Statistical and geostatistical techniques for geospatial modeling of soil cation exchange capacity

ABSTRACT

Soil cation exchange capacity (CEC) is a main criterion of soil quality and pollutant sequestration capacity. This research was carried out to evaluate cokriging prediction map of soil CEC spatial variability with the principal components derived from soil physical and chemical properties. Two hundred and forty-seven soil samples were collected that 75% of them were used for training soil CEC and 25% for testing of prediction. The first principal component (PC1) was highly correlated with soil CEC (r = 0.81, P < 0.01), whiles there was no significant correlation between CEC and PC2 (r = -0.19). Then, the PC1 was used as an auxiliary variable for the prediction of soil CEC in cokriging method. The determination coefficient (R²) of cross-validation for the test dataset was 0.47 for kriging and 0.71 for cokriging. Therefore, according to the results, principal components that have the highest positive and significant correlation with the dependent variable have the most potential for cokriging prediction.

KEYWORDS:

• CEC
• cokriging
• geostatistics
• kriging
• PCA
• Spatial variability interpolation

Acknowledgments

This project was funded by a grant from the research council of Regional water organization of Guilan province. The authors wish to express their sincere thanks to the Regional water organization of Guilan province for supporting field studies and samplings. The authors are grateful to anonymous reviewers who considerably improved the quality of the manuscript.

Additional information

Funding

The funding for the research was provided by the Regional water organization of Guilan province.