Skip to main content

Spatial Variability of Soil Properties at Hillslope Level

  • Conference paper
  • 560 Accesses

Part of the book series: Quantitative Geology and Geostatistics ((QGAG,volume 13))

Abstract

The aim of this paper is to analyze the spatial structure of several soil properties at 0–30 cm soil depth: pH in water and in KCl, contents of organic matter, sand, silt and clay, at a 2.1 ha hillslope in northwest Spain. The semivariograms and correlations between these soil properties and several variables derived from DEM (Digital Elevation Model) data, such as slope and elevation, were calculated. A medium correlation was found between pH and elevation, and the results obtained using kriging with external drift were similar to those obtained with ordinary kriging. Estimations of sand, silt and clay contents were used to calculate texture maps using ordinary kriging and Gaussian conditional simulation. Small differences were observed between maps obtained with these two methods.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Chilès, J-P. and Delfiner, P. (1999). Geostatistics Modeling Spatial Uncertainty. New York: John Wiley & Sons.

    Google Scholar 

  2. Deutsch, C.V. and Journel, A.G. (1997). GSLIB, Geostatistical Software Library and User’s Guide. New York: Oxford University Press.

    Google Scholar 

  3. Frogbrook, Z.L.; Oliver, M.A.; Salahi, M.; Ellis, R.H. (2002). Exploring the spatial relations between cereal yield and soil chemical properties and the implications for sampling. Soil Use and Management. 18:1–9

    Google Scholar 

  4. Gomes, F.P. (1984). A estatistica Moderna na Pesquisa Agropecuaria. Piraçicaba: Associaçao Brasileira para Pesquisa da Potassa e do Fosfato.

    Google Scholar 

  5. Goovaerts, P. (1997). Geostatistics for Natural Resources Evaluation. New York: Oxford University Press.

    Google Scholar 

  6. Goovaerts, P. (2000a). Estimation or simulation of soil properties? An optimization problem with conflicting criteria. Geoderma, 97: 165–186

    Article  Google Scholar 

  7. Goovaerts, P. (2000b). Geostatistical approaches for incorporating elevation into the spatial interpolation of rainfall. J. of Hydrology; 228: 113–129

    Article  Google Scholar 

  8. Guitián, F. & Carballas, T. (1976). Técnicas de Análisis de Suelos. Santiago de Compostela: Ed. Pico Sacro.

    Google Scholar 

  9. ISSS-FAO-ISRIC. (1994). World Reference Base for Soil Resources. Wageningen/Rome: ISSS-ISRIC-FAO.

    Google Scholar 

  10. MAPA (Ministerio de Agricultura, Pesca y Alimentación) (1986). Métodos Oficiales de Análisis de Suelos, Aguas y Plantas. Tomo III., Madrid: Ministerio de Agricultura, Pesca y Alimentación. Servicio de Publicaciones.

    Google Scholar 

  11. Martínez, J.R.; Klein, E.; de Pablo, J.G. & González, F. (1984). El Complejo de Órdenes: subdivisión, descripción y discusión sobre su origen. Cadernos Lab. Xeololóxico de Laxe; 7:139–210.

    Google Scholar 

  12. Pannatier, Y. (1996). VARIOWIN: Software for Spatial Data Analysis in 2D. New York: Springer-Verlag.

    Google Scholar 

  13. Parga Pondal, I. (1956). Nota explicativa de mapa geológico de la parte NO de la provincia de La Coruña. Leidse Geol. Med.; 21:468–484.

    Google Scholar 

  14. Pebesma, E.J. (2001). Gstat User’s Manual. Utrecht: Dept. of Physical Geography, Utrecht University.

    Google Scholar 

  15. PCRaster Environmental Software. (1997). PCRaster Version 2. Utretch: Dept. of Physical Geography, Utrecht University.

    Google Scholar 

  16. Samper, J. and Carrera, J. (1990). Geoestadística. Aplicaciones a la Hidrología Subterránea. Barcelona: CIMNE.

    Google Scholar 

  17. Wilding, L.P.; Bouma, J.; Boss, D.W. (1994). “Impact of spatial variability of interpretive modeling” In Quantitative Modeling of Soil Forming Processes SSSA Special Publ., No. 39, R.B. Bryant and R.W. Arnold (Ed.). Madison: SSSA.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2004 Kluwer Academic Publishers

About this paper

Cite this paper

Ulloa, M., Dafonte, J. (2004). Spatial Variability of Soil Properties at Hillslope Level. In: Sanchez-Vila, X., Carrera, J., Gómez-Hernández, J.J. (eds) geoENV IV — Geostatistics for Environmental Applications. Quantitative Geology and Geostatistics, vol 13. Springer, Dordrecht. https://doi.org/10.1007/1-4020-2115-1_41

Download citation

  • DOI: https://doi.org/10.1007/1-4020-2115-1_41

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-1-4020-2007-0

  • Online ISBN: 978-1-4020-2115-2

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics