Reliably Mapping Clay Content Coregionalized with Electrical Conductivity

Abstract

Core Ideas Surface clay content was derived through a combination of clay measurements and a proximal sensor. Apparent electrical conductivity (ECa) supported reliable clay content estimation. Predictions of clay coregionalized with ECa performed well, even for one soil sample per two hectares. Understanding the spatial variability of soil texture within field soils is important due to its influence on a large number of soil and plant related processes and for site‐specific application of inputs that are crucial to crop production. It remains a problem to obtain a reliable clay content map based on a limited number of sampling locations. The objective of this study was to identify spatial variability of soil clay content and the behavior of the estimation result for different spatial resolutions of measured clay content (0–20 cm depth) in combination with a coregionalization approach using apparent electrical conductivity (ECa). In a silty loam soil, soil clay content was measured at 96 points in a 50‐m by 50‐m grid within an agricultural field. ECa was measured using a contact sensor Veris 3150. Data were analyzed with ordinary kriging and cokriging while using ECa at a shallow depth. We analyzed different sampling scenarios based on clay subsamples of 48, 24, and 12 data points distributed over the 27‐ha field. In all scenarios investigated here, the RMSE stayed in the range of 3 to 4% by using different validations, with cokriging performing constantly better than ordinary kriging. Clay content maps estimated with cokriging maintained a satisfactory precision when the sampling density was reduced to one sample per two hectares, a result that leads to the conclusion that electrical conductivity in combination with spatial coregionalization demonstrated to be a promising tool to estimate the spatial variation of clay content even at a low clay sampling density.

Effect of Macroporosity on Pedotransfer Function Estimates at the Field Scale

“…]–corn ( Zea mays L.) rotation is practiced in the particular field of this study. Ten locations of soil samples across the field were selected by considering diverse conditions with regard to soil clay content based on the clay map in this field (Reyes et al, 2018). At each site, a soil pit was dug from the surface to the 1‐m depth (20‐cm depth increment, five depths).…”

Delineating Site‐Specific Management Zones and Evaluating Soil Water Temporal Dynamics in a Farmer's Field in Kentucky

“…For obtaining maps at a fine resolution in a reasonable computing time, all variables were interpolated in a 4-m-grid. For soil texture, a cokriging analysis was previously performed by combining soil clay content with EC as (Reyes et al, 2018). Detailed steps of kriging and cokriging procedures are explained in Nielsen and Wendroth (2003).…”

“…The electrodes are configured with a Wenner array, and measurements that integrate EC over a shallow depth (~0-30 cm) and a deep depth (~0-90 cm) were obtained, defined as EC as and EC ad , respectively. More details about the EC a measurement are provided in Reyes et al (2018).…”

Geophysical methods to assess soil characteristics

“…The second challenge is to interpret that basic physical property in terms of some soil property of interest (see Table 1). For example, Reyes et al (2018) employed the geostatistical interpolation such as ordinary kriging and cokriging with the electrical conductivity data to identify the spatial variability of soil clay content at the field scale. A laboratory work by Gao et al (2013) demonstrated a relationship to calibrate the soil penetration resistance (i.e., soil strength) and the shear modulus (i.e., elastic property); their relationship was later adopted by Shin et al (2017) to predict the penetration resistance from the shear modulus deduced by acoustic to seismic method.…”

“…The third method is an emerging method based on acoustic to seismic coupling. The first two methods have been used in agriculture and soil science for both mapping soil characteristics, such as salinity and clay content, and for more detailed studies of soil processes, often related to water and solute movement (Beff et al, 2013;Binley et al, 1996;Blanchy et al, 2020b;Dahlin et al, 2014;Koestel et al, 2008;Reyes, et al, 2018;Shanahan et al, 2015;. Methods based on the analysis of seismic waves are sensitive to the elastic properties of soil but also depend on soil water status and soil compaction.…”