KRIGING WITH CUMULATIVE DISTRIBUTION FUNCTION OF ORDER-STATISTICS FORDELINEATION OF HEAVY-METAL CONTAMINATED SOILS

Accurate delineation of contaminated soils is essential for risk asses sment and remediation. The probability of pollutant concentrations low er than a cutoff value is more important than the best estimate of pol lutant concentrations for unsampled locations in delineating contamina ted soils. In this study, a new method, kriging with the cumulative di stribution function (CDF) of order statistics (CDF kriging), is introd uced and compared with indicator kriging, It is used to predict the pr obability that extractable concentrations of Zn will be less than a cu t off value for soils to be declared hazardous. The 0.1 M HCl-extracta ble Zn concentrations of topsoil of a paddy field having an area of ab out 2000 ha located in Taiwan are used, A comparison of the CDF of ord er statistics and indicator function transformation shows that the var iance and the coefficient of variation (CV) of the CDF of order statis tics transformed data are smaller than those of the indicator function transformed data. This suggests that the CDF of order statistics tran sformation possesses less variability than does the indicator function transformation. In addition, based on cross-validation, CDF kriging i s found to reduce the mean squared errors of estimations by about 30% and to reduce the mean kriging variances by about 26% compared with in dicator kriging, This suggests that kriging with CDF of order statisti cs, which takes into account the magnitude of the deviation between an observed value z(x) and a cutoff value z(k), is a more accurate and r eliable method than is indicator kriging for estimating the probabilit y that a pollutant content is less than a cutoff value at an unsampled location.