ALBERT

Description: This study investigates the engineering applicability of two conceptually different finite-fault simulation techniques. We focus our attention on two important aspects: first to quantify the capability of the methods to reproduce the observed ground-motion parameters (peaks and integral quantities); second to quantify the dependence of the strong-motion parameters on the variability in the large-scale kinematic definition of the source (i.e., position of the nucleation point, value of the rupture velocity, and distribution of the final slip on the fault). We applied an approximated simulation technique, the deterministic-stochastic method and a broadband technique, the hybrid-integral-composite method, to model the 1984 M (sub w) 5.7 Gubbio, central Italy, earthquake, at five accelerometric stations. We first optimize the position of the nucleation point and the value of the rupture velocity for three different final slip distributions on the fault by minimizing an error function in terms of acceleration response spectra in the frequency band from 1 to 9 Hz. We found that the best model is given by a rupture propagating at about 2.65 km/sec from a hypocenter located approximately at the center of the fault. In the second part of the article we calculate more than 2400 scenarios varying the kinematic source parameters. At the five sites we compute the residuals distributions for the various strong-motion parameters and show that their standard deviations depend on the source parameterization adopted by the two techniques. Furthermore, we show that Arias Intensity (AI) and significant duration are characterized by the largest and smallest standard deviation, respectively. Housner Intensity is better modeled and less affected by uncertainties in the source kinematic parameters than AI. The fact that the uncertainties in the kinematic model affects the variability of different ground-motion parameters in different ways has to be taken into account when performing hazard assessment and earthquake engineering studies for future events.