LAUSR

Interest in soil pollution by multiple heavy metals has been growing over the last decades. However, few experiments combining numerical analyses with solute transport in layered soil can be found in the literature. Here, the retention and fate of three coexisting metal ions, Cu, Cd, and Zn, in layered soils were investigated to evaluate soil co-contamination through batch and column experiments. Results showed high amounts of Cu adsorption and retention by soils, followed by Cd and Zn. The partial concentration of Zn in effluent was greater than the input from competition adsorption and the 'snow plow effect'. These findings indicate the high potential risk of Zn and Cd groundwater pollution when Cu, Cd, and Zn co-exist in the soil. Adsorption isotherms obtained from batch experiments were well described by Freundlich equation. Breakthrough curves (BTCs) obtained from column experiments were well described by standard convection-dispersion equation (CDE) for Br, and Tow-site (TSM) and One-site models (OSM) for metals except for Zn, using the Levenberg-Marquardt nonlinear optimization algorithm. However, the parameters were poorly constrained by the available observational data due to high correlation between parameters, rather than insensitivity to model outputs. The Generalized Likelihood Uncertainty Estimation (GLUE) method did not only qualify the uncertainty of parameters for solute transport in layered medium, but estimate prediction uncertainty. Prediction bounds basically captured the observed Br, Zn and Cd BTCs, while systematically overestimated the effluent Cu concentration. Comparing with the optimization, GLUE method can improve prediction reliability of heavy metal transport in layered soils.