Application of Monte Carlo Analysis to Saturated Subsurface Contamination Modelling

Abstract

The prediction and evaluation of contamination in saturated subsurface environment by using contaminant transport models is necessary to plan remedial actions at existing sites and may also be useful in siting and designing new land-based waste treatment or disposal facilities. Most models used to make such predictions assume that the system behaves deterministically. A variety of factors, however, introduce uncertainty into the model predictions. The factors include model, parameters, and geometric uncertainty. The Monte Carlo technique is used to evaluate the uncertainty, as illustrated by applying three analytical saturated subsurface contaminant transport models. The uncertainty analysis provides estimates of statistical reliability in model outputs of contaminant concentration and arrival time. Examples are provided which demonstrate that (a) confidence limits around predicted values of concentration and arrival time can be obtained, (b) the selection of probability distributions for input parameters affects the output variables, and (c) the probability distribution of the output variables can be different from that of the input variables, even when all input parameters have the same probability distribution.