Assessment of the Influence of Catchment Characteristics on Thermal Regimes of Tropical Reservoirs through Landsat 8 Satellite Imagery

Assessment of the Influence of Catchment Characteristics on Thermal Regimes of Tropical Reservoirs through Landsat 8 Satellite Imagery | 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 Assessment of the Influence of Catchment Characteristics on Thermal Regimes of Tropical Reservoirs through Landsat 8 Satellite Imagery Avanthika Latwal, Shaik Rehana, K.S. Rajan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8181381/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 9 You are reading this latest preprint version Abstract Surface Water Temperature (SWT) is a key indicator for understanding ecological condition of inland water bodies and thermal dynamics, especially under increasing anthropogenic pressures and climatic variability. However, the scarcity of in situ observations in tropical regions poses challenges in analysing spatio-temporal thermal dynamics, primarily due to complex interactions among spatial, environmental, and localized factors. This study develops a remote sensing-based modeling framework to map and analyze SWT variations in two tropical reservoirs—Bhadra and Tungabhadra—within a same river basin in southern India. Despite their similar hydroclimatic conditions, the reservoirs exhibit distinct catchment characteristics. Using Landsat 8 thermal imagery from 2016 to 2021, the framework effectively spatial and temporal trends in SWT and examined the influence of potential factors of contributing catchment i.e., land use/land cover (LULC), rainfall, and air temperature using Google Earth Engine (GEE). The approach demonstrated robust performance (R² = 0.62; RMSE = 0.98), supporting its applicability in data-scarce regions. Thermal mapping revealed consistently higher SWT near inflow and periphery zones of the reservoirs adjacent to urban or agricultural land. Statistical analyses confirmed significant associations between elevated SWT and anthropogenically modified landscapes. These findings underscore the utility of medium-resolution satellite data for thermal monitoring and highlight the critical role of integrated catchment management in mitigating thermal stress in tropical reservoirs. Reservoir SWT Landsat 8 LULC Watersheds Water Quality Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 18 May, 2026 Reviews received at journal 16 May, 2026 Reviews received at journal 30 Mar, 2026 Reviewers agreed at journal 23 Mar, 2026 Reviewers agreed at journal 19 Mar, 2026 Reviewers invited by journal 29 Jan, 2026 Editor assigned by journal 27 Nov, 2025 Submission checks completed at journal 27 Nov, 2025 First submitted to journal 22 Nov, 2025 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-8181381","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":583198970,"identity":"0747a0c0-9a84-4930-a41e-7323d8eeaac5","order_by":0,"name":"Avanthika Latwal","email":"","orcid":"","institution":"International Institute of Information Technology, Hyderabad","correspondingAuthor":false,"prefix":"","firstName":"Avanthika","middleName":"","lastName":"Latwal","suffix":""},{"id":583198971,"identity":"083970e5-82f0-47b6-8976-6ffcd2db61da","order_by":1,"name":"Shaik Rehana","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAx0lEQVRIiWNgGAWjYFACHgjFz8zYcADMYiZWi2QzUMsBkrQYgJQfIMZZ5u29Bz8X1DDYGx9nbjz8gcFOnoGdF79OmTPnkqVnHGNI3HYY7LBkwwZmvgS8WiQkcgykedgYEswgWpgTGJh5DPBrkX9j/JvnH9BhEO/XE6FFgsdMmreNgXEDM1jLYSK08OSYWfP2SSTOADnsjMFxwzaCWtjPGN/m+WZjz99//PGHiopqeX7+M/i1wHRCaaBiNmLUj4JRMApGwSjADwCiojnuPjmDIwAAAABJRU5ErkJggg==","orcid":"","institution":"International Institute of Information Technology, Hyderabad","correspondingAuthor":true,"prefix":"","firstName":"Shaik","middleName":"","lastName":"Rehana","suffix":""},{"id":583198972,"identity":"67f5498c-8411-4f51-868c-809e9aeae15c","order_by":2,"name":"K.S. 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However, the scarcity of in situ observations in tropical regions poses challenges in analysing spatio-temporal thermal dynamics, primarily due to complex interactions among spatial, environmental, and localized factors. This study develops a remote sensing-based modeling framework to map and analyze SWT variations in two tropical reservoirs\u0026mdash;Bhadra and Tungabhadra\u0026mdash;within a same river basin in southern India. Despite their similar hydroclimatic conditions, the reservoirs exhibit distinct catchment characteristics. Using Landsat 8 thermal imagery from 2016 to 2021, the framework effectively spatial and temporal trends in SWT and examined the influence of potential factors of contributing catchment i.e., land use/land cover (LULC), rainfall, and air temperature using Google Earth Engine (GEE). The approach demonstrated robust performance (R\u0026sup2; = 0.62; RMSE\u0026thinsp;=\u0026thinsp;0.98), supporting its applicability in data-scarce regions. Thermal mapping revealed consistently higher SWT near inflow and periphery zones of the reservoirs adjacent to urban or agricultural land. Statistical analyses confirmed significant associations between elevated SWT and anthropogenically modified landscapes. These findings underscore the utility of medium-resolution satellite data for thermal monitoring and highlight the critical role of integrated catchment management in mitigating thermal stress in tropical reservoirs.\u003c/p\u003e","manuscriptTitle":"Assessment of the Influence of Catchment Characteristics on Thermal Regimes of Tropical Reservoirs through Landsat 8 Satellite Imagery","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-02 15:48:34","doi":"10.21203/rs.3.rs-8181381/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-18T09:28:53+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-16T18:27:27+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-30T14:53:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"241524240086598636085588951550165860025","date":"2026-03-23T15:00:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"59501972744480524257355658928370699738","date":"2026-03-19T21:05:28+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-29T16:36:47+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-27T11:19:08+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-27T11:18:13+00:00","index":"","fulltext":""},{"type":"submitted","content":"Applied Geomatics","date":"2025-11-22T15:24:12+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"applied-geomatics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"agmj","sideBox":"Learn more about [Applied Geomatics](http://link.springer.com/journal/12518)","snPcode":"12518","submissionUrl":"https://submission.nature.com/new-submission/12518/3","title":"Applied Geomatics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"cfe8dd26-89f7-4e42-8dd1-d89a830d3807","owner":[],"postedDate":"February 2nd, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-18T09:28:53+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-16T18:27:27+00:00","index":26,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-05-18T09:39:18+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-02 15:48:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8181381","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8181381","identity":"rs-8181381","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}