Arabian Journal of Geosciences

, Volume 8, Issue 12, pp 10693–10703 | Cite as

Characterizing spatial variability of soil properties in salt affected coastal India using geostatistics and kriging

  • Rahul Tripathi
  • A. K. Nayak
  • Mohammad Shahid
  • R. Raja
  • B. B. Panda
  • S. Mohanty
  • Anjani Kumar
  • B. Lal
  • Priyanka Gautam
  • R. N. Sahoo
Original Paper
First Online:
Received:
Accepted:

Abstract

Soil salinization is a major problem affecting 955 Mha globally and 7 Mha in India. Soil properties vary spatially and knowing the extent of spatial variability of soil physicochemical characteristics is highly essential for management of these soils and crop cultivation. This study was conducted in salt-affected coastal parts of eastern India, with the following objectives: (i) to explore the spatial variability of soil properties (soil electrical conductivity (ECe), soil pH, soil organic carbon (SOC), available soil nitrogen, available soil phosphorus, and available soil potassium) and fitting the semivariogram models; (ii) to estimate the values of soil properties at unsampled locations using geostatistical tools; and (iii) to prepare the spatial maps of soil properties using parameters of best fit semivariogram model and interpolation by ordinary kriging technique. A total of 132 soil samples were collected. Gaussian, exponential, circular, spherical, K-Bessel, and spherical semivariogram models were found to be the best fit for assessing the spatial variability in ECe, soil pH, SOC, available soil nitrogen, available soil phosphorus, and available soil potassium, respectively. The best fit model parameters were used to create the spatial maps for these soil properties by ordinary kriging. It was concluded that geostatistical and kriging tools can be used to estimate the value of soil properties at unsampled locations and ultimately to develop spatial maps for site-specific nutrient management.

Keywords

Soil electrical conductivity Interpolation Soil organic carbon Kriging Semivariogram Soil salinity 
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Notes

Acknowledgments

The authors would like to thank the Director of Central Rice Research Institute for providing the laboratory facilities and Indian Council of Agricultural Research, New Delhi, for providing financial support in conducting this study. Technical help provided by Chandan Kumar Ojha and Brindaban Das is also acknowledged.

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Copyright information

© Saudi Society for Geosciences 2015

Authors and Affiliations

  1. 1.Central Rice Research InstituteCuttackIndia
  2. 2.Indian Agricultural Research InstituteNew DelhiIndia

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