Based on the fuzzy optimum theory, neural network and genetic algorithm, an intelligent forecasting method for medium-and-long term runoff forecast is proposed. Firstly, a fuzzy optimum model is integrated with BP neural network to construct a new fuzzy neural network describing the complicated relations between forecast factors and runoff. The network may fall into local minimum during the training process. To overcome the shortcoming and improve training efficiency, an improved genetic algorithm, RAGA, is introduced to optimize the network weights. Finally, a case proves that the intelligent forecast methodology is efficient and has accuracy forecasting results.