With the development of economy, environmental problems are becoming more and more prominent, especially the water environment has received extensive attention from the society. As a new type of investment and financing model, the PPP model has obvious advantages, especially in the field of water pollution prevention and control, and has received widespread attention from the society. The purpose of this work is to study the PPP model of water pollution prevention and control engineering based on BP neural network. On the basis of in-depth study of domestic and foreign PPP model literature, combined with relevant successful PPP cases, this paper studies typical cases of water pollution control PPP projects in City A and their corresponding suggestions, identification and demonstration of PPP projects, stages of project implementation and deliver. It is recommended to set up PPP projects of "control units", implement mixed ownership of construction supervision, and adopt the method of "simultaneous projection of cities and counties". The total investment of the project is 726.1945 million yuan, which is mainly used to purchase the fixed assets of the project. Sensitivity analysis of the project shows that if the operating income decreases by 5%, the internal rate of return (IRR) of the total investment will drop to 6.72%, and if the operating cost increases by 5%, the IRR of the project will decrease. The total investment will be reduced to 7.52%.