Skip to main navigation menu Skip to main content Skip to site footer
Plant Science Today (PST)

Research Articles

Vol. 13 No. sp1 (2026): Recent Advances in Agriculture

Geostatistical variability of soil properties of Jajmau tannery industrial zone of Kanpur, Uttar Pradesh

DOI
https://doi.org/10.14719/pst.10700
Submitted
17 July 2025
Published
13-02-2026

Abstract

In the present study, different soil properties such as pH, electrical conductivity (EC), organic carbon (OC) and the heavy metals chromium (Cr), lead (Pb) and zinc (Zn) were mapped spatially using geostatistical methods. Geostatistical tools including ordinary kriging interpolation technique were utilized to investigate the variability. Accurate and rapid assessment of soil properties is a key component of agriculture. A total of 116 surface soil samples (0–25 cm) were obtained at an interval of 250 m with GPS coordinates from the study area. The highest (93.76 %) variation was observed in the total Cr, whereas the lowest (4.75 %) was found in soil pH. The best variogram model fit in ordinary kriging was selected based on the accuracy of standardized mean error (MSE) nearest to zero, the smallest root-mean-squared prediction error (RMSE), the average standard error (ASE) nearest the root-mean squared prediction error and the standardized root-mean-squared prediction error (RMSSE) nearest one. The results indicated that soil pH, EC and Cd were best fitted to the spherical model, whereas soil OC, Pb, Cr and Zn best fitted to the Gaussian model. All the soil pollutants (Cr, Cd, Pb and Zn) were found above the permissible limits in soil, with Cr around 10 times higher than the recommended threshold. The spatial variability of important soil properties is valuable for planning remediation and management practices at regional scale.

References

  1. 1. Tiwari KK, Singh NK, Patel MP, Tiwari MR, Rai UN. Metal contamination of soil and translocation in vegetables growing under industrial wastewater irrigated agricultural field of Vadodara, Gujarat, India. Ecotoxicol Environ Saf. 2011;74:1670–7. https://doi.org/10.1016/j.ecoenv.2011.04.029
  2. 2. Gandhi G, Savalia SG. Soil-site suitability evaluation for mustard in calcareous soils of Girnar toposequence in Southern Saurashtra region of Gujarat. J Oilseed Brassica. 2014;5:128–33.
  3. 3. Sahu N, Pipalde D, Jain RC, Gupta SC. Geo-statistical analysis of soil pollutants of tannery industrial area, Kanpur. Indian J Ecol. 2024;51(1):113–7.
  4. 4. Divya A, Josphineleela R, Jaba Sheela L. A machine learning based approach for prediction and interpretation of soil properties from soil spectral data. J Environ Biol. 2024;45(1):96–105. https://doi.org/10.22438/jeb/45/1/MRN-5134
  5. 5. Ramzan S, Wani MA, Bhat MA. Assessment of spatial variability of soil fertility parameters using geostatistical techniques in temperate Himalayas. Int J Geosci. 2017;8:1251–63. https://doi.org/10.4236/ijg.2017.810072
  6. 6. Li GS, Wang XZ, Zhang ZY, Zhang CH. Spatial variability of soil properties in a tobacco field of Central China. Soil Sci. 2008;173(9):659–67. https://doi.org/10.1097/SS.0b013e3181847ea0
  7. 7. Yong ZS, Yul L, Halin Z. Soil properties and their spatial pattern in a degraded sandy grassland under post-grazing restoration, Inner Mongolia, northern China. Biogeochemistry. 2006;79:297–314. https://doi.org/10.1007/s10533-005-5273-1
  8. 8. Nogiya M, Moharana PC, Meena R, Yadav B, Jangir A, Malav LC, et al. Spatial variability of soil variables using geostatistical approaches in the hot arid region of India. Environ Earth Sci. 2024;83:432. https://doi.org/10.1007/s12665-024-11737-5
  9. 9. Usowicz B, Lipiec J. Spatial variability of soil properties and cereal yield in a cultivated field on sandy soil. Soil Tillage Res. 2017;174:1–9. https://doi.org/10.1016/j.still.2017.07.015
  10. 10. World Health Organization. Permissible limits of heavy metals in soil and plants. Geneva: WHO; 1996.
  11. 11. McLean EO. Soil pH and lime requirement. In: Page AL, editor. Methods of Soil Analysis. Part 2. Agronomy Monograph No. 9. 2nd ed. Madison (WI): ASA; 1982. https://doi.org/10.2134/agronmonogr9.2.2ed.c12
  12. 12. Walkley A, Black IA. An examination of the Degtjareff method for determining soil organic matter and a proposed modification of the chromic acid titration method. Soil Sci. 1934;37(1):29–38. https://doi.org/10.1097/00010694-193401000-00003
  13. 13. Hutton M, Symon C. The quantities of cadmium, lead, mercury and arsenic entering the UK environment from human activities. Sci Total Environ. 1986;57:129–50. https://doi.org/10.1016/0048-9697(86)90018-5
  14. 14. Erxleben J, Elder K, Davis R. Comparison of spatial interpolation methods for estimating snow distribution in the Colorado Rocky Mountains. Hydrol Process. 2002;16(18):3627–49. https://doi.org/10.1002/hyp.1239
  15. 15. Robinson TP, Metternicht G. Testing the performance of spatial interpolation techniques for mapping soil properties. Comput Electron Agric. 2006;50:97–108. https://doi.org/10.1016/j.compag.2005.07.003
  16. 16. Kerry R, Goovaerts P, Rawlins BG, Marchant BP. Disaggregation of legacy soil data using area to point kriging for mapping soil organic carbon at the regional scale. Geoderma. 2012;170:347–58. https://doi.org/10.1016/j.geoderma.2011.10.007
  17. 17. Wilding LP. Spatial variability: Its documentation, accommodation and implication to soil surveys. In: Nielsen DR, Bouma J, editors. Soil Spatial Variability. Wageningen: Pudoc; 1985.
  18. 18. Bouma J, Pinke PA. Soil specific crop management. In: Robert PC, Rust RH, Larson WE, editors. Soil Specific Crop Management. Madison (WI): ASA, CSSA, SSSA; 1996. p. 207.
  19. 19. Cohen JE, Davis RA, Samorodnitsky G. Heavy-tailed distributions, correlations, kurtosis and Taylor’s law of fluctuation scaling. Proc R Soc A. 2020;476(2244):20200610. https://doi.org/10.1098/rspa.2020.0610
  20. 20. Hegde R, Bardhan G, KV, Bhaskar NB, BP, Singh SK. Spatial variability and mapping of selected soil properties in Kaligaudanahalli microwatershed, Gundlupet Taluk, Chamarajanagar District, Central Karnataka Plateau, India. SN Appl Sci. 2019. https://doi.org/10.1007/s42452-019-0486-4
  21. 21. Kumar P, Sharma M, Butail NP, Shukla AK, Kumar P. Spatial variability of soil properties and delineation of management zones for Suketi basin, Himachal Himalaya, India. Environ Dev Sustain. 2023. https://doi.org/10.1007/s10668-023-03181-5

Downloads

Download data is not yet available.