Probabilistic sensitivity analysis for one-dimensional contaminant transport in the vadose zone

A reliability algorithm is coupled to a van Genuchten model-based unsaturated flow and transport numerical solution to develop a probabilistic model of one-dimensional non-reactive and reactive contaminant transport in the vadose zone. The reliability approach provides two important quantitative results: an estimate of the probability that a contaminant concentration is exceeded at some time and location, and a probabilistic sensitivity measure which quantifies the relative importance of each uncertain variable to the probabilistic outcome. The method requires that each uncertain variable be assigned at least a mean and standard deviation but marginal distributions and correlation structure may be incorporated. Transport through an idealized soil column with fixed boundary conditions and constant source concentration is analyzed. The uncertain variables include the van Genuchten model shape parameters, the saturated and residual water contents, saturated hydraulic conductivity, dispersivity, dispersion coefficient, first-order decay terms, bulk density and partitioning coefficient. The objective is to examine the relative importance of each uncertain variable and marginal distributions assigned to each variable. The influence of correlation structure is not considered in this study. Results indicate that the probabilistic outcome is generally very sensitive to likely changes in the saturated water content. Uncertainty associated with the diffusion coefficient, residual water content and first-order decay coefficients is often not a significant issue with respect to the probabilistic outcome; thus, these variables may be treated as deterministic constants. Although these results are limited by the assumptions of the numerical code and by the conceptual setup of the idealized soil column, they provide insight into the critical issues to consider in a probabilistic analysis of contaminant transport in the vadose zone. Such information concerning the most important uncertain parameters can be used to guide field and laboratory investigations.