ABSTRACT
Abundant studies are devoted to transport of contaminants by groundwater research due to the growing concerns about water quality and pollution problems in the biosphere. A variety of more or less sophisticated modelling techniques is available for the simulation of subsurface flow and contaminant transport, but reliable predictions can be made only with sufficient knowledge of the geological and hydrogeological parameters of the system. Usually, only a limited number of direct measurements of hydrogeological parameters: ‘hard data’, such as hydraulic conductivity, porosity, storativity, dispersivity, etc. exists in the form of field observations and laboratory tests, while indirect subjective or qualitative information: ‘soft information’, may be more easily available. A stochastic characterization method based on coupled Markov Chain theory is developed to quantify soft information. A hybrid approach has been developed to merge flow and transport parameters that is derived both from hard data and soft information to enhance the statistical characterization of aquifer heterogeneity.
