Environmental Geology

, Volume 55, Issue 7, pp 1569–1576 | Cite as

Spatial variability of soil available Zn and Cu in paddy rice fields of China

  • Xingmei Liu
  • Jianming Xu
  • Minghua Zhang
  • Bingcheng Si
  • Keli Zhao
Original Article
First Online:
Received:
Accepted:

Abstract

As a source of nutrient supplements, the deficiency or excess of micronutrients in soil is directly connected to the plant uptake and, thereby, status of micronutrients in the human population. Proper management of micronutrients requires an understanding of the variations of soil micronutrients across the fields. This study is to investigate the spatial patterns of soil available Zn and Cu in paddy rice fields. Four hundred and sixty three soil samples were taken in Hangzhou–Jiaxing–Huzhou (HJH) watershed in Zhejiang Province, China, and available Zn and Cu were analyzed using an atomic adsorption spectrometer. Geostatistical semivariograms analysis indicated that the available Zn and Cu were best fitted to a spherical model with a range of 40.5 and 210.4 km, respectively. There were moderate spatial dependences for Zn and Cu over a long distance and the dependence were attributed to soil types and anthropogenic activities. The overlay analysis of spatial patterns and soil types gave us greater understanding about how intrinsic factors affect the spatial variation of available micronutrients. Based on the above, macroscopically regionalized management of soil available micronutrients and the implications to potential risk were discussed.

Keywords

Geostatistics Paddy rice fields Available micronutrients Spatial variability Risk assessment 
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Notes

Acknowledgments

This research was sponsored in part by the National Natural Science Foundation project of China (40601051) and the China Postdoctoral Science Foundation (20060391061). Authors thank the colleagues Darren Ficklin and Lisa Fernandez for providing precious review comments.

References

  1. Altman DG (1991) Practical statistics for medical research. Chapman & Hall, LondonGoogle Scholar
  2. Cahn MD, Hummel JW, Brouer BH (1994) Spatial analysis of soil fertility for site-specific crop management. Soil Sci Soc Am J 58:1240–1248CrossRefGoogle Scholar
  3. 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 58:1501–1511CrossRefGoogle Scholar
  4. Chang YH, Scrimshaw MD, Emmerson RH, Lester JN (1998) Geostatistical analysis of sampling uncertainty at the tollesbury managed retreat site in Blackwater Estuary, Essex, UK: kriging and cokriging approach to minimise sampling density. Sci Total Environ 221:43–57CrossRefGoogle Scholar
  5. Chien YJ, Lee DY, Guo HY (1997) Geostatistical analysis of soil properties of mid-west Taiwan soils. Soil Sci 162(4):291–298CrossRefGoogle Scholar
  6. Corwin DL, Lesch SM, Shouse PJ, Soppe R, Ayers JE (2003) Identifying soil properties that influence cotton yield using soil sampling directed by apparent soil electrical conductivity. Agron J 95:352–364CrossRefGoogle Scholar
  7. Cressie C (1990) The origins of kriging. Math Geol 22(2):239–252CrossRefGoogle Scholar
  8. Goovaerts P (1999) Geostatistics in soil science: state-of-the-art and perspectives. Geoderma 89(1–2):1–45CrossRefGoogle Scholar
  9. Huang SW (2002) Study on spatial variability and regionalized management of soil nutrients. PhD thesis, Beijing (in Chinese)Google Scholar
  10. Isaaks EH, Srivastava RM (1989) An introduction to applied geostatistics. Oxford University Press, New York, p 500Google Scholar
  11. Jeffrey GW, Robert JZ (1999) Mapping soil micronutrients. Field Crop Res 60:11–26CrossRefGoogle Scholar
  12. JAR Martion ML Arias JMG Corbi (2006) Heavy metals contents in agricultural topsoils in the Ebro basin (Spain). Application of the multivariate geostatistical methods to study spatial variations. Environ Pollut 144:1001–1012CrossRefGoogle Scholar
  13. Kashem MA, Singh BR (2001) Metal availability in contaminated soils: effects of flooding and organic matter on changes in Eh, pH and solubility of Cd, Ni and Zn. Nutr Cycl Agroecosyst 61:247–255CrossRefGoogle Scholar
  14. Lindsay WL, Norvell WL (1978) Development of DTPA soil test for zinc, iron, manganese and copper. Soil Sci Soc Am J 42:421–428CrossRefGoogle Scholar
  15. Liu XM, Xu JM, Zhang MK, Huang JH, Shi JC, Yu XF (2004) Application of geostatistics and GIS technique to characterize spatial variabilities of available micronutrients in paddy soils. Environ Geol 46:189–194CrossRefGoogle Scholar
  16. Liu XM, Wu JJ, Xu JM (2006) Characterizing the risk assessment of heavy metals and sampling uncertainty analysis in paddy field by geostatistics and GIS. Environ Pollut 141:257–264CrossRefGoogle Scholar
  17. Mantovi P, Bonazzi G, Marmiroli N (2003) Accumulation of copper and zinc from liquid manure in agricultural soils and crop plants. Plant Soil 250:249–257CrossRefGoogle Scholar
  18. Mueller TG, Hartsock NJ, Stombaugh TS, Shearer SA, Cornelius PL, Barnhise RI (2003) Soil electrical conductivity map variability in limestone soil overlain by loess. Agron J 95:496–507CrossRefGoogle Scholar
  19. Nicholson FA, Smith SR, Alloway BJ, Carlton-Smith C, Chambers BJ (2003) An inventory of heavy metal input to agricultural soil in England and Wales. Sci Total Environ 311:205–219CrossRefGoogle Scholar
  20. Oliver MA (1997) Soil and human health: a review. Eur J Soil Sci 48(4):573–592CrossRefGoogle Scholar
  21. Qian XH (2001) Evaluation for agricultural non-point source pollution in the HJH watershed and the control measures. M.Sc. thesis, Hangzhou (in Chinese)Google Scholar
  22. Sharma BD, Harsh-Arora, Raj-Kumar, Nayyar VK (2004) Relationships between soil characteristics and total and DTPA-extractable micronutrients in inceptisols of Punjab. Comm Soil Sci Plant Anal 35:799–818CrossRefGoogle Scholar
  23. Sokal RR, Rohlf FJ (1981) Biometry, 2 edn. W H Freeman and Company, New YorkGoogle Scholar
  24. Solie JB, Raun WR, Stone ML (1999) Submeter spatial variability of selected soil and bermudagrass production variables. Soil Sci Soc Am J 63:1724–1733CrossRefGoogle Scholar
  25. State Environmental Protection Administration of China (1995) Chinese environmental quality standard for soils (GB 15618–1995). http://www.chinaep.net/hjbiaozhun/hjbz/hjbz017.htm
  26. Wang ZQ (1999) Geostatistics and its application in ecology. Science Press, Beijing, pp 162–192 (in Chinese)Google Scholar
  27. Webster R, Nortcliff S (1984) Improved estimation of micro-nutrients in hectare plots of the Sonning series. J Soil Sci 35:667–672CrossRefGoogle Scholar
  28. Webster R, Oliver MA (2001) Geostatistics for environmental scientists. Wiley, New YorkGoogle Scholar
  29. White JG, Welch RM, Norvell WA (1997) Soil Zn map of the USA using geostatistics and geographic information systems. Soil Sci Soc Am J 61:185–194CrossRefGoogle Scholar
  30. Wilcke W (2000) Small-scale variability of metal concentrations in soil leachates. Soil Sci Soc Am J 64(1):138–143CrossRefGoogle Scholar
  31. Yost RS, Uehara G, Fox RL (1982) Geostatistical analysis of soil chemical properties of large land areas. I. Semivariagrams. Soil Sci Soc Am J 46:1028–1037CrossRefGoogle Scholar
  32. Zhejiang Provincial Bureau of Statistics (2001) Zhejiang statistical yearbook. Chinese Statistical Press, Beijing (in Chinese)Google Scholar

Copyright information

© Springer-Verlag 2007

Authors and Affiliations

  • Xingmei Liu
    • 1
    • 2
  • Jianming Xu
    • 1
  • Minghua Zhang
    • 2
  • Bingcheng Si
    • 3
  • Keli Zhao
    • 1
  1. 1.Institute of Soil and Water Resources and Environmental Science, College of Environmental and Natural Resources ScienceZhejiang UniversityHangzhouChina
  2. 2.Department of Land, Air and Water ResourcesUniversity of CaliforniaDavisUSA
  3. 3.Department of Soil ScienceUniversity of SaskatchewanSaskatoonCanada

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