Accuracy issues in electromagnetic induction sensing of soil electrical conductivity for precision agriculture

Abstract

Soil apparent electrical conductivity (EC a) has been used as a surrogate measure for such soil properties as salinity, moisture content, topsoil depth (TD), and clay content. Measurements of EC a can be accomplished with commercially available sensors and can be used to efficiently and inexpensively develop the dense datasets desirable for describing within-field spatial variability in precision agriculture. The objective of this research was to investigate accuracy issues in the collection of soil EC a data. A mobile data acquisition system for EC a was developed using the Geonics EM38 1 Mention of tradenames or commercial products is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the US Department of Agriculture. 1 sensor. The sensor was mounted on a wooden cart pulled behind an all-terrain vehicle, which also carried a GPS receiver and data collection computer. Tests showed that drift of the EM38 could be a significant fraction of within-field EC a variation. Use of a calibration transect to document and adjust for this drift was recommended. A procedure was described and tested to evaluate positional offset of the mobile EM38 data. Positional offset was due to both the distance from the sensor to the GPS antenna and the data acquisition system time lags. Sensitivity of EC a to variations in sensor operating speed and height was relatively minor. Procedures were developed to estimate TD on claypan soils from EC a measurements. Linear equations of an inverse or power function transformation of EC a provided the best estimates of TD. Collection of individual calibration datasets within each surveyed field was necessary for best results. Multiple measurements of EC a on a field were similar if they were obtained at the same time of the year. Whole-field maps of EC a-determined TD from multiple surveys were similar but not identical. There was a significant effect of soil moisture and temperature differences across measurement dates. Classification of measurement dates as hot vs. cold and wet vs. dry provided TD estimations nearly as accurate as when individual point soil moisture and temperature data were included in the calibration equation.