Physically-Based Probabilistic Fluvial Flood Hazard Screening Framework for Civil Infrastructure

Physically-Based Probabilistic Fluvial Flood Hazard Screening Framework for Civil Infrastructure | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Physically-Based Probabilistic Fluvial Flood Hazard Screening Framework for Civil Infrastructure Luigi Di Sarno, Danah Albuhairi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8450400/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Statistical flood frequency analysis yields probabilistic discharge estimates, yet current flood hazard modelling practice rarely translates these distributions into corresponding probabilistic hydraulic parameters. This disconnect limits the consideration of probabilistic information in infrastructure design, where water depth and velocity remain primary decision variables typically considered with several assumptions in practice and in state-of-the-art literature. This study introduces the first physically-based methodology that propagates hydrologic uncertainty into hydraulic flood hazard modelling using site-specific hydraulic geometry response functions. Results show that once uncertainty is propagated, depth and velocity at longer return periods span ranges that cross critical flood risk classification thresholds, and that return period migration, due to uncertainty and non-stationarity, materially increases encounter probabilities relevant to design service life. Application to representative European and North American freeboard assignments shows that reductions in effective freeboard due to uncertainty can substantially increase predicted damages when coupled with standard global depth–damage functions, with the North American cases exhibiting larger sensitivity due to lower design elevations and steeper damage curves. The framework remains compatible with standard flood hazard modelling workflows while offering a computationally efficient pathway for probabilistic flood hazard characterisation. By providing continuous hazard curves, the method supports risk-based screening for infrastructure design, spatial planning, and code calibration across diverse regional contexts, as well as in progressing flood resilience towards advanced performance-based engineering applications matured in other natural hazards. Natural hazard Flood Probabilistic flood hazard Uncertainty Civil infrastructure Risk-based design Full Text Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8450400","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":582346427,"identity":"156d0cb4-b51e-4c90-9776-93b228bae260","order_by":0,"name":"Luigi Di Sarno","email":"data:image/png;base64,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","orcid":"","institution":"University of Liverpool","correspondingAuthor":true,"prefix":"","firstName":"Luigi","middleName":"Di","lastName":"Sarno","suffix":""},{"id":582346429,"identity":"ae91250e-a9c8-439d-9495-d99a23e44ae6","order_by":1,"name":"Danah Albuhairi","email":"","orcid":"","institution":"University of Liverpool","correspondingAuthor":false,"prefix":"","firstName":"Danah","middleName":"","lastName":"Albuhairi","suffix":""}],"badges":[],"createdAt":"2025-12-25 17:38:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8450400/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8450400/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106728026,"identity":"4a97135c-43f4-4ee0-8793-0a67ba95488e","added_by":"auto","created_at":"2026-04-12 18:41:28","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1033132,"visible":true,"origin":"","legend":"","description":"","filename":"NaturalHazardsDraftrev01.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8450400/v1_covered_94de22ed-3a40-4ee8-9853-550000431e49.pdf"}],"financialInterests":"","formattedTitle":"Physically-Based Probabilistic Fluvial Flood Hazard Screening Framework for Civil Infrastructure","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Natural hazard, Flood, Probabilistic flood hazard, Uncertainty, Civil infrastructure, Risk-based design","lastPublishedDoi":"10.21203/rs.3.rs-8450400/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8450400/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eStatistical flood frequency analysis yields probabilistic discharge estimates, yet current flood hazard modelling practice rarely translates these distributions into corresponding probabilistic hydraulic parameters. 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Application to representative European and North American freeboard assignments shows that reductions in effective freeboard due to uncertainty can substantially increase predicted damages when coupled with standard global depth\u0026ndash;damage functions, with the North American cases exhibiting larger sensitivity due to lower design elevations and steeper damage curves. The framework remains compatible with standard flood hazard modelling workflows while offering a computationally efficient pathway for probabilistic flood hazard characterisation. 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