پهنه‎بندی ظرفیت تبادل کاتیونی خاک با استفاده از زمین آمار و تجزیه مؤلفه اصلی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری گروه علوم خاک دانشگاه تبریز

2 دانشجوی دکتری گروه علوم خاک دانشگاه تهران

3 دانشیار گروه علوم خاک دانشگاه گیلان

چکیده

ظرفیت تبادل کاتیونی خاک شاخصی حیاتی و مهم از کیفیت حاصل‌خیزی و ظرفیت توقیف آلاینده‎های خاک است. در این پژوهش، تغییرپذیری ظرفیت تبادل کاتیونی خاک با روش‎های کریجینگ و کوکریجینگ به کمک مؤلفه‎های اصلی به‌دست‌آمده از ویژگی‎های فیزیکی و شیمیایی خاک‌ـ‌ شامل رس، شن، سیلت، کربن آلی، هدایت الکتریکی، و pH‌ـ بررسی شد. برای این منظور، 247 نمونه خاک از مناطق مرکزی استان گیلان جمع‎آوری شد. 75 درصد نمونه‎ها برای آموزش و 25 درصد برای آزمون استفاده شد. مؤلفه‎های اصلی اول و دوم 54/68 درصد از واریانس کل ویژگی‎های فیزیکی و شیمیایی را به خود اختصاص دادند. مؤلفة اول بیشترین همبستگی مثبت و معنادار را با ظرفیت تبادل کاتیونی خاک داشت (01/0>P، 81/0=r)؛ در حالی ‎که مؤلفة دوم همبستگی معناداری با ظرفیت تبادل کاتیونی نداشت (19/0-=r). مؤلفة اول به منزلة متغیر کمکی برای برآورد ظرفیت تبادل کاتیونی در روش کوکریجینگ استفاده شد. میانگین ریشة دوم خطا برای داده‎های آزمون در روش کریجینگ 159/0 و برای روش کوکریجینگ 118/0 به دست آمد. ضریب تبیین ارزیابی تقاطعی داده‎های آزمون برای روش کریجینگ 49/0 و برای روش کوکریجینگ 71/0 در سطح 1 درصد معنادار بود. نتایج نشان داد روش کوکریجینگ با متغیر کمکی مؤلفة اصلی اول، به‌دست‌آمده از ویژگی‎های فیزیکی و شیمیایی خاک، ظرفیت تبادل کاتیونی خاک را معتبرتر از روش کریجینگ‌ برآورد می‎کند. علاوه بر این، مؤلفه‎های اصلی، که بیشترین همبستگی مثبت و معنادار را با متغیر وابسته دارند، بالاترین پتانسیل را برای برآورد متغیر وابسته به روش کوکریجینگ دارند.

کلیدواژه‌ها


عنوان مقاله [English]

Mapping of Cation Exchange Capacity Using Geostatistics and Particle Component Analysis

نویسندگان [English]

  • Javad Seied Mohammadi 1
  • Leila Esmaeilnejad 2
  • Hasan Ramezanpour 3
  • Mahmood Shabanpoor 3
1 Ph. D. Student, Dept. Soil Sciences, University of Tabriz
2 Ph. D. Student, Dept. Soil Sciences, University of Tehran
3 Associate Professor, Dept. Soil Sciences, University of Guilan
چکیده [English]

Soil Cation Exchange Capacity (CEC) is an important vital indicator of soil fertility and as well, of pollutant sequestration capacity. Throughout the present study, spatial variability of soil CEC was investigated Through Kriging and corking with the principal components derived from soil physico-chemical properties including texture, (clay, sand, and silt content), organic carbon, electrical conductivity as well as pH. To follow the purpose, 247 soil samples were collected from central areas of Guilan province. Seventy five percent of the soil samples were used for training and 25% for testing. The first two Principal Components (PC1 and PC2) together explained 68.54% of the total variance of soil physico-chemical properties. PC1 explained the highest significantly positive correlation with CEC (r=0.81, P<0.01), whereas there was no significant correlation observed between CEC and PC2 (r=-0.19). PC1 was then used as an auxiliary variable in cokriging method for the prediction of soil CEC. Root mean square error of kriging for the test dataset was found 0.159 and that of cokriging for the dataset amounted to 0.118. The cross-validation determination coefficient (R2) for the test dataset was recorded 0.49 for kriging while 0.71 for cokring at a 0.01 level. The results show that interpolation through cokriging, with an auxiliary variable PC1 derived from soil physico-chemical properties, proves more reliable than through kriging. In addition, the principal components that bear the highest positive significant correlation with the dependent variable are of the most potential for prediction through cokriging.

کلیدواژه‌ها [English]

  • Cokriging
  • GIS
  • interpolation
  • Kriging
  • Semivariogram
Altin, A. and Degirmenci, M. (2005). Lead (II) removal from natural soils by enhanced electrokinetic remediation. Science of the Total Environment, 337, 1-10.
Andronikov, S. V., Davidson, D. A., and Spiers, R. B. (2000). Variability in contamination by heavy metals: sampling implications. Water, Air and Soil Pollution, 120, 29-45.
Arias, M., Pérez-Novo, C., Osorio, F., López, E., and Soto, B. (2005). Adsorption and desorption of copper and zinc in the surface layer of acid soils. Journal of Colloid and Interface Science, 288, 21-29.
Asadzadeh, F., Akbarzadeh, A., Zolfaghari, A. A., Taghizadeh Mehrjardi, R., Mehrabanian, M., Rahimi Lake, H., and Sabeti, M. A. (2012). Study and comparison of some geostatistical methods for mapping cation exchange capacity in soils of northern Iran. Annals of Faculty Engineering Hunedoara, 1584-2665.
Burt, R. (2004). Soil survey laboratory methods manual. Soil survey investigations report No. 42, Version 4. United States Department of Agriculture, Natural Resources Conservation Service, National Soil Survey Center.
Chung, N. and Alexander, M. (2002). Effect of soil properties on bioavailability and extractability of phenanthrene and atrazine sequestered in soil. Chemosphere, 48, 109-115.
Clay, S. A. (2011). GIS application in agriculture. Tayler and Francis, CRC Press, 448 p.
Dou, F., Yu, X., Ping, C., Michaelson, G., Guo, L., and Jorgenson, T. (2010). Spatial variation of tundra soil organic carbon along the coastline of northern Alaska. Geoderma, 154, 328-335.
Fu, W., Tunney , H., and Zhang, C. (2010). Spatial variation of soil nutrients in a dairy farm and its implications for site-specific fertilizer application. Soil & Tillage Research, 106, 185-193.
Horn, A. L., Düring, R. A., and Gath, S. (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.
Houlding, S. (2000). Practical geostatistics: modelling and spatial analysis manual. Springer Science & Business Media, 159 p.
Igwe, C. A. and Nkemakosi, J. T. (2007). Nutrient element contents and cation exchange capacity in fine fractions of southeastern nigerian soils in relation to their stability. Communications in Soil Science and Plant Analysis, 38, 1221-1242.
Jung, W. K., Kitchen, N. R., Sudduth, K. A., and Anderson, S. H. (2006). Spatial characteristics of clay pan soil properties in an agricultural field. Soil Science Society of America Journal, 70, 1387-1397.
Keshavarzi1, A., Sarmadian, F., Rahmani, A., Ahmadi, A., Labbafi, R., and Iqbal, M. A. (2012). Fuzzy clustering analysis for modeling of soil cation exchange capacity. Australian Journal of Agricultural Engineering, 3(1), 27-33.
Kevin, J., Jay, M. V. H., Konstantin K., and Neil, L. (2003). Using ArcGIS Geostatistical Analyst. ESRI, 306 p.
Khattree, R. and Naik, D. N. (2000). Multivariate Data Reduction and Discrimination with SAS Software. SAS Institute Inc., Cary, NC.
Kumar, J. I. N., George, B., Kumar, R. N., Sajish, P. R., and Viyol, S. (2009). Assessment of spatial and temporal fluctuations in water quality of a tropical permanent estuarine system-Tapi, west coast India. Applied Ecology and Environmental Research, 7, 267-276.
Kvaerno, S. H., Haugen, L. E., and Borresen, T. (2007). Variability in topsoil texture and carbon content within soil map units and its implications in predicting soil water content for optimum workability. Soil & Tillage Research, 95, 332-347.
Li, Y., Shi, Z., Li, F., and Li, H. Y. (2007). Delineation of site-specific management zones using fuzzy clustering analysis in a coastal saline land. Computers and Electronics in Agriculture, 56, 174-186.
McBratney, A. B., Odeh, I. O. A., Bishop, T. F. A., Dunbar, M. S., and Shatar, T. M. (2000). An overview of pedometric techniques for use in soil survey. Geoderma, 97, 293-327.
Moral, F. J., Terrón, J. M., and Rebollo, F. J. (2011). Site-specific management zones based on the Rasch model and geostatistical techniques. Computers and Electronics in Agriculture, 75, 223-230.
Mouser, P. J., Rizzo, D. M., Roling, W. F. M., and Van Breukelen, B. M. (2005). A multivariate statistical approach to spatial representation of groundwater contamination using hydrochemistry and microbial community profiles. Environmental Science & Technology, 39, 7551-7559.
Paul, R. and Cressie, N. (2011). Lognormal block kriging for contaminated soil. European Journal of Soil Science, 62, 337-345.
Paz-González, A., Vieira, S. R., and Taboada, C. M. T. (2000). The effect of cultivation on the spatial variability of selected properties of an umbric horizon. Geoderma, 97, 273-292.
Robinson, T. P. and Metternicht, G. (2006). Testing the performance of spatial interpolation techniques for mapping soil properties. Computers and Electronics in Agriculture, 50, 97-108.
Seyedmohammadi, J. (2006). Study of some physicochemical and micromorphological characteristics of paddy soils in different landforms (in part of Guilan province). Ms.C Thesis, Faculty of Agriculture, University of Guilan, Rasht. (In Farsi)
Shi, J., Wang, H., Xu, J., Wu, J., Liu, X., Zhu, H., and Yu, C. (2007). Spatial distribution of heavy metals in soils: A case study of Changxing, China. Environmental Geology Journal, 52, 1-10.
Shi, W. J, Liu, J. Y., Du, Z. P., Song, Y. J., Chen, C. F., and Yue, T. X. (2009). Surface modelling of soil pH. Geoderma, 150, 113-119.
Site, A. D. (2001). Factors affecting sorption of organic compounds in natural sorbent/water systems and sorption coefficients for selected pollutants. A review. Journal of Physical and Chemical Reference Data, 30, 187-439.
Soil Survey Staff. (2014). Keys to Soil Taxonomy. 12th edition, United States Department of Agriculture, Washington D.C., USA.
Tang, L., Zeng, G. M., Nourbakhsh, F., and Shen, G. L. (2009). Artificial neural network approach for predicting cation exchange capacity in soil based on physico-chemical properties. Environmental Engineering Science, 26, 137-146.
Tesfahunegn, G. B., Tamene, L., and Vlek , P. L. G. (2011). Catchment-scale spatial variability of soil properties and implications on site-specific soil management in northern Ethiopia. Soil & Tillage Research, 117, 124-139.
Webster, R. and Oliver, M. (2007). Geostatistics for Environmental Scientists. 2nd edition, John Wiley & Sons Ltd, Chichester UK.
Wu, C. F., Wu, J. P., Luo, Y. M., Zhang, L. M., and DeGloria, S. D. (2009). Spatial estimation of soil total nitrogen using cokriging with predicted soil organic matter content. Soil Science Society of America Journal, 73, 1676-1681.
Wu, J., Norvell, W. A., Hopkins, D. G., Smith, D. B., Ulmer, M. G., and Welch, R. M. (2003). Improved prediction and mapping of soil copper by kriging with auxiliary data for cation-exchange capacity. Soil Science Society of America Journal, 67, 919-927.
Yanai, J., Sawamoto, T., Oe, T., Kusa, K., Yamakawa, K., Sawamoto, K., Naganawa, T., Inubushi, K., Hatano, R., and Kosaki, T. (2003). Spatial variability of nitrous oxide emissions and their soil related determining factors in an agricultural field. Journal of Environmental Quality, 32, 1965-1977.
Yong-dong, W., Na-na, F., Ting-xuan, L., Xi-zhou, Z., and Gui-tang, L. (2008). Spatial Variability of Soil Cation Exchange Capacity in Hilly Tea Plantation Soils Under Different Sampling Scales. Agricultural Sciences in China, 7(1), 96-103.