Geostatistical strategy for soil sampling: the survey and the census

A soil sampling strategy for spatially correlated variables using the tools of geostatistical analysis is developed. With a minimum of equations, the logic of geostatistical analysis is traced from the modeling of a semi-variogram to the output isomaps of pollution estimates and their standard deviations. These algorithms provide a method to balance precision, accuracy, and costs. Their axiomatic assumptions dictate a two-stage sampling strategy. The first stage is a sampling survey, using a radial gird, to collect enough data to define, by a semi-variogram, the ranges of influence and the orientation of the correlation structure of the pollutant plume. The second stage is a census of the suspected area with grid shape, sizes and orientation dictated by the semi-variogram. The subsequent kriging analysis of this data gives isopleth maps of the pollution field and the standard error isomap of this contouring. These outputs make the monitoring data understandable for the decision maker.     

Assessing soil lead contamination in Dallas Texas

During the summer of 1982, the U.S. Environmental Protection Agency conducted a comprehensive multimedia environmental monitoring program in the vicinity of two secondary lead smelters and at one reference site in Dallas, Texas. This monitoring program included a major soils investigation with the collection and analysis of over 2700 soil samples. In addition, approximately 1000 blood and 840 house dust samples were collected and analyzed for their lead content.Utilizing geostatistics and the data obtained from a portion of the soil samples, isopleths of constant soil lead concentrations within each of the three monitoring sites were identified. Presented are the soil monitoring strategy and the geostatistical techniques selected for identifying the distributions of soil lead patterns at each of the three monitoring sites. In addition, the soil sampling and analytical methods used, the sample handling and preparation procedures, and the geostatistical results obtained are identified.     

RCRA ground-water monitoring decision procedures viewed as quality control schemes

The problems of developing and comparing statistical procedures appropriate to the monitoring of ground water at hazardous waste sites are discussed. It is suggested that these decision procedures should be viewed as quality control schemes and compared in the same way that industrial quality control schemes are compared. The results of a Monte Carlo simulation study of run-length distribution of a combined Shewhart-CUSUM quality control scheme are reported.