Environmental Engineering Reference
In-Depth Information
Chapter 4
Statistical Sampling Strategies for Survey
of Soil Contamination
Dick J. Brus
Abstract
This chapter reviews methods for selecting sampling locations in con-
taminated soils for three situations. In the first situation a
global
estimate of the
soil contamination in an area is required. The result of the surey is a number or a
series of numbers per contaminant, e.g. the estimated mean concentration, median,
90th percentile, or the cumulative frequency distribution for the area as a whole.
In the second case we want more spatial detail, and interest is in the mean or
median concentration for several delineated blocks. Finally, in the third case the
aim is to construct a high resolution map of the concentrations, for instance by
geostatistical interpolation. For the first aim, design-based sampling methods, in
which locations are selected by probability sampling, are most appropriate. Several
basic sampling designs are described. Laboratory costs can be saved by bulking
soil samples. The precision of estimates can be increased by exploiting ancillary
information on variables correlated with the contaminants. For mapping purposes,
model-based sampling methods, in which locations typically are selected by pur-
posive sampling, are the best option. Examples are sampling on a centred grid,
spatial coverage sampling, and geostatistical sampling. A simple method, based on
the k-means clustering algorithm, is described for computing spatial coverage sam-
ples. For geostatistical interpolation a variogram is required. Variogram estimation
is enhanced by adding several tens of locations within short distance of the locations
of a grid or spatial coverage sample. A separate section describes sampling methods
for detecting and for delineating hot spots.
Contents
4.1 Introduction
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166
4.2 Estimating (Parameters of) the Spatial Cumulative Distribution Function
.......
167
4.2.1 Sampling Designs
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168
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