Hiruy Abdu

Geophysical imaging of watershed subsurface patterns and prediction of soil texture and water holding capacity

work we show how EMI can be used to image the subsurface of a � 38 ha watershed. We present an imaging approach using kriging to interpolate and sequential Gaussian simulation to estimate the uncertainty in the maps. We also explore the idea of difference ECa mapping to try to exploit changes in soil moisture to identify more hydrologically active locations. In addition, we use a digital elevation model to identify flow paths and compare these with the ECa measurement as a function of distance. Finally, we perform a more traditional calibration of ECa with clay percentage across the watershed and determine soil water holding capacity (SWHC). The values of SWHC range from 0.07 to 0.22 m 3 m � 3 across the watershed, which contrast with the uniform value of 0.13 derived from the traditional soil survey maps. Additional work is needed to appropriately interpret and incorporate EMI data into hydrological studies; however, we argue that there is considerable merit in identifying subsurface soil patterns from these geophysical images.

Electromagnetic induction mapping at varied soil moisture reveals field-scale soil textural patterns and gravel lenses

Knowledge of the spatial distribution of soil textural properties is important for determining soil moisture storage and soil hydraulic transport properties. Capturing field heterogeneity without exhaustive sampling and costly sample analysis is difficult. Our objective was to employ electromagnetic induction (EMI) mapping in low apparent electrical conductivity (ECa) soils at varying soil water contents to capture time invariant properties such as soil texture. Georeferenced ECa measurements were taken using a ground conductivity meter on six different days where volumetric water content (θv) varied from 0.11 to 0.23. The 50 m × 50 m field included a subsurface gravelly patch in an otherwise homogeneous silt-loam alluvial soil. Ordinary block kriging predicted ECa at unsampled areas to produce 1-m resolution maps. Temporal stability analysis was used to divide the field into three distinct ECa regions. Subsequent ground-truthing confirmed the lowest conductivity region correlated with coarse textured soil parent materials associated with a former high-energy alluvial depositional area. Combining maps using temporal stability analysis gives the clearest image of the textural difference. These maps could be informative for modeling, experimental design, sensor placement and targeted zone management strategies in soil science, ecology, hydrology, and agricultural applications.