SUPERFUND SITE CHARACTERIZATION USING NONPARAMETRIC VARIOGRAM MODELING

The spatial interpolation method of Kriging, originally developed for estimation of ore reserves in mining and prediction in meteorology, ha s become an important geostatical tool for assessment of contamination in Superfund site characterization. Kriging uses an estimated spatial covariance matrix, or alternatively the variogram, to find the best l inear unbiased estimate (BLUE) of contamination at an unsampled locati on. The modeling of the variogram (also called semi-variogram) is ther efore a necessary step that must be performed before using Kriging for spatial interpolation. In this paper, we propose and investigate a si mple non-parametric procedure based on ranks for variogram modeling. S ome simulated examples are used to illustrate the proposed procedure. The proposed procedure is compared with the usual method of Ordinary K riging for the Billings Smelter Superfund site data.