The recurrence time statistics of a cellular automaton modelling landslide events is analyzed by performing a numerical analysis in the parameter space and estimating Fano factor behaviors. Simulation results are qualitatively compared with those from a recent analysis performed by Witt et al.(Earth Surf. Process. Landforms, 35, 1138, 2010) for the first complete databases of landslide occurrences over a period as large as fifty years. From the comparison with the extensive landslide data set, the numerical analysis suggests that statistics of such landslide data seem to be described by a crossover region between a correlated regime and an uncorrelated regime, where recurrence time distributions are characterized by power-law and Weibull behaviors for short and long return times, respectively. Finally, in such a region of the parameter space, clear indications of temporal correlations and clustering by the Fano factor behaviors support, at least in part, the analysis performed by Witt et al. (2010).

Recurrence time statistics of landslide events simulated by a cellular automaton model / Piegari, E.; DI MAIO, Rosa; Avella, A.. - In: GEOPHYSICAL RESEARCH ABSTRACTS. - ISSN 1607-7962. - 16:(2014), pp. 8994-8994.

Recurrence time statistics of landslide events simulated by a cellular automaton model

PIEGARI E.;DI MAIO, ROSA;
2014

Abstract

The recurrence time statistics of a cellular automaton modelling landslide events is analyzed by performing a numerical analysis in the parameter space and estimating Fano factor behaviors. Simulation results are qualitatively compared with those from a recent analysis performed by Witt et al.(Earth Surf. Process. Landforms, 35, 1138, 2010) for the first complete databases of landslide occurrences over a period as large as fifty years. From the comparison with the extensive landslide data set, the numerical analysis suggests that statistics of such landslide data seem to be described by a crossover region between a correlated regime and an uncorrelated regime, where recurrence time distributions are characterized by power-law and Weibull behaviors for short and long return times, respectively. Finally, in such a region of the parameter space, clear indications of temporal correlations and clustering by the Fano factor behaviors support, at least in part, the analysis performed by Witt et al. (2010).
2014
Recurrence time statistics of landslide events simulated by a cellular automaton model / Piegari, E.; DI MAIO, Rosa; Avella, A.. - In: GEOPHYSICAL RESEARCH ABSTRACTS. - ISSN 1607-7962. - 16:(2014), pp. 8994-8994.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/577941
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