Evaluating Eutrophication and Water Clarity on Lake Victoria’s Ugandan Coast Using Landsat Data

Moses Kiwanuka, Randy Leslie, Anthony Gidudu, John Peter Obubu, Assefa Melesse and Maruthi Sridhar Balaji Bhaskar ()
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Moses Kiwanuka: Department of Earth and Environment, Florida International University, Miami, FL 33199, USA
Randy Leslie: Department of Civil Engineering, Florida International University, Miami, FL 33199, USA
Anthony Gidudu: Department of Geomatics and Land Management, Makerere University, Kampala 7062, Uganda
John Peter Obubu: Department of Water Quality Management, Ministry of Water and Environment, Kampala 20026, Uganda
Assefa Melesse: Department of Earth and Environment, Florida International University, Miami, FL 33199, USA
Maruthi Sridhar Balaji Bhaskar: Department of Earth and Environment, Florida International University, Miami, FL 33199, USA

Sustainability, 2025, vol. 17, issue 20, 1-24

Abstract: Satellite remote sensing has emerged as a reliable and cost-effective approach for monitoring inland water quality, offering spatial and temporal advantages over traditional in situ methods. Lake Victoria, the largest tropical lake and a critical freshwater resource for East Africa, faces increasing eutrophication driven by nutrient inflows from agriculture, urbanization, and industrial activities. This study assessed the spatiotemporal dynamics of water quality along Uganda’s Lake Victoria coast by integrating field measurements (2014–2024) with Landsat 8/9 imagery. Chlorophyll-a, a proxy for algal blooms, and Secchi disk depth, an indicator of water clarity, were selected as key parameters. Cloud-free satellite images were processed using the Dark Object Subtraction method, and spectral reflectance values were correlated with field data. Linear regression models from single bands and band ratios showed strong performance, with adjusted R 2 values of up to 0.88. When tested on unseen data, the models achieved R 2 values above 0.70, confirming robust predictive ability. Results revealed high algal concentrations for nearshore and clearer offshore waters. These models provide an efficient framework for monitoring eutrophication, guiding restoration priorities, and supporting sustainable water management in Lake Victoria.

Keywords: chlorophyll-a; Landsat 8/9; remote sensing; Secchi disk depth (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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