The inability to sufficiently characterize the spatial distribution of hydraulic conductivity (K) is an obstacle to constructing reliable predictive models of ground-water flow and pollutant transport, to remediating ground-water contamination, and to effectively managing and protecting ground-water resources. In glacially derived aquifers, it is common to have low-K facies (e.g. till or lacustrine clay) juxtaposed with high-K facies (e.g. sand and gravel outwash). In the buried-valley aquifers of the western and central plains of North America, assemblages of permeable outwash facies form large and productive regional aquifer systems. Although the exact geometry of the high-K and low-K facies can only be determined by a prohibitive amount of subsurface information, conditional indicator simulation provides a way to compute a number of realizations of facies distributions that have identical spatial covariance structure and that honor available data. Running transport simulations using a large number of these realizations, and examining the central tendency and variance of simulated contaminant travel times, or the simulated contaminant pathways, can give insight into how contaminants will move through the real system. However, conditional indicator simulations require that an adequate indicator variogram model of the spatial covariance of the facies assemblage can be defined from field data, when in fact the field data are often insufficient for this purpose. The objective of the proposed research under the Research at Undergraduate Institutions Program is to determine variogram models from field data at a number of locations in a buried-valley aquifer system. Two undergraduate students will be involved in field work that will create the basis for their senior research projects. One M.S. student will be involved in the geostatistical analysis of the data. The conceptual model of a specific facies assemblage will be combined with the variogram model to crate a quantitative hydrofacies model. As we begin to catalogue quantitative facies models, we will compare them for similarities and begin to test the hypothesis that one or more archetypal quantitative hydrofacies can be developed for general types of facies assemblages in buried-valley aquifer systems.
