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Measurements of Cu or other trace elements in soils are rarely available in sufficient abundance to permit accurate mapping of large areas. In contrast, information is more widely available for major soil characteristics, such as cation-exchange capacity (CEC). Using data for soils of northern North Dakota, we compared four geostatistical methods as predictors of soil Cu: ordinary kriging (OK), ordinary kriging combined with regression (OKR), ordinary cokriging (OCK), and standardized ordinary cokriging (SCK). Ordinary kriging utilized data for soil Cu only, whereas the other three methods made use of CEC, which served as a secondary variable to improve the prediction and mapping of soil Cu. Quantitative predictions of soil Cu were tested by partitioning 619 sites of Cu into a training set of 310 sites, which was used to build models, and a testing set of 309 sites, which was reserved to test predictions derived from the training set. All three of the methods utilizing CEC data improved predictions substantially in comparison to OK. A larger data set containing data for soil Cu, CEC, or both was compiled from several comparable sources to prepare maps of Cu in soils of the 18 counties of northern North Dakota. These maps, based on data for 1002 sites within northern North Dakota, were quite similar for the three kriging methods which used data for both Cu and CEC, but different from the map derived from OK. Thus, the differences among the maps for soil Cu were consistent with our conclusion that the prediction of soil Cu was substantially improved by the use of CEC as an auxiliary variable. |
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