A single semi-analytical algorithm to retrieve chlorophyll-a concentration in oligo-to-hypereutrophic waters of a tropical reservoir cascade

Abstract

Previous studies have shown the challenges in using a single model to estimate chlorophyll-a concentration (Chl-a) in water bodies with widely differing characteristics. A single model based on remote sensing to map the Chl-a distribution across the entire Tietê River Cascade System (TRCS) serves as a cost and time-efficient alternative to the conventional monitoring by providing trophic status over space and time. The Tietê River contains one of the largest cascade reservoir systems in the world, which sustains important ecological and socio-economic activities in the São Paulo State, Brazil. Surplus nutrients in water draining its surrounding catchments have been the main cause of eutrophication in the reservoirs of the TRCS. To assess the trophic state of the reservoirs, Chl-a has been regularly monitored by sampling points. However, they are limited by operational costs and dependent on weather conditions. Moreover, the current sampling method only produces point-based measurements. In this paper, we calibrate remote sensing images based on the absorption coefficient to map the spatial distribution patterns of Chl-a levels in the reservoirs. Mapping is done by estimating the Chl-a concentration. The absorption coefficients were retrieved from OLI/Landsat images using the Quasi-Analytical Algorithm (QAA). The total absorption (at) in 482 nm and 655 nm retrieved by QAA presented NRMSE of 17% and 18.5%, respectively. Both at (482 and 655 nm) were used in the model calibration and presented a satisfactory result covering all data ranges, with R2 of 0.646 and NRMSE of 15.3%. The proposed model in this study to retrieve Chl-a maps with relatively high accuracy can be incorporated into the operational monitoring system of the TRCS at a low cost that can provide timely information for reservoir managers to carry out necessary actions. This may include mitigating environmental impacts caused by sudden algae blooms.