A User-Oriented Local Coastal Flooding Early Warning System Using Metamodelling Techniques

Given recent scientific advances, coastal flooding events can be properly modelled. Nevertheless, such models are computationally expensive (requiring many hours), which prevents their use for forecasting and warning. In addition, there is a gap between the model outputs and information actually nee...

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Autores principales:	Déborah Idier, Axel Aurouet, François Bachoc, Audrey Baills, José Betancourt, Fabrice Gamboa, Thierry Klein, Andrés F. López-Lopera, Rodrigo Pedreros, Jérémy Rohmer, Alexandre Thibault
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	forecast flood local hydrodynamic modelling metamodelling Gâvres Naval architecture. Shipbuilding. Marine engineering VM1-989 Oceanography GC1-1581
Acceso en línea:	https://doaj.org/article/3db0e4a768ad477a909057ed6ace03de
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spelling	oai:doaj.org-article:3db0e4a768ad477a909057ed6ace03de2021-11-25T18:04:03ZA User-Oriented Local Coastal Flooding Early Warning System Using Metamodelling Techniques10.3390/jmse91111912077-1312https://doaj.org/article/3db0e4a768ad477a909057ed6ace03de2021-10-01T00:00:00Zhttps://www.mdpi.com/2077-1312/9/11/1191https://doaj.org/toc/2077-1312Given recent scientific advances, coastal flooding events can be properly modelled. Nevertheless, such models are computationally expensive (requiring many hours), which prevents their use for forecasting and warning. In addition, there is a gap between the model outputs and information actually needed by decision makers. The present work aims to develop and test a method capable of forecasting coastal flood information adapted to users’ needs. The method must be robust and fast and must integrate the complexity of coastal flood processes. The explored solution relies on metamodels, i.e., mathematical functions that precisely and efficiently (within minutes) estimate the results that would provide the numerical model. While the principle of relying on metamodel solutions is not new, the originality of the present work is to tackle and validate the entire process from the identification of user needs to the establishment and validation of the rapid forecast and early warning system (FEWS) while relying on numerical modelling, metamodelling, the development of indicators, and information technologies. The development and validation are performed at the study site of Gâvres (France). This site is subject to wave overtopping, so the numerical phase-resolving SWASH model is used to build the learning dataset required for the metamodel setup. Gaussian process- and random forest classifier-based metamodels are used and post-processed to estimate 14 indicators of interest for FEWS users. These metamodelling and post-processing schemes are implemented in an FEWS prototype, which is employed by local users and exhibits good warning skills during the validation period. Based on this experience, we provide recommendations for the improvement and/or application of this methodology and individual steps to other sites.Déborah IdierAxel AurouetFrançois BachocAudrey BaillsJosé BetancourtFabrice GamboaThierry KleinAndrés F. López-LoperaRodrigo PedrerosJérémy RohmerAlexandre ThibaultMDPI AGarticleforecastfloodlocalhydrodynamic modellingmetamodellingGâvresNaval architecture. Shipbuilding. Marine engineeringVM1-989OceanographyGC1-1581ENJournal of Marine Science and Engineering, Vol 9, Iss 1191, p 1191 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	forecast flood local hydrodynamic modelling metamodelling Gâvres Naval architecture. Shipbuilding. Marine engineering VM1-989 Oceanography GC1-1581
spellingShingle	forecast flood local hydrodynamic modelling metamodelling Gâvres Naval architecture. Shipbuilding. Marine engineering VM1-989 Oceanography GC1-1581 Déborah Idier Axel Aurouet François Bachoc Audrey Baills José Betancourt Fabrice Gamboa Thierry Klein Andrés F. López-Lopera Rodrigo Pedreros Jérémy Rohmer Alexandre Thibault A User-Oriented Local Coastal Flooding Early Warning System Using Metamodelling Techniques
description	Given recent scientific advances, coastal flooding events can be properly modelled. Nevertheless, such models are computationally expensive (requiring many hours), which prevents their use for forecasting and warning. In addition, there is a gap between the model outputs and information actually needed by decision makers. The present work aims to develop and test a method capable of forecasting coastal flood information adapted to users’ needs. The method must be robust and fast and must integrate the complexity of coastal flood processes. The explored solution relies on metamodels, i.e., mathematical functions that precisely and efficiently (within minutes) estimate the results that would provide the numerical model. While the principle of relying on metamodel solutions is not new, the originality of the present work is to tackle and validate the entire process from the identification of user needs to the establishment and validation of the rapid forecast and early warning system (FEWS) while relying on numerical modelling, metamodelling, the development of indicators, and information technologies. The development and validation are performed at the study site of Gâvres (France). This site is subject to wave overtopping, so the numerical phase-resolving SWASH model is used to build the learning dataset required for the metamodel setup. Gaussian process- and random forest classifier-based metamodels are used and post-processed to estimate 14 indicators of interest for FEWS users. These metamodelling and post-processing schemes are implemented in an FEWS prototype, which is employed by local users and exhibits good warning skills during the validation period. Based on this experience, we provide recommendations for the improvement and/or application of this methodology and individual steps to other sites.
format	article
author	Déborah Idier Axel Aurouet François Bachoc Audrey Baills José Betancourt Fabrice Gamboa Thierry Klein Andrés F. López-Lopera Rodrigo Pedreros Jérémy Rohmer Alexandre Thibault
author_facet	Déborah Idier Axel Aurouet François Bachoc Audrey Baills José Betancourt Fabrice Gamboa Thierry Klein Andrés F. López-Lopera Rodrigo Pedreros Jérémy Rohmer Alexandre Thibault
author_sort	Déborah Idier
title	A User-Oriented Local Coastal Flooding Early Warning System Using Metamodelling Techniques
title_short	A User-Oriented Local Coastal Flooding Early Warning System Using Metamodelling Techniques
title_full	A User-Oriented Local Coastal Flooding Early Warning System Using Metamodelling Techniques
title_fullStr	A User-Oriented Local Coastal Flooding Early Warning System Using Metamodelling Techniques
title_full_unstemmed	A User-Oriented Local Coastal Flooding Early Warning System Using Metamodelling Techniques
title_sort	user-oriented local coastal flooding early warning system using metamodelling techniques
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/3db0e4a768ad477a909057ed6ace03de
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A User-Oriented Local Coastal Flooding Early Warning System Using Metamodelling Techniques

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