Enhancing Flood Risk Management: A Comprehensive Review on Flood Early Warning Systems with Emphasis on Numerical Modeling

UDC.coleccionInvestigaciónes_ES
UDC.departamentoEnxeñaría Civiles_ES
UDC.grupoInvEnxeñaría da Auga e do Medio Ambiente (GEAMA)es_ES
UDC.institutoCentroCITEEC - Centro de Innovación Tecnolóxica en Edificación e Enxeñaría Civiles_ES
UDC.issue10es_ES
UDC.journalTitleWateres_ES
UDC.startPage1408es_ES
UDC.volume16es_ES
dc.contributor.authorFernández-Novoa, Diego
dc.contributor.authorGonzález-Cao, José
dc.contributor.authorGarcía-Feal, Orlando
dc.date.accessioned2024-11-20T20:29:26Z
dc.date.available2024-11-20T20:29:26Z
dc.date.issued2024
dc.description.abstract[Abstract:] During recent decades there has been an increase in extreme flood events and their intensity in most regions, mainly driven by climate change. Furthermore, these critical events are expected to intensify in the future. Therefore, the improvement of preparedness, mitigation, and adaptation counterparts is mandatory. Many scientific fields are involved in this task, but from a meteorological and hydrological perspective, one of the main tools that can contribute to mitigating the impact of floods is the development of Early Warning Systems. In this sense, this paper presents a scientific literature review of some of the most representative Flood Early Warning Systems worldwide, many of which are currently fully operational, with a special focus on the numerical modeling component when it is developed and integrated into the system. Thus, from basic to technically complex, and from basin or regional to continental or global scales of application, these systems have been reviewed. In this sense, a brief description of their main features, operational procedures, and implemented numerical models is also depicted. Additionally, a series of indications regarding the key aspects of the newly developed FEWSs, based on recent trends and advancements in FEWSs development found in the literature, are also summarized. Thus, this work aims to provide a literature review useful to scientists and engineers involved in flood analysis to improve and develop supporting tools to assist in the implementation of mitigation measures to reduce flood damage for people, goods, and ecosystems and to improve the community resilience.es_ES
dc.description.sponsorshipThis research has been partially supported by Xunta de Galicia, Consellería de Cultura, Educación e Universidade, under Project ED431C 2021/44 “Programa de Consolidación e Estructuración de Unidades de Investigación Competitivas”. This research has also been partially supported by the European Regional Development Fund under the INTERREG-POCTEP project RISC_PLUS (Code: 0031_RISC_PLUS_6_E). D.F.-N. was supported by Xunta de Galicia through a postdoctoral grant (ED481B-2021-108). O.G.-F. was supported by the postdoctoral fellowship “Juan de la Cierva” (ref. JDC2022-048667-I), funded by MCIN/AEI/10.13039/501100011033 and the European Union “NextGenerationEU”/PRTR.es_ES
dc.description.sponsorshipXunta de Galicia; ED431C 2021/44es_ES
dc.description.sponsorshipXunta de Galicia; ED481B-2021-108es_ES
dc.identifier.citationFernández-Nóvoa, D., González-Cao, J., García-Feal, O. (2024). Enhancing Flood Risk Management: A Comprehensive Review on Flood Early Warning Systems with Emphasis on Numerical Modeling. Water, 16(10), 1408. https://doi.org/10.3390/w16101408es_ES
dc.identifier.doi10.3390/w16101408
dc.identifier.urihttp://hdl.handle.net/2183/40213
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI//JDC2022-048667-I/ES/es_ES
dc.relation.urihttps://doi.org/10.3390/w16101408es_ES
dc.rightsAtribuciónes_ES
dc.rights.accessRightsopen accesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectFloodses_ES
dc.subjectEarly warning systemes_ES
dc.subjectNumerical modelinges_ES
dc.subjectLiterature reviewes_ES
dc.titleEnhancing Flood Risk Management: A Comprehensive Review on Flood Early Warning Systems with Emphasis on Numerical Modelinges_ES
dc.typejournal articlees_ES
dspace.entity.typePublication
relation.isAuthorOfPublicationb3a961d8-cb6a-45d2-8973-b41bf99fc637
relation.isAuthorOfPublication.latestForDiscoveryb3a961d8-cb6a-45d2-8973-b41bf99fc637

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