First results of PRISMA satellite data applied to water quality monitoring in Argentina

Abstract

Water has historically been considered a renewable resource, however in the last century a sustained degradation of its quality has been observed, both in continental and oceanic systems due to anthropic impact. In this context, the management of water resources by satellite technology represents a central point in public policies since they allow anticipating and adapting to these disturbances. In this work, Sentinel 2-MSI multispectral and PRISMA hyperspectral sensors are used to carry out an analysis of different optical water types in North-East of Argentina. Convolutional procedure was used to compare sensors responses for atmospheric corrected products and RMSE (root mean square error), BIAS and MAE (mean absolute error) metrics were used to assess their performance. Differences below 1 percent were obtained in all cases, indicating an excellent match-up between both sensors. From hyperspectral PRISMA data it was possible to detect quantitative shift towards reddish wavelengths as turbidity of Parana River increases along a transect as well as an increase of the peak value in magnitude. This work opens new opportunities to monitor water quality changes related to optical constituents with deeper details in space and time in highly urbanized and perturbed regions.