ASTM D5923-96e1
(Guide)Standard Guide for Selection of Kriging Methods in Geostatistical Site Investigations
Standard Guide for Selection of Kriging Methods in Geostatistical Site Investigations
SCOPE
1.1 This guide covers recommendations for selecting appropriate kriging methods based on study objectives, exploratory data analysis, and analysis of spatial variation.
1.2 This guide considers commonly used forms of kriging including ordinary kriging, simple kriging, lognormal kriging, universal kriging, and indicator kriging. Multivariate, space-time and other less-frequently used kriging methods are not discussed; however, this is not intended to reflect any judgement as to the validity of these methods.
1.3 This guide describes conditions for which kriging methods are not appropriate and for which geostatistical simulations approaches should be used.
1.4 This guide does not discuss non-geostatistical alternatives to kriging such as splines or inverse-distance techniques.
1.5 This guide does not discuss the basic principles of kriging. Introductions to geostatistics and kriging may be found in numerous texts including Refs (1), (2), and (3). A review of kriging methods is given in (4).
1.6 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use.
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Designation: D 5923 – 96
Standard Guide for
Selection of Kriging Methods in Geostatistical Site
Investigations
This standard is issued under the fixed designation D 5923; the number immediately following the designation indicates the year of
original adoption or, in the case of revision, the year of last revision. A number in parentheses indicates the year of last reapproval. A
superscript epsilon (e) indicates an editorial change since the last revision or reapproval.
e NOTE—Paragraph 1.7 was added editorially October 1998.
INTRODUCTION
Geostatistics is a framework for data analysis, estimation, and simulation in media whose
measurable attributes show erratic spatial variability yet also possess a degree of spatial continuity
imparted by the natural and anthropogenic processes operating therein. The soil, rock, and contained
fluids encountered in environmental or geotechnical site investigations present such features, and their
sampled attributes are therefore amenable to geostatistical treatment. Kriging methods are geostatis-
tical techniques for spatial estimation belonging to the class of least-squares estimators. This guide
reviews criteria for selecting a kriging method, offering direction based on a consensus of views
without recommending a standard practice to follow in all cases.
1. Scope 1.7 This guide offers an organized collection of information
or a series of options and does not recommend a specific
1.1 This guide covers recommendations for selecting appro-
course of action. This document cannot replace education or
priate kriging methods based on study objectives, exploratory
experience and should be used in conjunction with professional
data analysis, and analysis of spatial variation.
judgment. Not all aspects of this guide may be applicable in all
1.2 This guide considers commonly used forms of kriging
circumstances. This ASTM standard is not intended to repre-
including ordinary kriging, simple kriging, lognormal kriging,
sent or replace the standard of care by which the adequacy of
universal kriging, and indicator kriging. Multivariate, space-
a given professional service must be judged, nor should this
time and other less-frequently used kriging methods are not
document be applied without consideration of a project’s many
discussed; however, this is not intended to reflect any judge-
unique aspects. The word “Standard” in the title of this
ment as to the validity of these methods.
document means only that the document has been approved
1.3 This guide describes conditions for which kriging meth-
through the ASTM consensus process.
ods are not appropriate and for which geostatistical simulations
approaches should be used.
2. Referenced Documents
1.4 This guide does not discuss non-geostatistical alterna-
2.1 ASTM Standards:
tives to kriging such as splines or inverse-distance techniques.
D 653 Terminology Relating to Soil, Rock, and Contained
1.5 This guide does not discuss the basic principles of
Fluids
kriging. Introductions to geostatistics and kriging may be
2 D 5549 Guide for Report Geostatistical Site Investigations
found in numerous texts including Refs (1), (2), and (3). A
D 5922 Guide for Analysis of Spatial Variation in Geostatis-
review of kriging methods is given in (4).
tical Site Investigations
1.6 This standard does not purport to address all of the
D 5924 Guide for the Selection of Simulation Approaches
safety concerns, if any, associated with its use. It is the
in Geostatistical Site Investigations
responsibility of the user of this standard to establish appro-
priate safety and health practices and determine the applica-
3. Terminology
bility of regulatory limitations prior to use.
3.1 Definitions of Terms Specific to This Standard:
3.1.1 additivity, n—a mathematical property of a regional-
1 ized variable stating that it can be combined linearly in order to
This guide is under the jurisdiction of ASTM Committee D-18 on Soil and
define a similar variable on a larger support.
Rock and is the direct responsibility of Subcommittee D18.01 on Surface and
Subsurface Characterization.
Current edition approved April 10, 1996. Published June 1996.
2 3
The boldface numbers in parentheses refer to a list of references at the end of Annual Book of ASTM Standards, Vol 04.08.
the text. Annual Book of ASTM Standards, Vol 04.09.
Copyright © ASTM International, 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959, United States.
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D5923–96
3.1.2 drift, n—in geostatistics, a systematic spatial variation addition to honoring a random function model, the realizations
of the local mean of a variable, usually expressed as a may also be constrained to honor data values observed at
polynomial function of location coordinates. sampled locations.
3.1.13 smoothing effect, n—in geostatistics, the reduction in
3.1.3 estimation, n—a procedure by which the value of a
spatial variance of estimated values compared to true values.
variable at an unsampled location is predicted using a weighted
average of sample values from the neighborhood of that 3.1.14 spatial average, n—a quantity obtained by averaging
location. a regionalized variable over a finite region of space.
3.1.4 field, n—in geostatistics, the region of one-, two- or 3.1.15 support, n—in geostatistics, the spatial averaging
region over which a regionalized variable is defined, often
three-dimensional space within which a regionalized variable
is defined. approximated by a point for sample-scale variables.
3.1.16 variogram, n—a measure of spatial variation defined
3.1.5 indicator variable, n—a regionalized variable that can
as one half the variance of the difference between two variables
have only two possible values, 0 or 1.
and expressed as a function of the lag; it is also sometimes
3.1.6 kriging, n—an estimation method where sample
referred to as the semi-variogram.
weights are obtained using a linear least-squares optimization
3.2 For definitions of other terms used in this guide, refer to
procedure based on a mathematical model of spatial variability
Terminology D 653 and Guides D 5549, D 5922, and D 5924.
and where the unknown variable and the available sample
A complete glossary of geostatistical terminology is given in
values may have a point or block support.
Ref (7).
3.1.6.1 block kriging, n—a form of kriging in which the
variable to be estimated has a rectangular or possibly irregular
4. Significance and Use
one-, two- or three-dimensional support.
4.1 This guide is intended to encourage consistency and
3.1.6.2 indicator kriging, n—a form of kriging in which all
thoroughness in the application of kriging methods to environ-
data are indicator variables.
mental, geotechnical, and hydrogeological site investigations.
3.1.6.3 lognormal kriging, n—the kriging of log-
4.2 This guide may be used to assist those performing a
transformed variables followed by a back-transformation pro-
kriging study or as an explanation of procedures for qualified
cedure based on a lognormal distribution model.
nonparticipants that may be reviewing or auditing the study.
3.1.6.4 ordinary kriging, n—a form of kriging for which the
4.3 This guide encourages the use of site-specific informa-
mean of the estimated variable is an unknown constant and the
tion for the selection of an appropriate kriging method;
sample weights sum to one.
however, the quality of data, the sampling density, and site
3.1.6.5 point kriging, n—a form of kriging in which the
coverage cannot be improved or compensated by any choice of
variable to be estimated has the same support as the sample
kriging method.
data.
4.4 This guide describes conditions for which kriging or
3.1.6.6 simple kriging, n—a form of kriging for which the
particular kriging methods are recommended. However, these
mean of the estimated variable is a known constant and the sum
methods are not necessarily inappropriate if the stated condi-
of sample weights is unconstrained.
tions are not encountered.
3.1.6.7 universal kriging, n—a form of kriging in which
4.5 This guide should be used in conjunction with Guides
additional weighting constraints are introduced in order to
D 5549, D 5922, and D 5924.
account for a drift in the estimated variable.
3.1.7 kriging variance, n—the expected value of the
5. Selection of Kriging Methods
squared difference between the true value of an unknown
5.1 The following subsections describe conditions for which
variable and its kriging estimate, sometimes used as a measure
various kriging methods are appropriate. Each section corre-
of kriging precision.
sponds to a step in a geostatistical site investigation where a
3.1.8 nugget effect, n—the component of spatial variance
decision concerning the most appropriate form of kriging may
unresolved by the sample spacing including the variance due to
have to be made. Ordinary kriging is the most common form of
measurement error.
kriging and is the conventional default unless any of
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