Monitoring of Mine Tailings Ponds in Ghana: A Remote Sensing-Based Assessment

Monitoring of Mine Tailings Ponds in Ghana: A Remote Sensing-Based Assessment | 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 Monitoring of Mine Tailings Ponds in Ghana: A Remote Sensing-Based Assessment Samuel Nana Safo Kantanka, Michael Addaney, Prosper Kpiebaya, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6702134/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 Sep, 2025 Read the published version in Environmental Monitoring and Assessment → Version 1 posted 10 You are reading this latest preprint version Abstract Tailings storage facilities (TSFs) pose significant environmental and structural risks, especially in mining regions with evolving landscapes. This study investigates the storage capacity changes and dam failure risks of the Dokyiwaa (Sansu) Tailings Storage Facility (TSF) at AngloGold Ashanti Mines, Obuasi, Ghana, over the period from 2016 to 2024. The study employs publicly available remote sensing data including Sentinel-2 imagery, Digital Elevation Models (DEMs), and vegetation and water indices - Normalized Difference Water Index (NDWI), Enhanced Vegetation Index (EVI) and Soil-Adjusted Vegetation Index (SAVI) this study analyses environmental dynamics and structural stability. NDWI results reveal fluctuating water levels, suggesting potential seepage and increased liquefaction risks, particularly in steep-sloped zones. EVI and SAVI analyses show a sharp decline in vegetation cover, with barren areas expanding from 134.98 m² in 2016 to over 1.13 million m² by 2024, increasing susceptibility to erosion and surface destabilization. Slope and aspect data further highlight erosion-prone areas and structural weaknesses. Findings indicate that the TSF faces escalating risks due to vegetation loss, fluctuating hydrological conditions, and unstable terrain. The study indicates the urgent need for improved drainage systems, erosion control, and rehabilitation strategies to mitigate these risks. To mitigate these risks, the thesis recommends improved drainage systems, erosion control measures, and proactive rehabilitation strategies, emphasizing the need for sustainable tailings management. The insights from this research contribute to enhancing the safety protocols for tailings dams, promoting environmental stewardship, and aligning with broader sustainability goals within the mining sector. Tailings Storage Facility (TSF) Remote Sensing Dam Failure Risk Environmental Degradation Mine Waste Management Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 28 Sep, 2025 Read the published version in Environmental Monitoring and Assessment → Version 1 posted Editorial decision: Revision requested 04 Aug, 2025 Reviews received at journal 01 Aug, 2025 Reviewers agreed at journal 30 Jul, 2025 Reviews received at journal 23 Jul, 2025 Reviewers agreed at journal 29 Jun, 2025 Reviewers agreed at journal 26 Jun, 2025 Reviewers invited by journal 24 Jun, 2025 Editor assigned by journal 27 May, 2025 Submission checks completed at journal 27 May, 2025 First submitted to journal 19 May, 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-6702134","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":476349140,"identity":"04a679a2-e44e-4d7a-963e-ab3eef638b96","order_by":0,"name":"Samuel Nana Safo Kantanka","email":"","orcid":"","institution":"University of Energy and Natural Resources","correspondingAuthor":false,"prefix":"","firstName":"Samuel","middleName":"Nana Safo","lastName":"Kantanka","suffix":""},{"id":476349142,"identity":"600c4b98-80c2-4ece-b6dc-5bd887df80a9","order_by":1,"name":"Michael 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This study investigates the storage capacity changes and dam failure risks of the Dokyiwaa (Sansu) Tailings Storage Facility (TSF) at AngloGold Ashanti Mines, Obuasi, Ghana, over the period from 2016 to 2024. The study employs publicly available remote sensing data including Sentinel-2 imagery, Digital Elevation Models (DEMs), and vegetation and water indices - Normalized Difference Water Index (NDWI), Enhanced Vegetation Index (EVI) and Soil-Adjusted Vegetation Index (SAVI) this study analyses environmental dynamics and structural stability. NDWI results reveal fluctuating water levels, suggesting potential seepage and increased liquefaction risks, particularly in steep-sloped zones. EVI and SAVI analyses show a sharp decline in vegetation cover, with barren areas expanding from 134.98 m² in 2016 to over 1.13 million m² by 2024, increasing susceptibility to erosion and surface destabilization. Slope and aspect data further highlight erosion-prone areas and structural weaknesses. 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