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To accurately reflect the water quality of Fuyang River in Handan city, monitoring sampling and laboratory analysis of water quality were conducted, and two kinds of water quality evaluation models, the BP neural network model and the RBF neural network model, were constructed on the basis of artificial intelligence and neural network theories. Partial water quality data of surface water environmental quality standard were chosen as training samples, and the water quality monitoring data were chosen as input samples, these two water quality evaluation models were applied to assess the comprehensive water quality of Fuyang River in Handan city, the evaluation results show that the water quality grade of Fuyang River is III. And these two models are simple and convenient in application and have better practicability. And it can be seen that RBF neural network is superior to BP neural network in the network training process.