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Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 8, issue 4 | Copyright
Nat. Hazards Earth Syst. Sci., 8, 685-705, 2008
https://doi.org/10.5194/nhess-8-685-2008
© Author(s) 2008. This work is distributed under
the Creative Commons Attribution 3.0 License.

  16 Jul 2008

16 Jul 2008

Regional evaluation of three day snow depth for avalanche hazard mapping in Switzerland

D. Bocchiola1, E. Bianchi Janetti1, E. Gorni1, C. Marty2, and B. Sovilla2 D. Bocchiola et al.
  • 1Dept. of Hydraulic, Environmental, Surveying and Road Structures Engineering, Politecnico di Milano, L. Da Vinci Square 32, 20133 Milano, Italy
  • 2WSL, Swiss Federal Institute for Snow and Avalanche Research SLF, Flüelastr. 11, 7260 Davos Dorf, Switzerland

Abstract. The distribution of the maximum annual three day snow fall depth H72, used for avalanche hazard mapping according to the Swiss procedure (Sp), is investigated for a network of 124 stations in the Alpine part of Switzerland, using a data set dating back to 1931. Stationarity in time is investigated, showing in practice no significant trend for the considered period. Building on previous studies about climatology of Switzerland and using an iterative approach based on statistical tests for regional homogeneity and scaling of H72 with altitude, seven homogenous regions are identified. A regional approach based on the index value is then developed to estimate the T-years return period quantiles of H72 at each single site i, H72i(T). The index value is the single site sample average μH72i. The dimensionless values of H*72i=H72i / μH72i are grouped in one sample for each region and their frequency of occurrence is accommodated by a General Extreme Value, GEV, probability distribution, including Gumbel. The proposed distributions, valid in each site of the homogeneous regions, can be used to assess the T-years return period quantiles of H*72i. It is shown that the value of H72i(T) estimated with the regional approach is more accurate than that calculated by single site distribution fitting, particularly for high return periods. A sampling strategy based on accuracy is also suggested to estimate the single site index value, i.e. the sample average μH72i, critical for the evaluation of the distribution of H72i. The proposed regional approach is valuable because it gives more accurate snow depth input to dynamics models than the present procedure based on single site analysis, so decreasing uncertainty in hazard mapping procedure.

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