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The Epidemic Type Aftershock Sequence (ETAS) model describes how an earthquake generates its own aftershocks. The regular ETAS model assumes that distribution F of the number of direct aftershocks is Poissonian, however there is evidence suggesting that a geometric distribution might be more adequate. Let |${{V}_M}({{m}_ \bullet })$| be the number of |$m > M$| aftershocks generated by |${{m}_ \bullet }$| event. In this study we consider the |${{V}_M}({{m}_ \bullet })$| distribution within Epidemic-type Seismicity models, ETAS(F). These models include the Gutenberg–Richter law for magnitude and Utsu law for average |${{m}_ \bullet }$| -productivity, but differ in the type of F distribution for the number |$v({{m}_ \bullet })$| of direct aftershocks. The class of F is quite broad and includes both the Poisson distribution, which is the basis for the regular ETAS model, and its possible alternative, the Geometric distribution. We replace the traditional |$M = {{m}_ \bullet } - \Delta $| threshold in |$\Delta $| -analysis with |$M = {{m}_a} - \Delta $| where |${{m}_a}$| is the distribution mode of the strongest aftershocks. Under these conditions we find the limit |${{V}_M}({{m}_ \bullet })$| distribution at |${{m}_ \bullet } > > 1$|⁠. In the subcritical case, the limit distribution is extremely simple and identical to the |$v({{m}_\Delta })$| distribution with a suitable magnitude |${{m}_\Delta }$|⁠. This result allows us to validate both the priority of the geometric distribution of F for direct aftershocks and the very concept of epidemic-type clustering on global seismicity data. [ABSTRACT FROM AUTHOR]

Different approaches exist to describe the seismic triggering of rockfalls. Statistical approaches rely on the analysis of local terrain properties and their empirical correlation with observed rockfalls. Conversely, deterministic, or physically based approaches, rely on the modeling of individual trajectories of boulders set in motion by seismic shaking. They require different data and allow various interpretations and applications of their results. Here, we present a new method for earthquake-triggered rockfall scenario assessment adopting ground shaking estimates, produced in near real-time by a seismological monitoring network. Its key inputs are the locations of likely initiation points of rockfall trajectories, namely, rockfall sources, obtained by statistical analysis of digital topography. In the model, ground shaking maps corresponding to a specific earthquake suppress the probability of activation of sources at locations with low ground shaking while enhancing that in areas close to the epicenter. Rockfall trajectories are calculated from the probabilistic source map by three-dimensional kinematic modeling using the software STONE. We apply the method to the 1976 MI = 6.5 Friuli earthquake, for which an inventory of seismically-triggered rockfalls exists. We suggest that using peak ground acceleration as a modulating parameter to suppress/enhance rockfall source probability, the model reasonably reproduces observations. Results allow a preliminary impact evaluation before field observations become available. We suggest that the framework may be suitable for rapid rockfall impact assessment as soon as ground-shaking estimates (empirical or numerical models) are available after a seismic event. [ABSTRACT FROM AUTHOR]

In the network‐based on‐site earthquake early warning system (EEWS), the 'blind zone', namely the zone where the issued warning arrives later than the destructive S and surface waves, is one of the challenges affecting its effectiveness. The 'blind zone' is determined by the interstation distance, or equivalently the density of seismic stations, of the network. In this paper, we suggest a practical approach according to which, when in a region a temporary increase of seismic hazard is declared, additional stations are deployed in such a way that the blind zone is temporarily reduced. In the procedure, the time‐dependent neo‐deterministic seismic hazard assessment (TD‐NDSHA) plays a vital role in the identification of the regions potentially exposed to high macroseismic intensities. As a showcase example, we consider the scenario of year 2014 at the Sichuan‐Yunnan border of southwest China. The TD‐NDSHA is based on the standard NDSHA procedure at regional scale (bedrock conditions), with the 'controlling earthquakes' defined on the basis of the Annual Consultation. We show that the 'blind zone' can be reduced in the identified areas of interest (e.g., MMI ≥ VI), by deploying a limited number of additional seismic stations. In the case where false alarms can be tolerated, significant reduction of the 'blind zone' can be implemented by moving from a network‐based EEWS to a single‐sensor‐based EEWS and skipping the process of location and magnitude‐determination/prediction procedures. [ABSTRACT FROM AUTHOR]

In the neo-deterministic seismic hazard assessment (NDSHA) evaluation, great-earthquake-prone areas (GEPAs) play an important role in defining the 'controlling earthquakes' or 'scenario earthquakes'. When considering great earthquakes, their finite rupture attributes, which contribute to determine the strong ground motions and intensities, have to be taken into account. For continental earthquakes in China, the great earthquakes are located mainly within the boundary zones of the 'tectonic blocks'. The 'tectonic block' model indicates the focal mechanisms and some finite rupture attributes of the great earthquakes within the boundary zones. Accordingly, in the NDSHA for China, it is both necessary and feasible for the GEPAs to consider the finite rupture attributes of great earthquakes. The Sichuan-Yunnan border in southwest China has been taken as an example to naturally develop the originally used circular shape of GEPAs into one with more degrees-of-freedom, better reflecting the possible rupture processes of the considered earthquakes. [ABSTRACT FROM AUTHOR]

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. Plain Language Summary: Clustering, in both space and time, is a widely recognized feature of seismicity. An adequate identification of earthquake clusters allows splitting seismicity into background and clustered events (e.g., aftershocks) and is an essential step in several studies, ranging from seismic hazard assessment to long‐ and short‐term earthquake forecasting. Also, the space‐time patterns of identified clusters may provide useful insights on the structural and dynamic tectonic features of a region. Among the several methods proposed so far to identify and characterize seismic clusters, 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 may lead to different classifications of earthquakes into background events and clustered events. Therefore, this study aims to compare their performances, including clusters structure characterization, by exploiting tree graph representations and tools from network analysis. We found that (1) the two declustering algorithms produce similar partitions of the earthquake catalog; (2) they may differ in the internal structure outlined for individual clusters, with the nearest‐neighbor method usually providing simpler structures than the stochastic declustering method; and (3) these features can be robustly quantified by centrality measures widely used in network analysis. Key Points: Two recent data‐driven declustering methods are compared, one based on nearest‐neighbor distance and one on the ETAS modelSimilarities in classification and in earthquake clusters are investigated by tree graphs and tools from network analysisObtained clusters are consistent, though nearest‐neighbor method usually provides simpler structures than stochastic declustering method [ABSTRACT FROM AUTHOR]

Identification of earthquake clusters has a twofold scope: a) characterisation of clustering features and their possible relation to physical properties of the crust; b) declustering of the earthquake catalogues, to allow for space-time analysis of mainshocks occurrence. Since different methods, relying on different physical/statistical assumptions, may lead to diverse classifications of earthquakes into main events and related events, we investigate the classification differences for three different declustering techniques: the nearest-neighbour approach (NN) and the two widely used windows methods by Gardner-Knopoff and Uhrhammer. A formal selection and comparative analysis of earthquake clusters is carried out for selected earthquakes in north-eastern Italy and adjacent regions, as reported in the OGS catalogue since 1977. The comparison is, then, extended to earthquake sequences associated with strong earthquakes in central Italy, occurring in a different seismotectonic setting, by making use of INGV data over the period 1981-2017. The NN data-driven approach turns out well consistent with classical window approach for large events, while improving clusters identification in areas characterised by low to moderate seismic activity, where windowing methods necessitate adequate optimisation. Moreover, the declustering performed by NN method preserves the features of inhomogeneous and possibly nonstationary background seismicity, relevant for several studies. [ABSTRACT FROM AUTHOR]

Abstract 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). Highlights • Seismicity preceding the 2017 Mw = 7.3 Iran earthquake is analyzed by RTL algorithm. • An enhanced variant of RTL maps is proposed that highlights stable quiescences. • A quiescence lasting for several months is detected before the earthquake. • The quiescence extends in a broad region, along Zagros Mountains. [ABSTRACT FROM AUTHOR]

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). [ABSTRACT FROM AUTHOR]

The aim of this study is to associate the expected ground motions from Neo-Deterministic Seismic Hazard Assessment (NDSHA) to robust estimates of their long-term average occurrence rates. NDSHA means scenario-based methods for seismic hazard analysis, where realistic and duly validated synthetic time series, accounting for source, propagation, and site effects, are used to construct ground motion scenarios. NDSHA, in its standard form, defines the hazard as the envelope ground shaking at the site, namely the maximum estimate computed from a large set of possible scenario earthquakes. Thus, the standard NDSHA maps provide rather robust and conservative hazard estimates, which do not require any assumption about the probabilistic model of earthquakes occurrence. Some specific applications, however, may benefit from temporal information about the computed ground shaking, including a gross estimate of its average recurrence time. For this purpose, the definition of the Frequency-Magnitude (FM) relation for earthquakes in the Italian region is performed according to the multi-scale seismicity model and an occurrence rate estimate is associated to each of the modeled sources. The introduction of occurrence rate estimates in NDSHA also allows for the generation of ground shaking maps for specified time intervals (often improperly referred as “return periods”) that permit a straightforward comparison between the NDSHA and the PSHA maps. [ABSTRACT FROM AUTHOR]

A regional approach to the problem of assessing earthquake predictions inevitably faces a deficit of data. We point out some basic limits of assessment methods reported in the literature, considering the practical case of the performance of the CN pattern recognition method in the prediction of large Italian earthquakes. Along with the classical hypothesis testing, a new game approach, the so-called parimutuel gambling (PG) method, is examined. The PG, originally proposed for the evaluation of the probabilistic earthquake forecast, has been recently adapted for the case of 'alarm-based' CN prediction. The PG approach is a non-standard method; therefore it deserves careful examination and theoretical analysis. We show that the PG alarm-based version leads to an almost complete loss of information about predicted earthquakes (even for a large sample). As a result, any conclusions based on the alarm-based PG approach are not to be trusted. We also show that the original probabilistic PG approach does not necessarily identifies the genuine forecast correctly among competing seismicity rate models, even when applied to extensive data. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Rigorous and objective testing of seismic hazard assessments against the real seismic activity must become the necessary precondition for any responsible seismic risk estimation. Because seismic hazard maps seek to predict the shaking that would actually occur, the reference hazard maps for the Italian seismic code, obtained by probabilistic seismic hazard assessment (PSHA), and the alternative ground shaking maps based on the neo-deterministic approach (NDSHA), are cross-compared and tested against the real seismicity for the territory of Italy. The comparison between predicted intensities and those reported for past earthquakes shows that models generally provide rather conservative estimates, except for PGA with 10 % probability of being exceeded in 50 years, which underestimates the largest earthquakes. In terms of efficiency in predicting ground shaking, measured accounting for the rate of underestimated events and for the territorial extent of areas characterized by high seismic hazard, the NDSHA maps appear to outscore the PSHA ones. [ABSTRACT FROM AUTHOR]

Pattern informatics (PI) algorithm, which was introduced at the beginning of past decade, uses instrumental earthquake catalogs to investigate the time-dependent rate of seismicity in the study area and, based on the information from past events, calculates the probabilities for the occurrence of future large earthquakes. The main measure in this method is the number of events above a specified magnitude threshold M that is counted over a gridded area. PI has been applied in several regions of the world and different variants of the method have been developed over the past decade. Hence, the problem of formally evaluating and comparing the performances of the different PI variants needs to be addressed from an operational perspective, in order to identify the preferred application scheme and as well as to improve the performances of the method. In this study, PI is applied for the first time to the retrospective analysis of the earthquake catalogs of Iran and Italy, so as to check whether this method could forecast the past large events in these two regions with different level of data completeness and complex seismotectonic setting. The original PI algorithm and one of its modified variants, as well as the relative intensity (RI) model, are used to check the stability and statistical significance of the obtained results. In order to assess and compare the obtained results, the performances of the different PI variants are analyzed considering different evaluation strategies, which turn out to provide significantly different scores even for the same algorithm variant. We show that a critical point in the assessment of the obtained results is related with the definition and quantification of the space uncertainty of the issued forecasts, that is, with the extent of the territory where large earthquakes are to be expected. Accordingly, we emphasize the need for an appropriate definition of the evaluation strategies, clearly and unambiguously indicating the area where a large earthquake has to be expected. The study shows that, with respect to application in Iran and Italy, the performances of PI algorithm (both original and modified variants) are highly dependent on the selected evaluation strategy and do not provide better information than the simple RI model, which does not account for temporal properties of seismicity evolution. The overall performances can be improved by introducing specific thresholds that discard the less active cells; however, being based on some posterior optimization, a rigorous prospective testing is required to assess the forecasting capability of the method. In this paper, we aim to set up the rules for such testing, including advance definition of the evaluation strategy. [ABSTRACT FROM AUTHOR]

We perform a comparative analysis of regional and global earthquake catalogs currently available for the territory of Italy. We consider: (a) instrumental seismic catalogs provided by the Istituto Nazionale di Geofisica e Vulcanologia, Roma (INGV) for earthquake forecasting experiment in Italy within the Collaboratory for the Study of Earthquake Predictability (CSEP); (b) Global Hypocenters' Data provided by the USGS/NEIC, which is currently used in the real-time earthquake prediction experiment by CN and M8S algorithms in Italy, and (c) seismological Bulletin provided by the International Seismological Centre (ISC). We discuss advantages and shortcomings of these catalogs in the context of intermediate-term middle-range earthquake prediction problem in Italy, including the possibility of the catalog's combined or integrated use. Magnitude errors in the catalog can distort statistics of success-to-failure scoring and eventually falsify testing results. Therefore, the analysis of systematic and random errors in magnitude presented in Appendixes can be of significance in its own right. [ABSTRACT FROM AUTHOR]

Estimates of seismic hazard obtained using the neo-deterministic approach (NDSHA) and the probabilistic approach (PSHA) are compared for the Italian territory. The NDSHA provides values larger than those given by the PSHA in areas where large earthquakes are observed and in areas identified as prone to large earthquakes, but lower values in low-seismicity areas. These differences suggest the adoption of the flexible, robust and physically sound NDSHA approach to overcome the proven shortcomings of PSHA, thus allowing for a reliable seismic hazard estimation, especially for those areas characterized by a prolonged quiescence, i.e. in tectonically active sites where events of only moderate size have occurred in historical times. [ABSTRACT FROM AUTHOR]

The article discusses various reports published within the issue, including one by Asano and Iwata on prediction of inland crustal earthquakes, one by Ruiz and colleagues on earthquake asperities in the Chilean subduction zone, and one on the technique for evaluation of predicted ground motions.

We introduce a new method based on the analysis of the topographical alignments and used to delineate the structural boundaries of the nodes, which permits the definition of relatively narrow earthquake-prone areas by the pattern recognition approach. The structurally bounded nodes capable of earthquakes with M ≥ 6.0, identified with pattern recognition, in fact, cover a significantly smaller area of the study region as compared with that defined by Gorshkov et al. (2004) who used conventional circles. The proposed method thus improves the precision in the location of potential large earthquakes. [ABSTRACT FROM AUTHOR]

The numerical block-model of the lithosphere dynamics is used to simulate seismicity in Italy and its surroundings, based on the available structural and geodynamics information. The purpose of the study is to understand which are the tectonic processes that control the main features of the observed seismicity and the kinematics of the region. The influence of the rheology of the fault systems is studied as well. The model we use differs from other modeling approaches in that it simulates earthquakes and hence it possibly relates to seismicity and geodynamics. The model provides an effective capability to include the set of documented constraints supplied by widely available earthquake catalogs. This is done by means of the comparison of the GR relation, of the focal mechanisms and of the space distribution for observed and computed seismicity. The region is modeled as a system of perfectly rigid blocks, separated by infinitely thin fault planes, in viscoelastic interaction between themselves and with the underlying medium. The movement of the boundary blocks and of the underlying medium determines the motion of the blocks. The synthetic seismicity obtained with the defined block-model is similar to the observed one for the most seismically active areas. A linear frequency-magnitude (FM) relation (Gutenberg-Richter law) is obtained for synthetic earthquakes; the slope ( b-value) of the FM plot appears larger for the synthetic seismicity than for the observed one. Nevertheless, the b-value is essentially larger in northern and central Italy than that in southern Italy, both in the model and in the observations. The analysis of the source mechanisms of the synthetic earthquakes shows a good agreement with the observations. In the model normal faulting is typical for the Apennines, the eastern edge of Sicily and the Calabrian arc, while reverse faulting takes place at the northwestern boundary of the Adriatic Sea, in the southern Alps and along the eastern edge of the Adria, along the Dinarides. The model correctly reproduces the extension zone along the Apennines and the contraction zone along the northwestern boundary of the Adriatic Sea; the counter-clockwise rotation of the Adria is mimed. The resulting movements of the blocks are in overall agreement with GPS (Global Positioning System) observations. The results of the modeling experiments suggest that the main features of dynamics and seismicity in the central Mediterranean region cannot be satisfactorily explained as a consequence of Africa and Eurasia convergence only; the passive subduction in the Calabrian arc and the different rheology of faults are essential as well. [ABSTRACT FROM AUTHOR]

The possibility of intermediate-term earthquake prediction at Mt. Vesuvius by means of the CN algorithm is explored. CN was originally designed to identify the Times of Increased Probability (TIPs) for the occurrence of strong tectonic earthquakes, with magnitude M ≥ M 0, within a region a priori delimited. Here the CN algorithm is applied, for the first time, to the analysis of volcanic seismicity. The earthquakes recorded at Mt. Vesuvius during the period from February 1972 to June 2004 are considered, and the magnitude threshold M 0 selecting the events to be predicted is varied within the range: 3.0–3.3. Satisfactory prediction results are obtained, by retrospective analysis, when a time scaling is introduced. In particular, when the length of the time windows is reduced by a factor 2.5–3, with respect to the standard version of CN algorithm, more than 90% of the events with M ≥ M 0 occur within the TIP intervals, with TIPs occupying about 30% of the total time considered. The control experiment ``Seismic History'' demonstrates the stability of the obtained results and indicates that the CN algorithm can be applied to monitor the preparation of impending earthquakes with M ≥ 3.0 at Mt. Vesuvius. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The statistical features of earthquake clusters in North-Central Iran (Tehran Region) are investigated, with the aim of quantitatively characterizing the properties of earthquake triggering and allow exploring their possible relations with the tectonic setting of the study area. The nearest-neighbor approach is used for the identification of the earthquake clusters in the space-time-energy domain. This approach permits for a data-driven identification of clusters so that, within multi-event clusters, the features of secondary and higher orders dependent events can be explored. The study is based on a revised dataset that is extracted from the catalog compiled by the Iranian Seismological Center (IRSC) for the period of 1996–2022. In order to exclude the effect of non-tectonic events, which turn out quite numerous within the study region, explosions within quarry-rich areas are removed; the identification of non-tectonic events is performed by considering the normalized ratios of daytime to nighttime events in an iterative removal procedure. According to preliminary analysis of the resulting catalog, an area is selected, within which a satisfactory completeness level is assessed for events with magnitude >2.0. Robust values of the scaling parameters, namely the b-value and the fractal dimension of epicenters, are also computed and are used to calculate the nearest-neighbor distances and to identify the earthquake clusters. The nearest-neighbor method also permits to 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. The obtained results allow us identifying two macro-areas, approximately separated by the 52°E meridian, which are characterized by different clustering features, namely: high complexity indexes, indicating simple (burst-like) structure of clusters, to the East; low complexity index, corresponding to complex multi-level (swarm-like) structure of clusters, to the West. The complexity measures, borrowed from network theory (i.e. the Closeness and Outdegree Centralization indexes), consistently capture the complexity of the identified clusters, and confirm that the cluster structures have distinct preferred geographic locations. The territorial heterogeneity of the examined clustering properties can be related with the spatial variability of tectonic, structural and geophysical features of the Alborz region, in good agreement with findings from the Alps-Dinarides junction (Northeastern Italy), a region also characterized by a contractional structural setting, mainly including reverse and strike-slip faulting systems, and by moderate to high seismic activity. [Display omitted] • Earthquake clusters complexity in Alborz region (North-Central Iran) is investigated • A robust method to quantitatively and systematically analyze clustering features is proposed • Tree graphs and tools from network analysis are used to describe clusters topological structure • Two macro-areas are identified based on different measures of clustering features • Swarm-like sequences are typical in Central-West Alborz domain while burst-like prevail in Central-East one [ABSTRACT FROM AUTHOR]

Earthquake clustering is an essential property of seismicity and the space-time patterns of the identified seismic clusters may provide important information about the structural and dynamic features of an area. Still, the application of different methods, relying on different physical and/or statistical assumptions, may lead to diverse identification earthquake clusters and of their internal structure. Moreover, the techniques used to formally describe the topological complexity of clusters' related structure, including quantitative metrics and graphical tools, may provide a different insight on the same process. Hence we examine different declustering techniques, to investigate classification similarities and differences that might highlight their strengths/limits, and we explore the possible contribution to clusters characterization provided by some existing and new tools. In particular, two clustering approaches are applied: - the "nearest-neighbor" method (NN), which is based on nearest-neighbor distances between events in space-time-energy domain, - the stochastic declustering method (SD), which is based on the space-time ETAS (epidemic-type aftershock sequence) model, a branching point process defined by a hazard function conditional on the observation history.Both methods are data-driven and can be satisfactorily applied to decompose the seismic catalog into background seismicity and individual sequences of earthquakes; in addition, they provide the links between events forming each cluster (or even several possible realizations of it, in the case of SD method), and thus allow studying the internal structure of the identified sequences.In this study we investigate the spatio-temporal features of earthquake clustering in Northeastern Italy, based on a systematic analysis of robustly detected seismic sequences reported in the local bulletins, compiled at the National Institute of Oceanography and Experimental Geophysics (OGS) since 1977. We uniformly analyse the sequences identified by the two methods and we find that a comparable number of clusters is detected by both declustering methods: most of the events included in a SD-cluster are also included in the corresponding NN-cluster. Moreover, since both methods establish hierarchical relationships among events in a cluster, it is possible to represent each cluster as a tree graph in which the internal structure is displayed. Accordingly, we analyse in some detail the tree structure for a set of selected sequences. For this purpose we borrow some measures of centrality from network analysis, with the aim of characterizing the internal structure of the clusters in the study region, and to identify possible common features that emerge from both declustering methods. [ABSTRACT FROM AUTHOR]

The Region Time Length (RTL) algorithm is a method for intermediate term forecasts of large earthquakes, 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 of the World during the last decades. Recent versions of the algoritm permit to analyse the possible quiescence not only in the area surrounding the mainshock epicentre, but they allow drawing maps for the whole investigated region. The specific selection of the parameters affects the shape of the RTL and therefore the maps obtained, because of the different time and space window considered. In this study, we propose a new anhanced variant of RTL, which highlights only quiescences consistently detected for different choices of the free parameters, and hence is more stable.Just as many other methods developed for the analysis of seismicity, RTL algorithm needs as input a declustered catalogue. For this purpose, we apply a new declustering tecnique based on the nearest-neigbour distances between events in the space-time-energy domain; this method in fact, while removing the identified aftershocks, allows preserving the background seismicity. To exemplify the application of this variant of RTL algorithm we analyse seismicity preceding the Sarpol Zahab Mw 7.3 earthquake (12 November 2017), with the aim to understand whether the information from past events could provide some insights about the occurrence of this and other large earthquakes that occurred in the area. The retrospective application of RTL algorithm to Northwestern Iran, evidenced two broad quiescence regions, oriented NW-SE along the Zagros belt. One, located to the north, well corresponds to the Sarpol Zahab earthquake location and disappears immediately after the event. The second one, located in the southeastern part of the study region, persists up to the end of 2018. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

A major earthquake, with magnitude Mw=7.3, struck the Northwestern part of Iranon November 12 2017, causing extended damage and casualties. The aftershocksequence is still ongoing, as testified by the two recent M6.4 (November 25, 2018)and M5.9 (January 6, 2019) events that occurred in the area more than one yearafter the mainshock. Thus, we investigate the aftershock sequence following thisearthquake, with the aim to understand whether it fits the classical laws of aftershocksoccurrence (e.g. the Omori Law), and to explore whether observed deviations from theselaws could provide some insights about the occurrence of possible further largeaftershocks. The Delta/Sigma method (Caccamo et al., 2005. Physics of the Earth and PlanetaryInteriors 153, 175–180), is used for this purpose, which is based on the observation ofpossible anomalies in the temporal decay of an aftershock sequence. Specifically, if the decaycan be modeled as a non-stationary Poissonian process, where the intensity function is equalto n(t) = K ⋅ gt + c)−p + K1, the number of aftershocks in a short time interval Δtis themean value n(t) ⋅ Δt, with a standard deviation Sigma2 = n(t) ⋅ Δt. Given the differencebetween observed and estimated number of events Delta = |Nobs-Ncalc|, it was found that,before the occurrence of large aftershocks, the Delta/Sigma ratio may reach rather highvalues, which can be considered as seismic anomalies. The Delta/Sigma method has beenapplied to several aftershocks sequences worldwide and different improvements of themethod have been developed during the last years, but it still requires rigorousand extensive testing to assess its capability in describing observed aftershocksoccurrence. The basic data used in this study have been extracted from the regional catalog of the IranianSeismological Center (IGTU catalog), which is available at http://irsc.ut.ac.ir/bulletin.php/.The IGTU catalog lists events with magnitude M≥2.5, recorded in the Iranian plateau andadjacent areas since 1 January 2006. Various experiments are carried out in order to verify if this method could identify thelarge aftershocks (with M≥4.8), which occurred in the region surrounding the Mw 7.3mainshock occurred in November 2017. Different input parameters and configurations of themethod are considered, in order to check the stability and statistical significance of theobtained results. The preliminary results of the study indicate that the application ofDelta/Sigma method to the Northwestern region of Iran, surrounding the Mw 7.3earthquake occurred in November 2017, could highlight the possible occurrence ofseveral significant aftershocks. Based on these results, the analysis is expanded toANSS global data provided by USGS, in order to assess the stability of the detectedpattern, which might provide relevant information for seismic risk assessment. [ABSTRACT FROM AUTHOR]

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 shallow depth of such events (<2 km), they can generate serious damage and casualties, up to the complete destruction of urban centers located within short epicentral distance. 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 the town of Casamicciola. In fact, Casamicciola was completely destroyed by the 1883 earthquake (2313 victims) and experienced intensities up to XI degree on the Mercalli scale. Historical records show that the background seismicity here is almost absent, but larger earthquakes tend to occur in clusters, lasting some decades and 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 to tectonic earthquakes of similar magnitude, larger effects though limited to a relatively small area, make the seismicity in this island very peculiar. Despite such destructive record, till now official hazard maps strongly underestimated the seismic hazard in this area. On August 21st 2017, a very shallow earthquake with rather small magnitude struck the area of Casamicciola, killing two people, injuring many more and causing huge damage and partial to total collapse of edifices located just above 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 the same time, can avoid further grief due to possible occurrence of other destructive earthquakes within a short time interval. We describe the most likely building collapse 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 an example 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 earthquakes, which in Italy are often characterized by low or moderate magnitudes. • Low magnitude, very shallow earthquakes can be locally destructive • Ischia island is prone to shallow, destructive earthquakes, clustered in time • The 2017, M = 4.0 earthquake caused victims, injured people, and might indicate the beginning of a new earthquake cluster • Innovative methods to reliably assess seismic hazard, based on NDSHA, are presented • A fast, comprehensive procedure to secure urban areas from shallow earthquakes is presented [ABSTRACT FROM AUTHOR]