GNGTS 2014 - Atti del 33° Convegno Nazionale

12 GNGTS 2014 S essione 2.1 Improvement in ground motion predictions and effect on seismic hazard. A first answer to the provocative question posed above may be given by analyzing the residuals between observed and predicted ground motion values. In this study, we apply the method proposed by Spudich et al. (1999) which uses the maximum likelihood formalism to calculate the mean value of the residuals (bias) and their dependence on magnitude and distance. The residual analysis (Fig. 2) is carried out for the seismic stations AQP (L’Aquila) and MRN (Mirandola), which recorded the 2009 L’Aquila sequence and the 2012 Emilia seismic crisis, respectively. Analyzing Fig. 2 in conjunction with Fig. 1b indicates that, although sigma has been increasing with time, the (absolute) residuals between observed and predicted ground motion values tend to decrease, thus suggesting an improvement in the GMPE performance (i.e., in the predictions) that will be reflected in the hazard results. Fig. 2 – Residuals (absolute values) between observed and expected ground motion for the test sites of L’Aquila (AQP) and Mirandola (MRN). Residuals for BOR13 are not yet available. Inorder toassess the effect of eachGMPEon thehazard,we carriedout different computational runs by varying one GMPE at a time while keeping constant the remaining PSH input models (e.g., source zone model) and parameter values (e.g., b -values, M max ). The reference seismic hazard model considers the same set of input models and parameters adopted by Barani et al. (2009) for the disaggregation of the Italian ground motion hazard maps (Gruppo di Lavoro MPS, 2004). This set of inputs is that providing hazard results closer to the median values obtained using the entire logic tree (Gruppo di Lavoro MPS, 2004). If necessary, magnitude