Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/10571
AuthorsD'Amico, Maria* 
Tiberti, Mara Monica* 
Russo, Emiliano* 
Pacor, Francesca* 
Basili, Roberto* 
TitleGround-motion variability for single site and single source through deterministic stochastic method simulations: implications for PSHA
Issue DateApr-2017
Series/Report no.2/107 (2017)
DOI10.1785/0120150377
URIhttp://hdl.handle.net/2122/10571
Keywordsseismogenic sources
finite fault simulations
near source
directivity effects
ground motion variability
seismic hazard
Southern Italy
Subject Classification04.06. Seismology 
05.06. Methods 
AbstractThe ground-motion median and standard deviation of empirical groundmotion prediction equations (GMPEs) are usually poorly constrained in the nearsource region due to the general lack of strong-motion records. Here we explore the use of a deterministic–stochastic simulation technique, specifically tailored to reproduce directivity effects, to evaluate the expected ground motion and its variability at a near-source site, and seek a strategy to overcome the known GMPEs limitations. To this end, we simulated a large number of equally likely scenario events for three earthquake magnitudes (Mw 7.0, 6.0, and 5.0) and various source-to-site distances. The variability of the explored synthetic ground motion is heteroscedastic, with smaller values for larger earthquakes. The standard deviation is comparable with empirical estimates for smaller events and reduces by 30%–40% for stronger earthquakes. We then illustrate how to incorporate directivity effects into probabilistic seismichazard analysis (PSHA). This goal is pursued by calibrating a set of synthetic GMPEs and reducing their aleatory variability (∼50%) by including a predictive directivity term that depends on the apparent stress parameter obtained through the simulation method. Our results show that, for specific source-to-site configurations, the nonergodic PSHA is very sensitive to the additional epistemic uncertainty that may augment the exceedance probabilities when directivity effects are maximized. The proposed approach may represent a suitable way to compute more accurate hazard estimates.
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