Resolving the spatial distribution of the true electrical conductivity with depth using EM38 and EM31 signal data and a laterally constrained inversion model
J Triantafilis, FAM Santos - Soil Research, 2010 - CSIRO Publishing
J Triantafilis, FAM Santos
Soil Research, 2010•CSIRO PublishingThe ability to map the spatial distribution of average soil property values using geophysical
methods at the field and district level has been well described. This includes the use of
electromagnetic (EM) instruments which measure bulk soil electrical conductivity (σa).
However, soil is a 3-dimensional medium. In order to better represent the spatial distribution
of soil properties with depth, various methods of inverting EM instrument data have been
attempted and include Tikhonov regularisation and layered earth models. In this paper we …
methods at the field and district level has been well described. This includes the use of
electromagnetic (EM) instruments which measure bulk soil electrical conductivity (σa).
However, soil is a 3-dimensional medium. In order to better represent the spatial distribution
of soil properties with depth, various methods of inverting EM instrument data have been
attempted and include Tikhonov regularisation and layered earth models. In this paper we …
The ability to map the spatial distribution of average soil property values using geophysical methods at the field and district level has been well described. This includes the use of electromagnetic (EM) instruments which measure bulk soil electrical conductivity (σa). However, soil is a 3-dimensional medium. In order to better represent the spatial distribution of soil properties with depth, various methods of inverting EM instrument data have been attempted and include Tikhonov regularisation and layered earth models. In this paper we employ a 1-D inversion algorithm with 2-D smoothness constraints to predict the true electrical conductivity (σ) using σa data collected along a transect in an irrigated cotton field in the lower Namoi valley. The primary σa data include the root-zone measuring EM38 and the vadose-zone sensing EM31, in the vertical (v) and horizontal (h) dipole modes and at heights of 0.2 and 1.0 m, respectively. In addition, we collected σa with the EM38 at heights of 0.4 and 0.6 m. In order to compare and contrast the value of the various σa data we carry out individual inversions of EM38v and EM38h collected at heights of 0.2, 0.4, and 0.6 m, and EM31v and EM31h at 1.0 m. In addition, we conduct joint inversions of various combinations of EM38 σa data available at various heights (e.g. 0.2 and 0.4 m). Last we conduct joint inversions of the EM38v and EM38h σa data at 0.2, 0.4, and 0.6 m with the EM31v and EM31h at 1.0 m. We find that the values of σ achieved along the transect studied represent the duplex nature of the soil. In general, the EM38v and EM38h collected at a height of 0.2, 0.4, and 0.6 m assist in resolving solum and root-zone variability of the cation exchange capacity (cmol(+)/kg of soil solids) and the electrical conductivity of a saturated soil paste extract (ECe, dS/m), while the use of the EM31v and EM31h at 1.0 m assists in characterising the vadose zone and the likely location of a shallow perched-water table. In terms of identifying an optimal set of EM σa data for inversion we found that a joint inversion of the EM38 at a height of 0.6 m and EM31 signal data provided the best correlation with electrical conductivity of a saturated soil paste (ECp, dS/m) and ECe (respectively, 0.81 and 0.77) closely followed by a joint inversion of all the EM38 and EM31 σa data available (0.77 and 0.56).
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