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Citizen science has proven very useful to increase awareness and preparedness of societies prone to disaster risk. The active involvement of citizens is also strongly envisaged by strategic documents related to disaster risk reduction (e.g. SENDAI Framework, United Nations Global Assessment Report). Here, we describe the CEDAS (building CEnsus for seismic Damage ASsessment) project, which involved high-school students in citizen science activities related to seismic risk reduction. In particular, students collected data on building characteristics (e.g. height, material) near to their homes using their phone or personal computer. Prior to data collection students were trained on risk-related concepts (hazard, exposure and vulnerability) with specific focus on buildings exposure the area where the activity was carried out (northeastern Italy). CEDAS was implemented in 2021 and 2022 involving approximately 320 students who collected more than 6000 building forms. The CEDAS project is not only data collection: students also analyzed the data and compared the exposure parameters in different areas. Finally, the interpreted the results with the help of teachers and researchers. CEDAS has demonstrated its potential for collecting exposure data in seismic-prone areas and/or include characteristics useful for multi-hazard and multi-risk assessment. However, its generalization requires the adaptation of the training material to the specific context. This presentation will support the discussion on CEDAS based on active involvement of participants. Attendants will have the opportunity to test the CEDAS approach for selected buildings. Pictures of the building front and aerial view, together with a street view, will be displayed on the screen. The active involvement of participants will support the discussion both on technical (e.g. parameters to be prioritized during the collection) and communication (e.g. citizens engagement and training) aspects. The discussion will also cover future developments of CEDAS, in particular in relation to risk awareness and preparedness (e.g. definition of impact assessment metrics).

A tsunami induced by a shallow offshore earthquake of magnitude Mw=6.7 occurred south of the island of Crete (Greece) on May 2nd, 2020. The initial tsunami alert message (TAMs) received by the Egyptian National Tsunami Warning Focal Point for Egypt (i.e. Egyptian National Research Institute of Astronomy and Geophysics-NRIAG) was issued by the Geodynamic Institute of the National Observatory of Athens (NOA-HLNTWC), and was based on preliminary, rather inaccurate hypocenter and magnitude estimates. About 36 minutes after the earthquake, a follow-up message with an increased tsunami warning level was issued; the updated warning was motivated by a significant revision of earthquake source parameters estimates. The later message, however, was issued without taking into account the available observations from sea-level data. In this study we investigate the effectiveness and usefulness of the TAM messages received by NRIAG for the coastal areas of Egypt (including the issue time and the source parameters on which the messages are based), by cross-checking them against observed and modelled seismological and sea level data. Based on results from the critical review of the tsunami warning messages, disseminated by NOA-HLNTWC and other TSPs in the Eastern Mediterranean Sea and received by NRIAG (which is a TWFP for Egypt), a comprehensive revision of the tsunami early warning system tools and procedures seems urgently needed in the region. The active involvement of countries along the southern coast of the Mediterranean turns out to be crucial, as the analysis shows that tsunami warning can only be efficient with international cooperation on data (seismic and sea level) and procedures.

We investigate earthquake clustering, a prominent feature of seismic catalogs, in terms of distribution of the number of triggered events as described by a branching process (Kagan and Knopoff, Phys. Earth Planet. Inter., 1976; Saichev et al., Pure Appl. Geophys., 2005, and references therein). According to recent literature (e.g. Shebalin et al., Geophys. J. Int., 2020, and references therein), the productivity of a magnitude m event is defined as the number of triggered events of magnitude above m-Δ, where Δ is a positive default value. For a magnitude m event, we distinguish between the number of its direct descendants and the total number of its descendants, denoted respectively by the random variables v and V, both depending on Δ. Empirical analysis often testifies in favor of the identity of the type of distribution of both quantities (v and V) associated with the main event, and hypothetically is exponential. The testing or substantiation of this hypothesis is important for modeling seismicity and presents a serious challenge for seismic statistics. In the standard Epidemic Type Aftershock Sequence – ETAS – model (Ogata, Ann. Inst. Stat. Math., 1998), the distribution of v is Poissonian. Therefore we consider the general ETAS model adapted to any distribution of v and prove that the branching structure of the model excludes the possibility of having a common distribution type (for example, Poisson or exponential) for both v and V at once (Molchan et al., Geophys. J. Int., 2022). The second theoretical result relates to the behaviour of the tails of the productivity distribution. We show that there is a fundamental difference in tail behavior of the V-distributions for general-type clusters and for clusters with a dominant initial magnitude: the tail is heavy in the former case and light in the latter. The real data display similar behavior. Theoretical conclusions are also illustrated through the analysis of a synthetic earthquake catalog.

An adequate characterization of the temporal features of background seismicity, namely after removal of temporally and spatially clustered events (e.g. aftershocks), is a key element in several studies aimed at earthquake forecasting and seismic hazard assessment. In order to investigate the features of background seismicity component, we analyse the rate of background events, that is the rate of main/independent earthquakes as identified by Nearest Neighbour (NN) and Stochastic Declustering (SD) methods. The use of two different declustering methods, which are based on diverse statistical and physical assumptions, allows us to assess whether the identified features depend on the specific definition of background events. In this study, we carry out an in depth analysis of the time changes of background seismicity rate in Northeastern Italy, by means of continuous-time Hidden Markov Models, a stochastic tool that can be used to assess heterogeneity in the temporal pattern of seismicity rates. Specifically, we aim at understanding if the analysed time series can be better described by a homogeneous Poisson model, with unique constant rate, or by a switched Poisson model (i.e. linked to some systematic changes in earthquakes occurrence rates) or whether a basically different model is required. The analysis performed based on Markov modulated Poisson process, and according to Bayesian Information Criterion, shows that a switched Poisson process with three states is the best model describing the background rate identified by SD and NN approaches. The capability of adopted methodology in identifying seismicity rate changes, as well as the sensitivity of the method against the minimum magnitude threshold of analysis, have been verified by applying the method to synthetic catalogues with known properties, namely Poissonian time series with different rates prescribed in specific time intervals. The obtained results suggest that a Poisson model with multiple rates can be used to properly describe background seismicity in Northeastern Italy.

The National Institute of Oceanography and Applied Geophysics – OGS is engaged in a wide range of educational and training activities for more than a decade, mainly focused on seismic risk mitigation through data acquisition in the field and practical stages. To by-pass the restrictions imposed by the COVID-19 pandemic, in 2021 OGS started a new project, deployed in fully remote mode, to involve high-school students and increase their risk awareness and preparedness. The Project, named “CEDAS: building CEnsus for seismic Damage Assessment”, consists in the collection and elaboration of data which is included in the exposure database. Knowing the type and distribution of exposed assets, in particular buildings, is thus paramount for effective mitigation of disasters. The students classified and georeferenced the main residential buildings typologies of northeastern Italy, a seismically active area which suffered consequences from strong past earthquakes. During the project, 170 high school students collected reports on more than 3200 buildings, performing a statistical analysis of their results.The project activities consisted of two main phases: plenary virtual training meetings and individual data collection and processing. Tutors held intermediate meetings with students for verification and discussion and brainstorming sessions with their professors to discuss the efficacy of their actions. All the meetings, including those for direct training of students, were delivered in virtual mode. The training material (including the meeting recordings) was then shared remotely with students and teachers through cloud solutions, and remained available during the whole project. In this way the students were able to both collect basic data for exposure assessment, and carry out their preliminary analysis using standard statistical tools available online. The comparative data analysis, performed for selected sub-areas and for the overall dataset, allowed them for some basic interpretation and a better understanding of the exposed assets situation in sub-areas. The CEDAS project, though motivated by the need to provide a practical solution to the COVID-19-related restrictions, went well beyond the emergency situation, as it demonstrated that training activities can contribute to both enhancing the available exposure dataset and to increasing risk awareness among young students in the region.

Complex network theory has been recently applied to get new insights and a different perspective in the study of earthquake patterns. Several studies (see for instance Daskalaki et al., J Seismol, 2016; Telesca, Phys. Chem. Earth, 2015; Varini et al., J Geophys Res, 2020; Ebrahimi et al., Chaos Solitons Fractals, 2021, and references therein) were based on the preliminary mapping of the time series of earthquakes into networks, by applying visibility graph method or other clustering algorithms. In a second step, the topological properties of the obtained networks were analyze by exploiting tools of complex network theory with the aim of discovering possible precursory signatures of strong earthquakes or other features relevant to hazard assessment.In this study we investigated the earthquake clusters extracted by two data-driven declustering algorithms: the nearest-neighbor, which classifies the earthquakes on the basis of a nearest-neighbor distance between events in the space-time-energy domain (Zaliapin and Ben-Zion, J Geophys Res, 2013), and the stochastic declustering, which is based on the space-time ETAS point process model (Zhuang et al., J Geophys Res, 2004). Case studies from selected sequences, occurred in Central Italy from 1985 to 2021, are examined in some detail.The earthquake clusters extracted by the two declustering algorithms are compared by different tools, so as to assess the similarities and differences in their classification and characterization (Varini et al., J Geophys Res, 2020). The connections between events forming a cluster, as defined by the considered declustering method, allow us representing its hierarchical structure by means of a tree graph. The topological structure of the clusters is then investigated by means of centrality measures in the frame of Network analysis.

During the last two decades, an operational procedure for time-dependent seismic hazard scenarios has been developed, which integrates fully formalized and validated earthquake forecasting information from pattern recognition analysis (e.g. by CN algorithm), with the realistic modelling of earthquake ground motion by the neo-deterministic approach (NDSHA). The proposed methodology permits to define, both at regional and local scale, a set of scenarios of ground motion for the time interval for the time interval in which a strong event is likely to occur within the alerted areas. When dealing with offshore large earthquakes occurrence, this integrated approach can be naturally extended to the definition of time-dependent tsunami scenarios, based on physical scenario models of tsunami waves.CN forecasts for the Italian territory and its surroundings, as well as the corresponding time-dependent ground motion scenarios associated with the alarmed areas, are regularly updated since about two decades (Peresan, 2018, Geophysical Monograph Series, 234, pp. 149–172 and references therein). We review the results obtained so far by rigorous prospective testing of the developed procedure, including analysis of the statistical significance of issued forecasts. Special emphasis is placed on the recent earthquakes that occurred in the Adriatic region, which support validation of the applied methodologies, and evidence the opportunity of developing time-dependent tsunamis scenarios, by integrating forecast information with the modelling of tsunami waves propagation.In this study, tsunami modelling is performed by the NAMI DANCE software (Yalciner et al., 2006, Middle East Technical University, Ankara, Turkey), which allows us accounting for seismic source properties, variable bathymetry, and non-linear effects in waves propagation. Urban scale hazard scenarios for selected coastal sites are developed considering different potential tsunamigenic sources of tectonic origin, located in the Central and Southern Adriatic Sea. The results from parametric studies accounting for possible sources related to historical events, as well as for yet unobserved extreme events, are considered for this purpose. Their verification against recent earthquakes, allows us assessing the relevance of space-time information and uncertainties on source parameters, and their possible operational contribution towards effective tsunami warning system for the Adriatic Sea and in the whole Mediterranean area.

Earthquakes cannot be predicted with ultimate precision, so that the progressive reduction of the prediction uncertainty in space and time is an evergreen and challenging task, both from the scientific point of view for the intrinsic complexity of the seismic phenomenon and for its high societal relevance. To this aim, algorithms exist (like CN, M8, and M8S) based on objective recognition of seismicity patterns that have been already tested for some decades for intermediate-term middle-range prediction of strong earthquakes above a preassigned magnitude threshold. Here, we review the fundamental ideas of an integrated approach to earthquake prediction, based on the synergy of high-density geodetic observations (GNSS and SAR) and seismological information, and the results obtained so far through a completely new retrospective analysis of the 2016–17 seismic crisis in Central Italy and the 2012 Emilia sequence, where space-time precursory features are highlighted within intermediate-term ground velocities and seismicity. This integrated approach defines a new paradigm for time-dependent hazard assessment scenarios, and it is demonstrated that the proper integration of seismological and geodetic information can achieve what here is called intermediate-term narrow-range earthquake prediction. The extent of the alarmed areas, identified for the strong earthquakes by earthquake prediction algorithms based on seismicity patterns, can be significantly reduced from linear dimensions of a few hundred to a few tens of kilometers, leading to an improved more specific implementation of low-key preventive actions, like those recommended by UNESCO as early as in 1991.

An operational procedure for time-dependent seismic hazard assessment has been developed during the last 2 decades, which integrates fully formalized earthquake forecasting information from pattern recognition analysis (by CN and M8S algorithms), with the scenario-based neo-deterministic approach to seismic hazard assessment. The algorithms CN and M8S permit to deal with multiple sets of seismic precursors, and use a detectable inverse cascade of the seismic process to allow for a diagnosis of the intervals of time when a strong event is likely to occur inside a specified region. CN and M8S intermediate-term middle-range forecasts for the Italian territory and its surroundings, as well as the related time-dependent ground motion scenarios associated with the alarmed areas, are regularly updated since 2006. We review the results obtained so far by rigorous prospective testing of the developed procedure, including analysis of the statistical significance of issued forecasts, which supports validation of the applied methodologies.

A major earthquake, with magnitude Mw 7.3, struck Sarpol Zahab (Kermanshah province, Iran) on November 12, 2017, causing extended damage and casualties. The epicenter was located in the Northwestern part of the Zagros mountain range, an active belt originated by the Arabia-Eurasia collision. We explore seismicity preceding this earthquake, by using the Iranian Seismological Center instrumental earthquake catalog (IGTU), with the aim to identify possible anomalies in background seismicity that can be related with this and other future large events. For this purpose, we used a method for intermediate term forecasts of large earthquakes, namely the Region Time Length (RTL) algorithm, which analyzes declustered catalogs and is sensitive to quiescences that may precede major earthquakes. RTL has been progressively refined and has been applied in several regions worldwide during the last decades. To decluster the earthquake catalog we used a quite novel approach, based on the nearest-neigbour distances between events in the space-time-energy domain, a method that preserves the background seismicity while removing the clustered component. The retrospective application of RTL algorithm to the area surrounding the mainshock epicenter highlights two significant quiescences: one preceding the Sarpol Zahab Mw 7.3 earthquake, and the other occurring before a Mw 5.7 earthquake, which struck the same region on November 2013. The quiescences duration ranges from few months to one year and is compatible with earlier results from different regions of the world. In addition, we applied an enhanced variant of RTL algorithm, which allows us drawing maps for the whole study region and that shows only quiescences consistently detected for different choices of the free parameters, and hence more stable. The resulting map for Northwestern Iran, calculated for the time span 1 June 2017–11 November 2017, evidences two broad quiescence regions, oriented NW-SE along the Zagros belt. One, located to the north, evidences a significant seismic anomaly corresponding to the Sarpol Zahab earthquake, which disappeares immediately after the event. The second one, located in the southeastern part of the study region, persists up to the end of the available catalog (October 4, 2018).

The space concept of the Unified Scaling Law for Earthquakes (USLE), which generalizes the Gutenberg-Richter relationship making use of the fractal distribution of earthquake sources in a seismic region, has been applied to seismicity in Northeastern Italy. In particular, the temporal variations of USLE coefficients have been investigated, with the aim to get new insights in the evolving dynamics of seismicity within different tectonic domains of Friuli-Venezia Giulia region (FVG) and its surroundings.For this purpose, we resorted to the catalog compiled at the National Institute of Oceanography and Applied Geophysics (OGS), considering earthquakes occurred in the period 1995 – 2019, with epicenters within three sub-regions of the territory under investigation, delimited based on main geological and tectonic features (Bressan et al. 2018, J. Seismol. 22, 1563–1578). To quantify the observed variability of seismic dynamics, a multi-parametric analysis has been carried out for each sub-region by means of several moving averages, including: the inter-event time, τ; the cumulative Benioff strain release, Σ; the USLE control parameter, η and the USLE coefficients, estimated for moving six-years time intervals. The analysis evidenced that the USLE coefficients in FVG region are time-dependent and show up correlated (Nekrasova and Peresan 2021, Frontiers in Earth Science, 8, 624). Moreover, the dynamical features of the considered parameters in the three sub-regions highlighted a number of different seismic regimes; in particular, major changes in the parameters are associated to occurrence of the 12 April 1998 (M5.6) and the 12 July 2004 (M5.1) Kobarid (Slovenia) earthquakes within the corresponding sub-region.The results obtained for seismicity in Northeastern Italy and surrounding areas confirm similar analysis performed on a global scale, in advance and after the largest earthquakes worldwide. In addition, the analysis evidenced the spatially heterogeneous and non-stationary features of seismicity, in agreement with results from independent analysis of background seismicity within the investigated territory (Benali et al. 2020, Stoch. Environ. Res. Risk. Assess. 34, 775–791), thus suggesting the opportunity of resorting to time-dependent models of earthquakes occurrence for improving local seismic hazard assessment.

The concept of the Unified Scaling Law for Earthquakes (USLE), which generalizes the Gutenberg-Richter relationship making use of the fractal distribution of earthquake sources in a seismic region, is applied to seismicity in the Friuli-Venezia Giulia region, FVG (Northeastern Italy) and its surroundings. In particular, the temporal variations of USLE coefficients are investigated, with the aim to get new insights in the evolving dynamics of seismicity within different tectonic domains of FVG. To this purpose, we consider all magnitude 2.0 or larger earthquakes that occurred in 1995–2019, as reported in the catalog compiled at the National Institute of Oceanography and Applied Geophysics (OGS catalog), within the territory of its homogeneous completeness. The observed variability of seismic dynamics for three sub-regions of the territory under investigation, delimited based on main geological and tectonic features, is characterized in terms of several moving averages, including: the inter-event time,τ; the cumulative Benioff strain release, Ʃ; the USLE coefficients estimated for moving six-years time intervals, and the USLE control parameter,η. We found that: 1) the USLE coefficients in FVG region are time-dependent and show up correlated; 2) the dynamical changes ofτ, Ʃ, andηin the three sub-regions highlight a number of different seismic regimes; 3) seismic dynamics, prior and after the occurrence of the 1998 and 2004 Kobarid (Slovenia) strong main shocks, is characterized by different parameters in the related sub-region. The results obtained for the FVG region confirm similar analysis performed on a global scale, in advance and after the largest earthquakes worldwide. Moreover, our analysis highlights the spatially heterogeneous and non-stationary features of seismicity in the investigated territory, thus suggesting the opportunity of resorting to time-dependent estimates for improving local seismic hazard assessment. The applied methods and obtained parameters provide quantitative basis for developing suitable models and forecasting tools, toward a better characterization of future seismic hazard in the region.

We investigate the statistical properties of declustered catalogs as obtained from the application of two different data-driven declustering algorithms, namely the nearest-neighbor method and the stochastic declustering method (Benali et al., Stoch. Environ Res Risk Assess, 2020). The nearest-neighbor method partitions earthquakes into background and clustered components, based on nearest-neighbor distances between earthquakes in the space-time-magnitude domain (Zaliapin and Ben-Zion, J Geophys Res, 2013); the stochastic declustering method classifies earthquakes into background and clustered components through a probabilistic procedure based on the estimation of the space-time ETAS model (Zhuang et al., J Geophys Res, 2004).Two Italian case studies are considered: North-Eastern Italy (data from OGS Bulletins) and Central Italy (data from ISIDe catalog). For both case studies, the time series of background seismicity are obtained from the two declustering methods. Then we investigate the general assumption according to which the temporal sequence of background seismicity is suitably modelled by the stationary Poisson model. For this purpose, several features and statistical tests are considered to verify the main properties that characterize Poisson processes (e.g. events are independent, exponential inter-arrival times, etc.). Whenever the Poissonian hypothesis is rejected, we get evidence of certain heterogeneity in the background sequence, which leads us to rule out the simple Poisson process for background seismicity modeling. As a simple and more suitable alternative, we consider here the Markov Modulated Poisson Process (MMPP model), which allows the Poisson seismicity rate to change over time according to a finite (unknown) number of states of the system. The MMPP model turns out suitable for identifying and quantifying heterogeneities in background seismicity, as well as for comparing them against the two considered declustering algorithms.

Earthquake clustering is a significant feature of seismic catalogs, both in time and space. Several methodologies for earthquake cluster identification have been proposed in the literature in order to characterize clustering properties and to analyze background seismicity. We consider two recent data-driven declustering techniques, one based on nearest-neighbor distance and the other on a stochastic point process. These two methods use different underlying assumptions and lead to different classifications of earthquakes into background events and clustered events. We investigated the classification similarities by exploiting graph representations of earthquake clusters and tools from network analysis. We found that the two declustering algorithms produce similar partitions of the earthquake catalog into background events and earthquake clusters, but they may differ in the identified topological structure of the clusters. Especially the clusters obtained from the stochastic method have a deeper complexity than the clusters from the nearest-neighbor method. All of these similarities and differences can be robustly recognized and quantified by the outdegree centrality and closeness centrality measures from network analysis.

The Delta/Sigma method is applied in this study to investigate the seismic sequences following major earthquakes, with the aim to understand whether they fit the classical laws of aftershocks occurrence, such as the classical Omori Law and its recent variants, and to explore whether observed deviations from these laws may provide some statistically significant information about the possible occurrence of further large aftershocks. Specifically, the Delta/Sigma method is based on the observation of possible anomalies in the temporal decay of an aftershock sequence. In fact, given the number of events actually observed within a time window U (e.g. 1 day), its difference (Delta) with respect to theoretical number of events, and its standard deviation (Sigma), it was found that, before the occurrence of large aftershocks, the Delta/Sigma ratio may reach rather high values (e.g. above 2-2.5), which can be possibly followed within few days by some relevant aftershocks. The investigation area (referred as "Box") is defined as a rectangular sector, with dimensions proportional to the magnitude M of the mainshock, and with barycenter computed based on aftershocks occurred during the first Tb days from the mainshock.To investigate the performances of the Delta/Sigma method various earthquake sequences are selected from different regions worldwide, including those associated with recent destructive earthquakes in Italy and Iran. The input data necessary for this study are extracted from global datasets (ANSS-USGS and ISC catalogs) and regional catalogs (e.g. ISIDE bulletins for the Italian territory). A wide set of parametrics tests is carried out in order to verify if this method could forecast the moderate and large aftershocks, which occurred in the region surrounding the mainshocks epicenter. Different input parameters are considered, in order to check the stability and statistical significance of the obtained results.The preliminary results suggest that the application of Delta/Sigma method could highlight the possible occurrence of several significant aftershocks. Careful assessment of forecasting capability is essential, in order to provide relevant information for mitigation of risks associated with large aftershocks occurrence.

A novel forecasting tool, able to fully exploit the information content of the available data, is proposed for the synergic use of seismological and geodetic information, in order to delineate, at the intermediate-term narrow-range, the regions where to concentrate prevention actions and seismic risk mitigation planning. An application of the proposed interdisciplinary procedure, defining a new paradigm for time dependent hazard assessment scenarios, is exemplified illustrating its application to the Italian territory.From seismological viewpoint, long-lasting practice and results obtained for the Italian territory in two decades of rigorous prospective testing of fully formalized algorithms (e.g. CN), proved the feasibility of earthquake forecasting based on the analysis of seismicity patterns at the intermediate-term (i.e. several months) middle-range scale (i.e. few hundred kilometers). An improved but not ultimate precision can be achieved reducing as much as possible the space-time volume of the alarms, by jointly considering seismological and geodetic information. In the proposed scheme geodetic information (i.e. GNSS and SAR) are used to reconstruct the velocity and strain pattern along transects properly oriented according to the a priori known tectonic and seismological information. Specifically, considering properly defined transects within the regions monitored by CN algorithm, the possible velocity variations and the related strain accumulation can be highlighted, with due consideration of the errors involved in GNSS data.Through a refined retrospective analysis, duly involving the accuracy analysis of the newly available geodetic results, space­time precursory features could be highlighted within ground velocities and seismicity, analyzing the 2016-2017 seismic crisis in Central Italy and the 2012 Emilia sequence. The analysis, including counter examples, evidenced reliable anomalies in the strain rate distribution in space, whereas no time dependence was detected in the long term (more than 10 years) preceding the occurrence of the studied events.With these results acquired, a systematic analysis of velocity variations (together with their accuracy) is performed, by defining a set of transects uniformly distributed, as far as possible, along and across major seismotectonic features of the Italian region, with a spacing of about 40-50 km and properly covering the regions monitored by CN algorithm. As a rule most of the transects contain information that appear to be useful for earthquake forecasting purposes. The few exceptions, naturally connected with the local very limited extension of land, are in Calabria and Western Sicily.The obtained results show that the combined analysis of the results (time dependent within decadal interval) of intermediate-term middle-range earthquake prediction algorithms, like CN, with those from the processing of adequately dense and permanent GNSS network data (time independent within the same decadal interval), may allow to highlight in advance the localized strain accumulation. Accordingly the extent of the alarmed areas, identified based on seismicity patterns at the intermediate scale can be significantly reduced (from few hundred to few tens kilometres).

A multi-parametric approach, based on five different parameters quantifying seismicity, is proposed for investigating the space-time evolution of earthquakes occurrence in areas characterized by complex tectonics, namely by the interference of differently oriented faults and by the heterogeneous mechanical strength of the rocks. Specifically, the variations of entropy, the b-value from the Gutenberg-Richter law, the changes in fractal dimension, and the Nearest Neighbour distance (η) are used for assessing changes in the temporal patterns of seismicity. In parallel, the Principal Component Analysis (PCA) in 4D (space and time) is used to define the hypocentres distribution geometry and the propagation directions.In particular, we applied the methods mentioned above in a multi-parametric study of the seismicity space-time evolution from 2015 to the beginning of 2020 in a well-focused area. The study area, centred on the town of Tolmezzo, in Northeastern Italy, between the Alps and the Prealps, is characterized by a complex tectonic pattern resulting from the interference of differently oriented fault systems and involving mechanically heterogeneous rocks. After a long period of low seismic activity, lasting about 15 years, in 2018–2019, the area experienced a significant increase of radiated seismic energy, spatially clustered, with four sequences induced by earthquakes with MD (coda-duration magnitude) from 3.7 to 4.0 (http://www.crs.inogs.it/bollettino/RSFVG). Notably, the most energetic events are located in correspondence with the sharp transitions from zones of low damage to zones of intermediate damage. Two distinct periods of the seismic activity are identified, as revealed by the b-value and the fractal dimension, which show relevant fluctuations since the beginning of 2017. The temporal variation of the b-value can be related to crustal stress changes in the medium, which is characterized by different mechanical properties. The fractal dimension time evolution indicates a prevailing clustering of the earthquakes with a tendency to propagate linearly. The temporal variations of the Shannon entropy and η quantify the evolving organization and correlation of seismicity within an area; hence, they reflect a process of damage evolution in heterogeneous rocks that changes with time due to continuous strain energy redistribution. According to this view, the Shannon entropy and η can be considered parameters related to each other that reflect the memory of past deformations. The recovery of Shannon entropy and η to values preceding the crisis of 2018–2019 suggests that the system has reached a temporary new equilibrium.The solutions provided by the PCA analysis along a cross-section close to Tolmezzo confirm such observations. They reveal mostly vertical and sub-vertical planes changing orientation along the cross-section considered. The fracture propagates within the fracturing plane in the southernmost and northernmost parts of the cross-section. In contrast, the results suggest the activation of parallel planes in the central part of the section, closer to Tolmezzo. The orientation of the planes inferred from PCA analysis agrees with secondary NNE-SSW and E-W trends present in the region considered.

The main features of earthquake clusters in Northeastern Italy are explored, with the aim to get new insights on local scale patterns of seismicity in the area. The study is based on a systematic analysis of robustly and uniformly detected seismic clusters, which are identified by a statistical method, based on nearest-neighbor distances of events in the space-time-energy domain. The method permits us to highlight and investigate the internal structure of earthquake sequences, and to differentiate the spatial properties of seismicity according to the different topological features of the clusters structure. To analyze seismicity of Northeastern Italy, we use information from local OGS bulletins, compiled at the National Institute of Oceanography and Experimental Geophysics since 1977. A preliminary reappraisal of the earthquake bulletins is carried out and the area of sufficient completeness is outlined. Various techniques are considered to estimate the scaling parameters that characterize earthquakes occurrence in the region, namely the b-value and the fractal dimension of epicenters distribution, required for the application of the nearest-neighbor technique. Specifically, average robust estimates of the parameters of the Unified Scaling Law for Earthquakes, USLE, are assessed for the whole outlined region and are used to compute the nearest-neighbor distances. Clusters identification by the nearest-neighbor method turn out quite reliable and robust with respect to the minimum magnitude cutoff of the input catalog; the identified clusters are well consistent with those obtained from manual aftershocks identification of selected sequences. We demonstrate that the earthquake clusters have distinct preferred geographic locations, and we identify two areas that differ substantially in the examined clustering properties. Specifically, burst-like sequences are associated with the north-western part and swarm-like sequences with the south-eastern part of the study region. The territorial heterogeneity of earthquakes clustering is in good agreement with spatial variability of scaling parameters identified by the USLE. In particular, the fractal dimension is higher to the west (about 1.2–1.4), suggesting a spatially more distributed seismicity, compared to the eastern parte of the investigated territory, where fractal dimension is very low (about 0.8–1.0).

Many devastating earthquakes inflicted heavy casualties and property losses in the seismically active China Seismic Experimental Site area (CSES: 97.5° ~ 105.5°E, 21° ~ 32°N). We performed a first-order seismic zoning based on Neo-deterministic Seismic Hazard Assessment (NDSHA) in the study area delimited by 94° ~ 108°E and 19° ~ 35°N, containing the South-East margin of the Tibetan Plateau and the Sichuan-Yunnan region. The seismic hazard is expressed by maps of peak ground displacement (PGD), peak ground velocity (PGV) and design ground acceleration (DGA) values, extracted from synthetic seismograms computed at a regional scale and mapped on a regular grid of 0.2° × 0.2° over the study area. For the computation of synthetic seismograms, we considered and updated all the available geophysical-geological-tectonic information, including historical and instrumental earthquake catalogues, seismogenic zones, seismogenic nodes, focal mechanisms, and geophysical structural models. We tested the performance of our assessments with available data (i.e., after the Great Wenchuan (2008, May 12th, Ms = 8.0) and Lushan (2013, April 20th, Ms = 7.0) earthquakes) and verified the negligible influence of large events located “far” from the study area. The results indicate the high seismic hazard of the region, with a particular attention (i.e., where DGA > 0.6 g) to the areas located around the main fault zones, e.g., the Longmenshan, Anninghe and Zemuhe Fault Zones. These first-order NDSHA zoning findings may serve as a knowledge basis to support both large- to mid-range preparedness actions and (multi-scenario) site-specific studies.

A complex multiple mainshocks sequence (24/08/2016, Mw 6.0; 26/10/2016, Mw 5.4 and 5.9; 30/10/2016, Mw 6.5) occurred in central Italy, causing the death of nearly 300 people and widespread destruction of entire villages. The Region-Time-Length (RTL) method is used to analyze the seismicity preceding the first Mw 6.0 Amatrice mainshock. This analysis is performed using the earthquake catalogue maintained by the Istituto Nazionale di Geofisica e Vulcanologia (INGV) after a preprocessing, which includes the declustering of aftershocks. A well-evident quiescence that preceded the sequence was detected. The quiescence extended throughout a broad region north of the epicenter. The largest event of the sequence and the aftershocks covered most of the quiescence region, except for a small area to the west. The quiescence started from the beginning of September 2015 and lasted for approximately 1 year up to the Amatrice mainshock.

Current computational resources and physical knowledge of the seismic wave generation and propagation processes allow for reliable numerical and analytical models of waveform generation and propagation. From the simulation of ground motion, it is easy to extract the desired earthquake hazard parameters. Accordingly, a scenario-based approach to seismic hazard assessment has been developed, namely the neo-deterministic seismic hazard assessment (NDSHA), which allows for a wide range of possible seismic sources to be used in the definition of reliable scenarios by means of realistic waveforms modelling. Such reli- able and comprehensive characterization of expected earthquake ground motion is essential to improve building codes, particularly for the protection of critical infrastructures and for land use planning. Parvez et al. (Geophys J Int 155:489–508, 2003) published the first ever neo-deterministic seismic hazard map of India by computing synthetic seismograms with input data set consisting of structural models, seismogenic zones, focal mechanisms and earthquake catalogues. As described in Panza et al. (Adv Geophys 53:93–165, 2012), the NDSHA methodology evolved with respect to the original formulation used by Parvez et al. (Geophys J Int 155:489–508, 2003): the computer codes were improved to better fit the need of producing real- istic ground shaking maps and ground shaking scenar- ios, at different scale levels, exploiting the most significant pertinent progresses in data acquisition and modelling. Accordingly, the present study supplies a revised NDSHA map for India. The seismic hazard, expressed in terms of maximum displacement (Dmax), maximum velocity (Vmax) and design ground acceleration (DGA), has been extracted from the synthetic signals and mapped on a regular grid over the studied territory.

Earthquakes cannot be predicted with precision, but algorithms exist for intermediate-term middle range prediction of main shocks above a pre-assigned threshold, based on seismicity patterns. Few years ago, a first attempt was made in the framework of project SISMA, funded by Italian Space Agency, to jointly use seismological tools, like CN algorithm and scenario earthquakes, and geodetic methods and techniques, like GPS and SAR monitoring, in order to effectively constrain priority areas where to concentrate prevention and seismic risk mitigation. We present a further development of integration of seismological and geodetic information, clearly showing the contribution of geodesy to the understanding and prediction of earthquakes. As a relevant application, the seismic crisis that started in Central Italy in August 2016 is considered in a retrospective analysis. Differently from the much more common approach, here GPS data are not used to estimate the standard 2D velocity and strain field in the area, but to reconstruct the velocity and strain pattern along transects, which are properly oriented according to the a priori information about the known tectonic setting. Overall, the analysis of the available geodetic data indicates that it is possible to highlight the velocity variation and the related strain accumulation in the area of Amatrice event, within the area alarmed by CN since November 1st, 2012. The considered counter examples, across CN alarmed and not-alarmed areas, do not show any comparable spatial acceleration localized trend. Therefore, we show that the combined analysis of the results of CN prediction algorithms, with those from the processing of adequately dense and permanent GNSS network data, may allow the routine highlight in advance of the strain accumulation. Thus it is possible to significantly reduce the size of the CN alarmed areas., Added 1 reference

In this study, a long-term forecasting model is proposed to evaluate the probabilities of forthcoming M ≥ 5.0 earthquakes on a 0.2° grid for an area including the Iranian plateau. The model is built basically from smoothing the locations of preceding events, assuming a spatially heterogeneous and temporally homogeneous Poisson point process for seismicity. In order to calculate the expectations, the space distribution, from adaptively smoothed seismicity, has been scaled in time and magnitude by average number of events over a 5-year forecasting horizon and a tapered magnitude distribution, respectively. The model has been adjusted and applied considering two earthquake datasets: a regional unified catalog (MB14) and a global catalog (ISC). Only the events with M ≥ 4.5 have been retained from the datasets, based on preliminary completeness data analysis. A set of experiments has been carried out, testing different options in the model application, and the average probability gains for target earthquakes have been estimated. By optimizing the model parameters, which leads to increase of the predictive power of the model, it is shown that a declustered catalog has an advantage over a non-declustered one, and a low-magnitude threshold of a learning catalog can be preferred to a larger one. In order to examine the significance of the model results at 95% confidence level, a set of retrospective tests, namely, the L test, the N test, the R test, and the error diagram test, has been performed considering 13 target time windows. The error diagram test shows that the forecast results, obtained for both the two input catalogs, mostly fall outside the 5% critical region that is related to results from a random guess. The L test and the N test could not reject the model for most of the time intervals (i.e. ~85 and ~62% of times for the ISC and MB14 forecasts, respectively). Furthermore, after backwards extending the time span of the learning catalogs and repeating the L test and N test for the new dataset as well as the R test, it is observed that a low-quality longer catalog does not essentially improve the predictive skill of the model than a high-quality shorter one. The performed retrospective tests suggest that the model yields some statistically acceptable efficiency for the studied area, at least with respect to the spatially uniform reference model. Thus, the considered model may provide useful information as a reference for more refined time-independent models and also in combination with long-term indications from seismic hazard maps; this is particularly relevant in areas characterized by a high level of predicted ground shaking and high forecast rate.

Earthquakes cannot be predicted with ultimate precision, so that the progressive reduction of the prediction uncertainty in space and time is an evergreen and challenging task, both from the scientific point of view for the intrinsic complexity of seismic phenomenon and for its high societal relevance. To this aim, algorithms (like CN, M8 and M8S) based on objective recognition of seismicity patterns have been already tested for some decades for intermediate-term middle-range prediction of strong earthquakes above a pre-assigned magnitude threshold. Here, moving from some preliminary ideas, we propose an integrated approach to earthquake prediction, based on the synergy of high-density geodetic observations and seismological information, defining a new paradigm for time dependent hazard assessment scenarios. Through a wider and more refined retrospective analysis, duly involving the accuracy analysis of the newly available geodetic results, space–time precursory features are highlighted within ground velocities and seismicity, analyzing the 2016–2017 seismic crisis in Central Italy and the 2012 Emilia sequence. Overall, it is demonstrated that the proper integration of seismological and geodetic information can achieve what here is called intermediate-term narrow-range earthquake prediction. The extent of the alarmed areas, identified for the strong earthquakes by earthquake prediction algorithms based on seismicity patterns, can be significantly reduced from linear dimensions of a few hundred to a few tens of kilometers, leading to an improved more specific implementation of low-key preventive actions, like those recommended by UNESCO as early as in 1991.

Ischia island, in the province of Naples, is a densely populated volcanic island, in which small to moderate magnitude earthquakes occur. Due to the very shallowdepth of such events (< 2 km), they can generate serious damage and casualties, up to the complete destruction of urban centers located within short epicentraldistance. Almost all of the earthquakes at Ischia island occur at shallow depth, beneath the Northern slopes of the Mt. Epomeo horst, which is located very close to thetown of Casamicciola. In fact, Casamicciola was completely destroyed by the 1883 earthquake (2313 victims) and experienced intensities up to XI degree on theMercalli scale. Historical records show that the background seismicity here is almost absent, but larger earthquakes tend to occur in clusters, lasting some decadesand with intervals between consecutive events on the order of years to decades. The clustering in time and the very shallow hypocentres, which cause, with respect totectonic earthquakes of similar magnitude, larger effects though limited to a relatively small area, make the seismicity in this island very peculiar. Despite suchdestructive record, till now official hazard maps strongly underestimated the seismic hazard in this area. On August 21st 2017, a very shallow earthquake with rathersmall magnitude struck the area of Casamicciola, killing two people, injuring many more and causing huge damage and partial to total collapse of edifices located justabove the earthquake fault.The maximum acceleration recorded for this earthquake exceeded by more than a factor of two the reference acceleration that should be sustained by edifices,according to official hazard maps. We propose here a complete procedure to assess and mitigate the risk, which can be rapid and economically affordable and, at thesame time, can avoid further grief due to possible occurrence of other destructive earthquakes within a short time interval. We describe the most likely buildingcollapse and casualty scenarios, in case that low-to-moderate magnitude earthquakes would occur before the edifices would be appropriately reinforced and secured.Our scenarios demonstrate the urgent need for securing operations. The proposed procedures for assessing seismic hazard and for securing urban areas provide anexample that is potentially applicable to the whole Italian peninsula. They may allow in fact the mitigation of the destructive impact of a large number of earth-quakes, which in Italy are often characterized by low or moderate magnitudes.

The Neo-Deterministic Seismic Hazard Assessment (NDSHA) procedure for the development of seismic hazard maps at the regional scale has been validated by all the events occurred in regions where NDSHA maps were available at the time of the quake. NDSHA method reliably and realistically simulates the wide suite of earthquake ground motions that may impact civil populations as well as their heritage buildings. The scenario based NDSHA’s modeling technique is developed from comprehensive physical knowledge of: (i) the seismic source process; (ii) the propagation of earthquake waves; and (iii) their combined interactions with site effects. A useful safety factor conceptually similar to the ones used in structural engineering can be used to set the estimated magnitude of the scenario events. Using the signals generated by NDSHA, well rooted on the fundamental laws of physics and on the experimental evidence, a number of possible structural engineering approaches become available.

This study illustrates the application of the CN algorithm for the analysis of precursory seismicity patterns in the Zagros region (Iran), an area characterized by a complex seismotectonic setting and by remarkable seismic activity. CN is a formally defined and widely tested algorithm for intermediate-term middle-range earthquake prediction, based on the analysis of routinely compiled earthquake catalogs. To allow its application, the global and regional catalogs available for the territory of Iran have been analyzed so as to compile a data set sufficiently complete and homogeneous over a time span of about 3 decades, as required for CN application. A number of tests have been performed with respect to changes in the input catalogs, assuming different magnitude completeness levels as well as considering different magnitude thresholds for the selection of target earthquakes. Different variants of the regionalization have been outlined according to the seismotectonic model, and it was concluded that precursory seismicity patterns for the largest events need to be researched in the whole Zagros tectonic domain. Accordingly, an experiment was set up aimed at validation of intermediate-term middle-range prediction of earthquakes with magnitude M >= 6.0 in the Zagros region. Starting in March 2012, CN prediction results have been routinely updated based on the events with M >= Mc = 4.0 as they are reported in the International Seismological Centre catalog.

The paper by Taroni et al. (2016) considers results of forward prediction of Italian strong earthquakes by CN algorithm with the declared intent of providing "a careful assessment of CN prediction performances... using standard testing procedures". Given the very limited number of target events within each region, however, the considered situation is non statistical, and a priori it is clear that the standard statistical methods are not effective here. The attempt to replace the standard approaches by Pari-mutuel Gambling Score (PGS) method leads to almost complete loss of information about predicted earthquakes, even for a large sample of target events. Therefore, the conclusions based on PGS, are untenable., Comment: 4 pages, 1 table. Submitted to Annals of Geophysics

The influence of strain field variations associated with seasonal and longer term climatic phenomena on earthquake occurrence is investigated. Two regions (Himalaya and Alps), characterized by present day mountain building and relevant glaciers retreat, as well as by sufficiently long earthquake catalogues, are suitable for the analysis. Secular variations of permanent glaciers dimensions, which are naturally grossly correlated with long-term average surface atmosphere temperature changes, as well as seasonal snow load, cause crustal deformations that modulate seismicity.

Issues pertaining to urban risks are a pressing concern for people involved in disaster mitigation. With the progressing urban sprawl and the emergence of mega-cities around the world, disasters of all kinds become an inevitable consequence of uncontrolled urbanization. Growing environmental and social (purely scientific and practical disaster mitigation and preparedness) concerns, both on the part of decisionmakers and public opinion, have brought a new perspective to the perception of hazard assessment as a valid alternative in the long-term (e.g. retrofitting), and an effective complement in short and medium terms, to traditional design procedure for a resistant and safe environment. Recent earthquakes, Haiti earthquake of 12 January 2010 and Chile earthquake of 27 February 2010, in particular, exemplify the urgent need for society to develop the effective strategies and policies to reduce seismic risk and to mitigate earthquake disasters.

This paper deals with the neo-deterministic definition of the seismic input in the municipality of Nimis (Italy), aimed at the design of residential seismically isolated buildings. The seismic input is defined by the computation of realistic synthetic seismograms considering different levels of detail for the earthquake source, both for a bedrock model and taking into account the specific site conditions. The horizontal response spectrum, calculated in the centre of the municipality by modelling the most dangerous source, advises against the construction of a building with a fixed base, but it is compatible with the seismic isolation, and it has been, therefore, used for the design of a residential seismically isolated building. The maximum displacement for the isolation system has been estimated about 17 cm, a value much lower than that provided by the code design response spectrum (28 cm). The importance of the realistic modelling, which permits the generalization of empirical observations by means of, physically sound, theoretical considerations, is evident, as it allows for the optimisation of the structural design with respect to the site of interest.

The Italian territory has been the object of several studies devoted to the analysis of seismicity and to earthquake precursors' research. Although a number of observations have been claimed to precede large earthquakes, only few systematic studies have been carried out and almost no test of their performances is available up to now. In this paper, we review the application to the Italian territory of two formally defined intermediate-term middle-range earthquake prediction algorithms, namely CN and M8S. The general methodology common to the two different algorithms makes use of general concepts of pattern recognition that permit to deal with multiple sets of seismic precursors, and allows for a systematic monitoring of seismicity, as well as for a widespread testing of the prediction performances. Italy represents the only region of moderate seismic activity where the M8S and CN algorithms are applied simultaneously for routine monitoring. Significant efforts have been made to minimize the intrinsic space uncertainty of predictions and the subjectivity of the definition of the areas where precursors should be identified. Several experiments have been dedicated to assess the robustness of the methodology against the unavoidable uncertainties in the data. With these results acquired, starting in July 2003, an experiment was launched for the real-time test of M8S and CN predictions.

We analyse the seismic catalogue of the local earthquakes which occurred at Somma-Vesuvius volcano in the past three decades (1972–2000). The seismicity in this period can be described as composed of a background level, characterised by a low and rather uniform rate of energy release and by sporadic periods of increased seismic activity. Such relatively intense seismicity periods are characterised by energy rates and magnitudes progressively increasing in the critical periods. The analysis of the b value in the whole period evidences a well-defined pattern, with values of b progressively decreasing, from about 1.8 at the beginning of the considered period, to about 1.0 at present. This steady variation indicates an increasing dynamics in the volcanic system. Within this general trend it is possible to identify a substructure in the time sequence of the seismic events, formed by the alternating episodes of quiescence and activity. The analysis of the source moment tensor of the largest earthquakes shows that the processes at the seismic source are generally not consistent with simple double-couples, but that they are compatible with isotropic components, mostly indicating volumetric expansion. These components are shown to be statistically significant for most of the analysed events. Such focal mechanisms can be interpreted as the effect of explosion phenomena, possibly related to volatile exsolution from the crystallising magma. The availability of a reduced amount of high quality data necessary for the inversion of the source moment tensor, the still limited period of systematic observation of Vesuvius micro-earthquakes and, above all, the absence of eruptive events during such interval of time, cannot obviously permit the outlining of any formal premonitory signal. Nevertheless, the analysis reported in this paper indicates a progressively evolving dynamics, characterised by a generally increasing trend in the seismic activity in the volcanic system and by a significant volumetric component of recent major events, thus posing serious concern for a future evolution towards eruptive activity.

Objective testing is a key issue in the process of revision and improvement of seismic hazard assessments. Therefore we continue the rigorous comparative analysis of past and newly available hazard maps for the territory of Italy against the seismic activity observed in reality. The final Global Seismic Hazard Assessment Program (GSHAP) results and the most recent version of Seismic Hazard Harmonization in Europe (SHARE) project maps, along with the reference hazard maps for the Italian seismic code, all obtained by probabilistic seismic hazard assessment (PSHA), are cross-compared to the three ground shaking maps based on the duly physically and mathematically rooted neo-deterministic approach (NDSHA). These eight hazard maps for Italy are tested against the available data on ground shaking. The results of comparison between predicted macroseismic intensities and those reported for past earthquakes (in the time interval from 1000 to 2014 year) show that models provide rather conservative estimates, which tend to over-estimate seismic hazard at the ground shaking levels below the MCS intensity IX. Only exception is represented by the neo-deterministic maps associated with a fixed return period of 475 or 2475 years, which provide a better fit to observations, at the cost of model consistent 10% or 2% cases of exceedance respectively. In terms of the Kolmogorov-Smirnov goodness of fit criterion, although all of the eight hazard maps differ significantly from the distribution of the observed ground shaking reported in the available Italian databases, the NDSHA approach appears to outscore significantly the PSHA one.

In his SSA presidential address (Jordan, 2014), and later in a more extended publication with coauthors (Jordan et al. , 2014), Jordan presents a vision of forecast and prediction problems of earthquake system science. As experienced practitioners and in full appreciation of scientific studies on earthquake forecasting, we find it necessary to share a complementary viewpoint. Eight decades ago, Richter (1935) introduced the logarithmic scale for sizing earthquakes, in full appreciation of the observed multiplicative scaling of energy liberated in a seismic event, inspired from the first statistics of the frequency of shocks of various magnitudes in southern California. In the 1960s, Edward Lorenz discovered deterministic chaos in a system of ordinary differential equations describing natural processes, Leon Knopoff demonstrated that a simple system of interacting elements may reproduce a complex “seismic” sequence, and Vladimir Keilis‐Borok posed the problem of seismology and logics. In the 1970s, Israel Gelfand and John Tukey independently created a culture of exploratory data analysis that permits overcoming (though not completely) the complexity of a process by robust representation of information and exhaustive numerical tests validating the results. By the 1980s, the lithosphere of the Earth was recognized as a complex hierarchically self‐organized nonlinear dissipative system with critical phase transitions through larger earthquakes (Keilis‐Borok, 1990). Mathematically, such chaotic systems are predictable—but only up to a limit and after substantial averaging: a success …

The influence of random magnitude errors on the results of intermediate-term earthquake predictions is analyzed in this study. The particular case of predictions performed using the algorithm CN in central Italy is considered. The magnitudes of all events reported in the original catalog (OC) are randomly perturbed within the range of the expected errors, thus generating a set of randomized catalogs. The results of predictions for the original and the randomized catalogs, performed following the standard CN rules, are then compared. The average prediction quality of the algorithm CN appear stable with respect to magnitude errors up to ±0.3 units. Such a stable prediction is assured if the threshold setting period corresponds to a time interval sufficiently long and representative of the seismic activity within the region, while if the threshold setting period is too short, the average quality of CN decreases linearly for increasing maximum error in magnitude.

SUMMARY Prediction methods based on seismic precursors, and hence assuming that catalogues contain the necessary information to predict earthquakes, are sometimes criticised for their sensitivity to the unavoidable catalogue errors and possible undeclared variations in the evaluation of reported magnitudes. We consider a real example and we discuss the eVect, on CN predictions, of a long-lasting underestimation of the reported magnitudes. Starting approximately in 1988, the CN functions in Central Italy evidence an anomalous behaviour, not associated with TIPs, that indicates an unusual absence of moderate events. To investigate this phenomenon, the magnitudes given in the catalogue used, which since 1980 is defined by the ING bulletins, are compared to the magnitudes reported by the global catalogue NEIC (National Earthquake Information Centre, USGS, USA) and by the regional LDG bulletins issued at the Laboratoire de Detection et de Geophysique, Bruyeres-le-Chatel, France. The comparison is performed between the ING bulletins and the NEIC catalogue, considering the local, M L , and duration, M d , magnitudes, first within the Central region, and then extended to the whole Italian territory. To check the consistency of the conclusions drawn from ING and NEIC data, the comparison of local magnitudes is extended to a third data set, the LDG bulletins. The diVerences between duration magnitudes M d that are reported by ING and NEIC since 1983 appear quite constant with time. Starting in 1987, an average underestimation of about 0.5 can be attributed to M L reported by ING for the Central region; this diVerence decreases to about 0.2 when the whole Italian territory is considered. The anomalous behaviour of the CN functions disappears if a magnitude correction of +0.5 is applied to M L reported in the ING bulletins. However, such a simple magnitude shift cannot restore the real features of the seismic flow, and ING bulletins are not suitable for CN algorithm application.

According to the probabilistic seismic hazard analysis (PSHA) approach, the deterministically evaluated or historically defined largest credible earthquakes (often referred to as Maximum Credible Earthquakes, MCEs) are “an unconvincing possibility” and are treated as “likely impossibilities” within individual seismic zones. However, globally over the last decade such events keep occurring where PSHA predicted seismic hazard to be low. Systematic comparison of the observed ground shaking with the expected one reported by the Global Seismic Hazard Assessment Program (GSHAP) maps discloses gross underestimation worldwide. Several inconsistencies with available observation are found also for national scale PSHA maps (including Italy), developed using updated data sets. As a result, the expected numbers of fatalities in recent disastrous earthquakes have been underestimated by these maps by approximately two to three orders of magnitude. The total death toll in 2000–2011 (which exceeds 700,000 people, including tsunami victims) calls for a critical reappraisal of GSHAP results, as well as of the underlying methods. In this chapter, we discuss the limits in the formulation and use of PSHA, addressing some theoretical and practical issues of seismic hazard assessment, which range from the overly simplified assumption that one could reduce the tensor problem of seismic-wave generation and propagation into a scalar problem (as implied by ground motion prediction equations), to the insufficient size and quality of earthquake catalogs for a reliable probability modeling at the local scale. Specific case studies are discussed, which may help to better understand the practical relevance of the mentioned issues. The aim is to present a critical overview of different approaches, analyses, and observations in order to provide the readers with some general considerations and constructive ideas toward improved seismic hazard and effective risk assessment. Specifically, we show that seismic hazard analysis based on credible scenarios for real earthquakes, defined as neo-deterministic seismic hazard analysis, provides a robust alternative approach for seismic hazard and risk assessment. Therefore, it should be extensively tested as a suitable method for formulating scientifically sound and realistic public policy and building code practices.