Soil Mapping Units Research Articles

Spatial Variability of Soil Properties, Cotton Yield, and Quality in a Production Field

Successful precision agriculture requires an understanding of spatial variability of soil properties, crop growth, and their interactions. The objectives of this study were 1) to examine the spatial variability of soil properties, cotton lint yield, and fiber quality and 2) to evaluate the spatial variability within mapping units at a production‐field scale. This research was conducted on an irrigated 49‐ha cotton field in Texas from 1998 through 2000. Samples were collected from regular 1‐ha grids, triangular, and random points. Results indicated that soil properties had stronger spatial dependence than did cotton lint yields and fiber quality. Soil properties, except nitrate (NO3 −) nitrogen (N) and Olsen phosphorus (P), were strongly spatially dependent, whereas lint yield was moderately to strongly spatially dependent. Fiber quality was moderately spatially dependent. Spatial appearance of higher yield in drier years was associated with the distribution of soil properties favoring cotton growth, including lower pH and calcium (Ca) and higher P and sand content. There were differences in the means and spatial structure parameters of the selected measurements among the three soil mapping units, suggesting the need for careful sampling design to make reasonable estimation of soil properties under a nonstationary situation. Furthermore, the spatial variability of soil properties and cotton yield were intensified under limited water supply, implying that site‐specific cotton management may be appropriate for cotton producers in the Texas high plains. Contribution of the College of Agricultural Sciences and Natural Resources at Texas Tech University Scientific J. Series Paper Number T‐4‐572.

Soil distribution in the McMurdo Dry Valleys, Antarctica

The McMurdo Dry Valleys (MDVs) are the largest ice-free area (ca. 6692 km 2) in Antarctica. Here we present a reconnaissance (scale = 1:2 million) soil map of the MDVs. The soil map units are subgroups as identified in the U.S. Department of Agriculture Soil Taxonomy. The dominant soil subgroups in the MDVs are Typic Anhyorthels (43%), Typic Haploturbels (36%), and Typic Anhyturbels (14%). Soils of the MDVs represent an evolutionary sequence that include Glacic Haploturbels/Anhyturbels on Holocene surfaces, Typic Haploturbels/Anhyturbels on late Quaternary surfaces, Typic Anhyorthels on late to mid-Quaternary surfaces, Salic Anhyorthels on mid-to early Quaternary surfaces, and Petrosalic/Petrogypsic/Petronitric Anhyorthels on Pliocene and older surfaces. Soils on silt-rich tills of Pliocene and older age generally are Typic or Salic Anhyorthels; they feature less weathering than younger soils because (i) they are derived from quartzose materials largely devoid of weatherable minerals and (ii) they have been subject to considerable wind erosion.

SPATIAL DISTRIBUTION OF SOIL PHOSPHORUS ACROSS SELECTED NEW YORK DAIRY FARM PASTURES AND HAY FIELDS

Despite concerns that traditional soil sampling strategies are insufficient for assessing risk of surface water P contamination, there is no consensus that changes to these strategies, such as spatially explicit or discrete soil sampling within a field, represent enough of an improvement to justify the added cost. We conducted a study on four fields located on two dairy farms in Delaware County, New York, to characterize the spatial variability of P, Ca, Mg, Al, and Fe within two pastures and two hay fields at a 10-m scale and to interpret soil test P distribution relative to landscape and cultural practices. Pasture P distribution was characterized by various P hot spots that may be indicative of manure deposits by grazing animals. Hay fields contained large areas with elevated P relative to the rest of the field, with high-P areas occurring mostly near the gate and road where manure applications would be most accessible. Differences in soil properties associated with different soil map units also appear to partially explain P and Fe distributions in the mixed hay field. Results from a rainfall simulation study suggest that the use of a composite sampling strategy or an average P value for an entire field can potentially mask soil test P patterns such as those in the hay fields and result in an inaccurate estimation of P losses to surface waters. However, a composite sampling strategy may give a better estimation of P losses from pastures with hot spots because of the compositing effect whereby soluble P concentrations are affected by sorption processes that are controlled by low-P sediments.

Soil physical criteria for evaluating irrigation suitability of Okija upland soil of southeastern Nigeria

Suitability of upland soils of Anigbo Okija for irrigation was assessed using soil physical criteria of texture, depth, pore type, slope percent colour and soil structure for the purpose of estimating season farming and rainy season drought. Soils were classified using Soil Taxonomy and FAO/UNESCO legend. Mapping was done based on physiographic differences. Results showed two distinct soil mapping units A1 and A2 with two suitability classes: moderately suitable (S2) and marginally suitable (S3)., based on soil erosion and topographic limitations respectively. Two capability classes were consequently identified as e and IIIe for soil mapping units A1 and A2 respectively. Soils were classified as Typic Paleudalf and correlated to FAO/UNESCO legend as Dystric Nitisol for soil mapping unit A1 and Typic Paleudult (S.T.) or Dystric Nitisol (FAO/UNESCO legend) for A2. Journal of Agriculture, Forestry and the Social Sciences Vol. 3 (2) 2005: pp.99-105

Soil/Landscape Relationships in a Mesotidal Maine Estuary

Submerged sediments represent an important component of near‐shore coastal systems. Soil scientists have begun to study subaqueous soils from a pedological perspective, and conceptualize these soils as organic or mineral materials, having the ability to support rooted plants, which are submerged by estuarine, marine, or lacustrine water for a period of time such that their pedogenesis reflects an environment dominated by submergence. The objective of this study was to describe and classify subaqueous soils of a shallow, mesotidal, Maine estuary and identify the relationship between soil properties and landscape position. A detailed bathymetric map was created for the study site using a fathometer, Global Positioning System (GPS), tide gauges, surveying equipment, and Geographic Information System (GIS) software. The bathymetric map was used to identify the slope for each landscape unit and the mean water depth above each landscape unit. Slopes in the study range from 1 to >25%. Water depths above the soil surfaces are between 0.1 and 21.0 m at mean sea level (MSL). Soil samples were collected to depths between 1.0 and 5.5 m below the soil surface using a bucket auger, McCauley peat auger, or vibracoring device. Seven soil landscape units and 10 soil map units were differentiated from one another according slope class, geomorphic position, depositional environment, and soil characteristics. Most of the soil parent materials in the estuary are fine‐textured sediments. This work is the first estuary soil survey completed in Northern New England.

Pedodiversity in an old-growth northern hardwood forest in the Huron Mountains, Upper Peninsula, Michigan

We investigated three primary causes of old-growth forest pedodiversity imposed by top-down trophic interactions, including pit and mound topography from past tree fall events, current canopy gaps from tree falls, and the influence of individual tree species on soil properties and processes. In this paper, we discuss the effects of pits, mounds, gaps, and individual tree species on pedodiversity in a single soil map unit in an old-growth northern hardwood forest. Pits and level areas had significantly greater soil organic matter, cation-exchange capacity, and exchangeable K and Ca contents than mounds. Gap subplots had significantly less cation-exchange capacity, K, Mg, and Ca compared with level areas within the contiguous forest. Base cations (K, Mg, and Ca) were significantly greater under sugar maple ( Acer saccharum Marsh.) compared with eastern hemlock ( Tsuga canadensis (L.) Carr.). Extractable P was significantly greater under yellow birch ( Betula alleghaniensis Britt.) compared with eastern hemlock. We quantified pedodiversity in an old-growth northern hardwood forest stand and single soil map unit using principal components analyses, ArcGIS, and biodiversity indices. Our results suggest that pedodiversity should be considered in soil survey and forest management.

Land suitability classification using different sources of information: Soil maps and predicted soil attributes in Jordan

Preparing large-scale soil maps, with adequate accuracy, is costly and time consuming. The low homogeneity of soil mapping units in small-scale maps limits their use for detailed planning. These limitations call for alternative approaches to support the land use planning processes. Recently, models that utilize terrain attributes derived from digital elevation models (DEM) are used to predict soil attributes. The objective of this research is to explore the accuracy of land suitability classifications derived from predicted soil attributes versus those derived from traditional soil maps. Three suitability maps were derived, one from predicted soil attributes and two from traditional soil maps (scales 1:10,000 and 1:50,000). The accuracy of the three suitability maps was verified using two methods: a set of 1469 field observations or an interpolation from these observations (Thiessen polygons). The results indicated that the accuracy of the suitability classification derived from predicted soil attributes compares favorably with the accuracy of classifications derived from traditional soil maps. The use of an interpolation between field observations provides better chance of estimating the accuracy of suitability map. The accuracy of suitability map is higher for land utilizations that tolerate wider ranges of land characteristics. The spatial distribution of the suitability classification derived from the predicted soil attributes indicated more realistic pattern. This research emphasized that the use of soil attributes derived from the prediction model provides an alternative source of soil information in areas where soil maps are not available.

Variability in topsoil texture and carbon content within soil map units and its implications in predicting soil water content for optimum workability

The ability to predict the timing of optimum soil workability depends on knowledge of the extent and structure of variability in main physical characteristics of the soil. Our objectives were to quantify the variability in texture and carbon content within soil map units in a small agriculture-dominated catchment in South-east Norway and to assess implications of variability in texture and carbon content on land management operations, using the predicted maximum water content for optimum workability as an example. Information from three different sources were used: a soil map (1:5000), a large sample grid (100 m spacing, 270 ha extent), and a small sample grid (10 m spacing, 2.25 ha extent). Readily available information on texture and organic matter content from the soil map was found to be of limited use for soil management due to broad textural classes together with deviations from the mapped main textural classes. There were significant differences in clay, silt and sand content between the different soil textural classes on the soil map. Statistical distributions within soil map units were generally either positively or negatively skewed and the coefficient of variation was intermediate, 15–50%. Most of the variation in both grids was spatially correlated. The large grid was dominated by a patchy structure, whilst the small grid showed a systematic trend with a gradual transition indicating fuzzy boundaries between map units in this catchment. The effective range for texture was 16 times larger in the large grid. Implications of variability in texture and carbon content on land management operations were assessed for the maximum water content for optimum workability (Wopt), predicted using pedotransfer functions. Wopt was usually in the same range as the water content at–100 kPa matric potential, indicating that considerable evaporation in addition to drainage is required for obtaining workable conditions in the field. The time required for obtaining the water content was estimated to about 5 days, which is longer than an average length of periods without precipitation in the area, median 3.7 days. Wopt predicted from the soil map deviated strongly from Wopt predicted from the sample grids. Comparing estimates of Wopt from the large grid with measurements in the small grid showed differences corresponding to ±2–3 days of evaporation.

Quantifying Basalt Rock Outcrops in NRCS Soil Map Units Using Landsat-5 Data

Rock outcrop places many limitations on land use. For this reason, identifying its presence in a soil map unit is as important as identifying major soils. Presently the most accurate way to determine the percentage of rock outcrop in any one soil map unit involves transecting, which is time-consuming and not practical for large areas. Remote sensing can provide more accurate data for the surveys and a tremendous time saving. Endmembers, which are spectrally unique materials selected within the scene, were chosen for rock outcrop by analyzing National Aerial Photography Program (NAPP) photography under a stereoscope. Spectral Angle Mapper (SAM) classifications were performed on Landsat data of the study area to classify vegetation and rock outcrop. Global Positioning Satellite (GPS) ground-truth data with 30-meter buffers were used to validate the rock classifications. Although it is likely the amount of rock outcrop is overestimated in the final image, additional methods could ultimately produce a successful methodology to accurately map and quantify rock outcrop.

An assessment of the accuracy of soil map of Kwara state, Nigeria.

The variability of particle size fraction, pH, organic matter, total nitrogen, available phosphorus, exchangeable Ca, Mg, Na, exchangeable acidity, effective cation exchange capacity (CEC), base saturation, extractable Fe, Mn and Zn contents within and among the three major soil mapping units delineated in Kwara State, on the Federal Department of Agricultural Land Resources (FDALR) soil map of Nigeria was examined using some statistical measures. Sand content was the least variable (Cv=10.96-15.63%), while available phosphorus was the most Variable (CV=23.91%-181.05%) property. Except for Wilk's criterion (L), all the statistical tools used (coefficient of variation (CV), intra-class correlation coefficient (PI), Relative variance (RV), and the compliment of RV (I-RV) showed that the individual mapping units are heterogeneous. The F-ratio indicated that three mapping units were significantly different for17 out of 18 properties studied. If the usefulness of a soil map is judged by the precision with which it can predict soil conditions at any point of interest within the area covered by the map, the soil map evaluated here may not be practically accurate and its utility is limited. Nigerian Journal of Soil Science Vol. 17 2007: pp. 16-23

Spatial variability of Southeastern U.S. Coastal Plain soil physical properties: Implications for site-specific management

Our objectives were to describe the field-scale horizontal and vertical spatial variability of soil physical properties and their relations to soil map units in typical southeastern USA coastal plain soils, and to identify the soil properties, or clusters of properties, that defined most of the variability within the field. The study was conducted on a 12-ha field in Kinston, NC. A 1:2400 scale soil survey had delineated three soil map units in the field: Norfolk loamy sand, Goldsboro loamy sand, and Lynchburg sandy loam. These are representative of millions of hectares of farmland in the Coastal Plain of the southeastern USA. Sixty soil cores were taken to ∼ 1-m depth, sectioned into five depth increments, and analyzed for: soil texture as percentage sand, silt, and clay; soil water content (SWC) at − 33 and − 1500 kPa; plant available water (PAW); saturated hydraulic conductivity (Ksat); bulk density (BD); and total porosity. A penetrometer was used to measure cone index (CI) at each sample location. Variography, two mixed-model analyses, and principal components analysis were conducted. Results indicated that soil physical properties could be divided into two categories. The first category described the majority of the within-field variability and included particle size distribution (soil texture), SWC, PAW, and CI. These characteristics showed horizontal spatial structure that was captured by soil map units and especially by the division between sandy loams and finer loam soils. The second class of variables included BD, total porosity, and Ksat. These properties were not spatially correlated in the field and were unrelated to soil map unit. These findings support the hypothesis that coastal plain soil map units that delineate boundaries between sandy loams versus finer loam soils may be useful for developing management zones for site-specific crop management.

Soil Geomorphological Characteristics of a Semiarid Watershed

In the marginally productive rangelands of the semiarid, southwestern USA, the maintenance of organic C (OC) is essential to the stability of the ecosystem. This study was conducted to identify landscape factors responsible for the distribution of OC in watershed soils, its loss from upland areas and subsequent transport within the stream system of a large semiarid watershed (Walnut Gulch Experimental Watershed [WGEW], Tombstone, AZ). Samples were collected along transects from the surface 5 cm of each major soil mapping unit in six subwatersheds (SW). Data were recorded for slope class, landscape position, and aspect at each of the 435 sampling points. Soil analyses consisted of: total C and OC, particle‐size distribution, water dispersible clay, pH, quantitative color, and aggregation index (AI). Sediment samples were collected from flumes at each SW outlet. These 169 bedload and 59 suspended sediment samples were analyzed identically to the soils. Soil data indicated that OC distributions in the SWs were related to parent material with significantly (p ≤ 0.05) greater contents recorded on the steeper slopes (>9%), and backslope and toeslope positions. Fewer significant correlations were identified for aspect. Soil OC was significantly (p ≤ 0.01) correlated with silt and clay contents. Organic C contents of the soils and suspended sediments averaged 11.4 and 24.0 g kg−1, respectively, giving an enrichment ratio (ER) for OC in the suspended sediments of 2.13. Bedload sediment was depleted in OC by an average ratio of 0.65 relative to the soils. The results suggest that OC is transported through this watershed predominantly as silt‐ and clay‐size materials in concentrations controlled by the soil AI.

Including Topography and Vegetation Attributes for Developing Pedotransfer Functions

With the advent of advanced geographical informational systems (GIS) and remote sensing technologies in recent years, topographic (elevation, slope, aspect, and flow accumulation) and vegetation attributes are routinely available from digital elevation models (DEMs) and normalized difference vegetation index (NDVI) at different spatial (remote sensor footprint, watershed, regional) scales. Based on the correlation of soil distribution and vegetation growth patterns across a topographically heterogeneous landscape, this study explores the use of topographic and vegetation attributes in addition to pedologic attributes to develop pedotransfer functions (PTFs) for estimating soil hydraulic properties in the Southern Great Plains of the USA. The extensive Southern Great Plains 1997 (SGP97) hydrology experiment database was used to derive these functions by using artificial neural networks. Eighteen models combining bootstrapping technique with artificial neural networks were developed in a hierarchical manner to predict the soil water contents at eight different soil water potentials (θ at 5, 10, 333, 500, 1000, 3000, 8000, and 15 000 cm) and the van Genuchten hydraulic parameters (θr, θs, α, n). The performance of the neural network models was evaluated using the Spearman correlation coefficient between the observed and the predicted values and root mean square error (RMSE). Although variability exists within bootstrapped replications, improvements (of different levels of statistical significance) were achieved with certain input combinations of basic soil properties, topography and vegetation information compared with using only the basic soil properties as inputs. Topography (DEM) and vegetation (NDVI) attributes at finer scales were useful to capture the variations within the soil mapping units for the SGP97 region dominated by perennial grass cover.

Using pedostratigraphic levels and a GIS to generate three-dimensional maps of the Quaternary soil cover and reconstruct the geomorphological development of the Montagnola Senese (central Italy)

Pedostratigraphic levels (PLs) are characteristic assemblages of soil genetic horizons, formed in materials having a similar degree of weathering, and maximum age that is estimated by correlation to benchmark soils. In a pilot area of central Tuscany several soil profiles were studied and correlated with four different PLs, attributed to the Holocene, Late and Middle Pleistocene, and Early Pleistocene. The assignment of the surveyed depth made it possible to reproduce the geographic distribution of different pedostratigraphic sequences. Pedostratigraphic sequences were then related to soil map units, to obtain their geographical distribution. The objective of this work was to use PLs in a GIS environment to generate a set of three-dimensional (3D) maps of the Quaternary soil cover, and to analyze the spatial distribution of each level during main intervals of the Quaternary. The results indicate the geographical distribution of PLs is likely related to tectonic activity throughout Pleistocene and human utilization of the land during the Holocene.

Shallow Shear Velocity and Seismic Microzonation of the Urban Las Vegas, Nevada, Basin

Las Vegas Valley has a rapidly growing population exceeding 1.5 million, subject to significant seismic risk. Surveys of shallow shear velocity performed in the Las Vegas urban area included a 13-km-long transect parallel to Las Vegas Blvd. (The Strip), and borehole and surface-wave measurements of 30 additional sites. The transect was completed quickly and economically using the refraction microtremor method, providing shear velocity versus depth profiles at 49 locations. The lowest velocities in the transect, nehrp d class, are near intrabasin faults found near Interstate 15 and Lake Mead Blvd. Calcite cementation of alluvium (a.k.a. caliche) along the Las Vegas Strip elevates Vs30 values to 500–600 m/sec, nehrp c class. Our transect measurements correlate poorly against geologic map units, which do not predict the conditions of any individual site with accuracy sufficient for engineering application. Some usda soil map units do correlate, and Vs30 predictions based on measurements of soil units match transect measurements in the transect area. Extending soil-map predictions away from the area of dense measurement coverage generally failed to predict new measurements. Further, for several test sites the predictions were not conservative, in that the soil model predicted higher Vs30 than was later measured (predicting lesser potential ground motion). Subsurface information is needed to build a Vs30 model extending predictions throughout Las Vegas Valley. A detailed stratigraphic model built by correlating >1100 deep well logs in Las Vegas predicts Vs30 better than surface maps, but again only in parts of the Valley well-measured for velocity. The stratigraphic model yields good predictions of our transect Vs30 measurements. It is less accurate, although at least conservative, when extended to sites away from the transect.

Evaluating Methods of In‐Field Soil Organic Matter Analysis

The actual content of the soil organic carbon (SOC) has to be periodically measured for soil classification and nutrient management purposes. Traditional SOC tests are relatively time consuming and costly. A rapid field test would be valuable to delineate soil map units with similar SOC to simplify the process of land evaluation while increasing precision. The objectives of this study were to develop and evaluate a new field measurement technique for the quick assessment of SOC. The new method measures the emitted CO2 concentration 3 min after treatment of the soil sample with acidic potassium (K) permanganate solution. The inorganic carbonate content of the soil is measured separately with the addition of sulphuric acid only. Carbon dioxide concentration from both procedures is measured with a portable infrared gas analyzer. The difference between the concentrations measured after the two separate reactions provide an estimate of SOC. Samples from brown forest soils (ca Hapludalf) (0.19–5.53% SOC) were used for the method development. The correlation coefficient between the SOC determined by the new method and laboratory wet combustion method content was 0.76 for the full range of SOC and 0.81 for the soil samples with less than 20% carbonate.

Large-scale Soil Maps Improved by Digital Soil Mapping and GIS-based Soil Status Assessment

A key issue of the applicability of both traditional soil maps and soil information systems (SSISs) is their accuracy. Essentially, the main practical aim of soil surveys/mapping and spatial soil information is prediction. A traditional tool of this information extension is the classical (crisp) soil map (using soil mapping units), which generally constitute the geometric basis of SSISs, too. Numerous novel methods have been developed for producing more accurate soil maps, however traditional crisp soil maps are still extensively applied, as they offer the most easily interpretable results for the majority of users. On the other hand, accuracy of this kind of soil maps can be increased in several ways: with the refinement of soil contours; with the subdivision of mapping units taking into consideration smaller, within patch inhomogeneities; and with the refinement of attribute information (more recent data, more precise measurement, up-to-date methodology, more appropriate classification etc.). The GIS adaptation of soil information originating from the 1:25,000 scale practical soil mapping of Hungary is under construction. Compilation of the Kreybig Digital Soil Information System (KDSIS) involves both its integration within appropriate spatial data infrastructure and updating with efficient field correlation, which make an inherent refinement and upgrading of the system possible. The first attempts for the field-based updating of KDSIS have been done, using field GIS technology. Processes of desktop and field reambulation of the detailed, complex, national spatial soil information system are presented in this paper.

Soil Organic Nitrogen Enrichment Following Soybean in an Iowa Corn–Soybean Rotation

Understanding soil organic N (ON) pool enrichment may help explain why rates of N fertilization required to attain maximum corn (Zea mays L.) yields are usually lower for corn following soybean [Glycine max (L.) Merr.] than for corn following corn. Our objectives were to quantify the ON pools within a 16‐ha Iowa field and to correlate those results with corn yield. Spring and fall measurements of ON content (0–15 cm soil) as amino acids (AAs), amino sugars (ASs), and NH4+ were made using samples collected between 1997 and 1999 from 10 soil map units. The chemical extraction method determined an average 87% of the total N content (n = 10 soils) as identified ON but gave reduced ON recovery from depression soils that experienced periods of water ponding. The total AA concentrations measured in May were positively correlated (r2 = 0.84, P < 0.01) with corn yield during a dry year (1997) and 7 out of 10 soils provided near maximum yields. A wetter 1999 boosted overall corn yields 6.6% but resulted in a poorer relationship between May AA concentrations and corn yield. Microbial N compounds measured (May 1997) as glucosamine, galactosamine, and ornithine were also positively correlated with corn yield (r2 = 0.84, ρ < 0.01; r2 = 0.94, P < 0.001; r2 = 0.93, P < 0.001, respectively). The ON concentration decreased during corn production from May to September 1997 an average of 367 kg N ha−1 but increased following soybean growth in 1998 by 320 kg N ha−1 The chemical extraction methodology identified soils that may not require the full amount of N fertilizer currently being applied, thus decreasing the potential for N loss to surface and ground water resources without decreasing opportunities to achieve optimum yield.

Local soil classification and comparison of indigenous and technical soil maps in a Mesoamerican community using spatial analysis

The soil classification system developed by a Purhépecha community in central Mexico was formalized, incorporating symbolic, cognitive and practical components. The soil is recognized by farmers as a three-dimensional living body, composed of earth material, air and fluids, organic matter, and living organisms including plants and animals, and organized in layers. The indigenous soil taxonomy is hierarchical, with four categorical levels, and soil classification is flexible enough to adapt to a changing social and environmental context. The local soil map units were compared to those provided by a technical soil classification of general scope (USDA soil taxonomy), using spatial analysis within a GIS environment to determine levels of cartographic correlation. The average spatial correlation at high taxonomic level, computed taking into account only the dominant soils in each map unit, is 74% for the technical–local comparison and 75% for local–technical comparison. At low taxonomic level, the average spatial correlation based on dominant soils only is 62% for the technical–local comparison and 61% for the local–technical comparison. The variable levels of spatial correlation between technical and local soil map units reflect differences in the ways both systems classify soils. However, similarities and discrepancies between making technical and local soil maps reveal complementarities. Critical is the evaluation of topsoil characteristics, as the understanding and monitoring of topsoil dynamics are fundamental for land use decision-making by farmers. Spatial correlation analysis of topsoil properties provides a good basis for collaboration between farmers and soil surveyors. Merging technical and local thinking is indispensable to formulate sustainable land management schemes.

Studies on Nutrient Distribution in Some Zambian Soils with Special Reference to Sulphur Using GIS (Geographic Information Systems) I. Total Sulphur Distribution in Major Zambian Soils

Total sulphur content of some benchmark soils was evaluated by correlating with the contents of soil organic C and amorphous oxides (Al and Fe), and the particle size distribution. An equation model to calculate the content of total soil sulphur was first obtained by regression analysis. Introducing these chemical and physical data of all the map units except for the wetlands into the equation model, the sulphur level on a national scale was estimated for each soil mapping unit in the exploratory soil map of Zambia. Second, the total sulphur content was rated into 3 classes based on the frequency distribution of the total sulphur content in the benchmark soils. Finally, the rated total sulphur content was incorporated into the national soil map database of GIS to produce a map with the total sulphur content of Zambian soils. The extent of each class was calculated and the distribution of the areas was examined in relation to rainfall and soil formation.