Response of total suspended matter to natural and anthropogenic factors since 1990 in China's large lakes

Abstract

Total suspended matter (TSM) as a critical water quality parameter is closely linked with nutrients, micropollutants, and heavy metals threatening the ecological health of aquatic ecosystems. However, the long-term spatiotemporal dynamics of lake TSM in China and their response to natural and anthropogenic factors are rarely explored. In this study, based on Landsat top-of-atmosphere (TOA) reflectance embedded in GEE and in-situ TSM data collecting in the periods 2014–2020, we developed a unified empirical model (R2 = 0.87, RMSE = 10.16 mg/L, and MAPE = 38.37 %) to retrieve the autumn TSM of lakes at national scale. This model exhibited stable and reliable performances through transferability validation and comparative analysis with published TSM models, and was implemented to generate autumn TSM maps for large lakes (≥50 km2) across China during 1990–2020.We found that 78.03 % of large lakes with TSM < 20 mg/L were dominant in 2020 across China, and these lakes were mainly located in the plateau and mountain regions. In the first gradient terrain (FGT) and second gradient terrain (SGT), the number of lakes showing significant (p < 0.05) decreasing TSM trends increased from 1990–2004 to 2004–2020, while those with opposite directions in TSM decreased. Lakes in the third gradient terrain (TGT) exhibited the inverse quantitative change in these two TSM trends compared with the FGT and SGT. A relative contribution analysis at the watershed level indicated that the first two leading factors that control TSM significant change in the FGT were lake area and wind speed, in the SGT were lake area and NDVI, and in the TGT were population and NDVI, respectively. The impacts of anthropogenic factors on lakes are continuing, particularly in eastern China, and more efforts are needed to improve and protect the water environment in the future. Our findings might help water resource managers better grasp the current state of water quality.