The use of optimal remediation design can be applied to hydrodynamically contain a groundwater contaminant plume. Using a linear programming algorithm in combination with a calibrated groundwater flow model, a design that satisfies the salient design constraints while minimizing pumping and recharge is possible. The resulting pump-and-treat design can be shown to contain the plume and to reduce contaminant concentrations through integrated data and modeling analysis. The modeled optimal design is only a guide in field implementation because unanticipated practical challenges invariably are encountered. As such, the optimization formulation should consider implementation uncertainty (e.g., some wells cannot pump at design rates) by considering engineering overdesign (e.g., constrain with stronger inward gradient in particularly sensitive areas). This analysis can provide stakeholders with important information with regard to feasibility. In addition, system implementation should consider the fact that initial design is based on imperfect information and upon implementation and monitoring this information will improve dramatically. Therefore, periodic system re-optimization (on the order of five years depending on spatial scale) should be planned and be based on systematic analysis of the data (e.g., analysis of horizontal and vertical potentiometric gradients, temporal trends in water quality at monitoring pumping wells, and operation and maintenance costs).