assets such as buildings or transport infrastructure. In these environments, sea-level rise will exacerbate coastal erosion to an amount which remains uncertain. Sandy shoreline change projections inherit the uncertainties of future mean sea-level changes, of vertical ground motions, and of other natural and anthropogenic processes affecting shoreline change variability and trends. Furthermore, the erosive impact of sea-level rise itself can be quantified using two fundamentally different models. Here, we show that this latter source of uncertainty, which has been little quantified so far, can account for 20 to 40% of the variance of shoreline projections by 2100 and beyond. This is demonstrated for four contrasting sandy beaches that are relatively unaffected by human interventions in southwestern France, where a variance-based global sensitivity analysis of shoreline projection uncertainties can be performed owing to previous observations of beach profile and shoreline changes. This means that sustained coastal observations and efforts to develop sea-level rise impact models are needed to understand and eventually reduce uncertainties of shoreline change projections, in order to ultimately support coastal land-use planning and adaptation. Nature Publishing Group UK 2019-01-10 /pmc/articles/PMC6328552/ /pubmed/30631107 http://dx.doi.org/10.1038/s41598-018-37017-4 Text en © The Author(s) 2019 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Le Cozannet, Gonéri
Bulteau, Thomas
Castelle, Bruno
Ranasinghe, Roshanka
Wöppelmann, Guy
Rohmer, Jeremy
Bernon, Nicolas
Idier, Déborah
Louisor, Jessie
Salas-y-Mélia, David
Quantifying uncertainties of sandy shoreline change projections as sea level rises
title Quantifying uncertainties of sandy shoreline change projections as sea level rises
title_full Quantifying uncertainties of sandy shoreline change projections as sea level rises
title_fullStr Quantifying uncertainties of sandy shoreline change projections as sea level rises
title_full_unstemmed Quantifying uncertainties of sandy shoreline change projections as sea level rises
title_short Quantifying uncertainties of sandy shoreline change projections as sea level rises
title_sort quantifying uncertainties of sandy shoreline change projections as sea level rises
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6328552/
https://www.ncbi.nlm.nih.gov/pubmed/30631107
http://dx.doi.org/10.1038/s41598-018-37017-4
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