Relating apparent electrical conductivity to soil properties across the north-central USA

Apparent electrical conductivity (EC_a) of the soil profile can be used as an indirect indicator of a number of soil physical and chemical properties. Commercially available EC_a sensors can efficiently and inexpensively develop the spatially dense datasets desirable for describing within-field spatial soil variability in precision agriculture. The objective of this research was to relate EC_a data to measured soil properties across a wide range of soil types, management practices, and climatic conditions. Data were collected with a non-contact, electromagnetic induction-based EC_a sensor (Geonics EM38) and a coulter-based sensor (Veris 3100) on 12 fields in 6 states of the north-central United States. At 12-20 sampling sites in each field, 120-cm deep soil cores were obtained and used for soil property determination. Within individual fields, EM38 data collected in the vertical dipole orientation (0-150 cm depth) and Veris 3100 deep (0-100 cm depth) data were most highly correlated. Differences between EC_a sensors were more pronounced on more layered soils, such as the claypan soils of the Missouri fields, due to differences in depth-weighted sensor response curves. Correlations of EC_a with clay content and cation exchange capacity (CEC) were generally highest and most persistent across all fields and EC_a data types. Other soil properties (soil moisture, silt, sand, organic C, and paste EC) were strongly related to EC_a in some study fields but not in others. Regressions estimating clay and CEC as a function of EC_a across all study fields were reasonably accurate (r² ≥ 0.55). Thus, it may be feasible to develop relationships between EC_a and clay and CEC that are applicable across a wide range of soil and climatic conditions.