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Authors: Ameri, G.* 
Emolo, A.* 
Pacor, F.* 
Gallovic, F.* 
Title: Ground-Motion Simulations for the M 6.9 Irpinia 1980 Earthquake (Southern Italy) and Scenario Events
Issue Date: 2010
Keywords: Irpinia 1980 earthquake
ground-motion simulation
ground-motion variability
scenario events
Subject Classification04. Solid Earth::04.06. Seismology::04.06.99. General or miscellaneous 
04. Solid Earth::04.06. Seismology::04.06.03. Earthquake source and dynamics 
04. Solid Earth::04.06. Seismology::04.06.04. Ground motion 
Abstract: In this paper, we adopt three ground-motion simulation techniques (EXSIM, Motazedian and Atkinson, 2005, DSM, Pacor et al., 2005 and HIC, Gallovič and Brokešová, 2007), with the aim of investigating the different performances in near-fault strong-motion modeling and prediction from past and future events. The test case is the 1980, M 6.9, Irpinia earthquake, the strongest event recorded in Italy. First, we simulate the recorded strong-motion data and validate the model parameters by computing spectral acceleration and peak amplitudes residual distributions. The validated model is then used to investigate the influence of site effects and to compute synthetic ground motions around the fault. Afterward, we simulate the expected ground motions from scenario events on the Irpinia fault, varying the hypocenters, the rupture velocities and the slip distributions. We compare the median ground motions and related standard deviations from all scenario events with empirical ground motion prediction equations (GMPEs). The synthetic median values are included in the median ± one standard deviation of the considered GMPEs. Synthetic peak ground accelerations show median values smaller and with a faster decay with distance than the empirical ones. The synthetics total standard deviation is of the same order or smaller than the empirical one and it shows considerable differences from one simulation technique to another. We decomposed the total standard deviation into its between-scenario and within-scenario components. The larger contribution to the total sigma comes from the latter while the former is found to be smaller and in good agreement with empirical inter-event variability.
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