Decision making under uncertainty in case of soil remediation.

Decisions on soil remediation are one of the most difficult management issues of municipal and state agencies. The assessment of contamination is uncertain, the costs of remediation are high, and the impacts on the environment are multiple. This paper presents a general, transparent, and consistent method for decision making among the remediation alternatives.

Uncertainty assessment for management of soil contaminants with sparse data.

In order for soil resources to be sustainably managed, it is necessary to have reliable, valid data on the spatial distribution of their environmental impact. However, in practice, one often has to cope with spatial interpolation achieved from few data that show a skewed distribution and uncertain information about soil contamination. We present a case study with 76 soil samples taken from a site of 15 square km in order to assess the usability of information gleaned from sparse data.