Mapping of Soil Salinity and Sodicity Hazard Using Indicator Krijing in Ghorveh, Kurdistan Province

Authors

1 Assistant Professor Of Department of Soil Science and Engineering, University of Kurdistan, Sanandaj

2 MSc student, Department of Soil Science and Engineering, University of Kurdistan, Sanandaj

3 Assistant Professor Of Faculty of Agriculture & Natural Resources, University of Ardakan

Abstract

In the recent decades, application of geostatistic for mapping salinity and sodicity of soil and investigation of their changes has developed. The purpose of this study is to use Indicator Krijing to make probability maps of soil salinity and sodicity. In order to do this, in 178 points of the study area, 356 soil samples from two depths, i.e. 0-30 and 30-60 cm, were taken in Ghorveh soils, Kurdistan Province, using hypercube method. Then, electrical conductivity, pH, Na, Ca, Mg, and Sodium Adsorption Ratio characteristics were measured. Using Indicator Krijing, probability maps of soil salinity and sodicity were prepared for both depths based on two threshold indices of 4 dS/m for salinity and 13 (mmoll-1)0.5 for SAR. Results showed that probability maps of 0-30 cm depth for soil salinity and sodicity, respectively, with 0.53 and 0.94 Kappa index, had moderate and excellent accuracy levels, while in 30-60 cm depth, with 0.64 and 0.8 Kappa index, respectively, had good and excellent accuracy levels. Central part of the area had higher probability of salinity and sodicity compared to the other parts. This part of the area had lowland physiography and somewhat unsuitable water table near the soil surface.

Keywords


  1. دلبری، م. و افراسیاب، پ. 1393. کاربرد کریجینگ شاخص و معمولی در مدل کردن کلر آب زیرزمینی. محیط شناسی، 40 (3): 764-751.
  2. برزگر، ع. 1387. خاک­های شور و سدیمی. انتشارات دانشگاه شهید چمران اهواز، 355 ص.
  3. دائم­پناه، ر. حق­نیا، غ. علیزاده، ا. و کریمی­کارویه، ع. 1390. تهیه نقشه شوری و سدیمی خاک سطحی با روش­های دورسنجی و زمین آماری در جنوب شهرستان مه ولات. نشریه آب و خاک (علوم و صنایع کشاورزی)، 25 (3): 508-498.
  4. سکوتی اسکوئی، ر. مهدیان، م. محمودی، ش. و قهرمانی، ا. 1386. مقایسه کارایی برخی روش­های زمین آماری برای پیش بینی پراکنش مکانی شوری خاک، مطاله موردی دشت ارومیه. پژوهشی و سازندگی در زراعت و باغبانی، 74: 98-91.
  5. محمدی، ج. 1377، مطالعه تغییرات مکانی شوری خاک در منطقه رامهرمز (خوزستان) با استفاده از نظریه ژئواستاتیستیک (کریجینگ). علوم و فنون کشاورزی، 2 (4):49-63.
  6. Cambardella, C.A., T.B. Moormam. T.B. Parkin. D.L. Karlen. R.F. Turco. and A.E. Konopka. 1994. Field scale soils variability of soil properties in Central  Iowa soils. Soil Science Society of America Journal, 58: 1501-1511.
  7. Castrignano, A., G. Buttafuoco. and C. Giasi. 2008. Assessment of Ground water Salinisation Risk Using Multivariate Geostatistics. GeoENVVI – Geostatistics for Environmental Applications, 191-202.
  8. Chica-Olmo, M., J.A. Luque-Espinar. V. Rodriguez-Galiano. E. Pardo-Iguzquiza. and L. Chica-Rivas. 2014. Categorical Indicator Kriging for assessing the risk of groundwater nitrate pollution: The case of Vega de Granada aquifer (SE Spain). Science of the Total Environment, 470-471: 229-239.
  9. Farifte, J., A. Farshad. and R.J. George. 2005. Assessing salt – affected soils using remote sensing, solute modeling, and geophysics. Geoderma, 130: 191-206.
  10. Goovaerts, P. 1997. Geostatistics for Natural Resources Evaluation. Oxford Univer-sity Press, Oxford.
  11. Jang, C.H., and C.K. Chen. 2015. Integrating indicator-based geostatistical estimation and aquifer vulnerability of nitrate-N for establishing groundwater protection zones. Journal of Hydrology, 523: 441-451.
  12. Journel, A.G., and C.J. Huijbregts. 1978. Mining Geostatistics. Academic Press, New York, 600 pp.
  13. Kilic, K., and S. Kilic. 2007. Spatial variability of salinity and alkalinity of a field having salination risk in semi-arid climate in northern Turkey. Environ Monit Assess, 127: 55–65.
  14. Mamat, Z., H. Yimit. R.Z.A. Ji. and M. Eziz. 2014. Source identification and hazardous risk delineation of heavy metal contamination in Yanqi basin, northwest China, Science of the Total Environment, 493: 1098-1111.
  15. Mohammadi, J. 2006. Spatial Statistics (Geo statistics). Pelk. Press. Pp: 345-346.
  16. Nelson, R.E. 1982. Carbonate and gypsum. p. 181-196. In A.L. Page et al. (ed.) Methods of soil analysis. Part 2-chemical and microbiological properties. Madison, WI.
  17. Pontius Jr, R.G., and M. Millones. 2011. Death to Kappa: birth of quantity disagreement and allocation disagreement for accuracy assessment. International Journal of Remote Sensing, 32 (15): 4407-4429.
  18. Richards, L.A. 1954. Diagnosis and improvement of saline and alkali soils. Soil Sci, 78 (2), 154.
  19. Shi,  k., C.Q. Liu. N.S. Ai. X.H. Zhang. 2008. Using three methods to investigate time –scaling properties in air pollution indexes time series. Nonlinear Analysis: Real. World Application, 9: 693-707.
  20. Silva, A.F.D., A.P. Barbosa. C.R.L. Zimback. P.M.B. Landim. and A. Soares. 2015. Estimation of croplands using indicator kriging and fuzzy classification. Computers and Electronics in Agriculture, 111:1-11.
  21. Sparks, D.L., A.L. Page. P.A. Helmke. R.H. Leoppert. P.N. Soltanpour. M.A. Tabatabai. G.T. Johnston. and M.E. Summer. 1996. Methods of Soil Analysis. Soil. Sci. Soc. Am. J, Madison, Wisconsin.