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Assessment of spatial variability of cation exchange capacity with kriging and cokriging | ||
| Desert | ||
| مقاله 10، دوره 24، شماره 1، شهریور 2019، صفحه 99-108 اصل مقاله (592.87 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22059/jdesert.2019.72444 | ||
| نویسندگان | ||
| S.A.R. Seyed Jalali* 1؛ F. Sarmadian2؛ Z. Mohammad Esmaiel3؛ M. Navidi1 | ||
| 1Soil and Water Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran | ||
| 2Soil Science Dept., Faculty of Agriculture, University of Tehran, Karaj, Iran | ||
| 3Researcher of Soil and Water Research Institute, Karaj, Iran | ||
| چکیده | ||
| Cation exchange capacity (CEC) is one of the most important soil attributes which control some basic properties of soil such as acidity, water and nutrient retaining capacity. However, the measurement of cation exchange capacity in large areas is time consuming and requires high expenses. One way to save time and expenses is to use simple soil covariates and geostatistical methods in mapping CEC. Therefore, the aim of the present research was to investigate the role of soil covariates in the improvement of spatial variability of CEC. The study area is located in southwest Iran on the Aghili plain, Gotvand, Khuzestan province. In this study, ordinary kriging and cokriging methods were used to predict CEC. 107 soil samples were gathered on a random grid of 200-700 m. 74 samples were used for training and 33 samples for testing the results. A principle component analysis was performed for covariate selection. Clay was selected as a covariate in cokriging due to high correlation between clay and CEC[FE1] in the first principle component analysis. Based on the cross validation result of predicted dataset, RMSE and ME for cokriging were 2.16 and 0.03 cmol (+)/kg respectively, and 3.36 and 0.09 cmol (+)/kg for kriging, respectively. Based on these results, cokriging performed better than kriging for predition of cation exchange capacity since it used a covariate such as clay, for the improvement of CEC spatial prediction. | ||
| کلیدواژهها | ||
| Geostatistics؛ soil؛ Khuzestan؛ Gotvand | ||
| مراجع | ||
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Cahn, M. D., J. W. Hummel, B. H. Brouer, 1994. Spatial analysis of soil fertility for site specific crop management. Soil Science Society of America Journal, 58; 1240-1248. Cambardella, C. A., T. B. Moorman, J. M. Novak, 1994. Field-scale variability of soil properties in centres Iowa soils. Soil Science Society of America Journal, 58; 1501-1511. Chapman, H. D., 1965. Cation exchange capacity. PP. 891-901. In: Black, C.A. (Ed.), Methods of Soil Analysis, part 2. Second Edition, American Society of Agronomy, Madison, WI. Gee, G. W., J. W. Bauder, 1986. Particle-size Analysis. PP. 383 – 411. In A.L. Page (ed.). Methods of soil analysis, Part1, Physical and mineralogical methods. Second Edition, Agronomy Monograph 9, American Society of Agronomy, Madison, WI. Igwe, C. A., J. T. Nkemakosi, 2007. Nutrient element contents and cation exchange capacity in fine fractions of south-eastern Nigerian soils in relation to their stability. Communications in Soil Science and Plant Analysis, 38; 1221-1242. Horn, A. L., R. A. Düring, S. Gath, 2005. Comparison of the prediction efficiency of two pedotransfer functions for soil cation exchange capacity. Journal of Plant Nutrition and Soil Science, 168; 372-374. Istok, J. D., J. D. Smyth, A. L. Flint, 1993. Multivariate geostatistical analysis of groundwater contaminant: a case history. Groundwater, 31; 63-74. Jafari, A., P. A. Finke, J. V. De Wauw, S. Ayoubi, H. Khademi, 2012. Spatial prediction of USDA –great soil groups in the arid Zarand region, Iran: comparing logistic regression approaches to predict diagnostic horizons and soil types. Eur J Soil Sci., 63; 284–298. Journal, A. G., C. J. Huijbregts, 1978. Mining Geostatistics. Academic Press, New York, USA. pp. 1-600. Jung, W. K., N. R. Kitchen, K. A. Sudduth, S. H. Anderson, 2006. Spatial characteristics of clay pan soil properties in an agricultural field. Soil Science Society of America Journal, 70; 1387-1397. Khattree, R., D. N. Naik, 2000. Multivariate Data Reduction and Discrimination with SAS Software. SAS Institute Inc., Cary, NC. Li, Y., Z. Shi, F. Li, H. Y. Li, 2007. Delineation of site- specific management zones using fuzzy clustering analysis in a coastal saline land. Computers and Electronics in Agriculture, 56; 174-186. Loeppert, R. H., D. L. Suarez, 1996. Carbonate and gypsum, PP: 437-474.In: Sparks, D. L. (ed) Methods of soil analysis, part3. Second Edition, American Society of Agronomy, Madison, WI. McBratney, A.B., I.O.A. Odeh, T.F.A. Bishop, M.S. Dunbar, T.M. Shatar, 2000. An overview of pedometric techniques for use in soil survey. Geoderma, 97; 293–327. Manrique, L.A., C.A. Jones, P.T. Dyke, 1991. Predicting cation exchange capacity from soil physicalmand chemical properties. Soil Sci Soc Am J. 50; 787–794. Nelson, D. W., L. Sommers, 1982. Total carbon, organic carbon, and organic matter. PP. 539- 579. Methods of soil analysis. Part 2. Chemical and microbiological properties, Second Edition, American Society of Agronomy, Madison, WI. Obalum, S. E., Y. Watanabe, C. A. Igwe, M. E. Obi, 2013. Improving on the Prediction of Cation Exchange Capacity for Highly Weathered and Structurally Contrasting Tropical Soils from Their Fine-Earth Fractions. In comm. Soil Sci plant Anal. pp: 1831-1848. Rhodes, J.D., 1996. Salinity: electrical conductivity and total dissolved solids. PP: 417 – 435. In: Sparks, D.L. (Ed.), Methods of Soil Analysis. Part 3, Chemical Methods. SSSA Book Series No. 5. ASA, Madison, WI. Shi, W. J., J.Y. Liu, Z. P. Du, Y. J. Song, C. F. Chen, T. X. Yue, 2009. Surface modelling of soil pH. Geoderma, 150; 113-119. Shiri, J., A. Keshavarzi, O. Kisi, U. Iturraran-Viveros, A. Bagherzadeh, R. Mousavi, S. Karimi, 2017. Modeling soil cation exchange capacity using soil parameters: assessing the heuristic models. Comput. Electron. Agric., 135; 242-251. Stein, A., L. C. A. Corsten, 1991. Universal kriging and cokriging as regression procedure. Biometrics, 47; 575-587. Taghizadeh-Mehrjardi, R., B. Minasny, F. Sarmadian, B. P. Malone, 2014. Digital mapping of soil salinity in Ardakan region, central Iran. Geoderma. 213;15–28. Wander, M., G. A. Bollero, 1999. Soil quality assessment of tillage impacts in Illinois. Soil Science Society of America Journal, 63; 961-971. White, D., M. Richman, B. Yarnal, 1991. Climate regionalization and rotation of principal components. International Journal of Climatology, 11; 1-25. Wu, C. F., J. P. Wu, Y. M. Luo, L. M. Zhang, S. D. DeGloria, 2009. Spatial estimation of soil total nitrogen using cokriging with predicted soil organic matter content. Soil Science Society of America Journal, 73; 1676-1681. Yanai, J., T. Sawamoto, T. Oe, K. Kusa, K. Yamakawa K. Sawamoto, T. Naganawa, K. Inubushi, R. Hatano T. Kosaki, 2003. Spatial variability of nitrous oxide emissions and their soil- related determining factors in an agricultural field. Journal of Environmental Quality, 32; 1965-1977. | ||
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