Cost-effective long-term groundwater monitoring design using a genetic algorithm and global mass interpolation

new methodology for sampling plan design has been developed to reduce the c osts associated with long-term monitoring of sites with groundwater contami nation. The method combines a fate-and-transport model, plume interpolation , and a genetic algorithm to identify cost-effective sampling plans that ac curately quantify the total mass of dissolved contaminant. The plume interp olation methods considered were inverse-distance weighting, ordinary krigin g, 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% without significant loss in accuracy of the globa l mass estimates. Inverse-distance weighting was shown to be most effective as a screening tool for evaluating whether more comprehensive geostatistic al modeling is warranted. The hybrid method was effective for implementing such a tiered approach, reducing computational time by more than 60% relati ve to kriging alone.