Abstract
Common methods for measuring soil moisture disturb the soil and do not represent large areas with varying topography. We estimated volumetric water content (VWC) using apparent electrical conductivity (ECa) while comparing chisel plow tillage and no-till as well as crop rotations on a split-plot design. Weekly measurements of ECa were converted to VWC using multiple linear regression (r = 0.89, p = 0.0) with the additional variables growing degree days, elevation, clay content, and silt content using a principal component analysis. VWC and ECa were well correlated (r = 0.60, p = 2.2x10-12); with a similar percent decrease from April to October. Spring peas retained the highest predicted VWC, followed by spring barley and winter wheat. The spatial and temporal maps of moisture content provided a comprehensive view of the amount, location, and timing of volumetric water content as a function of agronomic management practices.