Impact of Probability Distribution of Hydraulic Conductivity on Groundwater Contaminant Transport

In this study, a simple approach using effective hydraulic conductivity ( K e ) was proposed to consider the spatial variability of K , and the impact of the probability density function (PDF) of K on contaminant transport in heterogeneous soil was investigated. To analyze the impact of the PDF of K according to the spatial variability of K , non-Gaussian random fields were generated for four probability distributions (Gaussian, log-Gaussian, Weibull, and gamma), and K e was calculated from the random fields to represent the flow through heterogeneous media. Subsequently, contaminant transport analysis was easily performed by the closed-form solution, and probabilistic analysis was performed using a Monte Carlo simulation. The results show that the statistical properties of K e were changed by the PDF and spatial variability of K h , and the PDF of K h has considerable effects on the probabilistic results for contaminant transport. In particular, the PDF has a greater impact on the probabilistic results when the autocorrelation distance is smaller (i.e., highly heterogeneous soil). Therefore, the selection of the PDF of K is very important for the stochastic modeling of contaminant transport, and the gamma distribution was found to be effective in expressing the probability distribution of K .