GNGTS 2013 - Atti del 32° Convegno Nazionale

Bousquet, J.C. and Lanzafame G.; 2004: The tectonics and geodynamics of Mt. Etna: synthesis and interpretation of geological and geophysical data . Bonaccorso A., Calvari S., Coltelli M., Del Negro C. and Falsaperla S. (eds.), Mt. Etna: Volcano Laboratory, AGU Monograph, 143 pp. pp. 29–45. Gresta, S. and Patanè D.; 1987: Review of seismological studies at Mount Etna . Pure Appl. Geophys . , 125 , 951-970. Gresta, S. and Langer H.; 2002: Assessment of seismic potential in southeastern Sicily . In: Brebbia C.A. (ed), Risk Analysis III, WITpress Southampton, Boston, pp. 617-626. Gruppo Analisi Dati Sismici; 2013: Catalogo dei terremoti della Sicilia Orientale – Calabria Meridionale (1999-2011) . Istituto Nazionale di Geofisica e Vulcanologia, Catania, http://www.ct.ingv.it/ufs/analisti/catalogolist.php. Margottini, C., Molin D., Narcisi B. and Serva L.; 1987: Intensity vs. acceleration: Italian data. Proc. of Workshop on Historical Seismicity of central-eastern Mediterranean Region, 213-226, ENEA-IAEA, Roma. Montaldo V., Faccioli E., Zonno G., Akinci A. andMalagnini L.; 2005: Treatment of ground-motion predictive relationships for the reference seismic hazard map of Italy . J. Seism. 9 , 295-316. A SIMPLE EARTHQUAKE SIMULATOR TO EXPLORE THE COEFFICIENT OF VARIATION OF THE RECURRENCE TIME F. Visini 1 , B. Pace 2 1 Istituto Nazionale di Geofisica e Vulcanologia, L’Aquila, Italy 2 DiSPUTer - Università “G. d’Annunzio” Chieti-Pescara, Italy Introduction. Probabilistic fault-based and time-dependent seismic hazard studies are commonly used to forecast the time between consecutive earthquakes; however, the correct evaluation of key parameters, that are average recurrence time and coefficient of variation of the recurrences, is critical for obtaining accurate results. This study focuses on a fault system earthquake simulator that explores the variability in the coefficient of variation of the recurrence time by analysing the effects of the tectonic loading stress, the slip-rate variability and the fault system geometry. The simulations incorporate variability in the magnitude threshold and stress-dependent earthquake nucleation. The variability in earthquake recurrence intervals is typically defined using the coefficient of variation (CV) for a sequence of earthquakes, which is defined as the standard deviation of the recurrence times over their mean. Several studies acknowledge that the CV values for earthquake recurrence intervals are poorly constrained (e.g., Ellsworth et al. , 1999), and small differences in the CV can lead to order of magnitude differences in earthquake probability forecasts. We analyse data from a synthetic seismicity catalogue, whose geometry is based on an active normal fault system in central Italy, to obtain predictive CV equations. Methods. This study employs synthetic catalogues that are generated using a simulation based on elastic rebound theory (Reid, 1910). The model uses individual seismogenic sources (faults) and stress interactions (static Coulomb failure stress, CFS). The model has four key elements: 1) a geometric and energetic (slip rate and characteristic magnitude) description of the sources embedded in a fault system (Fig. 1a), 2) a driving mechanism that pushes the sources towards failure, 3) a rupture threshold definition based on the characteristic magnitude and 4) fault failures and fault interactions via induced changes in the CFS. The slip rate defined for each source is characterised by both annual and long-term variability (Fig. 1b). The annual slip rate variability (SRV a ) is computed each year and is confined within a user-defined range with respect to the previous year, whereas the long-term slip rate variability (SRV lt ) controls the upper and lower bounds of the slip rate. This solution prevents any unobserved jumps in the slip rates during the simulations while simultaneously allowing fluctuations in the slip rate. The rupture threshold is computed using the characteristic magnitude defined for each fault (Fig. 1c). The model incorporates uncertainty in the definition of the characteristic magnitude, 158 GNGTS 2013 S essione 2.1