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Developing an Event-Tree Probabilistic Tsunami Inundation Model for NE Atlantic Coasts: Application to a Case Study

dc.contributor.authorOmira, Rachid
dc.contributor.authorMatias, Luís
dc.contributor.authorBaptista, Maria Ana Carvalho Viana
dc.date.accessioned2017-06-07T11:03:40Z
dc.date.available2017-06-07T11:03:40Z
dc.date.issued2016-12
dc.description.abstractThis study constitutes a preliminary assessment of probabilistic tsunami inundation in the NE Atlantic region. We developed an event-tree approach to calculate the likelihood of tsunami flood occurrence and exceedance of a specific near-shore wave height for a given exposure time. Only tsunamis of tectonic origin are considered here, taking into account local, regional, and far-field sources. The approach used here consists of an event-tree method that gathers probability models for seismic sources, tsunami numerical modeling, and statistical methods. It also includes a treatment of aleatoric uncertainties related to source location and tidal stage. Epistemic uncertainties are not addressed in this study. The methodology is applied to the coastal test-site of Sines located in the NE Atlantic coast of Portugal. We derive probabilistic high-resolution maximum wave amplitudes and flood distributions for the study test-site considering 100- and 500-year exposure times. We find that the probability that maximum wave amplitude exceeds 1 m somewhere along the Sines coasts reaches about 60 % for an exposure time of 100 years and is up to 97 % for an exposure time of 500 years. The probability of inundation occurrence (flow depth > 0 m) varies between 10 % and 57 %, and from 20 % up to 95 % for 100- and 500-year exposure times, respectively. No validation has been performed here with historical tsunamis. This paper illustrates a methodology through a case study, which is not an operational assessment.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationOMIRA, R.; MATIAS, Luís; BATISTA, M. A. - Developing an Event-Tree Probabilistic Tsunami Inundation Model for NE Atlantic Coasts: Application to a Case Study. Pure Appl. Geophys. ISSN: 0033-4553. Vol. 173, N.º 12 (2016), pp. 3775–3794.pt_PT
dc.identifier.doi10.1007/s00024-016-1367-z Pure and Applied Geophysicspt_PT
dc.identifier.issn0033-4553
dc.identifier.urihttp://hdl.handle.net/10400.21/7161
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherSpringerpt_PT
dc.relation.publisherversionhttp://download.springer.com/static/pdf/555/art%253A10.1007%252Fs00024-016-1367-z.pdf?originUrl=http%3A%2F%2Flink.springer.com%2Farticle%2F10.1007%2Fs00024-016-1367-z&token2=exp=1496057182~acl=%2Fstatic%2Fpdf%2F555%2Fart%25253A10.1007%25252Fs00024-016-1367-z.pdf%3ForiginUrl%3Dhttp%253A%252F%252Flink.springer.com%252Farticle%252F10.1007%252Fs00024-016-1367-z*~hmac=c196c3f02e24eeb969704b38f95e9a049e961dafd35aaa28942800d5c279c3d7pt_PT
dc.subjectTsunamipt_PT
dc.subjectProbabilistic approachpt_PT
dc.subjectEvent-treept_PT
dc.subjectInundationpt_PT
dc.subjectNE Atlantic.pt_PT
dc.titleDeveloping an Event-Tree Probabilistic Tsunami Inundation Model for NE Atlantic Coasts: Application to a Case Studypt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage3794pt_PT
oaire.citation.issue173pt_PT
oaire.citation.startPage3775pt_PT
oaire.citation.titlePure Appl. Geophyspt_PT
oaire.citation.volume12pt_PT
person.familyNameOmira
person.familyNamede Carvalho Viana Baptista
person.givenNameRachid
person.givenNameMARIA ANA
person.identifier972486
person.identifierhttps://scholar.google.pt/citations?user=ApQ9Bp4AAAAJ&hl=pt-PT
person.identifier.ciencia-idC116-66FF-BB9B
person.identifier.ciencia-idCF12-1EE3-F49B
person.identifier.orcid0000-0002-6198-7588
person.identifier.orcid0000-0002-6381-703X
person.identifier.ridN-2533-2013
person.identifier.scopus-author-id34971883700
person.identifier.scopus-author-idhttps://www.scopus.com/authid/detail.uri?authorId=7102934075
rcaap.rightsclosedAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublicationc57e1a9c-7628-49a3-98f9-4465f1ba5e5a
relation.isAuthorOfPublicationa01dd185-70d9-4a8e-9c8c-1418e555ef00
relation.isAuthorOfPublication.latestForDiscoveryc57e1a9c-7628-49a3-98f9-4465f1ba5e5a

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