During the South-to-North Water Diversion (SNWD) Project, water pollution (WP) is caused by industrial production, domestic garbage and other reasons, which may affect the role of the SNWD Project. Therefore, the WP governance project in the SNWD has become a very important social issue. Based on this, this paper studied the effect of WP prevention and control project of the SNWD Project, evaluated the water quality of the H section of the eastern route of the SNWD Project, proposed a prediction method of WP prevention and control effect based on machine learning (ML), and evaluated the water quality in the SNWD Project by combining the water quality index evaluation standard and fuzzy logic system. The results showed that the average absolute error of WP control effect prediction method was about 0.16, and the root mean square error was about 0.25. This method had certain accuracy. The water quality in the H section of the eastern route of the SNWD Project after prevention and control was good. The WP prevention and control project in the SNWD Project has played its due role, but there is still room for improvement.

Ken Lodewyk. Evaluation of Water Pollution Prevention and Control Project in the South-to-North Water Diversion Project Based on Machine Learning. Water Pollution Prevention and Control Project (2021), Vol. 2, Issue 4: 52-61. https://doi.org/10.38007/WPPCP.2021.020406.

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