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Inversion of soil electrical conductivity data to estimate layered soil properties

Published online by Cambridge University Press:  01 June 2017

K. A. Sudduth ,
N. R. Kitchen  and
S. T. Drummond
K. A. Sudduth*
Affiliation:
USDA-ARS-CSWQRU, 269 Ag. Eng. Bldg., Columbia, MO, 65211, USA
N. R. Kitchen
Affiliation:
USDA-ARS-CSWQRU, 269 Ag. Eng. Bldg., Columbia, MO, 65211, USA
S. T. Drummond
Affiliation:
USDA-ARS-CSWQRU, 269 Ag. Eng. Bldg., Columbia, MO, 65211, USA
*
†E-mail: ken.sudduth@ars.usda.gov
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Abstract

Bulk apparent soil electrical conductivity (ECa) sensors respond to multiple soil properties, including clay content, water content, and salt content (i.e. salinity). They provide a single sensor value for an entire soil profile down to a sensor-dependent measurement depth, weighted by a nonlinear response function. Because of this, it is generally difficult to elucidate strong relationships between ECa and the measured properties of individual soil layers. This research investigated inversion of the equations that govern the ECa-depth response relationship to reconstruct the soil conductivity in profile layers using data collected in multiple fields in the Midwest US. Layer conductivities obtained by inversion were first validated by comparison with true conductivities measured as a function of depth with an ECa-sensing penetrometer. Then, the validated layer conductivities were related to laboratory- measured soil properties. Inversion worked well but sometimes required iterative adjustment of initial conditions and other input parameters to obtain best results. Strong linear relationships (r2≥0.76) were obtained between inversion-estimated and measured layer conductivity data in all cases, sometimes with a truncated depth range. Layer conductivity data was successfully used to estimate soil texture fractions in the two alluvial fields examined. This was not the case for a claypan soil field, where there appeared to be parameters other than texture strongly affecting the EC response. Further examination of this approach is warranted to potentially provide improved ways to estimate depth-variable soil properties using ECa.

Keywords

soil electrical conductivitysoil texturemodel inversion
Type
Soil Sensing and Variability
Information
Advances in Animal Biosciences , Volume 8 , Special Issue 2: Papers presented at the 11th European Conference on Precision Agriculture (ECPA 2017), John McIntyre Centre, Edinburgh, UK, July 16–20 2017 , July 2017 , pp. 433 - 438
Copyright
© The Animal Consortium 2017. This is a work of the U.S. Government and is not subject to copyright protection in the United States 

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