The contamination of the soil by heavy metals is still of great interest to environmental scientists because
of further metal mobilization and the possibility of groundwater and surface water pollution. One of the
most efficient tools for risk assessment is a combination of an ex situ column leaching experiment with
computer modeling. This paper presents the results of a chemometric treatment of data from such experiments
and describes the development of a model based on an artificial neural networks topology. The
column leaching experiments have been used to find dependencies between different physiochemical parameters
of soil and heavy metals concentrations in leachate. Investigations of three different soil types
has been found to be sufficient to create the local model of heavy metal transport within soil profile.
