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.
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).
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).
|First order: very intensive – experimental plots, building sites|
|Second order: intensive – general agriculture; urban planning|
|Third order: extensive – range land, community planning|
|Fourth order: extensive – for broad land use potential and general land management|
|Fifth order: very extensive|
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.
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.
Soil maps and soil information systems are used for:
- Land evaluations and tax assessments
- Farm and management recommendations (e.g. fertilizer applications)
- Prediction of erosion losses
- Recommended conservation practices
- Development of productive ratings of soils
- Soil potentials
- Evaluations of sustainability in land management
- Water quality evaluation (e.g. nutrient leaching, pesticide yield)
- Decision support systems
- Water quality simulation models (e.g. AGNPS, SWAT, GLEAMS)
- Pedotransfer functions
- Mined land reclamation
- Planning, zoning, and other land use concerns – local, state, and regional
- Suitability of areas for septic tank filters where the areas are not served by central sewage systems
- Suitability for municipal sewage effluent and sludge disposal
- Highway route location
- Building and real estate development site locations
- Soil-related expert systems with included simulation models (e.g. crop growth models)
- many more……..
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 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):
- Systematic (structured)
- Random (unstructured and unknown causes)
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).
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.
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:
- a structural component, associated with a constant mean value or a polynomial trend (deterministic component)
- a spatially correlated random component (autocorrelative component)
- a white noise or residual error term that is spatially uncorrelated.
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 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).
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.
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.
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:
- 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.
- 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.
- 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.
- 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.
- 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.
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.