Falcone, Giuseppe

To study the characteristics of seismicity in Italy, we have made use of the ISIDE (Italian Seismic Instrumental and parametric Data-basE) catalogue since 2005 April 16, which was compiled by the Istituto Nazionale di Geofisica e Vulcanologia (INGV). This catalogue includes high quality records of the occurrence times, locations, magnitude and other information about the earthquakes that occurred in and near Italy. We made use of the original form and two extended versions of the space–time ETAS model, namely, the 2-D ETAS model, the hypocentral 3-D ETAS model and the finite-source (FS) ETAS model. Our results show that the rupture geometries of large earthquakes, including the L’Aquila (2009 April 6 Mw6.1/ML5.9 ), the Finale-Emilia (2012 May 20, Mw5.8/ML5.9), the Amatrice (2016 August 24 Mw6.0/ML6.0) and the Norcia (2016 October 30 Mw6.5/ML6.1) earthquakes, control the spatial locations of their direct aftershocks. These direct aftershocks are mainly distributed in some areas adjacent to, but seldom at, the parts with the biggest slips along the main shock rupture, implying that aftershocks compensate the rupture of the main shock. The background seismicity rate is not stationary in all these areas, but shows several phases tuned by the major events. Regarding the difference among the three versions of the ETAS model, we found: (i) hypocentral depth plays an important role in triggering; (ii) when classifying background and triggered seismicity, all three models give similar results, but when classifying the family trees in the catalogue, the geometry of an earthquake rupture should be considered. The FS ETAS model classifies most aftershock events as aftershocks of the main shock; (iii) adopting point sources together with isotropic spatial response causes underestimates of the effects triggered by the main shocks. Such biases can be corrected by incorporating the rupture geometries of major events into the model formulation. Compared to the original point-source model, more direct aftershocks from the main shock are estimated by using the FS ETAS model and (iv) The rupture geometry of a major earthquake can be inverted to some extent from small aftershocks following it by fitting to the finite-source ETAS model.

Parsons et al. (2012), compared the characteristic and Gutenberg–Richter (G-R) distributions for time-dependent M ≥ 7.9 earthquake probability in the Nankai-Tokai subduction zone, Japan, a region for which historical information about several repeating strong earthquakes does exist. The purpose of their paper was to assess the possibility of making reasonable hazard assessments without requiring a characteristic model, and the conclusion was yes. In fact, they found that a simulator that imposes no physical geometric rupture barriers (meaning gaps or steps in the faults), can replicate the spatial proportion of fault segment ruptures evident within the studied area (within 95% confidence bounds). They concluded that the adoption of a G-R model can attain very similar matches to the historical catalog of the Nankai-Tokai zone, and suggested that very simple earthquake rupture simulations based on empirical data and fundamental earthquake laws could be useful forecast tools in information-poor settings.

Earthquake forecasting is the ultimate challenge for seismologists, because it condenses the scientific knowledge about the earthquake occurrence process, and it is an essential component of any sound risk mitigation planning. It is commonly assumed that, in the short term, trustworthy earthquake forecasts are possible only for typical aftershock sequences, where the largest shock is followed by many smaller earthquakes that decay with time according to the Omori power law. We show that the current Italian operational earthquake forecasting system issued statistically reliable and skillful space-time-magnitude forecasts of the largest earthquakes during the complex 2016-2017 Amatrice-Norcia sequence, which is characterized by several bursts of seismicity and a significant deviation from the Omori law. This capability to deliver statistically reliable forecasts is an essential component of any program to assist public decision-makers and citizens in the challenging risk management of complex seismic sequences.

arthquake Occurrence provides the reader with a review of algorithms applicable for modeling seismicity, such as short-term earthquake clustering and pseudo-periodic long-term behavior of major earthquakes. The concept of the likelihood ratio of a set of observations under different hypotheses is applied for comparison among various models. In short-term models, known by the term ETAS, the occurrence space and time rate density of earthquakes is modeled as the sum of two terms, one representing the independent or spontaneous events, and the other representing the activity triggered by previous earthquakes. Examples of the application of such algorithms in real cases are also reported. Dealing with long-term recurrence models, renewal time-dependent models, implying a pseudo-periodicity of earthquake occurrence, are compared with the simple time-independent Poisson model, in which every event occurs regardless of what has occurred in the past. The book also introduces a number of computer codes developed by the authors over decades of seismological research.

The use of a newly developed earthquake simulator has allowed the production of catalogs lasting 100 kyr and containing more than 100,000 events of magnitudes ≥4.5. The model of the fault system upon which we applied the simulator code was obtained from the DISS 3.2.0 database, selecting all the faults that are recognized on the Calabria region, for a total of 22 fault segments. The application of our simulation algorithm provides typical features in time, space and magnitude behavior of the seismicity, which can be compared with those of the real observations. The results of the physics-based simulator algorithm were compared with those obtained by an alternative method using a slip-rate balanced technique. Finally, as an example of a possible use of synthetic catalogs, an attenuation law has been applied to all the events reported in the synthetic catalog for the production of maps showing the exceedance probability of given values of PGA on the territory under investigation.

In this study, we attempt to improve the standards in Probabilistic Seismic Hazard Assessment (PSHA) towards a time-dependent hazard assessment by using the most advanced methods and new databases for the Calabria region, Italy. In this perspective we improve the knowledge of the seismotectonic framework of the Calabrian region using geologic, tectonic, paleoseismological, and macroseismic information available in the literature. We built up a PSHA model based on the long-term recurrence behavior of seismogenic faults, together with the spatial distribution of historical earthquakes. We derive the characteristic earthquake model for those sources capable of rupturing the entire fault segment (full-rupture) independently with a single event of maximum magnitude. We apply the floating rupture model to those earthquakes whose location is not known sufficiently constrained. We thus associate these events with longer fault systems, assuming that any such earthquake can rupture anywhere within the particular fault system (floating partial-rupture) with uniform probability. We use a Brownian Passage Time (BPT) model characterized by mean recurrence, aperiodicity, or uncertainty in the recurrence distribution and elapsed time since the last characteristic earthquake. The purpose of this BPT model is to express the time-dependence of the seismic processes to predict the future ground motions in the region. Besides, we consider the influence on the probability of earthquake occurrence controlled by the change in static Coulomb stress (ΔCFF) due to fault interaction; to pursue this, we adopt a model built on the fusion of BPT model (BPT + ΔCFF). We present our results for both time-dependent (renewal) and time-independent (Poisson) models in terms of Peak Ground Acceleration (PGA) maps for 10% probability of exceedance in 50 years. The hazard may increase by more than 20% or decrease by as much as 50% depending on the different occurrence model. Seismic hazard in terms of PGA decreases about 20% in the Messina Strait, where a recent major earthquake took place, with respect to traditional time-independent estimates. PGA near the city of Cosenza reaches ~ 0.36 g for the time-independent model and 0.40 g for the case of the time-dependent one (i.e. a 15% increase). Both the time-dependent and time-independent models for the period of 2015–2065 demonstrate that the city of Cosenza and surrounding areas bear the highest seismic hazard in Calabria.

We forecast time-independent and time-dependent earthquake ruptures in the Marmara region of Turkey for the next 30 years using a new fault segmentation model. We also augment time-dependent Brownian passage time (BPT) probability with static Coulomb stress changes (ΔCFF) from interacting faults. We calculate Mw > 6.5 probability from 26 individual fault sources in the Marmara region. We also consider a multisegment rupture model that allows higher-magnitude ruptures over some segments of the northern branch of the North Anatolian Fault Zone beneath the Marmara Sea. A total of 10 different Mw = 7.0 to Mw = 8.0 multisegment ruptures are combined with the other regional faults at rates that balance the overall moment accumulation. We use Gaussian random distributions to treat parameter uncertainties (e.g., aperiodicity, maximum expected magnitude, slip rate, and consequently mean recurrence time) of the statistical distributions associated with each fault source. We then estimate uncertainties of the 30 year probability values for the next characteristic event obtained from three different models (Poisson, BPT, and BPT + ΔCFF) using a Monte Carlo procedure. The Gerede fault segment located at the eastern end of the Marmara region shows the highest 30 year probability, with a Poisson value of 29% and a time-dependent interaction probability of 48%. We find an aggregated 30 year Poisson probability of M > 7.3 earthquakes at Istanbul of 35%, which increases to 47% if time dependence and stress transfer are considered. We calculate a twofold probability gain (ratio time dependent to time independent) on the southern strands of the North Anatolian Fault Zone.

This paper deals with a preliminary spatial and temporal analysis of the b-value variability, observed in the area where the August 2016 Amatrice earthquake (ML6.0) occurred. With comparison of the pre- and post periods of the mainshock, an investigation of anomalous zone of b-values was performed aiming to find possible links with barriers and/or asperities in the crustal volume where seismic sequence was developed. Preliminary results show an area with high b-value (b=1.6) where the mainshock originated. Conversely, two low b-value (b=0.8) volumes are located at the border of the seismogenic structure. The location of these two areas is consistent with a preliminary fault slip inversion, suggesting the presence of two highly stressed patches of co-seismic deformation located NW and SE of the mainshock, with a high potentiality to rupture causing a possible moderate or larger event: the first one in the North (Norcia), the second one in South, next to the area of Amatrice and Campotosto.

The recent Amatrice strong event (Mw6.0) occurred on August 24, 2016 in Central Apennines (Italy) in a seismic gap zone, motivated us to study and provide better understanding of the seismic hazard assessment in the macro area defined as “Central Italy”. The area affected by the sequence is placed between the Mw6.0 1997 Colfiorito sequence to the north (Umbria-Marche region) the Campotosto area hit by the 2009 L’Aquila sequence Mw6.3 (Abruzzo region) to the south. The Amatrice earthquake occurred while there was an ongoing effort to update the 2004 seismic hazard map (MPS04) for the Italian territory, requested in 2015 by the Italian Civil Protection Agency to the Center for Seismic Hazard (CPS) of the Istituto Nazionale di Geofisica e Vulcanologia INGV. Therefore, in this study we brought to our attention new earthquake source data and recently developed ground-motion prediction equations (GMPEs). Our aim was to validate whether the seismic hazard assessment in this area has changed with respect to 2004, year in which the MPS04 map was released. In order to understand the impact of the recent earthquakes on the seismic hazard assessment in central Italy we compared the annual seismic rates calculated using a smoothed seismicity approach over two different periods; the Parametric Catalog of the Historical Italian earthquakes (CPTI15) from 1871 to 2003 and the historical and instrumental catalogs from 1871 up to 31 August 2016. Results are presented also in terms of peak ground acceleration (PGA), using the recent ground-motion prediction equations (GMPEs) at Amatrice, interested by the 2016 sequence.

Classical probabilistic seismic-hazard models (Cornell, 1968), which typically refer to the homogeneous Poisson process for earthquake occurrence, are not able to model explicitly the space-time clustering of earthquakes. Clustering may be particularly evident in time windows of days and weeks (e.g., Kagan and Knopoff, 1987; Ogata, 1988), but it may be still appreciable in the medium term, because the time sequences to large earthquakes may last long (Kagan and Jackson, 1991; Parsons, 2002; Faenza et al., 2003; Marzocchi and Lombardi, 2008). The modeling of such a space–time clustering is an important subject of seismological research (Jordan et al., 2011). In fact, accounting for time–space clustering of earthquakes may provide additional information, not only to seismic-hazard assessment aimed at structural design (e.g., Iervolino et al., 2014; Marzocchi and Taroni, 2014), but also to short-term seismic risk management. The latter issue has been explored by the International Commission for Earthquake Forecasting, established after the L’Aquila earthquake in 2009, which paves the way to the so-called operational earthquake forecasting (OEF). As defined by Jordan et al. (2011), OEF comprises procedures for gathering and disseminating authoritative information about the time dependence of seismic hazards to help communities prepare for potentially destructive earthquakes. Notwithstanding some recent earthquake sequences showing the importance of tracking the time evolution of seismic hazard (e.g., as for the recent Canterbury sequence in New Zealand; Wein and Becker, 2013), currently OEF represents a controversial issue in seismology. Most critics are not focused on debating the scientific credibility of the models used to describe short-term earthquake clustering, but they dispute the usefulness (if not the potential danger) of the information they provide, in particular, the probability of a damaging event in a short time frame. According to OEF models available in the literature, the weekly probability of a large earthquake (e.g., of magnitude six or larger) is above a few percent only after another large event. During a seismic sequence of moderate events (e.g., of maximum magnitude less than five), the weekly probability of a large event may increase also by two to three orders of magnitude with respect to the background value, but almost always this probability remains below a few percent (Jordan et al., 2011). These figures sparked a debate among seismologists about the usefulness and danger of releasing information on the time evolution of short-term earthquake probability. A comprehensive discussion of all these issues can be found in Jordan et al. (2014) and Wang and Rogers (2014). In this article, we focus our attention on one particular aspect of this discussion. In particular, we put forward a different perspective that should replace the common practice of discussing when the probability of a large earthquake can be considered small. As a matter of fact, in a risk-informed decision framework, the variable of interest should be a probabilistically assessed loss (consequence) metric, for instance, the expected loss. A comparison of such a risk metric with some risk thresholds for individuals and/or for communities may help in understanding whether the risk is tolerable or not, and in choosing the optimal risk management decision. A step in this direction has been recently made by Iervolino et al. (2015), which introduces the operational earthquake loss forecasting (OELF) concept. Specifically, OELF translates short-term seismic hazard (OEF) into risk assessment (i.e., the weekly expected loss), using some specific metric, such as the expected number of collapsed buildings, displaced residents, injuries, and fatalities (see also van Stiphout et al., 2010; Zechar et al., 2014). Along these lines, in this article we analyze the evolutions of seismicity forecasts and consequent seismic risk for a seismic sequence that occurred in southern Italy in 2012 and featuring an ML 5.0 largest shock (the Pollino sequence hereafter). This sequence lasted for more than one year, and it was not associated with any destructive earthquake. In particular, the OEF seismicity rates and consequent OELF weekly estimates are evaluated as a function of time for a period spanning 2010–2013 to capture the full evolution of the sequence. Seismic risk metrics are compared with some reference risk values referring to other events from the literature.