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Effectiveness assessment of risk reduction measures at coastal areas using a decision support system: Findings from Emma storm

2019-03Journal article Open access
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dc.contributor.authorFerreira, Óscar
dc.contributor.authorPlomaritis, Haris
dc.contributor.authorCostas, Susana
dc.date.accessioned2020-07-24T10:52:40Z
dc.date.available2020-07-24T10:52:40Z
dc.date.issued2019-03
dc.description.abstractStorms impact coastal areas often causing damages and losses at occupied areas. On a scenario of increasing human occupation at coastal zones and under climate change conditions (including sea level rise and increasing frequency of extreme sea levels), the consequences of storms arc expected to be amplified if no adaptation or further management actions are implemented. The selection of the best possible coastal management measures, considering both costs and effectiveness, will be mandatory in the future, in order to optimise resources. This work analyses the performance of risk reduction measures (beach nourishment and receptors - house and infrastructures - removal), using a decision support system comprised by a morphodynamic numerical model (XBeach) and a Bayesian network based on the source-pathway-receptor concept. The effectiveness of the risk reduction measures is then assessed by a simple index expressing the consequences to the receptors. The approach was tested at Faro Beach by evaluating its performance for a particular storm, Emma (Feb/March 2018), which fiercely impacted the southern coast of Portugal. The output results from the modelling were compared to field observations of the actual damages caused by the storm. The combined use of both measures or the solely use of the nourishment would avoid almost all observed impacts from this storm. The work is pioneer on demonstrating the use of a decision support system for coastal regions validated against observed impacts for a high-energy storm event. The methodology and the proposed index arc adaptable to any sandy coastal region and can be used to test (and improve) management options at a broad number of coastal areas worldwide, minimizing implementation costs and reducing the risk to the occupation and to the people. (C) 2018 Elsevier B.V. All rights reserved.
dc.description.sponsorshipFCT Investigator program [IF/01047/2014]
dc.description.sponsorshipEuropean Union 7th Framework ProgrammeEuropean Union (EU) [603458]
dc.description.sponsorshipproject EVREST [PTDC/MAR-EST/1031/2014]
dc.description.sponsorshipproject EW-COAST [G-LISBOA-01-145-FEDER-028657]
dc.description.sponsorshipPortuguese Science and Technology Foundation (FCT)Portuguese Foundation for Science and Technology [UID/MAR/00350/2013]
dc.description.sponsorshipresearch group RNM-328 of the Andalusian Research Plan (PAI)
dc.description.versioninfo:eu-repo/semantics/publishedVersion
dc.identifier.doi10.1016/j.scitotenv.2018.11.478
dc.identifier.issn0048-9697
dc.identifier.issn1879-1026
dc.identifier.urihttp://hdl.handle.net/10400.1/14390
dc.language.isoeng
dc.peerreviewedyes
dc.publisherElsevier Science
dc.subjectManagement effectiveness
dc.subjectBayesian network
dc.subjectErosion
dc.subjectBeach
dc.subjectSandy
dc.subjectVariability
dc.subjectDisaster
dc.subjectImpacts
dc.subjectHazards
dc.subjectPerformance
dc.titleEffectiveness assessment of risk reduction measures at coastal areas using a decision support system: Findings from Emma storm
dc.typejournal article
dspace.entity.typePublication
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/5876/UID%2FMAR%2F00350%2F2013/PT
oaire.citation.endPage135
oaire.citation.startPage124
oaire.citation.titleScience of the Total Environment
oaire.citation.volume657
oaire.fundingStream5876
person.familyNameFerreira
person.familyNamePlomaritis
person.familyNameCostas
person.givenNameÓscar
person.givenNameTheocharis A.
person.givenNameSusana
person.identifier1448818
person.identifier.ciencia-id1F1C-DF44-94C9
person.identifier.ciencia-idFB1D-6248-EB10
person.identifier.ciencia-idAF19-9EEE-7550
person.identifier.orcid0000-0001-9975-0036
person.identifier.orcid0000-0002-9819-0927
person.identifier.orcid0000-0002-4005-077X
person.identifier.scopus-author-id22836553200
person.identifier.scopus-author-id9043656500
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccess
rcaap.typearticle
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