Human activities and climate change are posing threats to the water quality of rivers in China. By using stacking machine-learning models, we simulated the monthly concentrations of various pollutants in the nation's major river basins from 1980 to 2050 based on a 16-year monitoring dataset. The results showed significant improvement in water quality, except for the concentration of total nitrogen (TN), which may be attributed to the lack of control targets and assessment systems for TN. Anthropogenic factors were found to play a bigger role than climatic and geographical drivers in determining the concentrations of TN, total phosphorus (TP), and ammonia-nitrogen (NH3-N).
Human activities and climate change threaten water quality in China's rivers. We simulated the monthly concentrations of riverine total nitrogen (TN), ammonia-nitrogen (NH3-N), total phosphorus (TP), and chemical oxygen demand (CODMn) in 613 sub-watersheds of the nation's 10 major river basins during the 1980-2050 period based on a 16-year (2003-2018) monitoring dataset using the stacking machine-learning models. The results showed that water quality improved markedly, except for the TN concentration, which was probably due to the lack of a TN control target and assessment system. Quantitative analysis indicated that anthropogenic factors were the primary controls compared with climatic drivers and geographical drivers for TN, TP, and NH3-N concentrations. On the basis of all 17 sustainable development goals (SDGs) relevant to water quality in China, the water resources, water environment, aquatic ecology and water security should be considered collectively to achieve improvements in the ecological status of China's rivers.
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