Near Fault Broadband Ground Motion Simulations, using Empirical Green's Functions: Application to l'Aquila (Italy) and Upper Rhine Graben (France-Germany) Case of Study

Classically the seismic hazard estimation relies on several ground motion prediction equations (GMPEs) predicting the expected motion level in function of several parameters characterizing the source and the site. However, large earthquakes at short distances from faults are still not represented at all in the records. For this reason, it is difficult to obtain reliable predictions for larger magnitude and short distances where the largest amount of damages are usually observed. A possible strategy to fill this lack of information is to generate synthetic accelerograms based on an accurate modeling of both source and propagation process. In this work we present two applications of the Empirical Green's Function simulation technique (EGFt) to generate strong ground motion in near field. The advantage of the EGFt is that it does not require a detailed knowledge of the propagation medium since small events are used as medium transfer function provided the availability of small earthquakes located on the target fault and recorded at the target site. The first application is on L'Aquila 2009 M 6.3 earthquake, where this condition is fully satisfied, and the main event records provide a benchmark for the synthetic waveforms. The second application is on Upper Rhine Graben where active faults, producing micro seismic activity, are likely to contribute to the seismic hazard level at long return period of the nuclear power plant located close by. In order to quantify the fault contribution to the hazard, it is necessary to reliably estimate the ground motion prediction in the fault vicinity. Because of the limitations of GMPEs in near field, it is interesting to use EGFt to perform ground motion simulations, keeping in mind that here we do not have a benchmark so we are in 'blind' conditions and we need to extensively investigate the selection criteria of records to be used as EGF and the impact of source parameters on the ground motion prediction generating populations of synthetics that represent the natural variability of the source process. (author)