1,721,033 research outputs found
Assessment of pre-crisis and syn-crisis seismic hazard at Campi Flegrei and Mt. Vesuvius volcanoes, Campania, southern Italy
No full textIn this study, we address the issue of short-term to medium-term probabilistic seismic hazard analysis for two volcanic areas, Campi Flegrei caldera and Mt. Vesuvius in the Campania region of southern Italy. Two different phases of the volcanic activity are considered. The first, which we term the pre-crisis phase, concerns the present quiescent state of the volcanoes that is characterized by low-to-moderate seismicity. The second phase, syn-crisis, concerns the unrest phase that can potentially lead to eruption. For the Campi Flegrei case study, we analyzed the pattern of seismicity during the 1982-1984 ground uplift episode (bradyseism). For Mt. Vesuvius, two different time-evolutionary models for seismicity were adopted, corresponding to different ways in which the volcano might erupt. We performed a site-specific analysis, linked with the hazard map, to investigate the effects of input parameters, in terms of source geometry, mean activity rate, periods of data collection, and return periods, for the syn-crisis phase. The analysis in the present study of the pre-crisis phase allowed a comparison of the results of probabilistic seismic hazard analysis for the two study areas with those provided in the Italian national hazard map. For the Mt. Vesuvius area in particular, the results show that the hazard can be greater than that reported in the national hazard map when information at a local scale is used. For the syn-crisis phase, the main result is that the data recorded during the early months of the unrest phase are substantially representative of the seismic hazard during the whole duration of the crisis
Ground Motion Predection Equations as proxy for monitoring and interpreting induced-seismicity data
No full textInvestigating Triggering of the Aftershocks of the 2014 Napa Earthquake
No full textThe occurrence of the Mw 6.0 South Napa California earthquake, on 24 August 2014 at 03:20 a.m. local time, triggered discussion in the seismological community about the level of damage associated with such a moderate-magnitude event and about the geometry and orientation of the causative fault. In addition, coulomb static stress change mapping does not seem to be able to fully explain near-source aftershock distribution. Here, we find clear evidence of a north-northwest source directivity from the analysis of the spatial distribution of peak ground motion. The area of the highest values of the estimated peak dynamic strain field, computed accounting for fault extent and source directivity, agrees with the near-source aftershock distribution. This might suggest that, in addition to coulomb static stress change, dynamic strain also contributed to the triggering of near-source Napa earthquake aftershocks. The approach used here might be useful to identify areas likely prone to aftershock occurrence
Author Correction: Deep learning forecasting of large induced earthquakes via precursory signals
No full textThe Cry-wolf Issue in Seismic Early Warning Applications: a feasibility study for the Campanian Region (southern Italy)
No full textSeismic risk management consists of mitigation strategies, planning and emergency preparedness. Early warning systems (EWS), based on real-time analysis of ground motion proxy measures, may play a role in reducing vulnerability of built environment and lifelines. EWS applications may not be cost free and their effectiveness is related to missed and false alarm probabilities (PMA and PFA respectively). The Campanian region in southern Italy is developing a seismic early warning systems for the active area where the Irpinia 1980 earthquake was generated. The work herein discussed represents a feasibility study on the cry wolf issue in seismic early warning applications. The false and missed alarm events are formulated in terms of structural response parameters and ground motion intensity measures. PMA and PFA are computed simulating the EWS prediction of ground motion by use of simulated ground motion; the site where the structure is supposed to be located is assumed to be at 100 km from the EW network. The I and II type risk are evaluated for the decisional rule adopted and operating characteristic curves are developed
Predizione dello spettro di risposta da misure in tempo reale di sistemi di Early Warning Sismico
No full textI Sistemi di Early Warning Sismico, in configurazione sia regionale che on-site, possono essere utili alla miti-gazione dell’impatto dei terremoti medi e forti. La capacità di tali sistemi di fornire la localizzazione e la ma-gnitudo del terremoto in tempo reale, può essere utilizzata per attivare contromisure prima dell’arrivo delle onde più energetiche al sito di interesse. Esistono però alcuni aspetti critici dei sistemi EWS che necessitano di analisi dettagliate: (1) le incertezze sulla stima della magnitudo e della localizzazione ottenute a partire dall’analisi dei segnali nei primissimi secondi di registrazione dell’evento sismico; (2) l’identificazione del parametro da utilizzare per la predizione del moto del suolo al sito di interesse; (3) come utilizzare le stime fornite dal sistema Early Warning Sismico per applicazioni di ingegneria sismica; (4) mancato e falso allarme.Nel presente studio, vengono affrontati i punti elencati utilizzando come area test la regione Campania (Italia) in cui è in fase di installazione un sistema prototipo di Early Warning Sismico. Lo studio delle incertezze vie-ne effettuato attraverso un’analisi probabilistica in tempo reale utilizzando due approcci di stima della magni-tudo: uno che utilizza una stima campionaria elementare ed uno bayesiano. Entrambi gli approcci sono stati applicati, in simulazione, a due siti ubicati a Napoli ed Avellino rispettivamente. L’analisi di mancato e false allarme è stata effettuata per un terremoto di magnitudo M 7.0 localizzato al centro della rete sismica. Perquanto concerne la predizione del moto del suolo, l’attenzione è stata focalizzata sullo spettro di risposta ela-stico, ritenuta la funzione più appropriata per applicazioni ingegneristiche dei sistemi EWS
A data-driven artificial neural network model for the prediction of ground motion from induced seismicity: The case of The Geysers geothermal field
No full textGround-motion models have gained foremost attention during recent years for being capable of predicting ground-motion intensity levels for future seismic scenarios. They are a key element for estimating seismic hazard and always demand timely refinement in order to improve the reliability of seismic hazard maps. In the present study, we propose a ground motion prediction model for induced earthquakes recorded in The Geysers geothermal area. We use a fully connected data-driven artificial neural network (ANN) model to fit ground motion parameters. Especially, we used data from 212 earthquakes recorded at 29 stations of the Berkeley–Geysers network between September 2009 and November 2010. The magnitude range is 1.3 and 3.3 moment magnitude (Mw), whereas the hypocentral distance range is between 0.5 and 20 km. The ground motions are predicted in terms of peak ground acceleration (PGA), peak ground velocity (PGV), and 5% damped spectral acceleration (SA) at T=0.2, 0.5, and 1 s. The predicted values from our deep learning model are compared with observed data and the predictions made by empirical ground motion prediction equations developed by Sharma et al. (2013) for the same data set by using the nonlinear mixed-effect (NLME) regression technique. For validation of the approach, we compared the models on a separate data made of 25 earthquakes in the same region, with magnitudes ranging between 1.0 and 3.1 and hypocentral distances ranging between 1.2 and 15.5 km, with the ANN model providing a 3% improvement compared to the baseline GMM model. The results obtained in the present study show a moderate improvement in ground motion predictions and unravel modeling features that were not taken into account by the empirical model. The comparison is measured in terms of both the R2 statistic and the total standard deviation, together with inter-event and intra-event components
Source parameter scaling and radiation efficiency of microearthquakes along the Irpinia fault zone in southern Apennines, Italy
No full textWe analyzed the P and S wave displacement spectra of 717 microearthquakes in the moment range 4 x 10(9) - 2 x 10(14) N m recorded at the dense networks operating in southern Apennines (Italy) and deployed along the 1980 M-s 6.9 Irpinia earthquake fault zone. Source, attenuation, and site parameters are estimated by using a parametric modeling approach, which is combined with a multistep, nonlinear inversion strategy. We found that in the analyzed frequency band, an attenuation model with constant Q has to be preferred to frequency- dependent Q models. Consistent estimates of the median P and S quality factors (Q) over tilde (P) = 167 (90; 296) and (Q) over tilde (S) = 226 (114; 417) are obtained from two different techniques and relatively high values of Q(S)/Q(P) (median value 1.3, (0.8; 2.1)) are found in the same depth range where high V-P/V-S and a peak in seismicity distribution are observed. This is the evidence for a highly fractured, partially, or completely fluid-saturated medium embedding the Irpinia fault zone, down to crustal depths of 15- 20 km. A nearly constant stress drop ((Delta sigma) over tilde = 1.4 MPa, (0.4; 5.0)) and apparent stress ((tau(a)) over tilde = 0.1 MPa, (0.03, 0.4)) scaling of P and S corner frequencies and seismic energies is observed above a seismic moment value of about 10(11) N m. The measured radiation efficiency is low ((eta(SW)) over tilde = 0.06; (0.03; 0.13)), e.g., the radiated energy is only a small fraction of the whole energy spent by friction and fracture development. A large positive dynamic overshoot (high dynamic shear strength) can be the dominant mechanism controlling the microearthquake fractures along the Irpinia fault zone
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