Inland water pollution poses significant risks to aquatic environments, affecting ecological and human health while increasing drinking-water treatment costs. Continuous monitoring using reliable techniques such as satellite remote sensing is essential. This study investigates the spatial and temporal water quality dynamics of Lake Okeechobee by integrating satellite imagery with in situ water samples. The objectives are (1) to analyze water quality trends and (2) to develop linear regression models for predicting Chlorophyll-a (Chla), turbidity, and Trophic State Index (TSI) for eutrophication monitoring. Landsat 8 and 9 imagery, coupled with water quality data from monitoring stations in the South Florida Water Management District’s DBHydro database, provided measurements of Chla, total nitrogen (TN), total phosphorus (TP), and turbidity. Statistical analyses determined optimal regression models with adjusted R2 values of 0.69 and 0.93 for individual band Chla and turbidity models and 0.65, 0.82, and 0.66 for spectral band ratio models of Chla, turbidity, and TSI, respectively. Northwestern and southwestern peripheries of Lake Okeechobee exhibited Chla concentrations exceeding the 20 µg/L threshold, while turbidity peaked near the lake’s center. From 2013 to 2019, TN increased significantly, followed by a slight decline from 2019 to 2023, whereas TP exhibited no clear trend. The TSI ranged from mesotrophic to hypereutrophic states. This study demonstrates satellite remote sensing as an efficient tool for monitoring water quality changes, guiding restoration measures, and identifying highly contaminated zones through threshold-based segmentation of satellite-derived water quality maps, rather than assessing the lake as a uniform whole.
Kiwanuka et al. (2025) studied this question.