Water Constituents and Water Depth Retrieval from Sentinel-2A-A First Evaluation in an Oligotrophic Lake

Satellite remote sensing may assist in meeting the needs of lake monitoring. In this study, we aim to evaluate the potential of Sentinel-2 to assess and monitor water constituents and bottom characteristics of lakes at spatio-temporal synoptic scales. In a field campaign at Lake Starnberg, Germany, we collected validation data concurrently to a Sentinel-2A (S2-A) overpass. We compared the results of three different atmospheric corrections, i.e., Sen2Cor, ACOLITE and MIP, with in situ reflectance measurements, whereof MIP performed best (r = 0.987, RMSE = 0.002 sr(-1)). Using the bio-optical modelling tool WASI-2D, we retrieved absorption by coloured dissolved organic matter (a(CDOM)(440)), backscattering and concentration of suspended particulate matter (SPM) in optically deep water; water depths, bottom substrates and a(CDOM)(440) were modelled in optically shallow water. In deep water, SPM and a(CDOM)(440) showed reasonable spatial patterns. Comparisons with in situ data (mean: 0.43 m(-1)) showed an underestimation of S2-A derived a(CDOM)(440) (mean: 0.14 m(-1)); S2-A backscattering of SPM was slightly higher than backscattering from in situ data (mean: 0.027 m(-1) vs. 0.019 m(-1)). Chlorophyll-a concentrations (similar to 1 mg.m(-3)) of the lake were too low for a retrieval. In shallow water, retrieved water depths exhibited a high correlation with echo sounding data (r = 0.95, residual standard deviation = 0.12 m) up to 2.5 m (Secchi disk depth: 4.2 m), though water depths were slightly underestimated (RMSE = 0.56 m). In deeper water, Sentinel-2A bands were incapable of allowing a WASI-2D based separation of macrophytes and sediment which led to erroneous water depths. Overall, the results encourage further research on lakes with varying optical properties and trophic states with Sentinel-2A.