Comparative analysis of methodologies for assessing chlorophyll-a concentration in the Billings Reservoir
DOI:
https://doi.org/10.5902/2179460X91411Keywords:
Remote sensing, Hydrodynamic modeling, In Situ Data, Water quality monitoringAbstract
Monitoring chlorophyll-a concentrations (Chl-a) is essential for managing water quality and mitigating eutrophication risks. Traditional in situ monitoring methods often suffer from data gaps, making remote sensing a valuable complementary tool. This study evaluates data from two remote sensing platforms (SNAP and AlgaeMap), the Delft3D hydrodynamic model, and in situ observations (CETESB) to analyze Chl-a in the Billings Reservoir, São Paulo, from 2017 to 2021. Chl-a behavior was assessed under different seasonal conditions. Results show that during the dry season, SNAP and AlgaeMap provided similar Chl-a estimates, though with some quantitative differences, particularly in marginal areas. AlgaeMap produced higher Chl-a concentrations in upstream regions during the rainy season. A 67.13% agreement was observed between SNAP and Delft3D, indicating challenges in aligning modeled and satellite-derived data. SNAP’s seasonal sensitivity was stronger, showing improved correlation with CETESB data in the dry season. With Chl-a below 100 µg/l, the correlation strengthened, reaching R² values of 0.71 for SNAP and 0.75 for AlgaeMap. The integration of Delft3D provided valuable spatial information, complementing satellite data and capturing temporal dynamics. The combined approach of remote sensing and hydrodynamic modeling enhances the accuracy of Chl-a assessments, offering a comprehensive strategy for reservoir management and eutrophication prevention.
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