A simple model for predicting hypoxic events in a tidal estuary

A simple model for predicting hypoxic events in a tidal estuary | 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 Short Report A simple model for predicting hypoxic events in a tidal estuary Ovidio García-Oliva, Kai Wirtz This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8288643/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 Low dissolved oxygen concentration threatens the ecosystem services provided by estuaries, especially in heavily modified water bodies such as the Elbe passing through Hamburg. In preparation of early warning systems, we developed for three monitoring stations along this river a simple auto-regressive statistical model to identify hypoxic events—days with mean oxygen below 4 mg L -1 . The model uses three predictors observed in preceding days: (1) daily mean oxygen concentration, (2) water-, and (3) air-temperature. Its performance improves as the observation window is extended and as more recent data is incorporated. The most parsimonious model, which balances accuracy and complexity, achieves high predictive skill: precision exceeds 90% of correctly predicted events at stations downstream of the port of Hamburg and 80% at upstream stations. By adjusting the forecast horizon and observation window, the approach can provide early warning up to seven days in advance, with precisions above 50% in the more affected downstream locations. Although the results are specific to the Elbe, the methodology is readily transferable to other water bodies. Marine and Freshwater Ecology Ecological Modeling Hypoxia Temperature sensitivity Water quality Auto-regressive model Full Text Additional Declarations The authors declare no competing interests. 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-8288643","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Short Report","associatedPublications":[],"authors":[{"id":555866502,"identity":"119aacb7-bf00-48a5-82be-f754b6361c76","order_by":0,"name":"Ovidio García-Oliva","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+UlEQVRIie3PMWvCUBDA8RNBl4jrCWK+wpNC6yDxq7wQiEtnyVBoghAncX1g6cdwfuEgXR6ZKzgoQicH3ewgbVICpcPDjELff7qD+w0HYDLdZLUQeTlKCGQ5NioTVYkA4C+PK5A2etH7NgBnsaSd/Hzd9B5m03QLk6GWdIQ7HXAFnsh8lsxXH3ddlY4ZZL6WMJXE6MbggbJAtlbkCny8x1pM14mdk+TyQs/CPhTkS0/eoh/isJxQKySOaBVEaklnFhW/IO+rBqNuSn1h+T7yzNOSdr25W5+D4ain6vvT4YlsbFKKx4mjJWXohn92fg3kjSrcmEwm03/tG4uQVv/fMoqbAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0001-6060-2001","institution":"Helmholtz-Zentrum hereon","correspondingAuthor":true,"prefix":"","firstName":"Ovidio","middleName":"","lastName":"García-Oliva","suffix":""},{"id":555866503,"identity":"679d5159-a91b-4369-a325-3ff5518a1ef0","order_by":1,"name":"Kai Wirtz","email":"","orcid":"https://orcid.org/0000-0002-6972-3878","institution":"Helmholtz-Zentrum hereon","correspondingAuthor":false,"prefix":"","firstName":"Kai","middleName":"","lastName":"Wirtz","suffix":""}],"badges":[],"createdAt":"2025-12-05 14:24:11","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-8288643/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8288643/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":97892759,"identity":"d6952dc9-69f9-47c5-bc77-70267a54c496","added_by":"auto","created_at":"2025-12-10 15:20:22","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":9547318,"visible":true,"origin":"","legend":"","description":"","filename":"empiricalhypoxiamodel.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8288643/v1_covered_7adfa8dd-e541-49f6-83c0-c22471355e8c.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eA simple model for predicting hypoxic events in a tidal estuary\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[{"identity":"508f036f-8390-49e1-bce4-15aae17323d0","identifier":"10.13039/501100004937","name":"Bundesministerium für Forschung und Technologie","awardNumber":"03F0954D","order_by":0}],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Helmholtz-Zentrum hereon","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":"Hypoxia, Temperature sensitivity, Water quality, Auto-regressive model","lastPublishedDoi":"10.21203/rs.3.rs-8288643/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8288643/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eLow dissolved oxygen concentration threatens the ecosystem services provided by estuaries, especially in heavily modified water bodies such as the Elbe passing through Hamburg. 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