Soil Electrical Conductivity Map Variability in Limestone Soils Overlain by Loess

Abstract

Sensors exist that allow rapid mapping of bulk soil electrical confurther research. Variation in bulk soil EC may occur ductivity (EC); however, the utility of these sensors for Kentucky producers is unknown. The purpose of this study was to assess the at spatial and temporal scales including the microscale nature and the causes of soil EC variability and to make a first assess-(variation in EC at distances or times less than the ment of its potential utility in Kentucky, particularly for fields consampling interval) and macroscale (variation in EC at taining soils derived from limestone residuum overlain by loess. Varidistances or times equal to or greater than the sampling ous geostatistical, correlation, and regression analyses were conducted interval). Errors associated with mapping procedures, at seven locations to examine EC map variability. Sensor drift and such as interpolation, are a function of measurement errors associated with changes in coulter depth were minimal. Bulk intensity and have been given considerable attention in soil EC related fairly well with clay content across locations and the literature for grid soil sampling (e.g., Mueller et al., sample dates (r 2 ϭ 0.40); however, many site-and time-specific correla-2001; Mueller and Pierce, 2003) but not EC mapping. tions were better. Clay (maximum r 2 ϭ 0.75), moisture content (maxi-It would be ideal if measurement error, microscale varimum r 2 ϭ 0.76), Ca (maximum r 2 ϭ 0.67), and Mg (maximum r 2 ϭ 0.64) were positively correlated with EC, and depth to argillic or ability, temporal variability, and errors associated with cambic horizon (maximum r 2 ϭ 0.62), depth to fragipan (maximum mapping were small and if macroscale spatial variability r 2 ϭ 0.81), and depth to bedrock (maximum r 2 ϭ 0.32) were negatively accounted for the greatest proportion of the EC variabilcorrelated with EC. A multiple-regression model (R 2 ϭ 0.70) was ity observed. developed to predict EC that included nine factors: clay, sand, soil Many of the factors governing soil EC variability are moisture, buffer pH, base saturation, Ca, soil temperature, depth to understood. The spatial and temporal variability of bulk cambic and argillic horizon, and slope. Soil EC variability was spatially soil EC is affected by the complex movement of elecstructured, and spatial patterns were stable over time; however, the trons through soil. Electrons may travel through the degree to which these patterns could be observed depended on the water in soil macropores, along the surfaces of soil minmapping procedures used. Our research suggested that EC mapping erals (i.e., via exchangeable ions), or through alternating may have utility for Kentucky farmers.

Interpreting Soil Electrical Conductivity and Terrain Attribute Variability with Soil Surveys

“…They were large for slope because slope phase was an important factor for soil mapping and perhaps the most easily observed feature. The first-order OLS F-values for EC values were fairly sizable because studies have shown that important taxonomic factors vary with EC such as topsoil thickness, depth to fragipan, drainage and clay content (Doolittle et al, 1994;Kravchenko et al, 2002;Mueller et al, 2003). The F-values for plan and profile curvature and aspect DFN were relatively small, consistent with the poor relationships observed between these variables and first-order soil mapping units (e.g., Figure 3).…”

“…In another Kentucky study, shallow EC increased as depth to the fragipan horizon surface decreased under dryer (r 2 ¼ 0.81) but not wetter (r 2 ¼ 0.11) conditions (Mueller et al, 2003). A similar relationship was not apparent in this (Table 4) potentially because the EC data for the Calloway County field were collected in March of 2001 when the soils were fairly wet.…”

“…Many properties important in the development of soil surveys are also are related to bulk soil electrical conductivity (EC) measurements including soil water content (Kachanoski et al, 1988), salinity (Rhoades and Ingvalson, 1971), cation concentrations (McBride et al, 1990), clay content (Williams and Hoey, 1987), depth of sand deposition (Kitchen et al, 1996), topsoil thickness (Doolittle et al, 1994), depth to fragipan (Mueller et al, 2003), depth to bedrock (Mueller et al, 2003), and drainage (Kravchenko et al, 2002). Soil survey map unit delineation also depends on factors that relate to terrain attributes (e.g., elevation and its derivatives) such as A-horizon depth (Moore et al, 1993), depth of silty clay loam surface horizons (Bourennane et al, 1996), soil organic carbon (Bell et al, 1995), depth to carbonates (Bell et al, 1995), soil texture (Bell et al, 1995), and soil drainage (Bell et al, 1992).…”

Soil Apparent Electrical Conductivity (ECa) as a Means of Monitoring Changesin Soil Inorganic N on Heterogeneous Morainic Soils in SE Norway During Two Growing Seasons

“…The contrasting effect of low temperature and high content of soil organic matter in the one replicate block was thus less important for the results. Mueller et al (2003) also suggested that other soil properties (e.g. soil particle size) masked the effect of soil temperature on EC a in their experiment.…”

“…EM H , EM V , soil water content and temperature were considered as sensor variables, and the best model was sought. The measurements of EC a (EM H and EM V ) were both 'true' sensor variables, whereas soil water content and temperature were considered as hypothetical sensor variables, since 'on-the-go' measurements of these variables are feasible (Mueller et al 2003). The variables were checked for multicolinearity by calculating the variance inflation factors (VIF).…”