Vague Set–Driven Decision Support System for Early Warning of Water Quality Deterioration in Aquaculture

Vague Set–Driven Decision Support System for Early Warning of Water Quality Deterioration in Aquaculture | 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 Vague Set–Driven Decision Support System for Early Warning of Water Quality Deterioration in Aquaculture Anita Pandey, Rajesh Dangwal, Ajay Pandey This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8664976/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 India, the world’s second-largest fish producer, relies heavily on aquaculture, which supports millions livelihoods. Sustaining this sector requires effective pond management, particularly the regulation of key water quality parameters—temperature, pH, dissolved oxygen, ammonia, hydrogen sulfide, hardness, alkalinity, TDS, and turbidity that directly influence fish growth, immunity, and survival. These parameters frequently deteriorate due to organic load accumulation and sudden temperature fluctuations, often going unnoticed by small and marginal farmers until losses become severe. This study proposes a vague set–driven decision support system to provide early warnings of water quality degradation in aquaculture ponds. The model incorporates truth and falsity membership functions to capture uncertainties associated with multiple physico-chemical parameters and their interdependencies (e.g., temperature–DO, pH–ammonia, hardness–alkalinity). Using optimal parameter thresholds from coldwater, warm-water and brackish systems aquaculture standards, the system computes a Vague Water Quality Risk Index (VWQRI) and generates interval-based alerts (Normal, Caution & Critical). Results indicate that vague-set modeling enhances interpretability and reduces false alarms under uncertain or overlapping conditions, offering a robust and adaptable tool for preventive pond management and sustainable aquaculture production. Vague Set Theory Decision Support System Water Quality Aquaculture Early Warning Uncertainty Modeling India. Full Text Additional Declarations No competing interests reported. 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. 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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-8664976","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":583473240,"identity":"b6dde1cd-b5e2-46c1-8110-6e6fc4225521","order_by":0,"name":"Anita Pandey","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA90lEQVRIiWNgGAWjYFACxgYgOgBitP/4AKTY2AlraWwAaeFhY26QnAHSwkyMNRAt7A3SPCA+IS38s5vbH/zccUfeXr6xwdjm1zZ5PmYGxg8fc3BrkbhzsLGx98wzwx42xobk3L7bhm3MDMySM7fhseZGYmMDb9thRpCWw7k9txmBWtiYefFokQdqafzbdtgeqKWx2bLntj1BLQZALc1AWxKBWpqZGX7cTiSoxRCoZbbsmcPJPccS2xh7G24ntzEzNuP1i9yN9Acf3+44bNvefPwZw48/t23ntzcf/PARn/dRAGMbmGwgVj0I/CFF8SgYBaNgFIwUAACNSVlWKt3xJAAAAABJRU5ErkJggg==","orcid":"","institution":"Hemwati Nandan Bahuguna Garhwal University","correspondingAuthor":true,"prefix":"","firstName":"Anita","middleName":"","lastName":"Pandey","suffix":""},{"id":583473241,"identity":"a3627376-7bbd-4f3c-807b-72095db85757","order_by":1,"name":"Rajesh Dangwal","email":"","orcid":"","institution":"Hemwati Nandan Bahuguna Garhwal University","correspondingAuthor":false,"prefix":"","firstName":"Rajesh","middleName":"","lastName":"Dangwal","suffix":""},{"id":583473242,"identity":"fd6b844e-76a2-46ac-9914-7d6b68bc6275","order_by":2,"name":"Ajay Pandey","email":"","orcid":"","institution":"Department of Fisheries, Uttarakhand","correspondingAuthor":false,"prefix":"","firstName":"Ajay","middleName":"","lastName":"Pandey","suffix":""}],"badges":[],"createdAt":"2026-01-22 03:54:41","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8664976/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8664976/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104891185,"identity":"77a753d7-b0f0-4bf7-8374-350b625f424a","added_by":"auto","created_at":"2026-03-18 10:43:11","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":423090,"visible":true,"origin":"","legend":"","description":"","filename":"MathsManuscriptAmended1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8664976/v1_covered_280115d1-1f11-4114-85a1-411ca2656409.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Vague Set–Driven Decision Support System for Early Warning of Water Quality Deterioration in Aquaculture","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"Vague Set Theory, Decision Support System, Water Quality, Aquaculture, Early Warning, Uncertainty Modeling, India.","lastPublishedDoi":"10.21203/rs.3.rs-8664976/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8664976/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIndia, the world’s second-largest fish producer, relies heavily on aquaculture, which supports millions livelihoods. Sustaining this sector requires effective pond management, particularly the regulation of key water quality parameters—temperature, pH, dissolved oxygen, ammonia, hydrogen sulfide, hardness, alkalinity, TDS, and turbidity that directly influence fish growth, immunity, and survival. These parameters frequently deteriorate due to organic load accumulation and sudden temperature fluctuations, often going unnoticed by small and marginal farmers until losses become severe.\u003c/p\u003e\n\u003cp\u003eThis study proposes a vague set–driven decision support system to provide early warnings of water quality degradation in aquaculture ponds. The model incorporates truth and falsity membership functions to capture uncertainties associated with multiple physico-chemical parameters and their interdependencies (e.g., temperature–DO, pH–ammonia, hardness–alkalinity). Using optimal parameter thresholds from coldwater, warm-water and brackish systems aquaculture standards, the system computes a Vague Water Quality Risk Index (VWQRI) and generates interval-based alerts (Normal, Caution \u0026amp; Critical). Results indicate that vague-set modeling enhances interpretability and reduces false alarms under uncertain or overlapping conditions, offering a robust and adaptable tool for preventive pond management and sustainable aquaculture production.\u003c/p\u003e","manuscriptTitle":"Vague Set–Driven Decision Support System for Early Warning of Water Quality Deterioration in Aquaculture","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-03 09:03:53","doi":"10.21203/rs.3.rs-8664976/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","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}}],"origin":"","ownerIdentity":"95a3bbd6-34ab-4120-99c5-188524fe8cd8","owner":[],"postedDate":"February 3rd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-18T10:42:36+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-03 09:03:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8664976","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8664976","identity":"rs-8664976","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}