Impact of Probability Distribution of Hydraulic Conductivity on Groundwater Contaminant Transport

Abstract

In this study, a simple approach using effective hydraulic conductivity (Ke) 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 Ke 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 Ke were changed by the PDF and spatial variability of Kh, and the PDF of Kh 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.