Hydraulic network calibration model is to minimize the sum of the squares of the differences between the calibrated and initial pipe roughness estimates, under a set of constraints determined from a sensitivity matrix. The upgrading problem of water distribution system was put forward after the preferable network model was obtained. Radial Basis Function neural network (RBF) based on genetic algorithm (GA) was proposed to solve the model. Genetic algorithm was applied to optimize the parameters of the neural network, and overcome the over-fitting problem. Case study concludes that using Radial Basis Function neural network (RBF) based on genetic algorithm (GA) and good results were obtained.