Spatial variability of Soil Macronutrients on Basaltic landscape of Central India: A Geostatistical approach

Article Views: 272

Spatial Variability of Soil Macronutrients on Basaltic landscape of Central India: A Geostatistical Approach

Nisha Sahu*, G.P. Obi reddy, Nirmal Kumar, M.S.S. Nagaraju, Rajeev Srivastava and S.K. Singh

ICAR-National Bureau of Soil Survey and Land Use Planning, Amravati Road, Nagpur-440 033, India

Keywords: Spatial variability, Semivariogram, Cross-validation, Soil properties, GPS

https://doi.org/10.37273/chesci.cs172050121 • PDF

Abstract

A study was conducted to interpolate and to explore the analysis of spatial variability of major soil nutrients in Basaltic Terrain of Nagpur district, Maharashtra. A total of 235 soil samples (0-25 cm) were collected grid wise at an interval of 250 m using GPS. Soil chemical properties i.e. available nutrients (N, P and K) were measured in laboratory. After normalization, data were interpolated by Ordinary Kriging (Spherical, Exponential and Gaussian). The performance of methods was evaluated using Mean Absolute Error (MAE), Root Mean Square Error (RMSE) and Goodness of prediction (G) obtained from a cross-validation procedure. The results showed that Ordinary Kriging (Spherical Model) was the best method to estimate available N and K whereas Gaussian Model fits well with highest precision for estimation of available P in this area. Available P and K have displayed moderate spatial dependence whereas Available N showed strong spatial dependence. Cross validation of kriged map showed that spatial prediction of soil nutrients using semi variogram parameters is better than assuming mean of observed value for any unsample location. Therefore, it is a suitable alternative method for accurate estimation of soil properties in unsampled positions as compared to direct measurement which has time and costs concerned.

References

  1. Goovaerts, P. Geo-statistical tools for characterizing the spatial variability of microbiological and physico-chemical soil properties. Biology and Fert. Soils. 1998, 27: 315-334.
  2. Godwin, R.J. and Miller, P.C.H. A review of the technologies for mapping within-field variability.Biosystems Engin. 2003, 84:393-407.
  3. Vrindts, E., Mouazen, A. M., Reyniers, M., Martens, K., Maleki, M. R., Ramon, H. and De Baerdemaeker, J. Management zones based on correlation between coil compaction, yield and crop data. Biosystems Engin. 2005, 9: 419-428.
  4. Bhattacharyya, P., Tiwari, A.K. and Bhatt, V.K. Spatial variation of soil strength in small hilly watershed of Shivalik-Himalayan region in India. Ind. J. Soil Conser. 2008, 36(1): 16-21.
  5. Smith, V.H., Tilman, G.D. and Nekola, J.C. Eutrophication: impacts of excess nutrient inputs on freshwater, marine, and terrestrial ecosystems. Environmental Pollution.1998, 100 (1-3): 179-196.
  6. Phupaibul, P., Chitbuntanorm, C., Chinoim, N., Kangyawongha, P. and Matoh, T. Phosphorus accumulation in soils and nitrate contamination in underground water under exportoriented asparagus farming in Nong Ngu Lauem Village, Nakhon Pathom Province, Thailand. Soil Science and Plant Nutrition. 2004, 50(3): 385-393.
  7. Ju, X.T., Kou, C.L., Christie, P., Dou, Z. X. and Zhang, F.S. Changes in the soil environment from excessive application of fertilizers and manures to two contrasting intensive cropping systems on the North China Plain. Environmental Pollution, 2007, 145(2): 497-506.
  8. Mc Bratney, A. B. and Pringle, M. J. Estimating average and proportional variograms of soil properties and their potential use in precision agriculture. Precision Agric. 1999, 1:125-152.
  9. Trangmar, B.B., Yost, R.S. and Uehara, G. Application of geostatistics to spatial studies of soil properties. Advances in Agronomy.1985, 38: 45-90.
  10. Huang, X., Skidmore, E.L. and Tibke, G. Spatial variability of soil properties along a transect of CRP and continuously cropped land. In: 10th International Soil Conservation Organization Meeting held, Purdue University and the USDA-ARS National Soil Erosion Research Laboratory, 1999, pp 641-647.
  11. Deutsch, C.V. Geostatistical reservoir modeling, 1st edn. Oxford University Press, New York. 2002.
  12. Schloeder, C.A., Zimmerman, N.E. and Jacobs, M.J. Comparison of methods for interpolating soil properties using limited data. Soil Science Society of America Journal, 2001, 65: 470-479.
  13. Robinson, T.P. and Metternicht, G. Testing the performance of spatial interpolation techniques for mapping soil properties. Computer and Electronic in Agriculture. 2006, 50: 97-108.
  14. Webster, R. The development of pedometrics. Geoderma.1994, 62: 1-15.
  15. Zhang, C.S., Selinus, O. and Schedin, J. Statistical analyses on heavy metal contents in till and root samples in an area of southeastern Sweden. Sci. Total Environ. 1998, 212: 217-232.
  16. Zhang, C.S., Selinusm O. and Wong, P. Spatial structures of cobalt, lead, and zinc contents in tills in southeastern Sweden. GFF (Transactions of the Geological Society in Stockholm) 2000, 122. 2:213-217.
  17. Webster, R. and Oliver, M.A. Geostatistics for Environmental Scientists. John Wiley and Sons, Brisbane, Australia. 2001.
  18. Corwin, D.L., Lesch, S.M., Shouse, P.J., Soppe, R. and Ayers, J.E. Identifying soil properties that influence cotton yield using soil sampling directed by apparent soil electrical conductivity. Agron. J. 2003, 95:352-364.
  19. Mueller, T.G., Hartsock, N.J., Stombaugh, T.S., Shearer, S.A., Cornelius, P.L. and Barnhise, R.I. Soil electrical conductivity map variability in limestone soil overlain by loess. Agron. J. 2003, 95:496-507.
  20. Sun, Y. X., Wu, C.Z., Zhu, K., Cui, Z., Chen, X. and Zhang, F. Influence of interpolation method and sampling number on spatial prediction accuracy of soil Olsen-P. Chinese J Applied Ecol. 2009, 20:673-678.
  21. Gundogdu, K.S. and Guney, I. Spatial analyses of groundwater levels using universal kriging. J Earth Sys Sci. 2007, 116(1): 49-55.
  22. Uyan, M. and Cay, T. Geostatistical methods for mapping groundwater nitrate concentrations. Paper presented at the 3rd international conference on cartography and GIS. Nessebar, Bulgaria. 15-20 June 2010.
  23. Burgess, T.M. and Webster, R. Optimal interpolation and isorithmic mapping of soil properties. I. 1980.
  24. Cambardella, C.A., Moorman, T.B., Novak, J.M., Parkin, T.B., Karlen, D.L., Turco, R.F. and Konopka, A.E. Field scale variability of soil properties in Central Iowa soils. Soil Science Society of America Journal 1994, 58:1501-1511.
  25. Cemek, B., Guler, M., Kilic¸ K., Demir, Y. and Arslan, H. Assessment of spatial variability in some soil properties as related to soil salinity and alkalinity in Bafra plain in northern Turkey. Environ. Monit. Assess. 2007, 124:223-234.
  26. Chien, Y.J., Lee, D.Y., Guo, H.Y. and Houng, K.H. Geostatistical analysis of soil properties of mid-west Taiwan Soils. Soil Sci. 1997, 162: 291-297.
  27. MacEachren, A.M and Davidson, J.V. Sampling and Isometric Mapping of Continuous Geographic Surfaces. The American Cartographer.1987, 14(4): 299-320.
  28. Carr, J.R. Data Visualization in the Geosciences. Upper Saddle River, NJ: Prentice Hall. 2002.
  29. Vos, B.D., Meirvenne, M.V., Quataert, P., Deckers, J. and Muys, B. Predictive quality of pedotransfer functions for estimating bulk density of forest soils. Soil Science Society of America Journal. 2005, 69(2): 500-510.
  30. Huang, S., Y. Yang and Y. Wang. A critical look at procedures for validating growth and yield models. In Modelling Forest Systems, eds. A. Amaro, D. Reed and P. Soares, 2003, 271-293. Wallingford, UK: CABI.
  31. Brouder, S.M., Hofmann, B.S. and Morris, D.K. Mapping soil pH: Accuracy of common soil sampling strategies and estimation techniques. Soil Science Society of America Journal 2005, 69: 427-442.
  32. Voltz, M. and Webster, R. A comparison of Kriging, cubic splines and classification for predicting soil properties from sample information. Journal of Soil Science. 1990, 31: 505-524.
  33. Bishop, T.F.A. and McBratney, A.B. A comparison of prediction methods for the creation of field-extent soil property maps. Geoderma. 2001, 103:149-160.
  34. Leenares, H., Okx, J.P. and Burrough, P.A. Comparison of spatial prediction methods for mapping floodplain soil pollution. CatenA. 1990, 17: 535-550.
  35. Salder, E.J., Busscher, W.J., Baur, P.J. and Karlen, D.L. Spatial scale requirements for precision farming: A case study in the southeastern USA. Agronomy Journal.1998, 90:191-197.
  36. Istok, J.D. and Cooper, R.M. Geostatistics applied to groundwater pollution. III: global estimates. J. Environ. Eng. 1998, 114: 915-928.
  37. Pisinaras, V., Tsihrintzis, V.A., Petalas, C. and Ouzounis, K. Soil salinization in the agricultural lands of Rhodope District, northeastern Greece. Environ Monit Assess. 2010, 166:79-94.
  38. Tsegaye, T. and Hill, R.L. Intensive tillage effects on spatial variability of soil test, plant growth, and nutrient uptake measurement. Soil Sci.1998, 163:155-165.
  39. Lark, R.M. Optimized spatial sampling of soil for estimation of the variogram by maximum likelihood. Geoderma. 2002, 105: 4980.
  40. Goovaerts, P. Geostatistics in soil science: state of the art and perspectives. Geoderma.1999, 89:1-45.
  41. Isaaks, E.H and R.M. Srivastava. An Introduction to Applied Geostatistics. New York, NY: Oxford University Press. 1989.
  42. Oliver, M.A. Geostatistics and its application to soil science. Soil Use and Management. 1987, 3:8-20.
  43. Vieira, S.R. and Gonzalez, A.P. Analysis of the spatial variability of crop yield and soil properties in small agricultural plots. Bragantia, Caminas. 2003, 62(1): 127-138.
  44. Santra, P., Chopra, U.K. and Chakraborty, D. Spatial variability of soil properties and its application in predicting surface map of hydraulic parameters in an agricultural farm. Current Science. 2008, 95:937-945.
  45. Ali, S.M. and Malik, R.N. Spatial distribution of metals in top soils of Islamabad city, Pakistan. Environ. Monit. Assess. 2011,172:1-16.
  46. Subbiah, B.W. and Asija, G.L. A rapid procedure for estimation of available nitrogen in soils. Curr. Sci. 1956, 25: 259-260.
  47. Olsen, S.R., Cole, C.V., Watanabe, F.S. and Dean, L.A. Estimation of available phosphorous in soils by extraction with sodium bicarbonate. U.S. Department of Agriculture.1954, Circular, 939.
  48. Hanway, J.J. and Heidel, H. Soil analyses methods as used in Iowa state college soil testing laboratory. Iowa Agric. 1952, 57:1-31.
  49. Lopez-Granados, F., Jurado-Exposito, M., Atenciano, S., Garcıa- Ferrer, A., Sanchez de la Orden, M., Garcıa-Torres, L. Spatial variability of agricultural soil parameters in southern Spain. Plant Soil. 2002, 246: 97-105.