Integrating Remote Sensing and Machine Learning for High-Resolution Vulnerability Mapping of Seasonal Wetland Shrinkage under Climate Change in Southern Malawi

Integrating Remote Sensing and Machine Learning for High-Resolution Vulnerability Mapping of Seasonal Wetland Shrinkage under Climate Change in Southern Malawi | 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 Integrating Remote Sensing and Machine Learning for High-Resolution Vulnerability Mapping of Seasonal Wetland Shrinkage under Climate Change in Southern Malawi Harineck Mayamiko Tholo, Precious Masuku, Weston Mwase, Daudi Kachamba, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6910161/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 15 You are reading this latest preprint version Abstract Malawi's Elephant Marsh, a RAMSAR site, is under intense pressure from climate change and human activities. This study utilized remote sensing and machine learning to analyze land use and land cover changes in the Elephant Marsh from 2009 to 2024, revealing a dynamic and surprising ecological trajectory. Contrary to dominant narratives of continuous degradation, our analysis shows two distinct phases. Phase 1 (2009–2018) saw clear environmental decline: water depletion, bareland expansion, and vegetation loss, largely due to unsustainable practices and drought. Yet, Phase 2 (2018–2024) demonstrated a dramatic recovery, characterized by robust water regeneration and vegetation increase, primarily driven by significant cyclonic events from 2021 onwards. This research fundamentally challenges the idea of linear wetland degradation, highlighting how high-magnitude, episodic weather events can temporarily override persistent anthropogenic pressures and catalyze rapid ecosystem recovery. While this short-term recovery is notable, it also contrasts with regional patterns of long-term wetland shrinkage, suggesting a nuanced relationship between immediate climatic impacts and broader environmental trends. Our findings advocate for adaptive environmental management that recognizes the episodic climatic events’ due role in both degrading and restoring these vital ecosystems. Wetland Dynamics Remote Sensing Ecological Regeneration Cyclonic Events Adaptive Management Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 08 Sep, 2025 Reviews received at journal 11 Aug, 2025 Reviews received at journal 09 Aug, 2025 Reviews received at journal 09 Aug, 2025 Reviewers agreed at journal 08 Aug, 2025 Reviewers agreed at journal 06 Aug, 2025 Reviews received at journal 06 Aug, 2025 Reviewers agreed at journal 02 Aug, 2025 Reviewers agreed at journal 01 Aug, 2025 Reviewers agreed at journal 01 Aug, 2025 Reviewers invited by journal 26 Jul, 2025 Editor invited by journal 16 Jul, 2025 Editor assigned by journal 19 Jun, 2025 Submission checks completed at journal 19 Jun, 2025 First submitted to journal 17 Jun, 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. 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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-6910161","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":472296203,"identity":"b6a42661-2b63-4a64-a6e4-561cc80d5783","order_by":0,"name":"Harineck Mayamiko Tholo","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7klEQVRIiWNgGAWjYBACAyA+AKYlGBgPMFQAmczMDcRp4ZEAMc6AtDAS1sIA18LYBmIT0GLOfvbh4YIKO2N76eYDBz7Oq43mbwdq+VGxDacWy550g8MzziSb8cgcSzg4c9vx3BmHGRsYe87cxu2wA2kMh3nbDtjwSOQYHObddiy3AaiFmbENj5bzz4Ba/sG0zDmWO5+glhsgWxoOmEG0NNTkbiCsBWgLz7FkY54baQkHZxw7kLsRqOUgXr+cT2P+zFNjZ9g+I/nggw81dbnzzh8++OBHBW4t6OAwmDxAtHogqCNF8SgYBaNgFIwQAACQNl/mPuE/ogAAAABJRU5ErkJggg==","orcid":"","institution":"Malawi University of Science and Technology","correspondingAuthor":true,"prefix":"","firstName":"Harineck","middleName":"Mayamiko","lastName":"Tholo","suffix":""},{"id":472296204,"identity":"d486a73b-de80-44e8-a3d0-156ee2382228","order_by":1,"name":"Precious Masuku","email":"","orcid":"","institution":"Word Alive Ministries International","correspondingAuthor":false,"prefix":"","firstName":"Precious","middleName":"","lastName":"Masuku","suffix":""},{"id":472296205,"identity":"1e4c70be-d307-4d61-ade4-4edbfbd86495","order_by":2,"name":"Weston Mwase","email":"","orcid":"","institution":"Lilongwe University of Agriculture and Natural Resources","correspondingAuthor":false,"prefix":"","firstName":"Weston","middleName":"","lastName":"Mwase","suffix":""},{"id":472296208,"identity":"e32c2a28-0e10-4c73-a3a4-5c957850e832","order_by":3,"name":"Daudi Kachamba","email":"","orcid":"","institution":"Lilongwe University of Agriculture and Natural Resources","correspondingAuthor":false,"prefix":"","firstName":"Daudi","middleName":"","lastName":"Kachamba","suffix":""},{"id":472296209,"identity":"e35fdffa-86ee-42a5-bbe4-cb3aa04ddf95","order_by":4,"name":"Allena Njala","email":"","orcid":"","institution":"Doshisha University - 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This study utilized remote sensing and machine learning to analyze land use and land cover changes in the Elephant Marsh from 2009 to 2024, revealing a dynamic and surprising ecological trajectory. Contrary to dominant narratives of continuous degradation, our analysis shows two distinct phases. Phase 1 (2009\u0026ndash;2018) saw clear environmental decline: water depletion, bareland expansion, and vegetation loss, largely due to unsustainable practices and drought. Yet, Phase 2 (2018\u0026ndash;2024) demonstrated a dramatic recovery, characterized by robust water regeneration and vegetation increase, primarily driven by significant cyclonic events from 2021 onwards. This research fundamentally challenges the idea of linear wetland degradation, highlighting how high-magnitude, episodic weather events can temporarily override persistent anthropogenic pressures and catalyze rapid ecosystem recovery. 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