Modelling wave attenuation by saltmarsh using satellite-derived vegetation properties
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.1/18516 |
Resumo: | Saltmarshes are increasingly recognised an important asset in coastal management as they dissipate wave energy and thus reduce the potential for coastal flooding. The frontal surface area (FSA) and the drag coefficient (C-d) are parameters commonly used in wave attenuation models to express the resistance of vegetation structure to incident waves. The FSA of vegetation represents the vertical surface area facing incoming waves which is calculated as the product of height, diameter and density whereas C-d is often used as tunable parameter that represents the vegetation-wave interactions that relies on both vegetation properties and wave conditions. Despite their importance in numerical modelling, substantial uncertainty remains in obtaining these parameters in the field due to the time-intensive and relatively expensive nature of data collection. An alternative structural vegetation parameter that can be included in wave attenuation models is the leaf area index (LAI). The primary advantage of the LAI is that it can be readily derived from satellite imagery, and thus provides a low-cost, fast alternative to field data collection. However, to date, its incorporation in widely-used coastal engineering models is lacking. The aim of this paper is to verify the use of remote-sensed LAI in numerical wave models as an alternative to FSA. Here, the widely used XBeach model for simulating storm impacts on a range of coastal systems is applied to two open coast sites with extensive saltmarsh; Chesapeake Bay, USA, and Brancaster, UK. To assess the performance of wave attenuation modelling using both methods, we compared the use of remote-sensed LAI from satellite imagery and field-based FSA as inputs into the model. The LAI-based model provides similar levels of accuracy as the FSA-based model. Likewise, higher uncertainties related to plant height, diameter, and density were found in the FSA-based model than in the LAI-based model. Therefore, the LAI-based model provides the advantage of a low-cost and fast method to accurately estimate and predict wave attenuation by vegetation using numerical models such as XBeach. Our practical application in the Brancaster site exemplifies an easy and fast approach to obtaining structural parameters of saltmarsh vegetation and estimating wave attenuation between natural and artificial saltmarshes as well as between seasons. |
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Modelling wave attenuation by saltmarsh using satellite-derived vegetation propertiesNumerical modellingLeaf area index (LAI)Remote sensingWave-vegetation interactionWave dissipationSaltmarshes are increasingly recognised an important asset in coastal management as they dissipate wave energy and thus reduce the potential for coastal flooding. The frontal surface area (FSA) and the drag coefficient (C-d) are parameters commonly used in wave attenuation models to express the resistance of vegetation structure to incident waves. The FSA of vegetation represents the vertical surface area facing incoming waves which is calculated as the product of height, diameter and density whereas C-d is often used as tunable parameter that represents the vegetation-wave interactions that relies on both vegetation properties and wave conditions. Despite their importance in numerical modelling, substantial uncertainty remains in obtaining these parameters in the field due to the time-intensive and relatively expensive nature of data collection. An alternative structural vegetation parameter that can be included in wave attenuation models is the leaf area index (LAI). The primary advantage of the LAI is that it can be readily derived from satellite imagery, and thus provides a low-cost, fast alternative to field data collection. However, to date, its incorporation in widely-used coastal engineering models is lacking. The aim of this paper is to verify the use of remote-sensed LAI in numerical wave models as an alternative to FSA. Here, the widely used XBeach model for simulating storm impacts on a range of coastal systems is applied to two open coast sites with extensive saltmarsh; Chesapeake Bay, USA, and Brancaster, UK. To assess the performance of wave attenuation modelling using both methods, we compared the use of remote-sensed LAI from satellite imagery and field-based FSA as inputs into the model. The LAI-based model provides similar levels of accuracy as the FSA-based model. Likewise, higher uncertainties related to plant height, diameter, and density were found in the FSA-based model than in the LAI-based model. Therefore, the LAI-based model provides the advantage of a low-cost and fast method to accurately estimate and predict wave attenuation by vegetation using numerical models such as XBeach. Our practical application in the Brancaster site exemplifies an easy and fast approach to obtaining structural parameters of saltmarsh vegetation and estimating wave attenuation between natural and artificial saltmarshes as well as between seasons.ElsevierSapientiaFigueroa-Alfaro, Richard W.Van Rooijen, ArnoldGarzon, Juan L.Evans, MartinHarris, Angela2024-01-01T01:30:12Z20222022-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.1/18516eng0925-857410.1016/j.ecoleng.2021.106528info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-01-03T02:00:37Zoai:sapientia.ualg.pt:10400.1/18516Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:08:16.194265Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Modelling wave attenuation by saltmarsh using satellite-derived vegetation properties |
title |
Modelling wave attenuation by saltmarsh using satellite-derived vegetation properties |
spellingShingle |
Modelling wave attenuation by saltmarsh using satellite-derived vegetation properties Figueroa-Alfaro, Richard W. Numerical modelling Leaf area index (LAI) Remote sensing Wave-vegetation interaction Wave dissipation |
title_short |
Modelling wave attenuation by saltmarsh using satellite-derived vegetation properties |
title_full |
Modelling wave attenuation by saltmarsh using satellite-derived vegetation properties |
title_fullStr |
Modelling wave attenuation by saltmarsh using satellite-derived vegetation properties |
title_full_unstemmed |
Modelling wave attenuation by saltmarsh using satellite-derived vegetation properties |
title_sort |
Modelling wave attenuation by saltmarsh using satellite-derived vegetation properties |
author |
Figueroa-Alfaro, Richard W. |
author_facet |
Figueroa-Alfaro, Richard W. Van Rooijen, Arnold Garzon, Juan L. Evans, Martin Harris, Angela |
author_role |
author |
author2 |
Van Rooijen, Arnold Garzon, Juan L. Evans, Martin Harris, Angela |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Sapientia |
dc.contributor.author.fl_str_mv |
Figueroa-Alfaro, Richard W. Van Rooijen, Arnold Garzon, Juan L. Evans, Martin Harris, Angela |
dc.subject.por.fl_str_mv |
Numerical modelling Leaf area index (LAI) Remote sensing Wave-vegetation interaction Wave dissipation |
topic |
Numerical modelling Leaf area index (LAI) Remote sensing Wave-vegetation interaction Wave dissipation |
description |
Saltmarshes are increasingly recognised an important asset in coastal management as they dissipate wave energy and thus reduce the potential for coastal flooding. The frontal surface area (FSA) and the drag coefficient (C-d) are parameters commonly used in wave attenuation models to express the resistance of vegetation structure to incident waves. The FSA of vegetation represents the vertical surface area facing incoming waves which is calculated as the product of height, diameter and density whereas C-d is often used as tunable parameter that represents the vegetation-wave interactions that relies on both vegetation properties and wave conditions. Despite their importance in numerical modelling, substantial uncertainty remains in obtaining these parameters in the field due to the time-intensive and relatively expensive nature of data collection. An alternative structural vegetation parameter that can be included in wave attenuation models is the leaf area index (LAI). The primary advantage of the LAI is that it can be readily derived from satellite imagery, and thus provides a low-cost, fast alternative to field data collection. However, to date, its incorporation in widely-used coastal engineering models is lacking. The aim of this paper is to verify the use of remote-sensed LAI in numerical wave models as an alternative to FSA. Here, the widely used XBeach model for simulating storm impacts on a range of coastal systems is applied to two open coast sites with extensive saltmarsh; Chesapeake Bay, USA, and Brancaster, UK. To assess the performance of wave attenuation modelling using both methods, we compared the use of remote-sensed LAI from satellite imagery and field-based FSA as inputs into the model. The LAI-based model provides similar levels of accuracy as the FSA-based model. Likewise, higher uncertainties related to plant height, diameter, and density were found in the FSA-based model than in the LAI-based model. Therefore, the LAI-based model provides the advantage of a low-cost and fast method to accurately estimate and predict wave attenuation by vegetation using numerical models such as XBeach. Our practical application in the Brancaster site exemplifies an easy and fast approach to obtaining structural parameters of saltmarsh vegetation and estimating wave attenuation between natural and artificial saltmarshes as well as between seasons. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022 2022-01-01T00:00:00Z 2024-01-01T01:30:12Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10400.1/18516 |
url |
http://hdl.handle.net/10400.1/18516 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
0925-8574 10.1016/j.ecoleng.2021.106528 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Elsevier |
publisher.none.fl_str_mv |
Elsevier |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799133328372137984 |