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| Cokriging of Soil Cation Exchange Capacity Using the First Principal Component Derived from Soil Physico-Chemical Properties |
| Department of Hydrosciences, Nanjing University |
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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.
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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Received: 07 September 2010
Accepted:
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Corresponding Authors:
Correspondence XU Shao-hui, Professor, Ph D, Tel/Fax: +86-532-85953967, E-mail: shhxu@qdu.edu.cn
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Cite this article:
LIAO Kai-hua, XU Shao-hui, WU Ji-chun, JI Shu-hua, LIN Qing.
2011.
Cokriging of Soil Cation Exchange Capacity Using the First Principal Component Derived from Soil Physico-Chemical Properties. Journal of Integrative Agriculture, 10(8): 1246-1253.
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| [1] Altin A, Degirmenci M. 2005. Lead (II) removal from naturalsoils by enhanced electrokinetic remediation. Science of theTotal Environment, 337, 1-10.[2] Arias M, Pérez-Novo C, Osorio F, López E, Soto B. 2005.Adsorption and desorption of copper and zinc in the surfacelayer of acid soils. Journal of Colloid and Interface Science,288, 21-29.[3] Burgess T M, Webster R. 1980. Optimal interpolation andisarithmic mapping of soil properties: the semivariogram andpunctual kriging. Soil Science, 31, 315-331.[4] Burrough P A, Webster R. 1976. Improving a reconnaissance soilclassification by multivariate methods. European Journal ofSoil Science, 27, 554-571.[5] Cahn M D, Hummel J W, Brouer B H. 1994. Spatial analysis ofsoil fertility for site-specific crop management. Soil ScienceSociety of America Journal, 58, 1240-1248.[6] Cambardella C A, Moorman T B, Novak J M. 1994. Field-scalevariability of soil properties in center Iowa soils. Soil ScienceSociety of America Journal, 58, 1501-1511.[7] Chung N, Alexander M. 2002. Effect of soil properties onbioavailability and extractability of phenanthrene and atrazine sequestered in soil. Chemosphere, 48, 109-115.[8] Cooperative Research Group of Chinese Soil Taxonomy. 2001.Chinese Soil Taxonomy. Science Press, Beijing. (in Chinese)Horn A L, Düring R A, Gath S. 2005. Comparison of the predictionefficiency of two pedotransfer functions for soil cationexchangecapacity. Journal of Plant Nutrition and SoilScience, 168, 372-374.[9] Igwe C A, Nkemakosi J T. 2007. Nutrient element contentsand cation exchange capacity in fine fractions ofsoutheastern nigerian soils in relation to their stability.Communications in Soil Science and Plant Analysis, 38,1221-1242.[10] Istok J D, Smyth J D, Flint A L. 1993. Multivariate geostatisticalanalysis of groundwater contaminant: a case history.Groundwater, 31, 63-74.[11] Journel A G, Huijbregts C J. 1978. Mining Geostatistics. AcademicPress, New York, USA. pp. 1-600.[12] Jung W K, Kitchen N R, Sudduth K A, Anderson S H. 2006.Spatial characteristics of claypan soil properties in anagricultural field. Soil Science Society of America Journal, 70,1387-1397.[13] Khattree R, Naik D N. 2000. Multivariate Data Reduction andDiscrimination with SAS Software. SAS Institute Inc., Cary,NC.Kumar J I N, George B, Kumar R N, Sajish P R, Viyol S. 2009.Assessment of spatial and temporal fluctuations in waterquality of a tropical permanent estuarine system-Tapi, westcoast India. Applied Ecology and Environmental Research,7, 267-276.[14] Li Y, Shi Z, Li F, Li H Y. 2007. Delineation of site-specificmanagement zones using fuzzy clustering analysis in a coastalsaline land. Computers and Electronics in Agriculture, 56,174-186.[15] Manrique L A, Jones C A, Dyke P T. 1991. Predicting cationexchangecapacity from soil physical and chemical properties.Soil Science Society of America Journal, 55, 787-794.[16] Mouser P J, Rizzo D M, Roling W F M, van Breukelen B M.2005. A multivariate statistical approach to spatialrepresentation of groundwater contamination usinghydrochemistry and microbial community profiles.Environmental Science & Technology, 39, 7551-7559.[17] Myers J C. 1997. Geostatistical Error Management: QuantifyingUncertainty for Environmental Sampling and Mapping(Industrial Engineering). Van Nostrand Reinhold, New York.Paz-González A, Vieira S R, Taboada C M T. 2000. The effect ofcultivation on the spatial variability of selected properties ofan umbric horizon. Geoderma, 97, 273-292.[18] Shi W J, Liu J Y, Du Z P, Song Y J, Chen C F, Yue T X. 2009.Surface modelling of soil pH. Geoderma, 150, 113-119.[19] Site A D. 2001. Factors affecting sorption of organic compoundsin natural sorbent/water systems and sorption coefficientsfor selected pollutants. A review. Journal of Physical andChemical Reference Data, 30, 187-439.[20] Soil Science Society of China. 2000. Methods of Soil and AgrochemistryAnalysis. Chinese Agricultural Science andTechnology Press, Beijing, China. pp. 1-357. (in Chinese)[21] Stein A, Corsten L C A. 1991. Universal kriging and cokriging asregression procedure. Biometrics, 47, 575-587.[22] Tang L, Zeng G M, Nourbakhsh F, Shen G L. 2009. Artificialneural network approach for predicting cation exchangecapacity in soil based on physico-chemical properties.Environmental Engineering Science, 26, 137-146.[23] Vauclin M, Vieira S R, Vachaud G, Nielsen D R. 1983. The use ofcokriging with limited field observations. Soil Science Societyof America Journal, 47, 175-184.[24] Wander M M, Bollero G A. 1999. Soil quality assessment oftillage impacts in Illinois. Soil Science Society of AmericaJournal, 63, 961-971.[25] White D, Richman M, Yarnal B. 1991. Climate regionalizationand rotation of principal components. International Journalof Climatology, 11, 1-25.[26] Wu C F, Wu J P, Luo Y M, Zhang L M, DeGloria S D. 2009.Spatial estimation of soil total nitrogen using cokriging withpredicted soil organic matter content. Soil Science Society ofAmerica Journal, 73, 1676-1681.[27] Wu J, Norvell W A, Hopkins D G, Smith D B, Ulmer M G,Welch R M. 2003. Improved prediction and mapping of soilcopper by kriging with auxiliary data for cation-exchangecapacity. Soil Science Society of America Journal, 67, 919-927.[28] Yanai J, Sawamoto T, Oe T, Kusa K, Yamakawa K, SawamotoK, Naganawa T, Inubushi K, Hatano R, Kosaki T. 2003.Spatial variability of nitrous oxide emissions and their soilrelateddetermining factors in an agricultural field. Journal ofEnvironmental Quality, 32, 1965-1977.[29] Yates S R, Warrick A W. 1987. Estimating soil water contentusing cokriging. Soil Science Society of America Journal, 51,23-30. |
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