GNGTS 2014 - Atti del 33° Convegno Nazionale

14 GNGTS 2014 S essione 2.1 P s are model outcomes in the form of exceedance probabilities (a Poisson process is assumed here) of any ground motion value g s in a fixed exposure time T s at the s -th site; N * indicates the number of times that g s is exceed by observations at S sites during the time period T s . The statistical test can be also applied to evaluate the feasibility of the models (i.e., probability p that N * or less exceedances are expected to occur if the i -th model is “correct”). The scoring procedure was applied taking into account the PGA values recorded at 73 accelerometric stations (belonging to the RAN – Rete Accelerometrica Nazionale) operating in Italy for at least 25 years. For these sites, the PGA hazard was calculated accounting for local soil conditions. Results (for PGA only) are presented in Tab. 2 and discussed in the next section. Discussion and conclusions. Two decades of research efforts on GMPEs seem to have lead to fruitful results: 1 - with the exception of CF08 andAB10, recent GMPEs (i.e., hazard models based on recent GMPEs) are found to be more effective in providing PGA hazard estimates supported by available observations, at least for short-to-medium mean return periods; 2 - BND 13 performs better than previous models based on European and Middle East data; 3 - BOR13 performs better than its predecessor BA08. Tab. 2 - Results of the scoring test. The values in each cell indicate the likelihood of each model. They may be adopted to select and weight GMPEs in a logic tree scheme. In addition to the previous observations, it is worth observing that: a) ITA08 is found to be the most effective model. The lower performance of ITA10 could be attributed to the distance metrics adopted. ITA08 uses R epi, a distance measure that is fully compatible with the way the earthquake sources (area sources in this application) are modeled in the code used for PSH analysis; b) PGA hazard models based on GMPEs that ignore the contribution of M < 5 (nearby) events (SP96, AMB05, CF08, and AB10) tend to underestimate observations; c) among dated GMPEs, AMB96 is found to be the most effective model. However, at lower mean return periods, it tends to provide PGA hazard values that overestimate observations (see also Fig. 3).