Apparent Electrical Conductivity, Soil Properties and Spatial Covariance in the U.S. Southern High Plains

Apparent Electrical Conductivity, Soil Properties and Spatial Covariance in the U.S. Southern... Site-specific soil and crop management will require rapid low-cost sensors that can generate position-referenced data that measure important soil properties that impact crop yields. Apparent electrical conductivity (ECa) is one such measure. Our main objective was to determine which commonly measured surface soil properties were related to ECa at six sites in the Texas Southern High Plains, USA. We used the Veris 3100 and Geonics EM-38 EC mapping systems on 12 to 47 ha areas in six center-pivot irrigation sites. Soil samples were taken from 0–150 mm on a 0.1 to 0.8 ha grid and analyzed for routine nutrients and particle size distribution. At four of the six sites, shallow ECa measured with the Veris 3100 (ECa-sh) positively correlated to clay content. Clay content was negatively related with ECa-sh at one site, possibly due to low bulk density of the shallow calcic horizon at that site. Other soil properties that were often correlated with ECa included soil extractable Ca2+, Mg2+, Na+, CEC, silt and soluble salts. Extractable K+, NO 3 − , SO 4 − , Mehlich-3-P, and pH were not related to ECa. Partial least squares regression (PLS) of seven soil properties explained an average of 61%, 51% and 37% of the variation in observed shallow ECa-sh, deep ECa with the Veris 3100 (ECa-dp) and ECa with the Geonics EM-38 (ECa-em), respectively. Including nugget, range and sill parameters from a spherical semivariance model of the residuals from PLS regression improved the fit of mixed models in 15 of 18 cases. Apparent EC, therefore can provide useful information to land-users about key soil properties such as clay content and extractable Ca2+, but that spatial covariance in these relationships should not be ignored. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Precision Agriculture Springer Journals

Apparent Electrical Conductivity, Soil Properties and Spatial Covariance in the U.S. Southern High Plains

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Publisher
Springer Journals
Copyright
Copyright © 2005 by Springer Science+Business Media, Inc.
Subject
Life Sciences; Agriculture; Soil Science & Conservation; Remote Sensing/Photogrammetry; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Atmospheric Sciences
ISSN
1385-2256
eISSN
1573-1618
D.O.I.
10.1007/s11119-005-1388-6
Publisher site
See Article on Publisher Site

Abstract

Site-specific soil and crop management will require rapid low-cost sensors that can generate position-referenced data that measure important soil properties that impact crop yields. Apparent electrical conductivity (ECa) is one such measure. Our main objective was to determine which commonly measured surface soil properties were related to ECa at six sites in the Texas Southern High Plains, USA. We used the Veris 3100 and Geonics EM-38 EC mapping systems on 12 to 47 ha areas in six center-pivot irrigation sites. Soil samples were taken from 0–150 mm on a 0.1 to 0.8 ha grid and analyzed for routine nutrients and particle size distribution. At four of the six sites, shallow ECa measured with the Veris 3100 (ECa-sh) positively correlated to clay content. Clay content was negatively related with ECa-sh at one site, possibly due to low bulk density of the shallow calcic horizon at that site. Other soil properties that were often correlated with ECa included soil extractable Ca2+, Mg2+, Na+, CEC, silt and soluble salts. Extractable K+, NO 3 − , SO 4 − , Mehlich-3-P, and pH were not related to ECa. Partial least squares regression (PLS) of seven soil properties explained an average of 61%, 51% and 37% of the variation in observed shallow ECa-sh, deep ECa with the Veris 3100 (ECa-dp) and ECa with the Geonics EM-38 (ECa-em), respectively. Including nugget, range and sill parameters from a spherical semivariance model of the residuals from PLS regression improved the fit of mixed models in 15 of 18 cases. Apparent EC, therefore can provide useful information to land-users about key soil properties such as clay content and extractable Ca2+, but that spatial covariance in these relationships should not be ignored.

Journal

Precision AgricultureSpringer Journals

Published: Apr 1, 2005

References

  • Spatial analysis of soil fertility parameters
    Cambardella, C.A.; Karlen, D.L.
  • Estimation of soil textural features from soil electrical conductivity recorded using the EM38
    Domsch, H.; Giebel, A.

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