Water Quality Assessment and Modelling Using Machine Learning

Water Quality Assessment and Modelling Using Machine Learning | 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 Water Quality Assessment and Modelling Using Machine Learning Km Shashi Prabha Mishra, Prabhat Kumar Patel, Asit Singh This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4616495/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 3 You are reading this latest preprint version Abstract One of the most essential sources of water for people to drink is groundwater. Several studies on groundwater have been carried out in India. However, the characteristics of groundwater have not been investigated through machine learning (ML tools). There is a need for a defined strategy which would concentrate on a specific part of groundwater management, which means the protection of groundwater from contamination. This study makes use of 97 groundwater samples that were taken from tube wells and dug wells in various places within Ayodhya, Uttar Pradesh, India from the year 2000–2018 groundwater data yearbook. Seven hydro-chemical parameters from each sample were ascertained and compared to the standard values recommended for drinking purposes by the Bureau of Indian Standards (BIS) 10,500:2012. Anticipating the Water Quality Index (WQI) and Water Quality Classification (WQC) so that WQI is a crucial indication for water validity is the difficulty this research aims to solve. Parameter adjustment and optimization are used in this work to increase the accuracy of multiple machine learning ARIMA model, in which the process of forecasting WQI and WQC is performed. The analysis of the proposed algorithms will assist the relevant government agencies in identifying substitute water for consumption in the affected regions. Groundwater management WQI WQC ARIMA Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editor assigned by journal 26 Jun, 2024 Submission checks completed at journal 21 Jun, 2024 First submitted to journal 21 Jun, 2024 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. 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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-4616495","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":319385765,"identity":"1f9808c3-d28d-431a-bf92-5650daa3eed1","order_by":0,"name":"Km Shashi Prabha Mishra","email":"","orcid":"","institution":"Institute of Engineering and Technology","correspondingAuthor":false,"prefix":"","firstName":"Km","middleName":"Shashi Prabha","lastName":"Mishra","suffix":""},{"id":319385766,"identity":"e89785e5-2434-4c17-a47d-32f28b231b6e","order_by":1,"name":"Prabhat Kumar Patel","email":"","orcid":"","institution":"Institute of Engineering and Technology","correspondingAuthor":false,"prefix":"","firstName":"Prabhat","middleName":"Kumar","lastName":"Patel","suffix":""},{"id":319385767,"identity":"ef551c25-6791-46da-9a12-0c118d0dc422","order_by":2,"name":"Asit Singh","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDklEQVRIiWNgGAWjYFACxgYgIQFCjA8//rMBiTQeIKClsQGqhdlYgi0NbAgBLRBrQFrYJHjYDoPZeLXw9x9uf8DwxyJPPrqBQUKC57zd2vbDQFtqbKJxaZG4kdjYwNgmUWx45wCDQYHE7eRtZxKBWo6l5Tbg0nMD6BfGBonEjTMSGBIkDG4nmx0AamFsOIxTi/z5g0Dv/4FoOcCTcC7Z7PxD/FoMDgAdBvR44nyJBMYGngMH7MxuELDFEOiXGYltEokbJBKbmSUbkhPMbgBtScDjF7nzxx98+PCnLnH+jOTjPz822NmbnU9/+OBDjQ1u74NAAtiFkPhJbICJEATyUEPtiVE8CkbBKBgFIwsAAGmYZ3MwxrM0AAAAAElFTkSuQmCC","orcid":"","institution":"Institute of Engineering and Technology","correspondingAuthor":true,"prefix":"","firstName":"Asit","middleName":"","lastName":"Singh","suffix":""}],"badges":[],"createdAt":"2024-06-21 09:42:41","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4616495/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4616495/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":60145176,"identity":"586804bb-be57-41c9-9741-3473d71281d9","added_by":"auto","created_at":"2024-07-12 09:50:27","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":703146,"visible":true,"origin":"","legend":"","description":"","filename":"shashimishramanuscriptayodhya.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4616495/v1_covered_4dce96a9-2cb4-40d8-a68f-24f2e1f3236c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Water Quality Assessment and Modelling Using Machine Learning","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":"environment-systems-and-decisions","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"envr","sideBox":"Learn more about [Environment Systems and Decisions](http://link.springer.com/journal/10669)","snPcode":"10669","submissionUrl":"https://submission.nature.com/new-submission/10669/3","title":"Environment Systems and Decisions","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Groundwater management, WQI, WQC, ARIMA","lastPublishedDoi":"10.21203/rs.3.rs-4616495/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4616495/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eOne of the most essential sources of water for people to drink is groundwater. Several studies on groundwater have been carried out in India. However, the characteristics of groundwater have not been investigated through machine learning (ML tools). There is a need for a defined strategy which would concentrate on a specific part of groundwater management, which means the protection of groundwater from contamination. This study makes use of 97 groundwater samples that were taken from tube wells and dug wells in various places within Ayodhya, Uttar Pradesh, India from the year 2000\u0026ndash;2018 groundwater data yearbook. Seven hydro-chemical parameters from each sample were ascertained and compared to the standard values recommended for drinking purposes by the Bureau of Indian Standards (BIS) 10,500:2012.\u003c/p\u003e \u003cp\u003eAnticipating the Water Quality Index (WQI) and Water Quality Classification (WQC) so that WQI is a crucial indication for water validity is the difficulty this research aims to solve. 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