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Quantifying the Influence of Uncertainty and Variability on Groundwater Risk Assessment for Trace Elements

^a Federal Institute for Geosciences and Natural Resources, Stilleweg 2, D-30655 Hannover, Germany
^b Dep. of Soil Science and Land Evaluation, Univ. of Hohenheim, D-70593 Stuttgart, Germany

Correspondence: ^* Corresponding author (sven.altfelder{at}bgr.de).

Received for publication 29 September 2006. The application of leaching models to predict field-scale heavy metal transport has been successful at several sites. Past studies involved site-specific sorption experiments to quantify the leaching process and to investigate its spatial variability. Uncertainty due to lack of knowledge was frequently ignored. Here we present a leaching model that is based on an extended Freundlich equation to describe sorption. The equation is derived on a nationwide scale and is applicable to arbitrary sites in Germany. Instead of relying on site-specific sorption experiments, it only requires information on the spatial variability of pH, organic carbon (C_org), and clay content. In addition to accounting for spatial variability, the model also considers the major sources of uncertainty influencing a leaching prediction. These sources involve uncertainty in the spatial distribution of pH, C_org, and clay content, as well as uncertainty of the extended Freundlich equation. The modeling strategy is based on a parallel soil column approach, in which a deterministic transport model is combined with a two-dimensional Monte Carlo method. The model's ability to predict downward movement is tested on two sites in Germany—a wastewater irrigation area and an area in the vicinity of a metal smelter—where cadmium leaching has been modeled previously using extended Freundlich equations derived from local sorption data. Without any parameter fitting involved, the predicted field-averaged cadmium profiles agree quite well with measured profiles in both cases.

Abbreviations: 2-D, two-dimensional • CDE, convection dispersion equation • CDF, cumulative density function • pdf, probability density functions • SCM, stochastic convective model.