Topsoil Clay Content Research Articles

Identifying potential management zones in a layered soil using several sources of ancillary information

AbstractVariation in soil texture has a profound effect on soil management, especially in texturally complex soils such as the polder soils of Belgium. The conventional point sampling approach requires high sampling intensity to take into account such spatial variation. In this study we investigated the use of two ancillary variables for the detailed mapping of soil texture and subsequent delineation of potential management zones for site‐specific management. In an 11.5 ha arable field in the polder area, the apparent electrical conductivity (ECa) was measured with an EM38DD electromagnetic induction instrument. The geometric mean values of the ECameasured in both vertical and horizontal orientations strongly correlated with the more heterogeneous subsoil clay content (r = 0.83), but the correlation was weaker with the homogenous topsoil clay content (r = 0.40). The gravimetric water content at wilting point (θg(−1.5 MPa)) correlated very well (r = 0.96) with the topsoil clay content. Thus maps of topsoil and subsoil clay contents were obtained from 63 clay analyses supplemented with 117θg(−1.5 MPa)and 4048ECameasurements, respectively, using standardized ordinary cokriging. Three potential management zones were identified based on the spatial variation of both top and subsoil clay contents. The influence of subsoil textural variation on crop behaviour was illustrated by an aerial image, confirming the reliability of the results from the small number of primary samples.

Prediction of topsoil organic matter and clay content from measurements of spectral reflectance and electrical conductivity

Soil organic matter (SOM) and clay content of a soil characterized as a coarse sandy loam were modelled using hyperspectral reflectance data acquired with a spectrometer and soil electrical conductivity (SEC) data acquired with an EM38 instrument manufactured by Geonics Ltd. The partial least squares (PLS) regression method was applied and the results validated using cross validation. First, the models were calibrated using only spectral reflectance data; then EM38 data were included in the X-matrix of predictors. Although SEC is significantly correlated with clay content, the results showed that EM38 data did not improve model performance for the estimation of soil organic matter content and clay content, despite the fact that EM38 showed significant correlation with clay content.

Using radiometric data to identify æolian dust additions to topsoil of the Hillston district, western NSW

The identification and characterisation of æolian dust additions to Australian soil profiles has been attempted using a wide range of analytical techniques. Such techniques are often reliant on specialised equipment and operator expertise, but do not necessarily yield information on the spatial distribution of deposited dust across the landscape. An airborne geophysical technique which measures naturally occurring gamma-rays may now assist in the rapid assessment of dust accumulation sites at the catchment scale. This technique, known as gamma ray spectrometry or radiometrics, assesses the potassium (K), uranium (U), and thorium (Th) contents of the Earth's surface, and may potentially distinguish æolian sediments from the underlying rock or in situ developed soil profile by their differing K, U, and/or Th-bearing mineral suites. This paper summarises a study of this technique for identifying æolian dust in topsoils of the Hillston district in western New South Wales. Using airborne with follow-up ground-based radiometric data, a variable relationship was established between large K signatures and apparent topsoil dust accumulations, which were identified as containing appreciable feldspar and illite. The previously established correlation between topsoil clay content and eTh (equivalent Th) concentration was also observed in this region, indicating that the technique may allow for rapid identification of landform features with significant clay and silt enrichment, as often occurs with dust accession. Despite the ubiquity of æolian sediments in this region, the radiometric data were moderately effective in discriminating different dune systems and may therefore represent a useful initial technique for discerning likely areas of dust accumulation in this environment. However, in areas influenced by fluvial sediments, the radiometric signatures were not necessarily indicative of the topsoil dust content.

PA—Precision AgricultureSoil Tillage Resistance as a Tool to map Soil Type Differences

Abstract Precision agriculture is based on spatial knowledge of soil and crop conditions in the management decisions. In this paper, a method to improve determination of soil physical properties is proposed. Current practice is to analyse soil samples, taken at several locations in a field, for physical properties. To obtain a sound coverage, many soil samples have to be analysed. When soil properties are correlated, it is possible to reduce the number of soil samples of one property and enhance its spatial resolution with the information of another, more densely sampled, property. In this study, information gathered automatically during the major soil tillage operation, ploughing, is used to improve the spatial resolution of sampled topsoil clay content. Plough draught was measured during two seasons on a 6 ha field. The specific plough draught varied between 30 and 50 kNm −2 . Clay content varied between 6 and 22% and topsoil moisture content range was 120–240 g kg −1 during the first year and 180–300 g kg −1 in the second year. The specific plough draught maps of both years showed a similar spatial pattern with a cross correlation coefficient at zero distance of 0·6. The use of specific plough draught as co-variable in the co-kriging technique made it possible to decrease the number of topsoil clay content samples from 60 to 18 ha −1 with only 20% increase in prediction error. On this field, the spatial variation in top soil clay content was correlated with the spatial variation of the crop yield.

PA—Precision Agriculture: Soil Tillage Resistance as a Tool to map Soil Type Differences

Precision agriculture is based on spatial knowledge of soil and crop conditions in the management decisions. In this paper, a method to improve determination of soil physical properties is proposed. Current practice is to analyse soil samples, taken at several locations in a field, for physical properties. To obtain a sound coverage, many soil samples have to be analysed. When soil properties are correlated, it is possible to reduce the number of soil samples of one property and enhance its spatial resolution with the information of another, more densely sampled, property. In this study, information gathered automatically during the major soil tillage operation, ploughing, is used to improve the spatial resolution of sampled topsoil clay content.Plough draught was measured during two seasons on a 6 ha field. The specific plough draught varied between 30 and 50 kNm−2. Clay content varied between 6 and 22% and topsoil moisture content range was 120–240 g kg−1during the first year and 180–300 g kg−1in the second year. The specific plough draught maps of both years showed a similar spatial pattern with a cross correlation coefficient at zero distance of 0·6.The use of specific plough draught as co-variable in the co-kriging technique made it possible to decrease the number of topsoil clay content samples from 60 to 18 ha−1with only 20% increase in prediction error. On this field, the spatial variation in top soil clay content was correlated with the spatial variation of the crop yield.

A comparison of the texture of grassland and eroded sandy soils from Shropshire, UK

In previous studies, periodic sampling of topsoils on runoff plots on sandy soils at the Hilton experimental site, Shropshire, UK, suggested erosion decreased the topsoil clay content and increased the coarse fraction. However, a comparison of soil and sediment properties suggested erosion selectively removed sand. Therefore, to cross-check the effects of erosion on soil properties, topsoil samples were collected from bare, eroded runoff plots and compared with samples from adjacent non-eroded grassland. Bare, eroded soil was stonier and particularly deficient in sand compared with grassed soil. Textural differences were very marked in the medium and coarse sands, especially the 0.5–1.0 mm fraction. On the basis of mean properties, the grassed soil was a very slightly stony loamy sand and the bare soil a slightly stony sandy loam. Soil organic matter was significantly less in the bare soils than the grassed soils and thus may have contributed to the higher erodibility of sands in bare soils.

Variation in the composition and structure of tropical savannas as a function of rainfall and soil texture along a large‐scale climatic gradient in the Northern Territory, Australia

Abstract. Variation in structural and compositional attributes of tropical savannas are described in relation to variation in annual rainfall and soil texture along a subcontinental‐scale gradient of rainfall in the wet‐dry tropics of the Northern Territory, Australia. Rainfall varies along the gradient from over 1500 mm p.a. in the Darwin region (c. 12° S) to less than 500 mm in the Tennant Creek region (c. 18° S). Soils are patchy, and sands, loams and clays may occur in all major districts within the region. We utilized a large data set (1657 quadrats ° 291 woody species; with numerous measured and derived sample variables) covering an area of 0.5 million km2. Correlations between floristic composition of woody species and environmental variables were assessed using DCA ordination and vector fitting of environmental variables. Vectors of annual rainfall and soil texture were highly correlated with variation in species composition. Multiple regression analyses incorporating linear and quadratic components of mean annual rainfall and topsoil clay content were performed on three structural attributes (tree height, tree cover, tree basal area) and two compositional attributes (woody species richness, deciduous tree species richness). Tree height declined with decreasing rainfall; cover, basal area, woody species richness and deciduous species richness all declined with decreasing rainfall and increasing soil clay content. Regression models accounted for between 17% and 45% of the variation in the data sets. Variation in other factors such as soil depth, landscape position and recent land‐use practices (for which there were no data on an individual quadrat basis) are likely to have contributed to the large residual variation in the data set.

Spatial Distribution of Soil Attributes on Reconstructed Minesoils

Mining companies and regulatory agencies need clearly defined methods by which sample data of reconstructed minesoils can be interpolated to determine the spatial distribution and suitability of minesoils for reclamation. Objectives of this study were to model spatial distributions of minesoil attributes across reconstructed landscapes at the Rosebud Mine in southeast Montana, and to evaluate geostatistical procedures that account for spatial dependence in data. Minesoils at the Rosebud Mine have been routinely sampled in an irregular pattern of 100-m sample intervals. The combined replacement depth of topsoil and subsoil material determined the depth of sampling. Topsoil and subsoil materials were analyzed separately for replacement depth, soil texture, soil pH, and electrical conductivity. Minesoil attributes in all cases were spatially independent at the 100-m sample spacing. Four soil attributes, topsoil clay content, topsoil pH, topsoil electrical conductivity, and subsoil replacement depth, were used to described the spatial relationships found in the minesoil data. Application of kriging techniques to interpolate between data points was deemed unnecessary due to the uncorrelated nature of the data and lack of reasonable fit of any semivariograms. Trend surface analysis was used to develop a model that predicts minesoil properties across the site. For topsoil clay content, pH, and electrical conductivity, a constant surface through the overall means was the best predictive model for these properties at the site. A quadratic surface was fit to replacement depth data, which exhibited a trend across the reconstructed landscape. This data set provides an example of how geostatistical techniques can be used to evaluate spatial dependence in data. In the absence of spatial dependence, more traditional satistical techniques that rely on independent data assumptions can be used, such as regression techniques.