Journal of Integrative Agriculture ›› 2011, Vol. 10 ›› Issue (8): 1246-1253.DOI: 10.1016/S1671-2927(11)60116-8

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Cokriging of Soil Cation Exchange Capacity Using the First Principal Component Derived from Soil Physico-Chemical Properties

  

  1. Department of Hydrosciences, Nanjing University
  • 收稿日期:2010-09-07 出版日期:2011-08-15 发布日期:2011-08-16
  • 通讯作者: Correspondence XU Shao-hui, Professor, Ph D, Tel/Fax: +86-532-85953967, E-mail: shhxu@qdu.edu.cn

Cokriging of Soil Cation Exchange Capacity Using the First Principal Component Derived from Soil Physico-Chemical Properties

  1. Department of Hydrosciences, Nanjing University
  • Received:2010-09-07 Online:2011-08-15 Published:2011-08-16
  • Contact: Correspondence XU Shao-hui, Professor, Ph D, Tel/Fax: +86-532-85953967, E-mail: shhxu@qdu.edu.cn

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摘要： As soil cation exchange capacity (CEC) is a vital indicator of soil quality and pollutant sequestration capacity, a study wasconducted to evaluate cokriging of CEC with the principal components derived from soil physico-chemical properties. InQingdao, China, 107 soil samples were collected. Soil CEC was estimated by using 86 soil samples for prediction and 21soil samples for test. The first two principal components (PC1 and PC2) together explained 60.2% of the total variance ofsoil physico-chemical properties. The PC1 was highly correlated with CEC (r=0.76, P<0.01), whereas there was no significantcorrelation between CEC and PC2 (r=0.03). The PC1 was then used as an auxiliary variable for the prediction of soil CEC.Mean error (ME) and root mean square error (RMSE) of kriging for the test dataset were -1.76 and 3.67 cmolc kg-1, and MEand RMSE of cokriging for the test dataset were -1.47 and 2.95 cmolc kg-1, respectively. The cross-validation R2 for theprediction dataset was 0.24 for kriging and 0.39 for cokriging. The results show that cokriging with PC1 is more reliablethan kriging for spatial interpolation. In addition, principal components have the highest potential for cokriging predictionswhen the principal components have good correlations with the primary variables.

关键词:

Abstract: As soil cation exchange capacity (CEC) is a vital indicator of soil quality and pollutant sequestration capacity, a study wasconducted to evaluate cokriging of CEC with the principal components derived from soil physico-chemical properties. InQingdao, China, 107 soil samples were collected. Soil CEC was estimated by using 86 soil samples for prediction and 21soil samples for test. The first two principal components (PC1 and PC2) together explained 60.2% of the total variance ofsoil physico-chemical properties. The PC1 was highly correlated with CEC (r=0.76, P<0.01), whereas there was no significantcorrelation between CEC and PC2 (r=0.03). The PC1 was then used as an auxiliary variable for the prediction of soil CEC.Mean error (ME) and root mean square error (RMSE) of kriging for the test dataset were -1.76 and 3.67 cmolc kg-1, and MEand RMSE of cokriging for the test dataset were -1.47 and 2.95 cmolc kg-1, respectively. The cross-validation R2 for theprediction dataset was 0.24 for kriging and 0.39 for cokriging. The results show that cokriging with PC1 is more reliablethan kriging for spatial interpolation. In addition, principal components have the highest potential for cokriging predictionswhen the principal components have good correlations with the primary variables.

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