Abstract
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 (aCDOM(440)), backscattering and concentration of suspended particulate matter (SPM) in optically deep water; water depths, bottom substrates and aCDOM(440) were modelled in optically shallow water. In deep water, SPM and aCDOM(440) showed reasonable spatial patterns. Comparisons with in situ data (mean: 0.43 m−1) showed an underestimation of S2-A derived aCDOM(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 (~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.
Highlights
The monitoring of lake water quality is gaining increasing importance due to an increase in stressors such as climate change, eutrophication, contamination of organic and inorganic substances, and anthropogenic influences which threaten ecological functions [1,2]
Clean Water Act [5] include regular monitoring schemes that observe the ecological states of lakes and detect changes which may influence lake ecology and water quality [6]
A common approach is to compare suspended particulate matter (SPM) mass concentrations derived from water samples with concentrations derived from remote sensing algorithms [10]
Summary
The monitoring of lake water quality is gaining increasing importance due to an increase in stressors such as climate change, eutrophication, contamination of organic and inorganic substances, and anthropogenic influences which threaten ecological functions [1,2]. To assess the performance of SPM and aCDOM (440) retrieval, we compared WASI-2D values with concentrations and backscattering or absorption coefficients from in situ measurements (Table 2). Common approach is to compare SPM mass concentrations derived from water samples with. A common approach is to compare SPM mass concentrations derived from water samples with concentrations derived from remote sensing algorithms [10]. The resulting map revealed reasonable spatial patterns with sandy sediment predominating along the south-eastern shoreline close to ”Seeshaup” (Figure 8d). Atalong the northern end of the lake, calculated depths rarely exceeded sandy the south-eastern shoreline close water to ”Seeshaup” 8d).
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