Coastal morphodynamic emulator for early warning short-term forecasts

Detalhes bibliográficos
Autor(a) principal: Weber de Melo, Willian
Data de Publicação: 2023
Outros Autores: Pinho, José L. S., Iglesias, Isabel
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://hdl.handle.net/1822/86809
Resumo: - Name of the Software: XBeach version 1.23. Developers: Deltares/XBeach Open-Source Community; First year available: 2009; Cost: Free; Software availability:https://download.deltares.nl/en/download/xbeach-open-source/; Program size: 330.97 MB. - The deep learning-based emulator used for surrogating the XBeach morphodynamic module was implemented in Python language (version 3.9) based on TensorFlow library. The authors used a Windows 11 Home OS environment, CPU Intel(R) Core (TM) i7-8750H 2.20 GHz, RAM 16 GB, GPU Nvidia GeForce GTX 1060. The architecture of the model is available at: http://www.hydroshare.org/resource/b4ae97df748842a1800816b32a3d640 b.
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spelling Coastal morphodynamic emulator for early warning short-term forecastsEngenharia e Tecnologia::Engenharia CivilAção climática- Name of the Software: XBeach version 1.23. Developers: Deltares/XBeach Open-Source Community; First year available: 2009; Cost: Free; Software availability:https://download.deltares.nl/en/download/xbeach-open-source/; Program size: 330.97 MB. - The deep learning-based emulator used for surrogating the XBeach morphodynamic module was implemented in Python language (version 3.9) based on TensorFlow library. The authors used a Windows 11 Home OS environment, CPU Intel(R) Core (TM) i7-8750H 2.20 GHz, RAM 16 GB, GPU Nvidia GeForce GTX 1060. The architecture of the model is available at: http://www.hydroshare.org/resource/b4ae97df748842a1800816b32a3d640 b.Data will be made available on request. Deep learning model for XBeach morphodynamic emulation (Original data) (HydroShare): https://www.hydroshare.org/resource/b4ae97df748842a1800816b32a3d640b/The use of numerical models to anticipate the effects of floods and storms in coastal regions is essential to mitigate the damages of these natural disasters. However, local studies require high spatial and temporal resolution numerical models, limiting their use due to the involved high computational costs. This constraint becomes even more critical when these models are used for real-time monitoring and warning systems. Therefore, the objective of this paper was to reduce the computational time of coastal morphodynamic models simulations by implementing a deep learning emulator. The emulator performance was evaluated using different scenarios run with the XBeach software, which considered different grid resolutions and the effects of a storm event in the morphodynamic patterns around a breakwater and a groin. The morphodynamic simulation time was reduced by 23%, and it was identified that the major restriction to reducing the computational cost was the hydrodynamic numerical model simulation.This research was supported by the Doctoral Grant SFRH/BD/151383/2021 financed by the Portuguese Foundation for Science and Technology (FCT), and with funds from the Ministry of Science, Technology and Higher Education, under the MIT Portugal Program. I. Iglesias also acknowledge the FCT financing through the CEEC program (2022.07420. CEECIND).ElsevierUniversidade do MinhoWeber de Melo, WillianPinho, José L. S.Iglesias, Isabel2023-072023-07-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/1822/86809engWeber de Melo, W., Pinho, J., & Iglesias, I. (2023, July). Coastal morphodynamic emulator for early warning short-term forecasts. Environmental Modelling & Software. Elsevier BV. http://doi.org/10.1016/j.envsoft.2023.105729cv-prod-329370910.1016/j.envsoft.2023.1057292-s2.0-85159622157https://www.sciencedirect.com/science/article/pii/S1364815223001159info: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:RCAAP2023-10-14T01:20:48Zoai:repositorium.sdum.uminho.pt:1822/86809Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T20:35:26.690722Repositório 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 Coastal morphodynamic emulator for early warning short-term forecasts
title Coastal morphodynamic emulator for early warning short-term forecasts
spellingShingle Coastal morphodynamic emulator for early warning short-term forecasts
Weber de Melo, Willian
Engenharia e Tecnologia::Engenharia Civil
Ação climática
title_short Coastal morphodynamic emulator for early warning short-term forecasts
title_full Coastal morphodynamic emulator for early warning short-term forecasts
title_fullStr Coastal morphodynamic emulator for early warning short-term forecasts
title_full_unstemmed Coastal morphodynamic emulator for early warning short-term forecasts
title_sort Coastal morphodynamic emulator for early warning short-term forecasts
author Weber de Melo, Willian
author_facet Weber de Melo, Willian
Pinho, José L. S.
Iglesias, Isabel
author_role author
author2 Pinho, José L. S.
Iglesias, Isabel
author2_role author
author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Weber de Melo, Willian
Pinho, José L. S.
Iglesias, Isabel
dc.subject.por.fl_str_mv Engenharia e Tecnologia::Engenharia Civil
Ação climática
topic Engenharia e Tecnologia::Engenharia Civil
Ação climática
description - Name of the Software: XBeach version 1.23. Developers: Deltares/XBeach Open-Source Community; First year available: 2009; Cost: Free; Software availability:https://download.deltares.nl/en/download/xbeach-open-source/; Program size: 330.97 MB. - The deep learning-based emulator used for surrogating the XBeach morphodynamic module was implemented in Python language (version 3.9) based on TensorFlow library. The authors used a Windows 11 Home OS environment, CPU Intel(R) Core (TM) i7-8750H 2.20 GHz, RAM 16 GB, GPU Nvidia GeForce GTX 1060. The architecture of the model is available at: http://www.hydroshare.org/resource/b4ae97df748842a1800816b32a3d640 b.
publishDate 2023
dc.date.none.fl_str_mv 2023-07
2023-07-01T00:00:00Z
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 https://hdl.handle.net/1822/86809
url https://hdl.handle.net/1822/86809
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Weber de Melo, W., Pinho, J., & Iglesias, I. (2023, July). Coastal morphodynamic emulator for early warning short-term forecasts. Environmental Modelling & Software. Elsevier BV. http://doi.org/10.1016/j.envsoft.2023.105729
cv-prod-3293709
10.1016/j.envsoft.2023.105729
2-s2.0-85159622157
https://www.sciencedirect.com/science/article/pii/S1364815223001159
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
repository.mail.fl_str_mv
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