Modeling trend of sediment yield under climate change using remote sensing integrated SWAT, Upper Tekeze basin, Northern Ethiopia

Modeling trend of sediment yield under climate change using remote sensing integrated SWAT, Upper Tekeze basin, Northern Ethiopia | 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 Modeling trend of sediment yield under climate change using remote sensing integrated SWAT, Upper Tekeze basin, Northern Ethiopia Hagos Gebreslassie Gebru This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9182184/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Modelling sediment yield in large river basins using hydrological models is often limited by the scarcity of field-based input data. In particular, the vegetation and management factor of the Modified Universal Soil Loss Equation (MUSLE-C) is frequently oversimplified, leading to reduced accuracy in sediment simulations. This study applied remote sensing to map the spatial distribution of MUSLE-C and incorporated it into the SWAT model to assess sediment yield responses to climate variability in the Upper Tekeze Basin. Model performance was evaluated using the coefficient of determination (R²), percent bias (PBIAS), and Nash–Sutcliffe efficiency (NSE), while trends and associations between climate and sediment variables were analysed using the Pettitt–Kendall trend test and Pearson correlation analysis. Results demonstrate that LSUA-based MUSLE-C mapping enabled improved SWAT simulations, achieving NSE = 0.84, PBIAS = 10%, and R² = 0.79. Climate analysis revealed no statistically significant trends in rainfall, maximum temperature, or minimum temperature at seasonal or annual scales. In contrast, simulated sediment yields at the Tekeze Dam exhibited a significant increasing trend, highlighting the limited influence of broad-scale climate trends on sediment transport. These findings underscore the need for higher-resolution climate and sediment data to better understand and manage erosion processes in the basin. Cover factor climate change sediment yield remote sensing Hydrologic model Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 23 Apr, 2026 Reviewers agreed at journal 20 Apr, 2026 Reviewers agreed at journal 15 Apr, 2026 Reviewers invited by journal 14 Apr, 2026 Editor assigned by journal 10 Apr, 2026 Submission checks completed at journal 01 Apr, 2026 First submitted to journal 01 Apr, 2026 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-9182184","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":626081069,"identity":"036c8274-c945-4c9f-a1e7-95dadfe00664","order_by":0,"name":"Hagos Gebreslassie Gebru","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAvElEQVRIiWNgGAWjYBACAxDB2GADIhsPkKIlDUySpOUwmEOcFnP241c3fNxx3m5t+2GgLTU20QS1WPbklN2ceeZ28rYziUAtx9JyGwg67EBO2m3ettvJZgeAWoAuJELL+Tdpt/+2nUs2O/+QWC030o/dZmw7YGd2g2hbbrxhu9l7JjnB7AbQlgSi/HI+/dmNnzvs7M3Opz988KHGhrAWBgYecNQkglUmEFYOAuwPQKQ9cYpHwSgYBaNgRAIARjpQ1fV0UP0AAAAASUVORK5CYII=","orcid":"","institution":"Adigrat University","correspondingAuthor":true,"prefix":"","firstName":"Hagos","middleName":"Gebreslassie","lastName":"Gebru","suffix":""}],"badges":[],"createdAt":"2026-03-20 22:38:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9182184/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9182184/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107569712,"identity":"0db962ad-0ed1-497d-abcb-edd946317456","added_by":"auto","created_at":"2026-04-22 17:58:37","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":760666,"visible":true,"origin":"","legend":"","description":"","filename":"Climateandsediment13.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9182184/v1_covered_51acd053-6151-43d3-ba09-13efce7bb8b1.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Modeling trend of sediment yield under climate change using remote sensing integrated SWAT, Upper Tekeze basin, Northern Ethiopia","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"discover-sustainability","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"disu","sideBox":"Learn more about [Discover Sustainability](https://www.springer.com/43621)","snPcode":"","submissionUrl":"","title":"Discover Sustainability","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Cover factor, climate change, sediment yield, remote sensing, Hydrologic model","lastPublishedDoi":"10.21203/rs.3.rs-9182184/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9182184/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eModelling sediment yield in large river basins using hydrological models is often limited by the scarcity of field-based input data. 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