Back to Search
Start Over
Spatio-temporal maps of past avalanche events derived from tree-ring analysis: A case study in the Zermatt valley (Valais, Switzerland)
- Source :
- Cold Regions Science and Technology, Cold Regions Science and Technology, Elsevier, 2018, 154, pp.9-22. ⟨10.1016/j.coldregions.2018.06.004⟩, Cold Regions Science and Technology, Elsevier, 2018, ⟨10.1016/j.coldregions.2018.06.004⟩, Cold Regions Science and Technology, 2018, 154, pp.9-22. ⟨10.1016/j.coldregions.2018.06.004⟩, Cold Regions Science and Technology, Vol. 154 (2018) pp. 9-22
- Publication Year :
- 2018
- Publisher :
- HAL CCSD, 2018.
-
Abstract
- [Departement_IRSTEA]Eaux [ADD1_IRSTEA]Hydrosystèmes et risques naturels; International audience; Expected runout distances and related return periods are the most important parameters needed for zoning in terrain prone to snow avalanching. Hazard mapping procedures usually allocate areas of land to zones with a different degree of danger based on return periods estimated for given snow volumes in the starting zone or with statistical/dynamical models. On forested avalanche paths, dendrogeomorphology has a great potential to add critical input data to these calculations in terms of recurrence intervals or return periods. However, quite paradoxically, recurrence interval maps of snow avalanches have only rarely been retrieved from tree-ring analysis and mostly represent the inverse of the mean frequency of avalanches that could be retrieved locally rather than the return period. The purpose of this study therefore was to propose a consistent approach for treering based recurrence interval mapping of snow avalanche events. On the basis of 71 snow avalanches retrieved from 2570 GD growth disturbances identified in 307 larch trees from three avalanche paths located in the vicinity of Tasch (Canton of Valais, Swiss Alps), we first followed the classical approach used in dendrogeomorphology and derived recurrence interval maps through interpolation from recurrence intervals observed at the level of individual trees. We then applied an expert delineation of the spatial extent of past events based on the location of disturbed trees. Our results show that the second step improved representation of expected patterns of recurrence intervals that typically increase as one moves down the centerline of the avalanche path. Despite remaining limitations and uncertainties precluding from direct use of our maps for hazard mapping purpose, these results suggest that dendrogeomorphic time series of snow avalanches can yield valuable information for the assessment of recurrence intervals of avalanches on forested paths for which only very limited or no historical data exists, and that this data can be obtained independently from meteorological data or numerical modeling.
- Subjects :
- Return period
ddc:333.7-333.9
021110 strategic, defence & security studies
010504 meteorology & atmospheric sciences
[SDE.MCG]Environmental Sciences/Global Changes
0211 other engineering and technologies
Terrain
02 engineering and technology
[SHS.GEO]Humanities and Social Sciences/Geography
15. Life on land
Geotechnical Engineering and Engineering Geology
Snow
Mean frequency
01 natural sciences
[SDE.ES]Environmental Sciences/Environmental and Society
Dendrochronology
ddc:550
General Earth and Planetary Sciences
Interval (graph theory)
Physical geography
Spatial extent
Geology
ComputingMilieux_MISCELLANEOUS
0105 earth and related environmental sciences
Interpolation
Subjects
Details
- Language :
- English
- ISSN :
- 0165232X
- Database :
- OpenAIRE
- Journal :
- Cold Regions Science and Technology, Cold Regions Science and Technology, Elsevier, 2018, 154, pp.9-22. ⟨10.1016/j.coldregions.2018.06.004⟩, Cold Regions Science and Technology, Elsevier, 2018, ⟨10.1016/j.coldregions.2018.06.004⟩, Cold Regions Science and Technology, 2018, 154, pp.9-22. ⟨10.1016/j.coldregions.2018.06.004⟩, Cold Regions Science and Technology, Vol. 154 (2018) pp. 9-22
- Accession number :
- edsair.doi.dedup.....a0a5a8a925bee967d56b339b2cacd0e3
- Full Text :
- https://doi.org/10.1016/j.coldregions.2018.06.004⟩