The simple case study has shown that the improved niched Pareto genetic algorithm (INPGA) is applicable to multiobjective optimal design of groundwater remediation system due to the simple procedure, the efficient computation, as well as the rational span of the Pareto solutions. However, the acceleration and efficiency of INPGA based on the message passing interface (MPI) is comparatively low for the simple application. To further demonstrate the applicability and usefulness of INPGA coupled with the MPI for parallel computing and the operation library of individual fitness under real field conditions, accordingly, an application project was conducted at the Massachusetts Military Reservation (MMR) in Cape Cod, Massachusetts, involving the multiobjective optimal design of a groundwater pump and treat system. The results of this study show that not only would it be possible using MPI to improve the parallel acceleration and efficiency, but also a nearParetofront tradeoff curve could be achieved by providing enough Pareto solutions to decisionmakers. This field application clearly demonstrates the attractive prospect of MPIbased INPGA in identifying multiobjective optimal design of groundwater remediation systems.