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| Titel |
Statistical correlation between meteorological and rockfall databases |
| VerfasserIn |
A. Delonca, Y. Gunzburger, T. Verdel |
| 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 Sciences ; 14, no. 8 ; Nr. 14, no. 8 (2014-08-04), S.1953-1964 |
| Datensatznummer |
250118589
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| Publikation (Nr.) |
 copernicus.org/nhess-14-1953-2014.pdf |
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| Zusammenfassung |
| Rockfalls are a major and essentially unpredictable sources of danger,
particularly along transportation routes (roads and railways). Thus, the
assessment of their probability of occurrence is a major challenge for risk
management. From a qualitative perspective, it is known that rockfalls occur
mainly during periods of rain, snowmelt, or freeze–thaw. Nevertheless, from
a quantitative perspective, these generally assumed correlations between
rockfalls and their possible meteorological triggering events are often
difficult to identify because (i) rockfalls are too rare for the use of
classical statistical analysis techniques and (ii) not all intensities of
triggering factors have the same probability. In this study, we
propose a new approach for investigating the correlation of rockfalls with
rain, freezing periods, and strong temperature variations. This approach is
tested on three French rockfall databases, the first of which exhibits a
high frequency of rockfalls (approximately 950 events over 11 years),
whereas the other two databases are more typical (approximately 140 events
over 11 years). These databases come from (1) national highway RN1 on Réunion, (2) a railway in Burgundy, and (3) a railway
in Auvergne. Whereas a basic correlation analysis is only able to
highlight an already obvious correlation in the case of the "rich"
database, the newly suggested method appears to detect correlations even in
the "poor" databases. Indeed, the use of this method confirms the positive
correlation between rainfall and rockfalls in the Réunion database.
This method highlights a correlation between cumulative rainfall and
rockfalls in Burgundy, and it detects a correlation between the
daily minimum temperature and rockfalls in the Auvergne database. This new
approach is easy to use and also serves to determine the conditional
probability of rockfall according to a given meteorological factor. The
approach will help to optimize risk management in the studied areas based on
their meteorological conditions. |
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