Affiliation:
1. The University of Toledo College of Natural Sciences and Mathematics
2. University of Minnesota College of Science and Engineering
3. The University of Toledo
Abstract
Abstract
Electromagnetic imaging (EMI) provides an efficient approach for characterizing variations in soil physicochemical properties at a high spatial resolution. While EMI has been widely used to estimate variations in soil properties in agricultural, geotechnical, and contaminated sites, limited applications have been reported for wetlands. This study assesses the use of EMI for estimating soil property distributions at a restored wetland in northwestern Ohio, USA. We acquired spatial distribution of soil apparent electrical conductivity (ECa) and apparent magnetic susceptibility (MSa) via EMI over a 162,000 m2 restored wetland using an EM-38-MK2 instrument towed behind a utility terrain vehicle equipped with a differential ground positioning system. We collected twenty-two undisturbed soil samples and analyzed them in the laboratory for soil moisture (SMC), organic matter (SOM), porosity, bulk density, and texture. A least squares linear regression model was used to compare the correlation between each soil property with measured ECa and MSa while ECa was used to predict the distribution of SMC and SOM using the statistical model validated using the leave-one-out technique. We observed strong correlations between soil texture, SMC, and SOM, and ECa with SOM showing a slightly dominant control. This study shows that ECa can predict the distribution of SMC and SOM in wetland soils to an accuracy of ~ 67–70% for these datasets. The spatial ECa patterns matched the USDA soil map for the site. This study validates the potential of extending EMI for characterizing wetland soil properties, improving sampling plans, and extrapolating soil property estimates to unsampled regions.
Publisher
Research Square Platform LLC