Skip to main content
SpringerLink
Log in

Application of geostatistics and GIS technique to characterize spatial variabilities of bioavailable micronutrients in paddy soils

  • Original Article
  • Published:
Environmental Geology

Abstract

To understand the spatial dependency of bioavailable micronutrients in paddy soils, 134 soil samples were taken from Pinghu County, Zhejiang Province, south-east China to characterize the spatial variabilities of bioavailable Cu, Zn, Fe, and Mn. The geostatistics and geographic information system (GIS) techniques were applied. Bioavailable Zn and Mn were fitted to an exponential model with a range of 4.4 km and 2.97 km, respectively. Bioavailable Fe was fitted to the linear model with the longest range of 23.48 km. Bioavailable Cu did not show any spatial correlation with the fitted pure nugget effect model. Bioavailable Zn and Mn had strong spatial dependence due to the effects of intrinsic factors such as parent material, relief and soil types. Bioavailable Fe had moderate spatial dependence over a long distance. The spatial distribution of the four bioavailable micronutrients were significantly correlated to the soil formation factors. Human activity, such as application of fertilizer and pesticide, emission of waste gas and industrial pollution also had significant effects on the spatial distributions of the bioavailable micronutrients.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  • Cambardella CA, Moorman TB, Novak JM, Parkin TB, Turco RF, Konopka AE (1994) Field-scale variability of soil properties in central lowa soils. Soil Sci Soc Am J 58:1501–1511

    Google Scholar 

  • Chen Yong-liang, Han Shi-jie, Zhou Yu-mei (2002) The rhizosphere pH of Pinus Koraiensis seedlings as affected by N sources of different levels and its effect on the availability and uptake of Fe, Mn, Cu and Zn. J Forest Res 13(1):37–40

    Article  Google Scholar 

  • Chien YL, Lee DY, Guo HY, Houng KH (1997) Geostatistical analysis of soil properties of mid-west Taiwan soils. Soil Sci 162:291–297

    CAS  Google Scholar 

  • Cressie C (1990) The origins of kriging. Math Geo 22(2):239–252

    Google Scholar 

  • Goovaerts P (1999) Geostatistics in soil science: state-of-the-art and perspectives. Geoderma 89:1–45

    Article  Google Scholar 

  • Isaaks EH, Srivastava RM (1989) An introduction to applied geostatistics. Oxford University Press, New York

  • Liu GX (1996) Soil physical and chemical analysis and description of soil profiles. Standard Press, Beijing, China, pp 62–70

  • Liu XM, Xu JM, Zhang MK, Shi Z, Shi JC (2003) Study on spatial variability of soil nutrients in Taihu lake region——a case of Pinghu City in Zhejiang Province. Journal of Zhejiang University (Agric. and Life Sci.) 29:76–82 (in Chinese)

    Google Scholar 

  • Pan XB (1998) Development and application of Netherlandish crop models. World Agri 233:17–19 (in Chinese)

    Google Scholar 

  • Romic M, Romic D (2003) Heavy metals distribution in agricultural topsoils in urban area. Environ Geo 43:795–805

    CAS  Google Scholar 

  • Sokal RR, Rohlf FJ (1981) Biometry, 2nd Edn. WH Freeman and Company, New York

  • Steiger B von, Webster R, Schulin R, Lehmann R (1996) Mapping heavy metals in polluted soil by disjunctive kriging. Environ Pollu 94(2):205–215

    Article  Google Scholar 

  • Wang ZQ (1999) Geostatistics and its application in ecology. Science Press, Beijing, China, pp 162–192 (In Chinese)

  • White JG, Welch RM, Norvell WA (1997) Soil zinc map of the USA using geostatistics and geographic information system. Soil Sci Soc Am J 61:185–194

    CAS  Google Scholar 

  • Yu Pin Lin, Tsun Kuo Chang, Tung Po Teng (2001) Characterization of soil lead by comparing sequential Gaussian simulation, simulated annealing simulation and kriging methods. Environ Geo l 41:189–199

    Article  Google Scholar 

Download references

Acknowledgments

This research was sponsored in part by the National Key Basic Research Support Foundation (NKBPSF) of China (No. 1999011809). The authors would like to acknowledge the laboratory assistants for their analysis of soil samples.

Author information

Authors and Affiliations

  1. Institute of Soil and Water Resources and Environmental Science, College of Natural Resource and Environmental Sciences, Zhejiang University, 310029, Hangzhou, China

    J. M. Xu

Authors
  1. X. M. Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. J. M. Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. M. K. Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. J. H. Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. J. C. Shi
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. X. F. Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to J. M. Xu.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Liu, X.M., Xu, J.M., Zhang, M.K. et al. Application of geostatistics and GIS technique to characterize spatial variabilities of bioavailable micronutrients in paddy soils. Env Geol 46, 189–194 (2004). https://doi.org/10.1007/s00254-004-1025-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00254-004-1025-0

Keywords

Search

Navigation