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| Titel |
Probabilistic approach to rock fall hazard assessment: potential of historical data analysis |
| VerfasserIn |
C. Dussauge-Peisser, A. Helmstetter, J.-R. Grasso, D. Hantz, P. Desvarreux, M. Jeannin, A. Giraud |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1561-8633
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| Digitales Dokument |
URL |
| Erschienen |
In: Natural Hazards and Earth System Science ; 2, no. 1/2 ; Nr. 2, no. 1/2, S.15-26 |
| Datensatznummer |
250000262
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| Publikation (Nr.) |
 copernicus.org/nhess-2-15-2002.pdf |
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| Zusammenfassung |
| We study the rock
fall volume distribution for three rock fall inventories and we fit the
observed data by a power-law distribution, which has recently been
proposed to describe landslide and rock fall volume distributions, and is
also observed for many other natural phenomena, such as volcanic eruptions
or earthquakes. We use these statistical distributions of past events to
estimate rock fall occurrence rates on the studied areas. It is an
alternative to deterministic approaches, which have not proved successful
in predicting individual rock falls. The first one concerns calcareous
cliffs around Grenoble, French Alps, from 1935 to 1995. The second data
set is gathered during the 1912–1992 time window in Yosemite Valley,
USA, in granite cliffs. The third one covers the 1954–1976 period in the
Arly gorges, French Alps, with metamorphic and sedimentary rocks. For the
three data sets, we find a good agreement between the observed volume
distributions and a fit by a power-law distribution for volumes larger
than 50 m3 , or 20 m3 for the Arly gorges. We obtain
similar values of the b exponent close to 0.45 for the 3 data sets. In
agreement with previous studies, this suggests, that the b value is
not dependant on the geological settings. Regarding the rate of rock fall
activity, determined as the number of rock fall events with volume larger
than 1 m3 per year, we find a large variability from one site
to the other. The rock fall activity, as part of a local erosion rate, is
thus spatially dependent. We discuss the implications of these
observations for the rock fall hazard evaluation. First, assuming that the
volume distributions are temporally stable, a complete rock fall inventory
allows for the prediction of recurrence rates for future events of a given
volume in the range of the observed historical data. Second, assuming that
the observed volume distribution follows a power-law distribution without
cutoff at small or large scales, we can extrapolate these predictions to
events smaller or larger than those reported in the data sets. Finally, we
discuss the possible biases induced by the poor quality of the rock fall
inventories, and the sensibility of the extrapolated predictions to
variations in the parameters of the power law. |
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