Estimation of extreme runout frequencies based on observed short term frequencies<br />Kalle Kronholm<br />Krister Kristen...
Hazard zoning in Norway<br />Level 1 (municipality): Susceptibility maps<br />Level 2 (regulation plan): mainly 1/1000 => ...
Motivation<br />Not rely on empirical or dynamical models alone, also use field information, as quantitatively as possible...
Classical model used: α-β model<br />Relate terrain parameters to run-out<br />Lied and Bakkehøi (1980), Bakkehøi et al. (...
Extended α-β model<br />Objective method for choosing actual hazard zone<br />Harbitz et al. (2001)<br />Additional assump...
Our use of the extended α-β model<br />Find a place in a path where the “safe” period Δtsafe can be estimated (e.g. 100 ye...
The study area<br />
Study area<br />
The study area<br />
The study area<br />
Field evidence used<br />Written and oral evidence<br />Old maps and air photos<br />Destroyed trees<br />Vegetation types...
Field evidence: Destroyed trees<br />
Field evidence: Old farm houses<br />
Field evidence: Plunge pools<br />
Results<br />Estimated 1/100-year “safe” return periods for 31 avalanche paths from field evidence<br />Calculated the 1/1...
Location of the “observed” 100y point<br />Flat profile which was just below 10° for long distance<br />Similar plot for t...
Location of calculated 1000y point<br />Very close agreement with the alfa-1 point<br />Use in hazard zoning when good obs...
Location of the actual hazard zone<br />The alfa 0 runout length was used for hazard zoning with minor local adjustments (...
Conclusions<br />Based on limited data!<br />Need data from other climate areas and larger areas<br />The method is promis...
Acknowledgements<br />Research was carried out through a snow avalanche research grant from OED/NVE 200905737-3<br />
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Kronholm IGS 2010, Sapporo

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Presentation at the International Glaciological Society seminar in Sapporo, Japan, 2010

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Kronholm IGS 2010, Sapporo

  1. 1. Estimation of extreme runout frequencies based on observed short term frequencies<br />Kalle Kronholm<br />Krister Kristensen<br />IGS 2010, Sapporo<br />
  2. 2. Hazard zoning in Norway<br />Level 1 (municipality): Susceptibility maps<br />Level 2 (regulation plan): mainly 1/1000 => purely frequency <br />Level 3 (building plan): if frequency >1/1000 => pressure to design and dimension<br />
  3. 3. Motivation<br />Not rely on empirical or dynamical models alone, also use field information, as quantitatively as possible<br />Estimating low frequency (extreme) events based on field evidence is impossible<br />Traces from frequent events can be observed in field and associated return period may be estimated<br />Use field observations on frequent events and their runout lengths to estimate low frequency events <br />
  4. 4. Classical model used: α-β model<br />Relate terrain parameters to run-out<br />Lied and Bakkehøi (1980), Bakkehøi et al. (1983)<br />α = 0.96β -1,4° + W, W~N(0, 2.3°)<br />Issue: any choice of σ can be chosen by practitioner to represent hazard zone (e.g. 1/1000)<br />
  5. 5. Extended α-β model<br />Objective method for choosing actual hazard zone<br />Harbitz et al. (2001)<br />Additional assumptions about extreme value (Gumbel) distributions of runout angles in classical model<br />The annual probability of being hit by an avalanche does not exceed 1/Δtsafe<br />The return period of avalanches in the path is Δtrelease<br />
  6. 6. Our use of the extended α-β model<br />Find a place in a path where the “safe” period Δtsafe can be estimated (e.g. 100 years)<br />Using the “extended” equations and assumptions, calculate the return period of avalanches in the path<br />Using the calculated return period, use the “extended” equations to calculate the needed Δtsafe (e.g. 1000 years)<br />
  7. 7. The study area<br />
  8. 8. Study area<br />
  9. 9.
  10. 10.
  11. 11.
  12. 12. The study area<br />
  13. 13. The study area<br />
  14. 14. Field evidence used<br />Written and oral evidence<br />Old maps and air photos<br />Destroyed trees<br />Vegetation types<br />Old farms<br />Plunge pools<br />
  15. 15. Field evidence: Destroyed trees<br />
  16. 16. Field evidence: Old farm houses<br />
  17. 17. Field evidence: Plunge pools<br />
  18. 18. Results<br />Estimated 1/100-year “safe” return periods for 31 avalanche paths from field evidence<br />Calculated the 1/1000-year points in paths (“extended” α-β model)<br />Calculated classical α-β model results, based on terrain and climate we used 0 and -1 σ<br />Hazard zones for 1/1000 years – the “truth”…?<br />
  19. 19. Location of the “observed” 100y point<br />Flat profile which was just below 10° for long distance<br />Similar plot for the angles, large variation in runout length<br />Generally located between beta point and alfa 0<br />100y point related to topographical parameters identified in the α-β model<br />
  20. 20. Location of calculated 1000y point<br />Very close agreement with the alfa-1 point<br />Use in hazard zoning when good observations available?<br />
  21. 21. Location of the actual hazard zone<br />The alfa 0 runout length was used for hazard zoning with minor local adjustments (local topography, climate)<br />Actual hazard zone less conservative than the calculated suggestions based on the most conservative estimate<br />
  22. 22. Conclusions<br />Based on limited data!<br />Need data from other climate areas and larger areas<br />The method is promising <br />Theoretically appealing because it objectively uses (subjective) information as quantitatively as possible<br />Method is more conservative than standard methods<br />There are other interpretations of the extreme value used, we tested the most conservative – test the others<br />Bad for customers, but it is a nice theoretical framework<br />
  23. 23. Acknowledgements<br />Research was carried out through a snow avalanche research grant from OED/NVE 200905737-3<br />

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