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Soil Mapping

Definitions
Pedon: A three-dimensional body of soil with lateral dimensions
large enough to permit the study of horizon shapes and relations. Its area
ranges from 1 to 10 m2. Where horizons
are intermittent or cyclic, and recur at linear intervals of 2 to 7 m, the
pedon includes one-half of the cycle. Where the cycle is <2 m, or all
horizons are continuous and of uniform thickness, the pedon has an area of
approximately 1 m2. If the horizons are
cyclic, but recur at intervals >7 m, the pedon reverts to the l m
2 size, and more than one soil will usually be represented
in each cycle.
Polypedon: A group of contiguous similar pedons. The limits of
a polypedon are reached at a place where there is no soil or where the pedons
have characteristics that differ significantly.
Soil map unit: (i) A conceptual group of one to many delineations
identified by the same name in a soil survey that represent similar landscape
areas comprised of either: (1) the same kind of component soil, plus inclusions,
or (2) two or more kinds of component soils, plus inclusions, or (3) component
soils and miscellaneous area, plus inclusions, or (4) two or more kinds
of component soils that may or may not occur together in various delineations
but all have similar, special use and management, plus inclusions, or (5)
a miscellaneous area and included soils. (ii) A loose synonym for a delineation.
A map unit is a collection of areas defined and named the same in terms
of their soil components or miscellaneous areas or both. Each map unit differs
in some respect from all others in a survey area and is uniquely identified
on a soil map. Each individual area on the map is a delineation. Map units
consist of one or more components. An individual component of a map unit
represents the collection of polypedons or parts of polypedons that are members
of the taxon or a kind of miscellaneous area. A delineation of a map unit
generally contains the dominant components in the map unit name, but it may
not always contain a representative of each kind of inclusion. A dominant
component is represented in a delineation by a part of a polypedon, a complete
polypedon, or several polypedons. A part of a polypedon is represented when
the phase criteria, such as a slope, requires that a polypedon be divided.
A complete polypedon is present when there are no phase criteria that require
the subdivision of the polypedon or the features exhibited by the individual
polypedon do not cross the limits of the phase. Several polypedons of a component
may be represented if the map unit consists of two or more dominant components
and the pattern is such that at least one component is not continuous but
occurs as an isolated body or polypedon. Similarly, each inclusion in a
delineation is represented by a part of a polypedon, a complete polypedon,
or several polypedons. Their extent, however, is small relative to the extent
of the dominant component(s). Soil boundaries can seldom be shown with complete
accuracy on soil maps, hence parts and pieces of adjacent polypedons are inadvertently
included or excluded from delineations.
Soil association: A kind of map unit used in soil surveys comprised
of delineations, each of which shows the size, shape, and location of a
landscape unit composed of two or more kinds of component soils or component
soils and miscellaneous areas, plus allowable inclusions in either case.
The individual bodies of component soils and miscellaneous areas are large
enough to be delineated at the scale of 1:24,000. Several to numerous bodies
of each kind of component soil or miscellaneous area are apt to occur in
each delineation and they occur in a fairly repetitive and describable pattern.
Soil map: A map showing the distribution of soils or other soil
map units in relation to the prominent physical and cultural features of
the earth's surface. The following kinds of soil maps are recognized in the
USA: (i) soil map, detailed - A soil map on which the boundaries are
shown between all soils that are significant to potential use as field management
systems. The scale of the map will depend upon the purpose to be served,
the intensity of land use, the pattern of soils, and the scale of the other
cartographic materials available. Traverses are usually made at 400-m, or
more frequent, intervals. Commonly a scale of 10 cm = 1609 m is now used
for field mapping in the USA. (ii) soil map, detailed reconnaissance
- A reconnaissance map on which some areas or features are shown in greater
detail than usual, or than others. (iii) soil map, generalized - A
small-scale soil map which shows the general distribution of soils within
a large area and thus in less detail than on a detailed soil map. Generalized
soil maps may vary from soil association maps of a county, on a scale of
1 cm = 633 m, to maps of larger regions showing associations dominated by
one or more great soil groups. (iv) soil map, reconnaissance - A map
showing the distribution of soils over a large area as determined by traversing
the area at intervals varying from about 800 m to several kilometers. The
units shown are soil associations. Such a map is usually made only for exploratory
purposes to outline areas of soil suitable for more intensive development.
The scale is usually much smaller than for detailed soil maps. (v) soil
map, schematic - A soil map compiled from scant knowledge of the soils
of new and undeveloped regions by the application of available information
about the soil-formation factors of the area. Usually on a small scale (
1:1 000 000 or smaller).
The basic distinction between soil mapping units and soil taxa
is that the latter is an abstract concept in that it is a grouping according
to specific ranges of soil properties for purposes of scientific categorization,
whereas a soil mapping unit is a cartographic representation on a map of
the polypedons as they actually oocur in the field.
In chapter 11.1. Soil Classification the categories used in the U.S. Soil
Taxonomy were listed ranging from orders, suborders, great groups, subgroups,
families, to series. Additionally, the terms consociations, taxadjuncts,
and variants are used to describe inclusions of areas of small differences
from the main soil units. They help to define the degree of geographic purity
of soil mapping units.
Consociations: Mapped areas dominated by a single soil taxon and
similar soils. At least half of the pedons on each delineation of a consociation
are of the same soil components that supply the name for the map unit. Much
of the remainder of the mapping unit consists of soils so similar to the
named soil that major use and management interpretations are not significantly
different. Generally, the total area of dissimilar inclusions of other components
in a map unit does not exceed 15 to 25 %. A single component of dissimilar
inclusions generally does not exceed 10 % if very contrasting.
Taxadjuncts: (i) Polypedons with properties outside the range of
any recognized soil series and exceeding the higher category class limits
by one or more differentiating characteristics of the series. (ii) A soil
that is correlated as a recognized, existing soil series for the purpose
of expediency. They are so like the soils of the defined series in morphology,
composition, and behavior that little or nothing is gained by adding a new
series.
Variants: A soil with characteristics outside the limits of any
known soil series and which is less than 2000 acres in extent is classified
as a variant.
Soil surveys produced by the United States National Cooperative Soil Survey
are described as being at least 85 % pure (Soil Survey Division Staff, 1993),
although field checks suggest that the figure may be lower.
Scale Related Issues in Soil Mapping
The purpose of soil classification is to reduce a complex system of varying
soil characteristics into explicitly defined classes. Soils occur as a continuum
in nature, however, crisp classes are used to distinguish soil map units,
which differ in one or more characteristics from each other. These soil
map units are our best approximations of what we perceive to be truths.
Soil mapping scales range from coarse (small) to fine (large) scale (Table
1. and 2.).
Table 1. Soil mapping scales (Buol et al. 1997).
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Map scale
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Scale length
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national (macro scale)
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> 1500 km
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regional
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2 to 1500 km
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polypedonic
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few meters to 2 km
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pedonic (micro scale)
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< 3.5 m
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Table 2. Information of scales of soil maps and map units representing
them (Buol et al., 1997).
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Intensity of soil survey
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Range of map scale
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Corresponding area of delineation [ha]
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Syntheses
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< 1 : 1,000,000
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4030
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Exploratory
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1 : 250,000 to 1 : 1,000,000
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252 to 4030
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Low intensity
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1 : 100,000 to 1 : 250,000
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40.3 to 252
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Medium intensity
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1 : 25,000 to 1 : 100,000
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2.52 to 40.3
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High intensity
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1: 10,000 to 1 : 25,000
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0.40 to 2.52
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Very high intensity
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> 1 : 10,000
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< 0.40
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Some users of soil surveys need very specific and detailed information
about soils. For these potential users, the information needed is about
the nature of soil areas of a few hectares or less. Other users may need
only broad soil information such as areas of thousands of hectares each.
Therefore, different levels of detail are provided in the soil survey maps.
These sizes and levels of detail are arranged in classes of soil surveys
called 'orders of soil survey' (Soil Survey Division Staff, 1993). These
orders differ in kind of map units reflected in the soil survey legend as
consociations, complexes, and associations.
Table 3. Order of soil survey (Soil Survey Staff, 1993).
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Orders of soil survey
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Minimum size of delineation [ha]
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First order:
very intensive - experimental plots, building sites
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1 or less
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Second order:
intensive - general agriculture; urban planning
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0.6 - 4
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Third order:
extensive - range land, community planning
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1.6 - 16
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Fourth order:
extensive - for broad land use potential and general land
management
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16 - 252
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Fifth order:
very extensive
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252 - 4000
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References
Buol S.W., Hole F.D., McCracken R.J., and Southard R.J., 1997. Soil Genesis
and Classification. Iowa State University Press, Ames, Iowa.
Soil Survey Staff. 1993. Soil Survey Manual 18, US Govt, Printing Office,
Washington, DC.
Soil Surveys
What is a soil survey: (i) The systematic examination, description, classification,
and mapping of soils in an area. Soil surveys are classified according to
the kind and intensity of field examination. (ii) The program of the National
Cooperative Soil Survey that includes developing and implementing standards
for describing, classifying, mapping, writing, and publishing information
about soils of a specific area.
How are soil surveys carried out?
The National Cooperative Soil Survey (NCSS) is a joint effort among the
Natural Resource Conservation Service (NRCS), land-grant universities, and
other state and federal agencies with an interest in the soil resource.
Soil surveys are carried out by soil scientists with good experience in
soil descriptions and soil forming processes. Aerial photographs are used
to determine land use pattern, drainage, and some other characteristics
of the soil surface. Stereo photography is used to analyze the topographic
attributes such as elevation, slope, and slope shape. Soil data are derived
by sampling with augers or soil pit descriptions. For the development of
a detailed soil map many data have to be collected in the field for soil
classification and the delineation of the boundary for each soil map unit.
Comparisons to other soil data (e.g. nearby counties) are necessary. Finally,
digital orthophotos are used in the process to derive detailed soil maps.
Additionally, representative soil samples are analyzed in the laboratory.
Interpretations regarding the suitability of these soils for various land
uses are based on detailed understanding of soil characteristics, field
experience, and consultation with local landowners and other experts located
in the county and state.
Soil surveyors (keen observers with experience) have the ability to integrate
the soil forming factors and processes. However, the computer with appropriate
software programs is now as important a tool in soil survey as the auger,
spade, map board and color book.
Soil surveys were carried out for most of the United States. The Soil
Survey Manual provides the major principles and practices needed for making
and using soil surveys and for assembling and using data related to them.
The Manual is intended primarily for use by a soil scientist engaged in the
classification and mapping of soils and in the interpretation of soil surveys.
How to access soil
surveys?
Hardcopy soil surveys are available
from the Natural Resource Conservation Service (NRCS). Contact your closest NRCS
office. For numerous counties historical replica in digital format (pdf) are
available upon request.
Use of Soil Maps and Soil Information Systems
Soil maps and soil information systems are used for:
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Land evaluations and tax assessments
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Farm and management recommendations (e.g. fertilizer applications)
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Prediction of erosion losses
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Recommended conservation practices
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Development of productive ratings of soils
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Soil potentials
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Evaluations of sustainability in land
management
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Water quality evaluation (e.g. nutrient leaching, pesticide yield)
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Decision support systems
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Water quality simulation models (e.g. AGNPS, SWAT, GLEAMS)
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Pedotransfer functions
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Mined land reclamation
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Planning, zoning, and other land use
concerns - local, state, and regional
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Suitability of areas for septic tank filters where the areas are not served
by central sewage systems
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Suitability for municipal sewage effluent and sludge disposal
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Highway route location
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Building and real estate development site
locations
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Soil-related expert systems with included simulation models (e.g. crop
growth models)
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many more........
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Soil survey interpretation and soil information systems are prepared to
help land users, planners, policy makers, legislative officials, engineers,
and scientists to transfer technology about the use and management of soils
- both agricultural and non-farm - more accurately. The interpretations help
predict potentials, limitations, problems, and management needs for soils.
Spatial Variability of Soil Properties
Spatial variability is governed by the processes of soil formation which
are in turn interactively conditioned by lithology, climate, biology, and
relief through geologic time. Spatial variability in soil systems belongs
to two broad categories (Wilding et al., 1994):
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Systematic (structured)
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Random (unstructured and unknown causes)
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Systematic variability is a gradual or marked change in soil properties
as a function of physiography, geomorphology and interactions of soil-forming
factors. Systematic variation permits pedologists to partition spatial variability
in soils of subsets of properties that constitute soil survey map units
corresponding to geomorphic landscape elements (summit, shoulder, backslope,
etc.). Large-scale spatial variability of a systematic nature may be as
great or greater than long-range interval changes. An example of this are
shrink-swell phenomena in soils that give rise to gilgai topographic relief
variability in physical, and corresponding subsoil chemical and biological
properties at intervals of meters or less. Fine scale variability occurs
in aggregate ped units or microfabrics such as coatings of clay along void
surfaces, zonation of oxyhydroxides, and concentrations of carbonates within
the soil matrix. These distribution patterns reflect hydraulic flow, diffusion,
immobilization and microbial colonization processes at micron and submicron
scales in soil systems.
Causes of vertical and lateral anisotropy that yield spatial variability
of a random nature over short-range or intermediate distances include: differential
lithology, intensity of pedogenic weathering processes, hydrology, biological
activity, erosion, deposition and pedoturbation; temporal effects of soil
management; sampling and analytical errors. All of the above, except the
latter two, may contribute to systematic variation, but the effects may be
too subtle or complex to be discerned visibly or by measurement (Wilding
et al., 1994).
The purpose of soil surveys is to partition spatial variability of landforms
and soils. It is important to note, however, that appreciable variability
still remains in mapping units of soil series (cartographic units) used
to partition real geomorphic landscape components. Current NCSS standards
for map unit composition require at least 75 % of the soils comprising the
map unit to have similar interpretative ratings.
Magnitude of Soil Property
Variability
In Table 4 means and ranges in coefficient of variability (CV) are listed
which have been reported in the literature for a selected number of soil
properties sampled from equivalent horizons or depths within landscape mapping
units of the same soil series (Upchurch et al., 1988). While these are only
guidelines, they serve as useful indices in the absence of on-site data.
The CV's for more stable properties range from 5 to 10 %, while for the
more dynamic ones, they commonly range from 10 to 20 %, with extremes up
to 35 %. Laboratory error analysis is property dependent but commonly with
CV's less than 5 %. More permanent (stable) soil properties such as soil
texture, mineralogy soil thickness, and color are less variable than temporal
or more dynamic properties such as water content, hydraulic conductivity,
redox state, salt content, biological activity, exchangeable cations and
organic matter content. Properties which are measured and closely calibrated
to a standard (e.g. texture, color, pH, etc.) are less variable than qualitatively
accessed parameters such as soil structure, consistency, porosity, or root
abundance. It should be stressed that the spatial variability in terms of
pedological features may be significantly different from the spatial variability
in terms of some functional feature.
Table 4. Relative variability of selected soil properties sampled within
mapping units of a given soil series (Wilding et al., 1994).
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Soil property
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CV [%]
Mean
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CV [%]
Range
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Relative order of soil variability
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Bulk density
Soil color hue
Soil color value
Soil pH
Plasticity limit
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7
9
10
10
15
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5 - 13
2 - 20
4 - 12
5 - 15
5 - 28
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Least variable
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Liquid limit
A horizon thickness
Water retention (33 kPa)
Base saturation
Total sand content
Total clay content
Ca-carbonate
Soil color chroma
Depth to carbonates
Cation exchange capacity
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17
18
25
25
25
28
28
30
32
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8 - 31
8 - 31
10 - 31
17 - 33
8 - 46
10 - 61
20 - 30
15 - 50
20 - 49
20 - 40
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Moderately variable
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Depth to mottling
Organic matter content
Plasticity index
Soil thickness
Exchangable Ca
Exchangeable K
Exchangeable Mg
Water-soluble salt extract
Hydraulic conductivity
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35
39
41
43
48
57
58
48
75
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20 - 50
20 - 61
20 - 63
25 - 58
30 - 73
7 - 160
31 - 121
13 - 150
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Most variable
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Generally, the spatial variability in soils increases with the nature
of the parent materials in the following order (Drees and Wilding, 1973):
loess
glacial till
glacial outwash = glacial lacustrine sediments = alluvium
pyroclastic and tectonic rocks
drastically disturbed materials
Elemental K = Ti
Zr
Fe
Ca
No consistent trend is evident among A, B, and C horizons.
Figure 3. The relative variability of soil properties as a function of
the permanence of the property (Wilding et al., 1994).
Figure 4. The relative variability of soil properties as a function of
size of the sampling unit (Wilding et al., 1994).
Geostatistics
Geostatistics can be used to analyze the spatial variability of soil attributes.
Rationale: Two data close
to each other are more likely to have similar values than two data that
are far apart. The regionalized variable concept is the basis for geostatistics,
which states that a spatial variation of any variable might be expressed
as the sum of three components:
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a structural component, associated with a constant mean value or a polynomial
trend (deterministic component)
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a spatially correlated random component (autocorrelative component)
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a white noise or residual error term that is spatially uncorrelated.
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Regionalized variable theory is used to model the spatial dependence of
soil properties by variogram analysis, which is required for kriging (spatial
prediction). The variogram describes the degree of similarity between attribute
values at sample sites x and x+h as function of their geographical
separation or lag h. In variograms the distance between data points (x-axis)
is plotted against the semivariance (y-axis). The semivariance is computed
by the following equation:
Important to note is that variances as functions of the distance between
measured points are considered, rather than the measurements of points.
(Isaaks et al., 1989).
Figure 5. Example - Variogram: A spherical model describes the spatial
variability of the soil property. In this case there is no spatial dependence
for points which are more than 75 m apart.
Different variogram models are used to describe the spatial relationship
for different soil properties. The same soil property might show a different
spatial variability in different landscapes. For example, clay content might
show different spatial variability in a mountain landscape with steep slopes
in contrast to an alluvial landscape with low slopes. Therefore, variograms
cannot be transferred from one landscape to another without testing its
validity.
Figure 6. Digital elevation model for a field on the West Madison Research
Station, in Southern WI (Grunwald et al., 1998).
Figure 7. Cross-section showing the spatial distribution of cone index
values (penetration resistance) from a summit position (elevation 329 m) to
a lower landscape position (321 m). A variogram analysis and ordinary kriging was used
to interpolate measured cone index (Grunwald et al, 1998).
Recommended Reading
Goovaerts P. 1997. Geostatistics for
Natural Resources Evaluation. Oxford University Press, New York.
Isaaks E.H., and R.M. Srivastava. 1989. An Introduction to Applied Geostatistics.
Oxford University Press, New York.
References
Drees L.R., and L.P. Wilding. 1973. Elemental Variability within a Sampling
Unit. Soil Sci. Soc. Am. Proc. 37: 82-87.
Grunwald S., K. McSweeney, B. Lowery, and D. Rooney. 1998. Continuous
Description of Soil Attributes on a Landscape in Southern Wisconsin. Abstracts
ASA-CSA-SSSA Annual Meeting, Baltimore, Maryland, Oct. 18-22, p. 253.
Isaaks E.H., and R.M. Srivastava. 1989. An Introduction to Applied Geostatistics.
Oxford University Press, New York.
Upchurch D.R., L.P. Wilding, and J.L. Hatfield. 1988. Methods to evaluate
spatial variability: 201-229. In: Wilding L.P., and J.L. Hatfield (eds.)
- Reclamation of disturbed lands. CRC press, Boca Raton, FL.
Wilding L.P., J. Bouma, and D.W. Boss. 1994. Impact of Spatial Variability
on Interpretive Modeling. In: Bryant R.B. and R.W. Arnold - Quantitative
Modeling of Soil Forming Processes. SSSA Special Publ., No. 39: 61-75.
Soil Sampling Designs
Samples can be taken with a bucket auger and analyzed
in the field (e.g. soil color, soil structure) or in the laboratory (e.g.
Fe content, bulk density). There are two different methods for sampling:
(i) sampling at fixed depths (e.g. 30, 60, 90-cm depth), or (ii) sampling
in each horizon. Conventionally, soil sampling is carried out using different
sampling designs. Common sampling designs are:
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Grid sampling
: A grid with suitable spacing is placed on a landscape to be studied.
Sites can be selected at intersections of the grid lines or within the grid
cells. Grid sampling does provide equally spaced observations and it reveals
any systematic variation across the tract under study. The drawback in geostatistical
analysis is the equal distance between all sampling points. It should be
noted that there is no randomization associated with grid sampling, therefore,
the assumptions underlying several statistical analysis (e.g. ANOVA - analysis
of variance) can not be fulfilled.
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Random sampling:
Sample locations are selected at random, with equal probabilities of selection
and independently from each other. The rationale is to exclude any form
of bias, such as a conscious or even unconscious process of discriminatory
selection on parts of the individuals. The technique has advantages of being
statistically sound and unbiased, however, random samplings tend to cluster
spatially (nonuniform density of observations per unit area and of dispersion
of sites over the delineations) and are not likely to detect and measure
systematic variation.
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Random stratified sampling
: The area is first divided into a number of sub-regions, called strata,
and then random sampling is applied to each of the strata separately. The
sample sizes in the strata may be chosen such that the probabilities of
the locations of being sampled differ between strata.
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Transects
: Soil samples are taken along straight lines across a landscape. The spacing
between sampling points might be equal, nested, or random. Transect sampling
reveals spatial variability along a line (often downhills), however, spatial
variability in other directions is neglected.
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Target sampling:
Two or more attributes (e.g. topographic attributes such as slope, aspect,
plan or profile curvature) are used to identify homogeneous and heterogeneous
patterns. The goal is to identify 'representative sampling points'. This
is a technique which minimizes the effort (costs) and maximizes the
information content, on the assumption, that the sampling points are representative
for the total data set (study area). It should be
noted that there is no randomization associated with target sampling, therefore,
the assumptions underlying several statistical analysis (e.g. ANOVA - analysis
of variance) can not be fulfilled.
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Different sampling approaches must be used depending on the objectives,
which are strongly influenced by scale. Each experimental design has constraints
and strengths with regard to the analysis of data.
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