COMBINED GEOPHYSICS AND DOUBLE-RING INFILTRATION TESTS ESTIMATE SPATIAL DISTRIBUTION OF INFILTRATION RATES IN WETLAND SOILS

Quantifying soil water infiltration rates at a field scale is important in assessing water storage and nutrient retention functions of restored wetlands. In situ measurements of infiltration rates, however, do not capture their spatial variation, which depends on the soil texture, mineralogy, and biochemical composition. In this research, the spatial variation in infiltration rates was characterized at a restored wetland in Northwest Ohio using a combination of geophysical methods and multiple double-ring infiltration tests. We first characterized the site using multiple 2D transects of electrical resistivity imaging (ERI) validated with soil cores to delineate the stratigraphic units at the site, while electromagnetic imaging (EMI) was used to determine the spatial distribution of soil bulk apparent conductivity (σ_b). A SuperSting R8 resistivity meter with 84 electrodes spaced every 0.5 m was used to acquire ERI data using a dipole-dipole configuration, while the EMI data were acquired using a Geonics EM38-MK2 in both vertical and horizontal modes. Double-ring infiltrometer tests were conducted at nine locations with contrasting bulk electrical conductivity by measuring the infiltrating water volume with time in the inner ring while keeping water levels in the outer ring constant. The infiltration rate–time plot was used to estimate the soil saturated hydraulic conductivity (K_sat). A least-squared linear regression model was used to assess the correlation between the estimated soil saturated hydraulic conductivity (K_sat) from the infiltration test and bulk electrical conductivity (σ_b). Using a leave-one-out model validation technique, we used the linear regression model between K_sat and σ_b to predict K_sat based on measured σb. Results of this study showed a topsoil with a thickness of about 1.5 m overlying a 7 m thick till. Areas with higher σ_b values correspond with lower K_sat values, following an inverse correlation with a coefficient of determination (R²) value of 0.8. Further studies will examine the impact of soil properties, including texture, moisture, and organic matter, on the distribution of σ_b and K_sat values. We will also develop a petrophysical model accounting for the effect of formation factor and surface conduction on the relationship between σ_b and K_sat.