Analysis of subsurface contaminant migration and remediation using high performance computing

Highly resolved simulations of groundwater flow, chemical migration and con taminant recovery processes are used to test the applicability of stochasti c models of flow and transport in a typical field setting. A simulation dom ain encompassing a portion of the upper saturated aquifer materials beneath the Lawrence Livermore National Laboratory was developed to hierarchically represent known hydrostratigraphic units and more detailed stochastic repr esentations of geologic heterogeneity within them. Within each unit, Gaussi an random field models were used to represent hydraulic conductivity variat ion, as parameterized from well test data and geologic interpretation of sp atial variability. Groundwater flow, transport and remedial extraction of t wo hypothetical contaminants were made in six different statistical realiza tions of the system. The effective flow and transport behavior observed in the simulations compared reasonably with the predictions of stochastic theo ries based upon the Gaussian models, even though more exacting comparisons were prevented by inherent nonidealities of the geologic model and how syst em. More importantly, however, biases and limitations in the hydraulic data appear to have reduced the applicability of the Gaussian representations a nd clouded the utility of the simulations and effective behavior based upon them. This suggests a need for better and unbiased methods for delineating the spatial distribution and structure of geologic materials and hydraulic properties in field systems. High performance computing can be of critical importance in these endeavors, especially with respect to resolving transp ort processes within highly variable media. (C) 1998 Elsevier Science Limit ed. All rights reserved.