SSSAJ Journal of Natural Resources and Life Sciences Education
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Published online 21 January 2009
Published in Soil Sci Soc Am J 73:164-169 (2009)
DOI: 10.2136/sssaj2008.0074
© 2009 Soil Science Society of America
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PEDOLOGY

Predicting Regional-Scale Soil Variability using a Single Calibrated Apparent Soil Electrical Conductivity Model

Omar R. Harveya,* and Cristine L. S. Morganb

a Water Management & Hydrological Sci., Texas A&M Univ., 3408 TAMU, College Station, TX 77843-3408
b Dep. of Soil & Crop Science, Texas A&M Univ., 2474 TAMU, College Station, TX 77843-2474

* Corresponding author (orharvey{at}tamu.edu).

Multi-field/multi-season approaches used to calibrate apparent soil electrical conductivity (ECa) models for predicting soil spatial variability across large landscapes are time-consuming. In this study an alternative calibration approach was evaluated. The study was conducted on an agricultural watershed in Texas with the objectives of (i) assessing the contribution of different soil properties to ECa variability; and (ii) evaluating the feasibility of using a single calibration approach to predict soil variability across different fields. Of the soil properties measured, clay content contributed the greatest to ECa variability. The single calibration approach was used to calibrate an ECa–clay model using data from a designated calibration area (CA). When the calibrated model was used to predict clay content in four validation fields, prediction accuracies were between 2 and 4% clay. Accuracies were comparable with other methods indicating that the single-calibration approach was a suitable alternative to multi-field/multi-season calibration approaches.

Abbreviations: ANOCOVA, analysis of covariance • CA, calibration area • ECa, apparent electrical conductivity • HUA, hydrologic unit A • RMSD, root mean squared deviation






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