The design of the water distribution networks is typically based on providing acceptable hydraulic performance, i.e., appropriate nodal pressure heads and pipes’ velocities. Inevitable model uncertainty such as reservoir heads, nodal demands, and pipes’ roughness, could affect network performance significantly. In the present study, a fuzzy uncertainty analysis approach is developed to handle the uncertainty of reservoir heads and nodal demands for long-term simulation, based on type-2 fuzzy logic. Furthermore, the long-term uncertainty of Hazen-Williams (HW) coefficient is also considered. A parallel genetic algorithm is developed to solve a multi-objective optimization problem for fuzzy uncertainty analysis. A modified fuzzy uncertainty analysis method is also introduced which is based on network performance indices. In this method, only a single objective optimization tool is required to calculate the least possible value of network performance under uncertainties. Maximizing this value along with minimizing the cost and maximizing hydraulic sustainability is implemented in a three-objective optimization model to find the optimal pipe diameters. A new method based on optimization and is introduced as the pressure dependent hydraulic simulator. The presented approach has successfully used to design a case study network. The results show that this method could obtain economic pipe diameters, which provide higher hydraulic performance under uncertainty.