Improving Map Accuracy of Soil Variables Using Soil Electrical Conductivity as a Covariate

Abstract

Accurate characterization of soil properties across a field can be difficult, especially when compounded with the diverse landscapes used for pastureland. Indirect methods of data collection have the advantage of being rapid, noninvasive, and dense; they may improve mapping accuracy of selected soil parameters. The objective of this study was to determine if the use of soil electrical conductivity (EC) as a covariate improved mapping accuracy of five soil variables across four sampling schemes and two sampling densities in a central Iowa, USA pasture. In this study, cokriging methods were compared to kriging methods for the measured soil properties of soil pH, available P and K, organic matter and moisture. Maps resulting from cokriging each of the soil variables with soil EC exhibited more local detail than the kriged maps of each soil variable. A small, but inconsistent, improvement occurred in kriging variance and prediction accuracy of non-sampled sites when cokriging was implemented. The improvement was generally greater for soil variables more highly correlated with soil EC. This work indicates that cokriging of EC with less densely and invasively collected soil parameters of P, K, pH, organic matter (OM) and moisture does not consistently and substantially improve the characterization accuracy of pasture soil variability.