Eutrophication state in the Eastern China based on Landsat 35-year observations

Eutrophication of the eastern plain lake (EPL) region has a significant impact on the sustainable economic development and is closely related to the shortage of water resources in China. Remote sensing provides an effective tool for quantifying the trophic state of inland waters by associating the trophic state index (TSI) with optically active water quality parameters. However, limited by the satellite coverage range and operation time, the long-term changes in the trophic state of the EPL region have not been thoroughly investigated. This study aims to fill this gap by generating a 35-year (1986-2020) TSI dataset of lakes in the eastern plain based on Landsat images. The TSI inversion algorithm based on the algal biomass index (ABI) was designed for Landsat series after consistency analysis. The seasonal variations of the TSI showed the highest TSI (62.0 +/- 11.4) in summer and the lowest TSI (51.6 +/- 8.0) in winter, with uncertainties caused by the limitation of ABI for extremely turbid waters and the number of Landsat seasonal images. The TSI of the EPLs increased over the past 35 years by about 8.2%. Four change patterns were defined for the long-term interannual TSI variations: increasing trend less than 50% (Mode 1) or more than 50% (Mode 2), breaking points that show a surge trend (Mode 3), and decreasing trend (Mode 4). The contribution of meteorological and anthropogenic factors was calculated using a generalized linear model, which revealed that the eutrophication of inland lakes in the EPL region is mainly affected by industrial wastewater discharge and urban expansion. The influence of these explanatory variables becomes more complex with an increase in lake area. Our research provides an estimation of the TSI for the first 35-year basin-scale in the EPL region and a comprehensive evaluation of the driving factors of inland water eutrophication. The results can be used for the effective management and restoration of lakes.