Assessing water quality restoration measures in Lake Pampulha (Brazil) through remote sensing imagery

Urban reservoirs are frequently exposed to impacts from high population density, polluting activities, and the absence of environmental control measures and monitoring. In this study, we investigated the use of satellite imagery to assess restoration measures and support decision-making in a hypereutrophic urban reservoir. Since 2016, Lake Pampulha (Brazil) has undergone restoration measures, including the application of Phoslock®, to mitigate its poor water quality conditions. Satellite images from Landsat-8 (L8) and Sentinel-2 (S2) and historical monitoring data were used to estimate total suspended matter (TSM), chlorophyll-a (Chla), and Secchi disk depth (SDD). We explored both established models from existing literature and novel alternatives, the latter employing machine learning approaches. Model performance was assessed through the coefficient of determination (R $$ ) during calibration and using the root mean square error (RMSE) and its normalization by the observed mean (nRMSE) during validation. Random forest regressor presented superior performance for the three water quality parameters and both satellites. The performance metrics for Landsat-8 were TSM (n=44) R $$ of 0.62; Chla (n=48) R $$ of 0.74; and SDD (n=23) R $$ of 0.67. For Sentinel-2, TSM (n=53) R $$ of 0.72; Chla (n=54) R $$ of 0.64; SDD (n=33) R $$ of 0.89. The selected models were then applied to cloud-free images from 2013 to 2022 to provide modeled TSM, Chla, and SDD values. These were used for spatiotemporal analysis, encompassing cluster analysis, sample comparisons, and trend analysis. Three distinct regions within Lake Pampulha were identified, with the upstream region displaying poorer conditions for TSM, Chla, and SDD. Restoration measures have contributed positively to improving water quality in Lake Pampulha; however, rainy periods pose a challenge due to water quality deterioration associated with urban runoff. Remote sensing has proven to be a robust tool for assisting managers in assessing recovery measures in urban lakes.