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| Titel |
Recurrence time distribution and temporal clustering properties of a cellular automaton modelling landslide events |
| VerfasserIn |
E. Piegari, R. Maio, A. Avella |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1023-5809
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| Digitales Dokument |
URL |
| Erschienen |
In: Nonlinear Processes in Geophysics ; 20, no. 6 ; Nr. 20, no. 6 (2013-12-05), S.1071-1078 |
| Datensatznummer |
250086080
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| Publikation (Nr.) |
 copernicus.org/npg-20-1071-2013.pdf |
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| Zusammenfassung |
| Reasonable prediction of landslide occurrences in a given area requires the
choice of an appropriate probability distribution of recurrence time
intervals. Although landslides are widespread and frequent in many parts of
the world, complete databases of landslide occurrences over large periods are
missing and often such natural disasters are treated as processes
uncorrelated in time and, therefore, Poisson distributed. In this paper, we
examine the recurrence time statistics of landslide events simulated by a
cellular automaton model that reproduces well the actual frequency-size
statistics of landslide catalogues. The complex time series are
analysed by varying both the
threshold above which the time between events is recorded and the values of
the key model parameters. The synthetic recurrence time probability
distribution is shown to be strongly dependent on the rate at which
instability is approached, providing a smooth crossover from a power-law
regime to a Weibull regime. Moreover, a Fano factor analysis shows a clear
indication of different degrees of correlation in landslide time series. Such
a finding supports, at least in part, a recent analysis performed for the
first time of an historical landslide time series over a time window of fifty
years. |
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