Abstract: A new methodology for sampling plan design has been developed to reduce the costs associated with long-term monitoring of sites with groundwater contamination. The method combines a fate-and-transport model, plume interpolation, and a genetic algorithm to identify cost-effective sampling plans that accurately quantify the total mass of dissolved contaminant. The plume interpolation methods considered were inverse-distance weighting, ordinary kriging, and a hybrid method that combines the two approaches. Application of the methodology to Hill Air Force Base indicated that sampling costs could be reduced by as much as 60 percent without significant loss in accuracy of the global mass estimates. Inverse-distance weighting was shown to be most effective as a screening tool for evaluating whether more comprehensive geostatistical modeling is warranted. The hybrid method was effective for implementing such a tiered approach, reducing computational time by more than 60 percent relative to kriging alone.