Uncertainties caused by soil heterogeneity play an important role in the prediction of contaminant migration. A process-based approach is shown as a method to generate better predictions of the contaminant migration in the presence of large uncertainties. The method discussed here, emphasises integrating the uncertainties throughout the entire process of predicting contaminant migration. A case study in the Netherlands provides a practical example of this approach.
A process-based approach can be applied to deal with uncertainties in the investigation of contaminant migration in heterogeneous soils. The process-based approach predicts contaminant migration based upon understanding the subsoil conditions together with the character of the contamination and is part of the concept of Flexible Emission Control (FEC). The predictions of the process-based approach are used to determine whether advanced site investigation and/or remedial measures should be carried out (Van Meurs et all., 1997). The concept of Flexible Emission Control is recently developed by GeoDelft and Grontmij. FEC is a dynamic approach of dealing with soil contamination problems.
A probabilistic approach appears to offer the best way of dealing with uncertainties caused by subsurface heterogeneities. They often make it difficult to construct a single definitive reliable geological model of the subsurface. Yet these uncertainties must be taken into account, because they affect the predictions of contaminant migration. These predictions in turn result in important decisions concerning remediative actions. This probabilistic approach can be used to create different geological models that reflect a variety of possible approximations of the subsurface reality. These alternative models are made by combining information from field measurements (boreholes, soundings, etc) with knowledge of the geological history of the area. The geological models are translated into contaminant migration models by adding parameters that are important for contaminant transport, such as adsorption and rate of biodegradation.
