Risk Estimation of Surface Water Pollution in Vam Co Tay River Based on Remote Sensing Data and Multi-criteria Decision Analysis Methods

Risk Estimation of Surface Water Pollution in Vam Co Tay River Based on Remote Sensing Data and Multi-criteria Decision Analysis Methods | 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 Risk Estimation of Surface Water Pollution in Vam Co Tay River Based on Remote Sensing Data and Multi-criteria Decision Analysis Methods Trung Hung Vo, Hien Than Nguyen, Thi Thuy Hang Nguyen, Trong Dieu Hien Le This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4072169/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 Satellite remote sensing (SRS) is a technique that can provide effective method on surface water quality assessment at large spatial scales studies. The analysis research involves: (1) analysis of changes in surface water quality in the Vam Co Tay River, Long An province, Vietnam in the period 2015–2020, (2) select a model to estimate water quality assessment index from remote sensing data based on Bayesian Model Averaging - BMA ; and (3) quantitative assessment of surface water pollution risks in the study area. The results show that the predictive coefficients of determination (R 2 ) for water quality (BOD5, COD, and TSS) are higher than 0.70 for all three parameters. In particular, the upstream of ​​Vam Co Tay river with "very high risk level" in 2015 tended to decrease to "high risk level" in 2020. Besides, the results also show the increasing of the risk in downstream from "low risk" in 2015 to "moderate risk" in 2020. The study demonstrated the potential of SRS for providing an overall assessment of the spatial distribution of risks associated with surface water pollution and forecasting the concentration change trends in the future, and supporting to overcome data shortages in water monitoring Satellite remote sensing Vam Co Tay river Bayesian Model Averaging Full Text Additional Declarations No competing interests reported. Supplementary Files VN.tif 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. 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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-4072169","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":283295915,"identity":"b9543a70-e87b-4424-87b1-1137fe9f3881","order_by":0,"name":"Trung Hung Vo","email":"","orcid":"","institution":"Thu Dau Mot University","correspondingAuthor":false,"prefix":"","firstName":"Trung","middleName":"Hung","lastName":"Vo","suffix":""},{"id":283295916,"identity":"ea709825-072a-4f6d-a69f-b64f2efddcee","order_by":1,"name":"Hien Than Nguyen","email":"","orcid":"","institution":"Thu Dau Mot University","correspondingAuthor":false,"prefix":"","firstName":"Hien","middleName":"Than","lastName":"Nguyen","suffix":""},{"id":283295917,"identity":"6c307fe9-a962-4cc6-9bc2-e207563749a2","order_by":2,"name":"Thi Thuy Hang Nguyen","email":"","orcid":"","institution":"Vietnam National University, Ho Chi Minh City","correspondingAuthor":false,"prefix":"","firstName":"Thi","middleName":"Thuy Hang","lastName":"Nguyen","suffix":""},{"id":283295918,"identity":"838f3022-4ab6-4131-bd42-a885837f4f34","order_by":3,"name":"Trong Dieu Hien Le","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzElEQVRIiWNgGAWjYBACA2Yg8YCBWY6BIQHEZyZSS0ICszEP8VoYIFoSe4jWYs7OfOxB4g/r9P3s2WkSDBXWiQ0SuQfwarFsZks3SEhIz+3hebtNguFMOlBLXgJ+hx3mMZNISDic2yORu02Cse1wYgPPGQMCWvi/gbSk84C1/CNKCw8bSEsCREsDUAt7DyEtbECHpaUb9px5u9ki4Vi6cRtBLecPP5P4YGMtz96eu/HGhxpr2X5mHvxaUEECELORoH4UjIJRMApGAQ4AALh+QVHflWLUAAAAAElFTkSuQmCC","orcid":"","institution":"Thu Dau Mot University","correspondingAuthor":true,"prefix":"","firstName":"Trong","middleName":"Dieu Hien","lastName":"Le","suffix":""}],"badges":[],"createdAt":"2024-03-11 09:31:52","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4072169/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4072169/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":53783927,"identity":"94137d3e-7668-482e-ad83-1fc6eca9b72a","added_by":"auto","created_at":"2024-03-30 13:06:38","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1352848,"visible":true,"origin":"","legend":"","description":"","filename":"ManuscriptLTDH28022024.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4072169/v1_covered_477090cc-e517-481a-84e2-0e37a6fc2c6d.pdf"},{"id":53395706,"identity":"5f4fd8d4-628c-4b16-ac04-552851a50c8f","added_by":"auto","created_at":"2024-03-25 13:26:59","extension":"tif","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":345868,"visible":true,"origin":"","legend":"","description":"","filename":"VN.tif","url":"https://assets-eu.researchsquare.com/files/rs-4072169/v1/856b6878a7be9a2febf724f7.tif"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eRisk Estimation of Surface Water Pollution in Vam Co Tay River Based on Remote Sensing Data and Multi-criteria Decision Analysis Methods\u003c/p\u003e","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":"Satellite remote sensing, Vam Co Tay river, Bayesian Model Averaging","lastPublishedDoi":"10.21203/rs.3.rs-4072169/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4072169/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSatellite remote sensing (SRS) is a technique that can provide effective method on surface water quality assessment at large spatial scales studies. The analysis research involves: (1) analysis of changes in surface water quality in the Vam Co Tay River, Long An province, Vietnam in the period 2015\u0026ndash;2020, (2) select a model to estimate water quality assessment index from remote sensing data based on \u003cem\u003eBayesian Model Averaging\u003c/em\u003e - \u003cem\u003eBMA\u003c/em\u003e; and (3) quantitative assessment of surface water pollution risks in the study area. The results show that the predictive coefficients of determination (R\u003csup\u003e2\u003c/sup\u003e) for water quality (BOD5, COD, and TSS) are higher than 0.70 for all three parameters. In particular, the upstream of ​​Vam Co Tay river with \"very high risk level\" in 2015 tended to decrease to \"high risk level\" in 2020. Besides, the results also show the increasing of the risk in downstream from \"low risk\" in 2015 to \"moderate risk\" in 2020. 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