This work presents an up-to-date model for the simulation of non-stationary ground motions, including several novelties compared to the original study of Sabetta and Pugliese (Bull Seism Soc Am 86:337–352, 1996). The selection of the input motion in the framework of earthquake engineering has become progressively more important with the growing use of nonlinear dynamic analyses. Regardless of the increasing availability of large strong motion databases, ground motion records are not always available for a given earthquake scenario and site condition, requiring the adoption of simulated time series. Among the different techniques for the generation of ground motion records, we focused on the methods based on stochastic simulations, considering the time- frequency decomposition of the seismic ground motion. We updated the non-stationary stochastic model initially developed in Sabetta and Pugliese (Bull Seism Soc Am 86:337–352, 1996) and later modified by Pousse et al. (Bull Seism Soc Am 96:2103–2117, 2006) and Laurendeau et al. (Nonstationary stochastic simulation of strong ground-motion time histories: application to the Japanese database. 15 WCEE Lisbon, 2012). The model is based on the S-transform that implicitly considers both the amplitude and frequency modulation. The four model parameters required for the simulation are: Arias intensity, significant duration, central frequency, and frequency bandwidth. They were obtained from an empirical ground motion model calibrated using the accelerometric records included in the updated Italian strong-motion database ITACA. The simulated accelerograms show a good match with the ground motion model prediction of several amplitude and frequency measures, such as Arias intensity, peak acceleration, peak velocity, Fourier spectra, and response spectra.

The latest studies concerning seismic risk assessment in Italy were developed without considering the site geo-lithological effects, thus limiting the assessment to rock soil type. In this study, for the evaluation of site amplification effects, we used the results of recent works based on the Italian seismic microzonation data. As this first study is performed for the entire Italian territory at the municipality scale, the site amplification factors (AFs) have been assigned to the chief town of each of the 7715 Italian municipalities, assuming that the building stock is concentrated in that small area. The AFs have been compared with those foreseen by the Italian building code (NTC2018). The PGA amplification with the new AFs ranges from 1 to 2.2 bringing to an average increase of 75% in the hazard, compared to 27% if using the NTC2018 amplification. The seismic risk has been evaluated using the probabilistic hazard assessment adopted in the NTC2018 and recent vulnerability/exposure models developed for Italy. The residential building stock was subdivided into 5 vulnerability classes (3 for masonry and 2 for concrete) derived from the national census data and further refined using the construction age and building height. The results show that, for a rock site condition, the loss estimates are comparable with those of previous works in terms of casualties, homeless, and economic damage. The introduction of the site effects brings to a significant increase in the expected losses resulting higher than the historical data retrieved from a careful analysis of the major Italian earthquakes. This suggests the importance of developing new fragility curves based on updated AFs. To support the implementation of risk reduction programs, a seismic risk index is introduced, allowing a municipality ranking by risk, a cost estimation of the seismic retrofitting in the highest risk municipalities, and an assessment of the consequent risk reduction.

Ground motion prediction equations are a key element of seismic hazard assessments. Pakistan lacks a robust ground motion prediction equation specifically developed using a Pakistan seismic ground motion databank. In this study, performance assessment of the ground motion prediction equations for usage in seismic hazard and risk studies in Pakistan, a seismically highly active region, is performed. In this study, an evaluation of the global ground motion prediction equations developed for the shallow active regions is carried out based on a databank of strong ground motion that was compiled in this study. Thirteen ground motion prediction equations were considered applicable, and their goodness of fit was evaluated using the databank of 147 peak ground acceleration of 27 shallow earthquakes in Pakistan. Residual analysis and three goodness of fit procedures were implemented in the evaluation of the equations. The results of this study suggest that global ground motion prediction equations can be applicable in the shallow active regions of Pakistan. These equations were developed based on data from Europe and the Middle East. Next Generation Attenuation West-2 equations were also applicable, but they did not perform as well as the European and Middle Eastern databank-derived equations. A total of four global equations were applicable in Pakistan. The best performing equation in this study should be applied with the highest weight, and the others should be applied with small weights on the logic tree to perform better. These equations can be employed in seismic hazard and risk assessment studies for disaster risk mitigation measures.

In this paper, the main features of the policies adopted in Italy for seismic risk reduction are discussed. Particular attention is given to the Pre-disaster prevention activities such as the implementation of the building code, the seismic risk assessment for a priority scale of intervention, tax incentives and public funding for the vulnerability reduction of the existing buildings, information to population and school education, technical training of experts. The phases of response and post-disaster activities, including emergency management, search and rescue, loss scenarios, and safety assessment of buildings, are also discussed taking example from the most recent devastating earthquakes in Italy (L.Aquila 2009, Amatrice 2016).

Author supplied incorrect ESM as tables were duplicated.