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Dep. of Crop Sciences, 1102 S. Goodwin Ave., Univ. of Illinois, Urbana, IL 61801
* Corresponding author (dbullock{at}uiuc.edu)
In this study we applied discriminant analysis and geostatistics to create soil drainage maps using topographical and soil electrical conductivity (EC) data as auxiliary information. Drainage classes were determined on 107 soil cores collected from a 20-ha field in Illinois. Approximately 1500 elevation points and 6500 EC points were collected from the field. Slope, curvature, and flow accumulation were derived. Discriminant analysis and logistic discrimination were applied to study the effect of topography and EC on drainage. Spatial variability of the soil drainage data and its relationship with variability of topography and EC were analyzed using variograms and cross-variograms. Indicator kriging and soft indicator cokriging were used. Soil EC, terrain slope, and distance to a drainageway were selected by a stepwise discriminant procedure as significant predictors of the soil drainage class (P = 0.15). When these variables were used as additional information in predicting soil drainage class using either discriminant analysis or cokriging procedures, they slightly improved overall prediction accuracy, compared with the soil survey map (scale 1:15840) and indicator kriging. Discriminant analysis and cokriging correctly estimated drainage classes for more than 90% of the sites, compared with 85 and 63% correct estimates obtained from indicator kriging and soil survey data, respectively. Indicator kriging and cokriging are exact estimators and thus are more suitable for mapping than is discriminant analysis. We recommend the use of stepwise discriminant procedure to select among the available secondary variables and to create drainage maps using cokriging with the selected variables.
Abbreviations: EC, electrical conductivity • GPS, global positioning system • MWD, moderately well-drained soil • PD, poorly drained soil • SWPD, somewhat poorly drained soil
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