ESTIMATING THE DISTRIBUTION OF SOIL MOISTURE AND ORGANIC MATTER CONTENT IN RESTORED WETLANDS USING ELECTROMAGNETIC IMAGING

Soil moisture and organic matter contents are important soil properties for assessing nutrient retention in restored wetlands. However, characterizing their variability at a high spatial and temporal scale using routine soil sampling is insufficient, expensive, time-consuming, and invasive. Here we test the hypotheses that variation in soil moisture content (SMC) and organic matter (OM) within wetlands create changes in the soil bulk conductivity; hence, conductivity measurements from electromagnetic imaging (EMI) measurements can be used to predict their variations. This study focuses on using non-invasive EMI to predict the distribution of soil moisture content and organic matter in restored wetlands in Northwestern Ohio. In this study, we used the EM-38 MK2 conductivity meter to obtain apparent soil electrical conductivity (ECa) that covers an area of 160 km². Core samples were collected at regions of high and low ECa as observed in the geophysical investigation results. The soil samples were analyzed in the laboratory using the Loss on ignition (LOI) approach which determined the organic matter (OM), moisture content, and porosity. The measured ECa was combined with laboratory results to estimate pore water electrical conductivity ECw using Archie’s law. From this, a prediction model was generated which relates geologic properties like tortuosity (c), saturation (n) and cementation (m) exponents of the soil matrix to SMC. The model prediction results show a strong correlation of R² = 0.87 between measured SMC and predicted SMC. There was also a strong correlation of R² = 0.75 between the measured ECa and OM. Thus, this study provides geologic information of the vadose zone which helps in monitoring hydrologic properties in wetlands and extrapolating soil properties at unsampled regions.