Uso de Sensoriamento Remoto e Quimiometria como Ferramentas para Estimar Parâmetros de Qualidade da Água em Lagos Intermitentes do Baixo Rio Doce

Use of Remote Sensing and Chemometrics as Tools to Estimate Parameters of Water Quality in Intermittent Lakes of the Lower Doce River

Resumo

In this work, chemometric prediction models were developed using remote sensing images associated
with limnological parameters to evaluate the water quality of intermittent lakes of the Baixo Rio Doce
(Southeast - Brazil). The lakes, popularly known as Lagoa Juparanã and Lagoa Nova, are located in areas
that were affected by the environmental disaster of the Fundão iron ore tailings dam (Minas Gerais). The
visible and near infrared reflectance bands were extracted from images of the lakes surface, which were
recorded by the Landsat-8 satellite on the dates closest to the days of field collection. After atmospheric
correction of the spectral data, the models were built using Regression by Support Vectors to estimate
the water quality parameters, which presented results satisfactory by the correlation coefficient of the
prediction (R²pred) and by the square root of the mean squared prediction error (RMSEP), respectively:
total phosphorus (0.817; 7.305 μg L-1), turbidity (0.984; 1.467 UNT), transparency (0.705; 0.785 m),
chlorophyll-a (0.850; 0.457 μg L-1) and developed average trophic state index based on the Carlson
equation (0.712; 2.617). This technique enables remote analysis of limnological parameters, which can
help in environmental monitoring and equipping managers for more efficient decision-making in water
resources conservation actions.