Validation of a synthetic chlorophyll index for remote estimates of Chlorophyll-a in a turbid hypereutrophic lake

摘要

Remote sensing techniques can offer powerful tools for measuring concentrations of Chlorophyll-α (chl-a), which is an important proxy for water quality. However, remote estimates of chl-a can be difficult in water bodies that have high levels of total suspended matter (TSM). In this study, we examined the applicability of the synthetic chlorophyll index (SCI) and a parameter relevant to chlorophyll pigments (H_(chl)) used in conjunction with remote-sensing data to predict chl-a concentrations (C_(chl-a)) in Taihu Lake, a highly turbid hypereutrophic lake in eastern China. We sampled water quality and surface spectral properties at 250 field stations throughout the lake over five sampling periods spanning 2 years. Because data acquired at 31 stations could not be used due to equipment failure or blue-green algal blooms, we used data acquired at the remaining 219 stations. We then randomly selected parts of the spectral properties data (N = 164) to calibrate bands used in the SCI algorithm and established cubic polynomial models to estimate C_(chl-a) with SCI and H_(chl) as the independent variables. We evaluated the accuracy of these models using data from the remaining 55 stations that were not used for calibration. Our results showed the following trends: (1) the parameter of H_(chl) performed better than SCI in estimating C_(chla) in Taihu Lake; (2) H_(chl) showed optimal performance in winter, average performance in spring, and poor performance in summer and autumn; (3) H_(chl) was appropriate for the NAP-dominant waters with high C_(TSM) and low C_(chl-a), but was not suitable for organism-dominant waters with low C_(TSM); and (4) in short, H_(chl) had limited usability in turbid and eutrophic waters.