ArticlePublisher preview available

A new approach for a fully automated earthquake monitoring: the local seismic network of the Trentino region (NE Italy)

Journal of Seismology

April 2021
25(5):1-14

DOI:10.1007/s10950-021-09993-0

Authors:

Alfio Viganò

Autonomous Province of Trento, Italy

Davide Scafidi

University of Genoa

An application of the Complete Automatic Seismic Processor (CASP) for seismic monitoring is presented. Its integrated and iterative fully automatic procedure is able to achieve complete data analysis and significantly rapid elaborations. Its performance in real-time seismic monitoring and alerting is tested in the Trentino region (NE Italy) for the period 1st March 2018 – 31st August 2019. CASP precisely and accurately located 386 seismic events, with local magnitudes in the -0.8–3.4 range, and produced a seismic catalogue with a magnitude of completeness around 1.1. Automatic earthquake solutions, with average horizontal and vertical errors of 1.1 and 1.5 km, are very similar to those included in a manually revised reference catalogue. In addition, 146 detected events are located in the area of the local porphyry quarries. CASP alerts are delivered as Short Message Service (SMS), Telegram and e-mail messages within an average time of just over two minutes from the earthquake origin time. These alerts contain earthquake source parameters, ground shaking levels and instrumental intensities. CASP reliability, promptness and robustness permit to civil protection and decision makers to perform a monitoring primarily dedicated to emergency management, in order to evaluate both seismic sources and their effects (peak ground acceleration) at local targets, such as more inhabited territories and critical infrastructures (dams and hydropower plants).

Distribution of seismic stations of the Trentino local network (ST code) and other surrounding stations used for monitoring of the study area (green box). The blue polygon delimits the region of Northern Italy where other seismic stations are acquired. Labels are registered station codes (acc, accelerometers; vel, velocimeters). Networks (nets): CH = Switzerland Seismological network (Swiss Seismological Service (SED) at ETH Zürich 1983), GU = Regional seismic network of North Western Italy (University of Genova 1967), IT = Italian strong motion network (Presidency of Council of Ministers—Civil Protection Department 1972), IV = Italian National seismic network (INGV Seismological Data Centre 2006), OE = Austrian seismic network (ZAMG – Zentralanstalt für Meterologie und Geodynamik 1987), SI = Province Südtirol seismic network, ST = Trentino seismic network (Geological Survey–Provincia Autonoma di Trento 1981). Seismic data from stations DBUS, DPIA, DPRA, DSCO and DSPE were not used for this study because not available for the period under consideration

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a Geological map with epicentral distribution of tectonic earthquakes in the periods 1st March 2018–31st August 2019 (in blue) and 1994–2007 (in black, reference revised catalogue from Viganò et al. 2015). b Distribution of cumulative seismic moment release (5 × 5 km squares), considering historical seismicity (CFTI5med; Guidoboni et al. 2018) and 1994–2019 seismicity (data from Viganò et al. 2015, the annual bulletin of the Trentino seismic network, and this study). Buildings of the Autonomous province of Trento highlighted in black. Green boxes as in Fig. 1

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Probabilistic power spectral density (PPSD) of background seismic noise recorded at a DOSS station (velocimeter; HHZ channel), b DVSC station (accelerometer; HNZ channel), and c all ST stations (medians of each channel). Analyzed data for January 2019. See station locations in Fig. 1. The new low noise model (NLNM) and new high noise model (NHNM) from Peterson (1993) are shown for reference

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Horizontal-to-vertical Fourier spectral ratio curves (HVSR) for velocimetric (vel) and accelerometric stations (acc), obtained considering 24-h background noise. DOSS and DVSC curves are highlighted (cf. Fig. 2). The gray box delimits the area with HVSR equal to 2, according to SESAME Working Group (2004) guidelines (see text for comments)

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Flowchart of the CASP integrated iterative working procedure, applied for the automatic monitoring of the Trentino region, compared with a standard procedure where the different phases of analysis are separated and independent (modified from Scafidi et al. 2019)

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ORIGINAL ARTICLE

A new approach for a fully automated earthquake

monitoring: the local seismic network of the Trentino

region (NE Italy)

Alfio Viganò &Davide Scafidi &Gabriele Ferretti

Received: 3 April 2020 /Accepted: 18 February 2021

#The Author(s), under exclusive licence to Springer Nature B.V. part of Springer Nature 2021

Abstract An application of the Complete Automatic

Seismic Processor (CASP) for seismic monitoring is

presented. Its integrated and iterative fully automatic

procedure is able to achieve complete data analysis

and significantly rapid elaborations. Its performance in

real-time seismic monitoring and alerting is tested in the

Trentino region (NE Italy) for the period 1

March 2018

–31

August 2019. CASP precisely and accurately

located 386 seismic events, with local magnitudes in

the -0.8–3.4 range, and produced a seismic catalogue

with a magnitude of completeness around 1.1. Automat-

ic earthquake solutions, with average horizontal and

vertical errors of 1.1 and 1.5 km, are very similar to

those included in a manually revised reference cata-

logue. In addition, 146 detected events are located in

the area of the local porphyry quarries. CASP alerts are

delivered as Short Message Service (SMS), Telegram

and e-mail messages within an average time of just over

two minutes from the earthquake origin time. These

alerts contain earthquake source parameters, ground

shaking levels and instrumental intensities. CASP reli-

ability, promptness and robustness permit to civil pro-

tection and decision makers to perform a monitoring

primarily dedicated to emergency management, in order

to evaluate both seismic sources and their effects (peak

ground acceleration) at local targets, such as more

inhabited territories and critical infrastructures (dams

and hydropower plants).

Keywords Seismic monitoring .automatic seismic

analysis .seismic alert .Complete Automatic Seismic

Processor CASP .Trentino .Italian Alps

1Introduction

Automatic seismic analyses are becoming an increas-

ingly urgent demand, because of the huge amount of

data to be processed and the growth of more and more

specific applications. On the one hand, the scientific

community is avid for high-quality elaborations in order

to satisfy geophysical models and make deep investiga-

tions (e.g., Afonso et al. 2013; DeVries et al. 2018). On

the other hand, real-time earthquake information is

shared in many ways to meet the needs of different

end users (citizens, technicians, civil protection, politi-

cians, and decision makers) (National Research Council

2006). Automatic seismological procedures are com-

monly applied for seismic and environmental monitor-

ing (e.g., Allen 1982; Lomax et al. 2012;Spallarossa

et al. 2014) but their use still does not fully meet the

need of society (e.g., people awareness, resilience ca-

pacity, emergency management) or even remains con-

finedintostrictacademicpurposes.Scafidietal.(2016,

2018) showed that advanced processing for complete

https://doi.org/10.1007/s10950-021-09993-0

A. Viganò (*)

Servizio Geologico, Provincia autonoma di Trento, Via Zambra

42, 38121 Trento, Italy

e-mail: alfio.vigano@provincia.tn.it

D. Scafidi :G. Ferretti

Dipartimento di Scienze della Terra, dell’Ambiente e della Vita,

Università degli Studi di Genova, Corso Europa 26,

16132 Genova, Italy

/ Published online: 26 February 2021

J Seismol (2021) 25:419–432

Content courtesy of Springer Nature, terms of use apply. Rights reserved.

ResearchGate has not been able to resolve any citations for this publication.

Deep learning of aftershock patterns following large earthquakes

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Aug 2018
NATURE

Aftershocks are a response to changes in stress generated by large earthquakes and represent the most common observations of the triggering of earthquakes. The maximum magnitude of aftershocks and their temporal decay are well described by empirical laws (such as Bath’s law¹ and Omori’s law²), but explaining and forecasting the spatial distribution of aftershocks is more difficult. Coulomb failure stress change³ is perhaps the most widely used criterion to explain the spatial distributions of aftershocks4–8, but its applicability has been disputed9–11. Here we use a deep-learning approach to identify a static-stress-based criterion that forecasts aftershock locations without prior assumptions about fault orientation. We show that a neural network trained on more than 131,000 mainshock–aftershock pairs can predict the locations of aftershocks in an independent test dataset of more than 30,000 mainshock–aftershock pairs more accurately (area under curve of 0.849) than can classic Coulomb failure stress change (area under curve of 0.583). We find that the learned aftershock pattern is physically interpretable: the maximum change in shear stress, the von Mises yield criterion (a scaled version of the second invariant of the deviatoric stress-change tensor) and the sum of the absolute values of the independent components of the stress-change tensor each explain more than 98 per cent of the variance in the neural-network prediction. This machine-learning-driven insight provides improved forecasts of aftershock locations and identifies physical quantities that may control earthquake triggering during the most active part of the seismic cycle.

CFTI5Med, Catalogo dei Forti Terremoti in Italia (461 a.C.-1997) e nell'area Mediterranea (760 a.C.-1500) - Istituto Nazionale di Geofisica e Vulcanologia (INGV). doi: https://doi.org/10.6092/ingv.it-cfti5

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The Catalogo dei Forti Terremoti in ltalia (Catalogue of Strong Italian Earthquakes) is the most important outcome of a well-established collaboration between the Istituto Nazionale di Geofisica (ING; since 2000 Istituto Nazionale di Geofisica e Vulcanologia, INGV), the leading Italian institution for basic and applied research in seismology and solid earth geophysics, and SGA (Storia Geofisica Ambiente), a private firm specializing in the historical investigation and systematization of adverse natural phenomena. The collaboration with SGA came to an end in 2007, when part of its personnel became INGV permanent staff. The Catalogo dei Forti Terremoti in ltalia, 461 a.C. - 1980 was first published in Italian in 1995 by Boschi et al. (1995: CFTI 1). It was intended as a complete account of Italian "strong earthquakes", of their territorial impact and of the social and economic upheaval caused. The decision of focusing only on the largest earthquakes was dictated by the need to establish a priority among the vast number of events reported in traditional catalogues. Only earthquakes with a reported maximum intensity equal to or bigger than intensity VIII-IX on the MCS scale were considered in the first release of the catalogue, but this threshold was progressively relaxed for its subsequent versions. The second release, that appeared two years later, included more earthquakes, was based on more accurate research, and covered a longer time span (461 B.C. to 1990) (Boschi et al., 1997: CFTI 2). Knowing that the record of Italian historical seismicity is probably the most extensive of the whole world, and hence that the catalogue could be of interest for a wider international readership, Boschi et al. (2000) decided to share this experience with colleagues from foreign countries by preparing an English version of the catalogue. The new release (CFTI 3) entailed much additional research and fine tuning of methodologies and algorithms, including earthquakes up to 1997. Following the publication of two large research bodies on the seismicity of the Mediterranean region up to the 10th century (Guidoboni et al., 1994) and between the 11th and 15th century (Guidoboni and Comastri, 2005), the area of relevance of the catalogue was extended to the entire Mediterranean basin. The new contents, which included only basic seismological parameters (felt reports and epicentral location for Italian earthquakes, epicentral location only for the other Mediterranean earthquakes), appeared in a new version of the catalogue (CFTI4Med), published in 2007 as a web and web-GIS repository (Guidoboni et al., 2007).

MONTAGNE IN EVOLUZIONE E TERREMOTI ALCUNI CASI NELLE PREALPI VENETE, TRENTINE E GARDESANE

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Jan 2018

The purpose of this paper is to present the state of art about the knowledge on the recent morphotectonic evolution of the Fore-Alps of Veneto, Trentino and Garda Lake area. The work is divided into three parts. The first part discusses some general aspects of the geological and geomorphological features of the alpine relief. In the second part different types of geomorphological and sedimentological evidences of recent seismotectonics events are described. In the third part, are being analyzed, with a morphostratigraphic approach, some morphological and structural units of the Venetian Alps in order to understand, as far as possible, the evolution of the relief in the course of time intervals comprised between a few millions and several tens of millions of years.

Erratum The Wood–Anderson of Trieste (Northeast Italy): One of the Last Operating Torsion Seismometers:

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Jan 2017

The Wood Anderson of Trieste (NE Italy): one of the last operating torsion seismometers

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Nov 2015

The Wood–Anderson (WA) torsion seismograph, used by Richter (1935) for the definition of the local magnitude (ML) of an earthquake, has been abandoned over time due to the cumbersome nature of its use. With the progress of technology, modern digital broadband (BB) instruments have replaced older instruments such as the WA, and the equivalent ML, obtained from simulated WA seismograms after convolution of the recorded BB data with a proper transfer function (Bormann, 2002a,b), has replaced the WA ML. Despite the paucity of WA instruments today, the ML in its original form remains relevant for continuity with old earthquake catalogs and as a long-standing reference for all other magnitude scales up to approximately ML 6.5. For larger earthquakes, the ML scale progressively underestimates the actual energy release and ML is said to saturate (Kanamori, 1983). Even so, ML is a good predictor of structural damage caused by earthquakes because many buildings have resonant periods close to that of the WA seismograph (0.8 s). In Trieste, located in northeastern Italy, there is one of the few stations equipped with an original pair of WA instruments that are still operating. The two horizontal WA seismometers (Lehner-Griffith TS-220) were installed in September 1971 and have been managed since then by the Osservatorio Geofisico Sperimentale, presently the Istituto Nazionale di Oceanografia e di Geofisica Sperimentale (OGS). The Trieste station was part of theWorldwide Standardized Seismographic Station Network (WWSSN) with the code TRI-117, and it dates its operation back to 29 July 1963. At that time, three Benioff seismometers were employed as short-period seismographs, and three Ewing-Press seismometers were used for teleseismic detection. The WWSSN seismometers were installed at the bottom (161 m above sea level) of Grotta Gigante, a giant cave of the Trieste karst, 12 km away from the city center. The WA seismometers were placed over a plinth in a darkroom at the surface (336 m above sea level, latitude 45.709° N, longitude 13.764° E). The daily processing of the photographic paper was quite expensive and very time consuming. This aspect also contributed to the abandonment of the Trieste WA recordings in April 1992. In 2002, the WA instruments were recovered and upgraded by replacing the recording on photographic paper with an electronic device. From 17 December 2002 to 31 December 2013, the refurbished WA seismometer recorded 1252 events, with a break between May 2005 and March 2010 due to the restoration of the building where it was operated. At present, the Trieste station concurrently acquires data from (1) the upgraded digitized WA seismometer, (2) the Güralp 40-T BB instrument placed at the top of the cave (since 2004), and (3) the BB Streckeisen STS-1 seismometers installed at the bottom of the cave (since 1995). The STS-1 instrument corresponds to station TRI of the MedNet network (Mazza et al., 1998). In this paper, after describing the upgrade of the WA seismograph and verifying its static magnification (Gs), we reevaluate old estimates of ML and compile a new catalog of Trieste WA ML values updated to 2013. Finally, we compare the Trieste WA ML values with moment magnitudes.

A Complete Automatic Procedure to Compile Reliable Seismic Catalogs and Travel‐Time and Strong‐Motion Parameters Datasets

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Robust Picking and Accurate Location with RSNI‐Picker2: Real‐Time Automatic Monitoring of Earthquakes and Nontectonic Events

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The RSNI-Picker2 (Regional Seismic network of Northwestern Italy, University of Genova) automatic phase detector, picker, and locator is presented, as well as the analysis of its performance in real-time monitoring of earthquakes and nontectonic events. The major improvements of this algorithm with respect to previous ones are the iterative coupling between picking and probabilistic nonlinear locations and a dynamic selection of time windows for close phase onsets or contemporary events. Calculation of strong-motion parameters and discrimination of outof- network events can also be achieved. Automatic results from RSNI-Picker2, its original version (RSNI-Picker), and other automatic picking codes are compared with a reference manual dataset of 1445 local earthquakes of northwestern Italy. RSNI-Picker2 shows significantly higher precision (91%) and accuracy (98.3% within 0:1 s) in P-phase picking, with a recall of 75% for the selected setup. A similar robust picking of S phases (94% precision, 71% recall), with 89.2% of residuals within 0:2 s, ensures accurate and reliable automatic earthquake locations, especially for local-suited setup with well-constrained crustal velocity models. We find RSNIPicker2 also applicable for real-time automatic environmental monitoring, as for quarry shots and large rockfalls.

Facing the Communication Challenges during an Earthquake Swarm Period

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When earthquake swarms catch public attention, seismologists face a difficult communication challenge. On the one hand, they do not want to create unnecessary anxiety, because most swarms eventually die off, but at the same time, they know that these events could also be foreshocks to a larger, possibly damaging, earthquake. What then should a seismologist say that will remain within the scope of science to assist the public and community leaders to make appropriate choices? Probabilistic statements are scientifically verifiable but provide little comfort to anxious people and, for most citizens, give no guidance about whether they should or should not prepare for an earthquake. We are proponents of actions that allow individuals, families, and communities to acquire a sense of control that encourages individual and collective efficacy—a key element of fostering resilience in times of high anxiety. Seismologists can help foster resilience by capitalizing on windows of opportunity when people are inclined to pay attention to the scientists’ message and to take action based upon practical and credible information. Making the most of a window of opportunity will also improve the likelihood of an appropriate response if an event does occur. We believe that the public is ready to accept the limitations of the Earth Sciences (such as the inability to make definite predictions), especially if the guidance is reasonable, comforting, makes logical sense, and is conveyed with compassion. Based on these premises, we propose a message that should form the basis of press releases, webpage content, Tweets, etc., for seismologists who communicate with the public to use during earthquake swarm periods.

Automatic P‐ and S‐Wave Local Earthquake Tomography: Testing Performance of the Automatic Phase‐Picker Engine “RSNI‐Picker”

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In this work, we test a fully automatic procedure to obtain local earthquake tomography (LET), starting from seismic waveforms and applying the capability of the automatic phase picker and locator engine “RSNI-Picker” (Spallarossa et al., 2014), which is based on a multistep iterative procedure working on P and S arrival times. This code is currently operating as part of the Earthquake Monitoring System at the University of Genoa (RSNI designates the regional seismic network of northwestern Italy). In particular, we compare P- and S-wave tomographic results obtained using this fully automatic procedure for picking and locations with those based on data from accurate manual picking and revised locations. We use a dataset of 409 earthquakes that occurred in the Trentino region (Northeastern Italy) in the 1994–2007 period. The highly variable waveform qualities (e.g., signal-tonoise ratio), mainly due to recording stations equipped with different types of sensors and digitizers (including both one-component narrowband stations and three-component broadband seismic stations), ensure a severe test for the automatic procedure. The comparison of the two 3D velocity propagation models for the Trentino region (i.e., LET images) from the automatic and manual procedures, shows maximum differences of 0.54 and 0:34 km=s for P and S waves, respectively (if we consider 90% of all the computed absolute velocities, as a reference percentage). The automatic LET shows velocity anomaly distributions and reliability patterns (e.g., resolution diagonal element [RDE] values) similar to those obtained using the manual procedure; 90% of RDE differences are lower than 0.15. The results obtained by testing the RSNI-Picker engine suggest it can be used to automatically process large amounts of seismic recordings in order to identify P and S wavepicks for reliable LET analysis.

Probabilistic Earthquake Location in 3D and Layered Models

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Jan 2000

Probabilistic earthquake location with non-linear, global search methods allows the use of 3D models and produces comprehensive uncertainty and resolution information represented by a probability density function over the unknown hypocentral parameters. We describe a probabilistic earthquake location methodology and introduce an efficient Metropolis-Gibbs, non-linear, global sampling algorithm to obtain such locations. Using synthetic travel times generated in a 3D model, we examine the locations and uncertainties given by an exhaustive grid-search and the Metropolis-Gibbs sampler using 3D and layered velocity models, and by a iterative, linear method in the layered model. We also investigate the relation of average station residuals to known static delays in the travel times, and the quality of the recovery of known focal mechanisms. With the 3D model and exact data, the location probability density functions obtained with the Metropolis-Gibbs method are nearly identical to those of the slower but exhaustive grid-search. The location PDFs can be large and irregular outside of a station network even for the case of exact data. With location in the 3D model and static shifts added to the data, there are systematic biases in the event locations. Locations using the layered model show that both linear and global methods give systematic biases in the event locations and that the error volumes do not include the “true” location — absolute event locations and errors are not recovered. The iterative, linear location method can fail for locations near sharp contrasts in velocity and outside of a network. Metropolis-Gibbs is a practical method to obtain complete, probabilistic locations for large numbers of events and for location in 3D models. It is only about 10 times slower than linearized methods but is stable for cases where linearized methods fail. The exhaustive grid-search method is about 1000 times slower than linearized methods but is useful for location of smaller number of events and to obtain accurate images of location probability density functions that may be highly-irregular.

A new approach for a fully automated earthquake monitoring: the local seismic network of the Trentino region (NE Italy)

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