Empirical and semi-empirical chlorophyll-a modeling for water quality assessment through river-lake transition in extreme Southern Brazil.

Abstract

Mirim lagoon is the second largest lacustrine water body in Southern Brazil, providing water for local communities. However, algae growth and water quality in the lagoon and in tributaries rivers is influenced by nutrient's increase. In this context, this study performs the empirical and semi-empirical chlorophyll-a (Chl-a) modeling using remote sensing and in situ data for water quality assessment. Water quality data were collected at 15 sample locations in the lagoon on the date of Sentinel-2 satellite overpass. Surface reflectance data were derived from the Sen2Cor atmospheric correction method and correlated with Chl-a concentration. The best model presented a Pearson's correlation coefficient = 0.81 and Mean Absolute Error = 0.13µg.L-1. Low Chl-a concentration is observed at the Northern lagoon, possibly due to suspended solids presence. The same occurs in the left margin, being associated with the influence of land use for agriculture. High Chl-a concentrations are associated with shallower and lentic areas. The mean Chl-a concentration predicted by the model was 17.34μg.L-1, similar to the observed value in situ (16.32μg.L-1). Overall, the empirical model developed can be applied as a tool to reduce costs and efforts in fieldwork measures and to understand eutrophication in this river-lake transition ecosystem.