Spatio-temporal dynamics of the Río de la Plata turbidity front; combining remote sensing with in-situ measurements and numerical modeling

Abstract

The Río de la Plata is a micro-tidal estuary located in Southeast South America. With an annual mean flow of 26,500 m3/s, it receives 160 million tons/yr of suspended sediments. The high content of cohesive fine sediments in the estuary generates high turbidity levels in its inner and intermediate zones, which can be clearly seen in color satellite images. In this work, an image-based algorithm was successfully implemented to remotely detect the turbidity front of the Río de la Plata, based on the top of the atmosphere (TOA) reflectance in the red band of MODIS-Aqua satellite. The algorithm finds the reflectance level that ‘best’ separates two water classes: turbid fluvial and clear ocean waters. The front dynamic was studied combining remotely sensed information and data of river discharge, winds, salinity and sea level time series, in the four-year period 2014–2017. River discharge was identified as the main external forcing, revealing a solid general pattern of behavior: when discharge was high (low) the front tended to be located in the outer (intermediate) zone of the estuary. Sea level seemed to be a secondary forcing, presenting higher correlations along the center of the estuary than near both coasts. Local winds needed to have a relatively persistent (2-day) component in a given direction to affect the location of the front. Additionally, results of an already implemented numerical model of the Río de la Plata were evaluated in terms of spatio-temporal performance, considering turbidity and salinity fronts locations. New strengths and limitations of the model were identified, and an improvement in the parameterization of sediments’ settling velocity was tested. Model results revealed the relative importance of bottom shear stress on the general location of the front, and of salinity on the flocculation process of cohesive sediments. This work provided new insights for the understanding of the Río de la Plata estuarine dynamics through the combination of three complementary tools – remote sensing, in situ data, and numerical modeling, – which may be extended to other systems around the world.