Abstract
Analysis of subsurface soil cores from the site of a field-scale groundwater remediation experiment at Dover Air Force Base, Delaware, has revealed that tetrachloroethene and trichloroethene contamination extends into an aquitard underlying a groundwater aquifer. Geostatistical inverse modeling is used to make inferences regarding the historical concentration conditions in the overlying aquifer. Because geostatistical inverse modeling is a stochastic approach, it treats parameters as jointly distributed random fields. Therefore, this approach is used to compute confidence intervals in addition to best estimates. This framework is also used to compute large numbers of conditional realizations, which are equally probable solutions given the data, and which allow for a better understanding of the form of the unknown function. Finally, a Markov Chain Monte Carlo method combined with the application of Lagrange multipliers is used to enforce concentration non-negativity.
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