Skip to main content
SpringerLink
Log in

Surface Generation

  • Chapter
  • First Online:
Distributed Hydrologic Modeling Using GIS

Part of the book series: Water Science and Technology Library ((WSTL,volume 74))

Abstract

The importance in hydrology of generating two-dimensional surfaces from data measured at points cannot be overstated. Transformation from point to raster data structures is often accomplished through interpolation of point data to form a two-dimensional surface. The difficulty with some interpolation methods is that the surface is organized around the point locations. The inverse distance weighting interpolation assigns a grid value based on the surrounding point values and distance away. If interpolated with the IDW method, it can appear that rain preferentially falls around the gauge, rather than having a more natural distribution geographically. It is important to understand how these surfaces are generated and the influence of the resulting surface on hydrologic modeling. The subject of this chapter is the methods and pitfalls of interpolation.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 109.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 139.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 139.99
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

Institutional subscriptions

References

  • Barnes, S.L. 1964. A technique for maximizing details in a numerical weather map analysis. Journal of Applied Meteorology 3: 396–409.

    Article  Google Scholar 

  • Bartier, P.M., and P. Keller. 1996. Multivariate interpolation to incorporate thematic surface data using inverse distance weighting (IDW). Computers & Geosciences 22(7): 795–799.

    Article  Google Scholar 

  • Borga, M., and A. Vizzaccaro. 1997. On the interpolation of hydrologic variables: formal equivalence of multiquadratic surface fitting and Kriging. Journal of Hydrology 195: 160–171.

    Article  Google Scholar 

  • Cappelaere, B., B.E. Vieux, C. Peugeot, A. Maia, and L. Séguis. 2003. Hydrologic process simulation of a semi-arid, endoreic catchment in Sahelian West Niger, Africa: II. Model calibration and uncertainty characterization. Journal of Hydrology 279(1–4): 244–261.

    Article  Google Scholar 

  • Chaturvedi, A.K., and L.A. Piegl. 1996. Procedural method for terrain surface interpolation. Computer & Graphics 20(4): 541–566.

    Article  Google Scholar 

  • Clarke, K.C. 1990. Analytical and computer cartography, 290. New Jersey: Prentice-Hall, Englewood.

    Google Scholar 

  • Desconnets, J.C., B.E. Vieux, B. Cappelaere, and F. Delclaux. 1996. A GIS for hydrological modelling in the semi-arid, HAPEX-Sahel experiment area of Niger, Africa. Transactions in GIS 1(2): 82–94.

    Article  Google Scholar 

  • Goutorbe, J.-P., T. Lebel, A. Tinga, P. Bessemoulin, J. Bouwer, A.J. Dolman, E.T. Wingman, J.H.C. Gash, M. Hoepffner, P. Kabat, Y.H. Kerr, B. Monteny, S.D. Prince, F. Saïd, P. Sellers, and J.S. Wallace. 1994. Hapex-Sahel: a large scale study of land-surface interactions in the semi-arid tropics. Annales Geophysicae 12: 53–64.

    Article  Google Scholar 

  • Hengl, T., G.B. Heuvelink, and D.G. Rossiter. 2007. About regression-kriging: from equations to case studies. Computers & Geosciences 33(10): 1301–1315.

    Article  Google Scholar 

  • Hutchinson, M.F., and P.E. Gessler. 1994. Splines—more than just a smooth interpolator. Geoderma 62: 45–67.

    Article  Google Scholar 

  • Journel, A.G., and C.J. Huijbregts. 1978. Mining Geostatistics. New York: Academic Press.

    Google Scholar 

  • Krige, D.G. 1951. A statistical approach to some mine valuations and allied problems at the Witwatersrand, Master’s thesis of the University of Witwatersrand.

    Google Scholar 

  • Laslett, G.M., A.B. McBratney, P.H. Pahl, and M.F. Hutchinson. 1987. Comparison of several spatial prediction methods for soil pH. Journal of Soil Science 37: 617–639.

    Google Scholar 

  • Laslett, G.M. 1994. Kriging and splines: An empirical comparison of their predictive performance in some applications. Journal of American Statistical Association 89: 391–409.

    Article  Google Scholar 

  • Matheron, G. 1965. Les Variables Régionalisées et leur Estimation. Paris: Masson.

    Google Scholar 

  • Matheron, G. 1981. Splines and Kriging: their formal equivalence. In: Down to Earth statistics: solutions looking for geological problems. Syracuse University.

    Google Scholar 

  • Mitasova, H., and J. Hofierka. 1993. Interpolation by regularized spline with tension: II. Application to terrain modeling and surface geometry analysis. Mathematical Geology 25(6): 657–669.

    Article  Google Scholar 

  • Mitasova, H., and L. Mitas. 1993. Interpolation by regularized spline with tension I. Theory and implementation. Mathematical Geology 25(6): 641–655.

    Article  Google Scholar 

  • Neteler, M., M.H. Bowman, M. Landa, and M. Metz. 2012. GRASS GIS: A multi-purpose open source GIS. Environmental Modelling & Software, 31: 124–130.

    Google Scholar 

  •  Odeha, I.O., A.B. McBratney, and D.J. Chittleborough. 1994. Spatial prediction of soil properties from landform attributes derived from a digital elevation model. Geoderma 63(3): 197–214.

    Article  Google Scholar 

  • Odeha, I.O., A.B. McBratney, and D.J. Chittleborough. 1995. Further results on prediction of soil properties from terrain attributes: heterotopic cokriging, and regression kriging. Geoderma 67(3): 215–226.

    Article  Google Scholar 

  • Peugeot, C., B. Cappelaere, B.E. Vieux, L. Séguis, and A. Maia. 2003. Hydrologic process simulation of a semi-arid, endoreic catchment in Sahelian West Niger, Africa: I. Model-aided data analysis and screening. Journal of Hydrology 279(1–4): 244–261.

    Google Scholar 

  • Séguis, L., B. Cappelaere, C. Peugeot, and B.E. Vieux. 2002. Impact on Sahelian runoff of stochastic and elevation-induced spatial distributions of soil parameters. Journal of Hydrological Processes 16(2): 313–332.

    Article  Google Scholar 

  • Todini, E., and M. Ferraresi. 1996. Influence of parameter estimation uncertainty in Kriging. Journal of Hydrology 175: 555–566.

    Article  Google Scholar 

  • Vieux, 2006. Rain Gauge Network Optimization Study. West Palm Beach Florida: Report submitted to the South Florida Water Management District.

    Google Scholar 

  • Vieux, B., and Pathak, C. 2007. Evaluation of Rain Gauge Network Density and NEXRAD Rainfall Accuracy. Proceedings of the American Society of Civil Engineers, World Environmental and Water Resources Congress, 1–12. doi:10.1061/40927(243)278.

  • Voltz, M., and R. Webster. 1990. A comparison of kriging, cubic splines and classification for predicting soil properties from sample information. Journal of Soil Science 41: 473–490.

    Article  Google Scholar 

  • Zhu, Q., and H.S. Lin. 2010. Comparing ordinary kriging and regression kriging for soil properties in contrasting landscapes. Pedosphere 20(5): 594–606.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Professor Emeritus, School of Civil Engineering and Environmental Science, University of Oklahoma, Norman, OK, USA

    Baxter E. Vieux

  2. Principal, Vieux & Associates, Inc., Norman, OK, USA

    Baxter E. Vieux

Authors
  1. Baxter E. Vieux
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Baxter E. Vieux .

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer Science+Business Media Dordrecht

About this chapter

Cite this chapter

Vieux, B.E. (2016). Surface Generation. In: Distributed Hydrologic Modeling Using GIS. Water Science and Technology Library, vol 74. Springer, Dordrecht. https://doi.org/10.1007/978-94-024-0930-7_3

Download citation

Publish with us

Policies and ethics

Search

Navigation