Perspective on uncertainty quantification and reduction in compound flood modeling and forecasting

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dc.contributor.authorAbbaszadeh, Peymanen
dc.contributor.authorMuñoz, David F.en
dc.contributor.authorMoftakhari, Hameden
dc.contributor.authorJafarzadegan, Keighobaden
dc.contributor.authorMoradkhani, Hamiden
dc.date.accessioned2023-02-24T14:10:46Zen
dc.date.available2023-02-24T14:10:46Zen
dc.date.issued2022-10en
dc.date.updated2023-02-23T23:16:03Zen
dc.description.abstractThis perspective discusses the importance of characterizing, quantifying, and accounting for various sources of uncertainties involved in different layers of hydrometeorological and hydrodynamic model simulations as well as their complex interactions and cascading effects (e.g., uncertainty propagation) in forecasting compound flooding (CF). Over the past few decades, CF has come to attention across the globe as this natural hazard results from a combination of either concurrent or successive flood drivers with larger economic, societal, and environmental impacts than those from isolated drivers. A warming climate and increased urbanization in flood-prone areas are expected to contribute to an escalation in the risk of CF in the near future. Recent advances in remote sensing and data science can provide a wide range of possibilities to account for and reduce the predictive uncertainties; hence improving the predictability of CF events, enabling risk-informed decision-making, and ensuring a sustainable CF risk governance.en
dc.description.versionPublished versionen
dc.format.mimetypeapplication/pdfen
dc.identifier105201 (Article number)en
dc.identifier.doihttps://doi.org/10.1016/j.isci.2022.105201en
dc.identifier.eissn2589-0042en
dc.identifier.issn2589-0042en
dc.identifier.issue10en
dc.identifier.orcidMunoz Pauta, David [0000-0001-6032-1082]en
dc.identifier.otherPMC9547283en
dc.identifier.otherS2589-0042(22)01473-0 (PII)en
dc.identifier.pmid36217549en
dc.identifier.urihttp://hdl.handle.net/10919/113931en
dc.identifier.volume25en
dc.language.isoenen
dc.publisherElsevieren
dc.relation.urihttps://www.ncbi.nlm.nih.gov/pubmed/36217549en
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivatives 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.subjectClimatologyen
dc.subjectEarth surface fluid flowen
dc.subjectHydrologyen
dc.subjectFlood forecastingen
dc.titlePerspective on uncertainty quantification and reduction in compound flood modeling and forecastingen
dc.title.serialiScienceen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten
dc.type.otherJournal Articleen
pubs.organisational-group/Virginia Techen
pubs.organisational-group/Virginia Tech/Engineeringen
pubs.organisational-group/Virginia Tech/Engineering/Civil & Environmental Engineeringen
pubs.organisational-group/Virginia Tech/All T&R Facultyen
pubs.organisational-group/Virginia Tech/Engineering/COE T&R Facultyen

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