Skip to main content

Abstract

In Canada, ice jam events have frequently produced the most extreme and dangerous flood events on record, resulting in millions of dollars in associated damages. However, our ability to forecast such events remains quite limited. An example of this is the Athabasca River at Fort McMurray, Alberta, where severe ice jam events have been documented for over 100 years, and where breakup has been monitored intensively for the past 25 years. Despite these efforts, no reliable flood forecast model is yet available. Here, the use of Fuzzy Expert Systems is explored to examine their potential for developing long lead time ice jam risk forecasts for this site. The developed System identified seven out of twenty two years that had the potential for high water levels, including all four years where high water levels actually occurred. These preliminary results suggest that Fuzzy Expert Systems are promising tools for long range ice jam flood forecasting.

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

Access this chapter

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

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Bardossy A, Duckstein L (1995) Fuzzy rule-based modeling with applications to geophysical, biological and engineering systems. Bahill AT (ed) CRC Press, Inc. Boca, Florida

    Google Scholar 

  • Beltaos S (1984) Study of river ice breakup using hydrometric station records. Proc Workshop on Hydraulics of River Ice. Fredericton, Canada, pp 41–59

    Google Scholar 

  • Doyle CJ (1987) Hydrometeorological aspects of ice jam formation at Fort McMurray, Alberta. M.Sc. thesis, University of Alberta, Edmonton, Alberta

    Google Scholar 

  • Hicks F, Beltaos S (2007) River ice. (Vol. II, this book)

    Google Scholar 

  • Ishibuchi H, Nakashima T (2001) Effect of rule weights in fuzzy rule-based classification systems. IEEE T Fuzzy Syst 9:506–515

    Article  Google Scholar 

  • Klir GJ, St Clair UT, Yuan B (1997) Fuzzy set theory foundations and applications. Prentice-Hall, Inc.

    Google Scholar 

  • Mahabir C, Hicks F, Fayek AR (2002) Forecasting ice jam risk at Fort McMurray, AB, using fuzzy logic. Proc 16th IAHR International Symposium on Ice, International Association of Hydraulic Engineering and Research, New Zealand, December 2–6, pp 91–98

    Google Scholar 

  • Robichaud C (2003) Hydrometeorological factors influencing breakup ice jam occurrence at Fort McMurray, Alberta. M.Sc. thesis, University of Alberta, Edmonton, Alberta

    Google Scholar 

  • Robichaud C, Hicks F (2001) A remote water level network for breakup monitoring and flood forecasting. Proc. 11th Workshop on River Ice, Ottawa, May, pp 292–307

    Google Scholar 

  • See L, Openshaw S (1999) Applying soft computing approaches to river level forecasting. Hydrol Sci J 44:763–776

    Article  Google Scholar 

  • Shulyakovskii LG (1963) Manual of ice-formation forecasting for rivers and inland lakes. Israel Program for Scientific Translations TT 66–51016, Jerusalem, Israel (1966)

    Google Scholar 

  • Zadeh LA (1965) Fuzzy sets. Inform Control 8:338–353

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Mahabir, C., Robichaud, C., Hicks, F., Fayek, A.R. (2008). Regression and Fuzzy Logic Based Ice Jam Flood Forecasting. In: Woo, Mk. (eds) Cold Region Atmospheric and Hydrologic Studies. The Mackenzie GEWEX Experience. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75136-6_16

Download citation

Publish with us

Policies and ethics