Remote sensing retrieval of water constituents in shallow coastal waters with applications to the Venice lagoon

Lagoons and estuaries worldwide are experiencing accelerated ecosystem degradation due to increased direct and indirect anthropogenic pressure. Monitoring the environmental state and trends in such environment would benefit from the use of remote sensing techniques, which can access a wide range of spatial and temporal scales. However, most remote sensors are not suitable for monitoring shallow and optically-complex waters, because of their low spatial and spectral-resolution and of the uncertainties associated with the contribution of the bottom sediment to the observed remote sensing signal. We apply here a remote sensing-based approach to mapping suspended sediment and chlorophyll concentrations in the shallow Venice lagoon, which integrates hyperspectral remote sensing data, a simplified radiative transfer model, and in-situ water quality measurements. First, we calibrate and validate the key parameters of the model, such as bottom albedo and absorption/backscattering coefficients of sediment, by comparing remote sensing derived water constituent concentrations with in-situ data. We then determine the statistics of those parameters, and the associated estimation uncertainty, by applying a bootstrapping technique. Finally, the lagoon-wide distribution of water constituent concentrations, and of the estimation uncertainty, is derived by inverting the model. The estimates are consistent with measured concentrations and their known optical properties, particularly for the suspended sediment concentrations, while chlorophyll concentration estimates remain more uncertain. Our analyses show that remote sensing methods can provide reliable water constituent concentrations at the system scale and that uncertainties become overwhelming only in particularly shallow areas (water depths indicatively lower than 1 m in the present application). Importantly, the joint use of radiative transfer models, in situ observations, and statistical techniques allows the production of maps of both the estimated concentrations and of the associated uncertainties.