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United States Department of Agriculture

Agricultural Research Service

Research Project: SYSTEMS AND TECHNOLOGIES FOR SUSTAINABLE SITE-SPECIFIC SOIL AND CROP MANAGEMENT Title: Combining Proximal and Penetrating Conductivity Sensors for High Resolution Soil Mapping

item Myers, David - UNIV. OF MISSOURI
item Kitchen, Newell
item Sudduth, Kenneth
item Grunwald, Sabine - UNIV. OF FLORIDA
item Miles, Randall - UNIV. OF MISSOURI
item Sadler, Edward
item Udawatta, Ranjith - UNIV. OF MISSOURI

Submitted to: Global Worshop on High Resolution Digital Soil Sensing and Mapping
Publication Type: Proceedings
Publication Acceptance Date: January 11, 2008
Publication Date: February 5, 2008
Citation: Myers, D.B., Kitchen, N.R., Sudduth, K.A., Grunwald, S., Miles, R.J., Sadler, E.J., and Udawatta, R. 2008. Combining proximal and penetrating conductivity sensors for high resolution soil mapping. In: Proceedings of the First Global Workshop on High Resolution Digital Soil Sensing and Mapping, February 5-8, Sydney, Austrailia. 2008 CDROM.

Interpretive Summary: Obtaining information for creating high-resolution soil maps remains a challenge, largely because it is difficult to carefully examine the soil other than at the soil surface. Yet many differences in soil chemical and physical properties that are important for managing crops can only be seen below the surface. One answer to this dilemma is the use of field sensing approaches that are sensitive to subsoil variations. One such approach is the sensing of soil electrical conductivity (EC). This research was conducted to examine if combinations of data from several different commercial EC sensors in concert with a special penetrating EC probe sensor could be used to accurately characterize subsoil properties for mapping purposes. We discovered that for claypan soils of the U.S. Midwest high readings of soil EC were caused by four overlapping features: clay content, cations, moisture, and bulk density. Which of these properties were most strongly related to soil EC at a particular location depended on their distribution within the soil profile. Depth to the claypan soil horizon was related to data from the penetrating EC probe. Thus, the penetrating EC sensor along with conventional EC sensors could be used to improve high resolution mapping of subsoil features. Detailed maps of subsoil properties could be used by farmers and consultants for targeting inputs and developing conservation practices. These site-specific management actions will improve cropping efficiency and establish more sustainable food, fuel, and fiber production systems for the U.S.

Technical Abstract: Proximal ground conductivity sensors produce a high spatial resolution map that integrates the bulk electrical conductivity (ECa) of the soil profile. Variability in the conductivity map must either be inverted to estimate profile conductivity, or be directly calibrated to soil profile properties for meaningful interpretation. Penetrating apparent electrical conductivity (ECp) sensors produce high depth resolution data at relatively fewer spatial locations. The objectives of this research are to (i) investigate the profile source of the ECa in claypan soils via a detailed examination of ECp profiles, (ii) examine the potential for feature detection with ECp in claypan soils, and (iii) consider the utility of ECp data in inversion problems. Two study areas were chosen in the claypan soils of northeast Missouri, USA– three fields with a loess solumn and a paired watershed with a loess-till solumn. Profile conductivity was measured at high depth resolution on soil cores using a custom Wenner-style conductivity probe and in the field using a conductivity penetrometer. Proximal ground conductivity was mapped with one direct contact sensor and two non-contact sensors providing 5 distinct coil/electrode geometries. High ECa was observed below the claypan correlating with decreasing clay and water content and increasing bulk density. Depth to the claypan was successfully calibrated to derivative peaks on ECp profiles (r^2 0.72, p<0.001). Relationships between ECa and ECp features were poor (r^2 ~0.21) to good (r^2~0.87) on a field specific basis. Results show that ECp can be used to augment field observations for calibration of ECa to the depth to claypan.

Last Modified: 3/1/2015
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