Chlorophyll-a (Chl-a) concentrations are usually measured as the proxy of phytoplankton biomass and used to evaluate the trophic status of inland waters. Based on 49 in situ samples taken from two measurement campaigns in Lake Hongze in 2016, we evaluate the performance of five Chl-a estimation algorithms (including the band ratio, three-band, FLH algorithm, MCI, and UMOC algorithms). The results showed that the UMOC model was the most suitable model for the estimation of Chl-a in Lake Hongze. The mean relative error (MRE) of UMOC was 32.30%, much lower than the band ratio algorithm (75.17%), three-band algorithm (62.44%), FLH algorithm (45.87%), and MCI algorithm (56.95%). The best-performing UMOC model was applied to the atmospherically corrected 689 MERIS images between 2002-2012 and long time series MERIS Chl-a concentration estimation products were acquired. Between 2002 and 2012, the mean Chl-a concentration in Lake Hongze was 19.560 mg·m-3 with substantial spatial and temporal variability. Based on the variability of monthly mean Chl-a concentrations in each pixel, the Lake Hongze waterbody was divided into three water types, Region A, Region B, and Region C. The annual mean Chl-a concentrations of Region B and Region C showed no significant changes, while the concentrations in Region A increased markedly. The analysis of the meteorological factors showed that the fluctuations of the annual mean Chl-a concentrations in Region B and Region C were mainly affected by annual precipitation, suggesting that the Chl-a concentrations of these two regions are dominated by the intensity of the lake flow. The annual mean Chl-a concentrations of Region A showed a strong negative correlation with the annual mean wind speed. The descending trend of the annual wind speed may enhance the eutrophication degree of this region, threatening the safety of the water quality of the South-North Water Transfer Project. The Chl-a concentrations showed a strong positive correlation with the distance from the Huaihe Estuary in the wet season suggesting that the Huaihe River has an obvious inhibitory effect on algal biomass in Lake Hongze during this period.
Keywords: Climate Change; Huaihe River; Lake Hongze; MERIS; chlorophyll-a; spatial-temporal variation.