Water environment is an important basis for urban development, which directly affects all aspects of people’s production and life. However, with the improvement of people’s living standards and the acceleration of urbanization, the water crisis has also become one of the focuses of social attention. In recent years, water pollution incidents have occurred frequently, causing serious environmental pollution and ecological damage, and the environmental situation is not optimistic. In the face of this situation, the government attaches great importance to strengthening the treatment of water pollution. However, due to the lack of scientific and effective management methods, its effect is not ideal, and even has a growing trend, which affects the sustainable use of water resources and restricts economic development and social progress. Therefore, how to realize the coordination and unification between water quality safety and environmental protection has become an urgent problem to be solved in this era. Data mining is a new method based on this demand. It can provide people with relevant information accurately and timely to guide decision-making to a certain extent, thus improving the operation efficiency of water treatment system and reducing the loss caused by human factors, which has brought great convenience to human survival, life and other aspects. This paper analyzed and studied the current situation of urban water environment. Through data analysis, the deficiencies and causes were found, and corresponding countermeasures were proposed to prevent and control pollution, so as to promote the healthy and orderly development of the water environment. The original water pollution prevention and control system was compared with the optimized prevention and control model based on data mining theory. The results showed that the use of artificial intelligence technology to monitor and manage the water quality can not only improve the management efficiency but also ensure the accuracy of the water quality monitoring results. The treatment cost was also reduced by about 24.03%. It can be seen that data mining has certain advantages in solving urban water pollution problems, providing people with a new way of thinking and making people have more confidence in improving environmental quality. 

Diana Raufelder. Data Mining Water Pollution Prevention Project. Water Pollution Prevention and Control Project (2020), Vol. 1, Issue 4: 41-50. https://doi.org/10.38007/WPPCP.2020.010405.

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