Multivariate design events for compound flooding analysis in estuaries

Understanding Compound Flood (CF) hazard in estuaries requires moving beyond univariate approaches toward multivariate frameworks that capture the joint behavior of multiple drivers. Although the relevance of such approaches is increasingly recognized, most existing methods remain limited to bivaria...

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Autores: Gómez Rave, Dina Vanessa, Urrea Méndez, Diego Armando, Jesús Peñil, Manuel del|||0000-0003-0703-8960
Tipo de recurso: artículo
Fecha de publicación:2025
País:España
Institución:Universidad de Cantabria (UC)
Repositorio:UCrea Repositorio Abierto de la Universidad de Cantabria
Idioma:inglés
OAI Identifier:oai:repositorio.unican.es:10902/38670
Acceso en línea:https://hdl.handle.net/10902/38670
Access Level:acceso abierto
Palabra clave:Compound flooding
Estuarine flooding
Copulas
Multivariate analysis
Joint return period
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spelling Multivariate design events for compound flooding analysis in estuariesGómez Rave, Dina VanessaUrrea Méndez, Diego ArmandoJesús Peñil, Manuel del|||0000-0003-0703-8960Compound floodingEstuarine floodingCopulasMultivariate analysisJoint return periodUnderstanding Compound Flood (CF) hazard in estuaries requires moving beyond univariate approaches toward multivariate frameworks that capture the joint behavior of multiple drivers. Although the relevance of such approaches is increasingly recognized, most existing methods remain limited to bivariate analyses. Extending to higher dimensions poses conceptual and computational challenges, particularly in estimating Joint Return Periods (JRP) and defining representative design events. This limitation is especially relevant in estuarine systems, where the hazard may result from the combined action of interacting drivers ? including precipitation, river discharge, storm surge, and waves ? that rarely occur in isolation. In this context, restricting the analysis to two variables may overlook relevant dependencies, reinforcing the need for models that account for higher-order interactions. This study examines the role of multivariate dependence structures within a six-dimensional case-study, comparing different copula families to evaluate their suitability for CF hazard analysis. Focusing on the Santoña estuary, we assess how model choice influences the estimation of joint events and the selection of representative conditions for design. Among the models explored, vine constructions incorporating extreme-value copulas led to more coherent joint estimates, offering improved stability across dependence scenarios. Rather than seeking a universally optimal model, the analysis illustrates how the choice of dependence structure can influence the representation of joint extremes. The proposed framework supports physically interpretable and statistically consistent multivariate design events for compound hazard analysis in coastal settings.This work received financial support from the Government of Cantabria through the Fénix Programme and from Grant RTI2018-096449-B-I00, funded by MCIN/AEI/10.13039/501100011033 and by ‘‘ERDF A way of making Europe’’.ElsevierUniversidad de Cantabria20252025-12-15journal articlehttp://purl.org/coar/resource_type/c_6501NAhttp://purl.org/coar/version/c_be7fb7dd8ff6fe43info:eu-repo/semantics/articlehttps://hdl.handle.net/10902/38670Coastal Engineering, 2025, 202, 104850reponame:UCrea Repositorio Abierto de la Universidad de Cantabriainstname:Universidad de Cantabria (UC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:repositorio.unican.es:10902/386702026-06-02T12:39:31Z
dc.title.none.fl_str_mv Multivariate design events for compound flooding analysis in estuaries
title Multivariate design events for compound flooding analysis in estuaries
spellingShingle Multivariate design events for compound flooding analysis in estuaries
Gómez Rave, Dina Vanessa
Compound flooding
Estuarine flooding
Copulas
Multivariate analysis
Joint return period
title_short Multivariate design events for compound flooding analysis in estuaries
title_full Multivariate design events for compound flooding analysis in estuaries
title_fullStr Multivariate design events for compound flooding analysis in estuaries
title_full_unstemmed Multivariate design events for compound flooding analysis in estuaries
title_sort Multivariate design events for compound flooding analysis in estuaries
dc.creator.none.fl_str_mv Gómez Rave, Dina Vanessa
Urrea Méndez, Diego Armando
Jesús Peñil, Manuel del|||0000-0003-0703-8960
author Gómez Rave, Dina Vanessa
author_facet Gómez Rave, Dina Vanessa
Urrea Méndez, Diego Armando
Jesús Peñil, Manuel del|||0000-0003-0703-8960
author_role author
author2 Urrea Méndez, Diego Armando
Jesús Peñil, Manuel del|||0000-0003-0703-8960
author2_role author
author
dc.contributor.none.fl_str_mv Universidad de Cantabria
dc.subject.none.fl_str_mv Compound flooding
Estuarine flooding
Copulas
Multivariate analysis
Joint return period
topic Compound flooding
Estuarine flooding
Copulas
Multivariate analysis
Joint return period
description Understanding Compound Flood (CF) hazard in estuaries requires moving beyond univariate approaches toward multivariate frameworks that capture the joint behavior of multiple drivers. Although the relevance of such approaches is increasingly recognized, most existing methods remain limited to bivariate analyses. Extending to higher dimensions poses conceptual and computational challenges, particularly in estimating Joint Return Periods (JRP) and defining representative design events. This limitation is especially relevant in estuarine systems, where the hazard may result from the combined action of interacting drivers ? including precipitation, river discharge, storm surge, and waves ? that rarely occur in isolation. In this context, restricting the analysis to two variables may overlook relevant dependencies, reinforcing the need for models that account for higher-order interactions. This study examines the role of multivariate dependence structures within a six-dimensional case-study, comparing different copula families to evaluate their suitability for CF hazard analysis. Focusing on the Santoña estuary, we assess how model choice influences the estimation of joint events and the selection of representative conditions for design. Among the models explored, vine constructions incorporating extreme-value copulas led to more coherent joint estimates, offering improved stability across dependence scenarios. Rather than seeking a universally optimal model, the analysis illustrates how the choice of dependence structure can influence the representation of joint extremes. The proposed framework supports physically interpretable and statistically consistent multivariate design events for compound hazard analysis in coastal settings.
publishDate 2025
dc.date.none.fl_str_mv 2025
2025-12-15
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
NA
http://purl.org/coar/version/c_be7fb7dd8ff6fe43
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/10902/38670
url https://hdl.handle.net/10902/38670
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv Coastal Engineering, 2025, 202, 104850
reponame:UCrea Repositorio Abierto de la Universidad de Cantabria
instname:Universidad de Cantabria (UC)
instname_str Universidad de Cantabria (UC)
reponame_str UCrea Repositorio Abierto de la Universidad de Cantabria
collection UCrea Repositorio Abierto de la Universidad de Cantabria
repository.name.fl_str_mv
repository.mail.fl_str_mv
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