Mapping and Predicting Soil Properties: Theory

Abstract

The problem of assessment of distribution and variation of random subsoil properties and conditions from available sets of field and laboratory measurement is treated in detail. Distinction is made between biased and unbiased measurements as well as borehole and block data. Calibration of data sets provides the basic parameters describing the soil property and allows combining data sets from different field and laboratory tests. Once the spatial trend is fitted, residuals are then examined, taking anisotropy into account; their autocorrelation is established. These parameters then enable prediction of the means, variances, and covariances of the soil property at desired locations. Some applications of the analytical model are given in a joint paper, with respect to the St. Jean Vianney case study.