In order to study the influence of rainfall runoff in Baoding City on water quality of Fuhe River, based on the conventional water quality monitoring data of Fuhe River in 2019 and 2020, based on particle swarm optimization algorithm(PSO) and multi-layer perceptrons(MLP), the PSO-MLP water quality prediction model was established. PSO-MLP, MLP and one-dimensional water quality model were used for comparison and prediction respectively. The results show that the mean absolute error of PSO-MLP is reduced by 64.5%~74.7% compared with the one-dimensional water quality model. Compared with the MLP model, the mean absolute error is reduced by 6.6%-12.6%. A typical rainfall in July 2021 was selected to forecast the three control sections of Shanmamiao, Anzhou and Nanliuzhuang, which shows that PSO-MLP has stronger generalization ability and smaller prediction error, and is superior to the one-dimensional water quality model and the MLP model. The established PSO-MLP water quality prediction model of Fuhe River can accurately predict the ammonia nitrogen concentration of each section of Fuhe river 4 h in advance, with an average absolute error less than 0.3 mg/ L. It can be applied to the prediction and early warning of water pollution of Fuhe River by rainfall and runoff in Baoding urban area, and avoid rainfall runoff through the Fuhe River to affect the water quality of Baiyangdian.