Identification of Parameter Importance for Benzene Transport in the Unsaturated Zone Using Global Sensitivity Analysis
Abstract. One of the greatest threats to groundwater is contamination from fuel derivatives. Benzene, a highly mobile and toxic fuel derivative, can easily reach groundwater from fuel sources and lead to extensive groundwater contamination and drinking water disqualification. Modelling benzene transport in the unsaturated zone can provide quantification of the risk for groundwater contamination and needed remediation. Yet, characterization of the problem is often complicated, due to typical soil heterogeneity and numerous unknown site and solute parameters, as well as the difficulty in distinguishing important from non-important parameters, resulting in high uncertainty. Thus, the application of sensitivity analysis (SA) methods, such as global SA (GSA), is required to reduce uncertainty and detect important parameters for groundwater contamination, mitigation, and remediation. Nevertheless, studies devoted to identification of the driving parameters for fuel derivatives transport in the unsaturated zone are scarce. Here, we performed GSA on a problem of benzene transport in the unsaturated zone. First, a simple GSA ‘Morris’ screening method was used for a homogenous sandy vadose zone. Then, a more computationally-demanding ‘Sobol’ variance-based GSA was run on the most influential parameters. Finally, the ‘Morris’ method was tested for a heterogeneous medium containing clay layers. To overcome the problem of model crashes during GSA, several methods were tested for imputation of missing data. The GSA results found benzene degradation rate (λk) to be the utmost influential parameter controlling benzene mobility. The depth of aquifer followed in importance in the homogenous media, while in the heterogeneous media parameters related to the clay layers, such as clay adsorption coefficient and the number of clay layers, followed in importance. The study emphasizes the significance of λk and the presence of clay layers in predicting aquifer contamination. The study also strengthen the importance of heterogenous media representation in the GSA, since different parameters control the transport in different soil layers. Overall, GSA is demonstrated here as an important tool for the analysis of transport models. The results also show that in higher dimensionality models, the radial basis function (RBF) is an efficient surrogate model for missing data imputation.
Viewed (geographical distribution)