Expanding the Application of Sentinel-2 Chlorophyll Monitoring across United States Lakes

Abstract

Eutrophication of inland lakes poses various societal and ecological threats, making water quality monitoring crucial. Satellites provide a comprehensive and cost-effective supplement to traditional in situ sampling. The Sentinel-2 MultiSpectral Instrument (S2 MSI) offers unique spectral bands positioned to quantify chlorophyll <i>a</i>, a water-quality and trophic-state indicator, along with fine spatial resolution, enabling the monitoring of small waterbodies. In this study, two algorithms-the Maximum Chlorophyll Index (MCI) and the Normalized Difference Chlorophyll Index (NDCI)-were applied to S2 MSI data. They were calibrated and validated using in situ chlorophyll <i>a</i> measurements for 103 lakes across the contiguous U.S. Both algorithms were tested using top-of-atmosphere reflectances (<i>ρ</i> _t), Rayleigh-corrected reflectances (<i>ρ</i> _s), and remote sensing reflectances (<i>R</i> _<i>rs</i> ). MCI slightly outperformed NDCI across all reflectance products. MCI using <i>ρ</i> _t showed the best overall performance, with a mean absolute error factor of 2.08 and a mean bias factor of 1.15. Conversion of derived chlorophyll <i>a</i> to trophic state improved the potential for management applications, with 82% accuracy using a binary classification. We report algorithm-to-chlorophyll-<i>a</i> conversions that show potential for application across the U.S., demonstrating that S2 can serve as a monitoring tool for inland lakes across broad spatial scales.