Search

Italy has been majorly affected by the COVID-19 pandemic. The government declared a full lockdown and limited human and commercial activities to keep the pandemic under control. The limited human activity reduced the spread of the virus and the cultural noise it created. The effect of the lockdown is detected by the Italian strong motion network, which covers the entire country with their stations mostly located in the settlements. To assess the effect of the lockdown, background noise information up to 1 s from 2022 is used as a comparison. It is found that the background noise levels dropped around 1.46 dB during the lockdown, with a nationwide reduction in almost all of the stations. Noise levels have dropped both in the daytime and nighttime during the lockdown, with a more significant noise drop during the nighttime, which can be linked to the ban on dining in restaurants and bars and the curfew. A similar trend is found in weekday and weekend comparisons; in both time ranges, 2022 was noisier regarding the lockdown period. Stations located in public spaces such as schools and city halls observed noise reduction of up to 7.99 dB, and this noise level reduction is visible in major cities. We analyzed the 10 most populated Italian cities and their surroundings and found noise reduction of up to 5.5 and 2.1 dB in the median. [ABSTRACT FROM AUTHOR]

Seismic monitoring is recognized as an effective tool for investigating rock bursts in coal mines; however, a universally accepted and rational assessment method for the detection capabilities of coal mine seismic monitoring systems has yet to be established. A method based on event energy has been developed to evaluate the monitoring performance of a mine seismic network. Utilizing statistical principles, this methodology quantifies the detection capabilities of individual seismic stations in mine monitoring and provides a comprehensive assessment of the overall network monitoring quality in critical surveillance areas. This is achieved by considering the detection probability of fixed-energy events and the minimum integrity energy across the entire seismic network. Experimental trials were conducted at the Dongtan Coal Mine, where a seismic network was established. A comparison of detection probability maps for different stations revealed performance variations under various energy and distance conditions. The overall detection capability of the network for the critical monitoring area, specifically the 6306 longwall, was calculated and validated using blasting test data. The experimental results demonstrate the successful application of this new method in practical mine environments, with potential advancements in the technology of mine seismic source monitoring for both academic and engineering practices. Highlights: Utilizing a novel evaluation criterion based on energy and distance to calculate the detection capability of individual stations. Employ rationalization methods to enhance the credibility of computational results from a single station. Introducing two new indicators, namely the Minimum Integrity Energy and the detection probability for fixed energy, to assess the detection capability of the seismic network. [ABSTRACT FROM AUTHOR]

On March 18, 2024, the seismic monitoring network in the central part of the East European Platform (EEP) registered an earthquake near Rybinsk (58.22° N, 38.52° E) with an ML (local magnitude) of 3.1 with an epicenter localized to epicenter to the long-lived Central Russian Deformation Belt, which inherits a structure and direction of dislocations of the platform basement of the craton. Tectonic seismic events were registered in the central part of the EEP in the last decade. Analysis of their epicenter locations shows they also belong to the same zone. It is concluded that the modern seismicity in the Central Russian Deformation Belt is activated. This fact has to be considered in the arrangement of infrastructure within this zone. [ABSTRACT FROM AUTHOR]

Tens of thousands of earthquakes are located by GeoNet across Aotearoa every year. However, spatial variability – both in station coverage and earthquake distributions – produce heterogeneity in earthquake location quality throughout the GeoNet catalogue. Here we consider simple, established criteria (including station azimuthal coverage, minimum station distance, phase arrival coverage and fixed location criteria) to score earthquakes on a network location Quality Score (QS) scale of QS0 (unconstrained) to QS6 (best constrained). Significant variation in QS exists nationwide; 48% and 20% of earthquakes score QS6 for the North and South Islands respectively. The Hawkes Bay region scores highest (68% QS6) closely followed by other Hikurangi regions. However, several regions score extremely poorly, with Fiordland, West Coast, Nelson, Otago-Southland and Auckland-Northland regions having ≤5% QS6 events and >75% of events scoring QS3 or lower. Low QS mostly arises from the failure of minimum distance criteria, whereby the closest station is too far from the earthquake to provide sufficient depth control. Our analysis quantitatively assesses the impact of network heterogeneity on GeoNet earthquake catalogue location quality to inform end users. This work also provides motivation for the expansion of the weak-motion network in critically under-instrumented regions, especially those with high seismic hazard. [ABSTRACT FROM AUTHOR]

Italy has been majorly affected by the COVID-19 pandemic. The government declared a full lockdown and limited human and commercial activities to keep the pandemic under control. The limited human activity reduced the spread of the virus and the cultural noise it created. The effect of the lockdown is detected by the Italian strong motion network, which covers the entire country with their stations mostly located in the settlements. To assess the effect of the lockdown, background noise information up to 1 s from 2022 is used as a comparison. It is found that the background noise levels dropped around 1.46 dB during the lockdown, with a nationwide reduction in almost all of the stations. Noise levels have dropped both in the daytime and nighttime during the lockdown, with a more significant noise drop during the nighttime, which can be linked to the ban on dining in restaurants and bars and the curfew. A similar trend is found in weekday and weekend comparisons; in both time ranges, 2022 was noisier regarding the lockdown period. Stations located in public spaces such as schools and city halls observed noise reduction of up to 7.99 dB, and this noise level reduction is visible in major cities. We analyzed the 10 most populated Italian cities and their surroundings and found noise reduction of up to 5.5 and 2.1 dB in the median.

Copyright of Dokuz Eylul University Muhendislik Faculty of Engineering Journal of Science & Engineering / Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen ve Mühendislik Dergisi is the property of Dokuz Eylul Universitesi Muhendislik Fakultesi Fen ve Muhendislik Dergisi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Due to high-intensity mining and complex geological conditions, frequent occurrence of rock burst disasters in deep coal mines in China is posing serious threats to mine safety and efficiency. The insufficient locating accuracy of the seismic monitoring system in burst-prone coal mines is still presented, which leads to difficulties in accurately identifying and controlling coal burst hazards. To precisely characterize spatial evolution of seismic activities and reduce the impact of location error on the seismic pre-warning, this paper used the current seismic networks in burst-prone coal mines to conduct forward modeling experiments to explore the distribution characteristics of source location error vectors in the mining field. A new method for characterizing seismic fracture connectivity that considers location accuracy impacts was proposed and applied for coal burst pre-warning in a longwall face. The results show that significant vectorial differences of seismic source location accuracy at different area of the mining field is a key factor in false identifying coal burst risks. The proposed Fracture-connectivity-probability Index (\begin{document}$ F{_{{\mathrm{sum}}}} $\end{document}) characterizes the rupture scale by using the near-field radius that relates to the seismic energy level, which considers the locating error impacts on fracture connectivity between seismic sources at different distances. \begin{document}$ F{_{{\mathrm{sum}}}} $\end{document} can restore the distribution law of the fracture extension and connectivity probabilities of the coal-rock mass in the greatest extent, and it also corresponds well to the coal burst risks. \begin{document}$ F{_{{\mathrm{sum}}}} $\end{document} can balance forecast accuracy and recall rate and have better correlation with coal burst, which can be an ideal indicator for periodical coal burst risk assessment. The outcome of this research can provide references for evaluating the monitoring capability of seismic networks and improving the ability and efficiency of coal burst pre-warning and prevention.

Until now, numerous efforts have been made to find earthquake precursors. One of the factors that can predict the occurrence of future earthquakes is a decrease in the b-value parameter. In this study, for the metropolis of Tehran, with a population of over 8 million, located on or near many active faults, it is estimated that if the maximum seismic potential of these faults happened again, the greatest disaster in human history would occur. In this case, the analyses indicate a minimum of several hundred thousand casualties and sometimes more than a million. In the current study, various faults around Tehran were investigated, and given that the faults on Tehran have not had serious seismic activity for over a thousand years, this article focused exclusively on adjacent faults, particularly the Eshtehard faults. Therefore, in the current study, the seismicity and tectonics of western Tehran were investigated by analyzing seismic parameters using earthquake data collected from 2003 to 2023. In general, the investigation of the temporal changes in the study area showed that the b-value decreased before the December 20, 2017, earthquake and an increasing trend afterward. Observing anomalies in the b-value before and after the main movement in the area shows that changes in this parameter can be considered a precursor for estimating the time and location of earthquakes. Therefore, a useful step can be taken toward knowing the local seismic hazards by using earthquake data recorded by seismic networks and continuously monitoring the changes in the b-value. [ABSTRACT FROM AUTHOR]

Copyright of Coal Science & Technology (0253-2336) is the property of Coal Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Early warning systems can estimate the possible-shaking intensity of the earthquake based on the initial P-waves on-site. Researchers have used the following two indicators: the initial peak P-wave displacement ( P d ) and the ground motion characteristic period ( τ c ). In this study, we re-examine the performance of the two indicators by employing ground motion data from the P-Alert low-cost network in Taiwan. We have found that the signal-to-noise ratio of displacement ( S N R d ) is effective for data selection. In addition, we have observed the irregular behavior of τ c in the P-Alert dataset. [ABSTRACT FROM AUTHOR]

Abstract The Thai Meteorological Department (TMD) seismic network began development in 2008. There are a total of 71 seismic stations consisting of 26 borehole stations and 45 surface stations currently installed. The three-component data from the TMD seismic network have been widely used in previous seismological studies. In a recent analysis, we have found that sensor orientation as reported in the site metadata is sometimes significantly incorrect, especially for borehole stations. In this study, we analyze P-wave polarization data from regional and teleseismic earthquakes recorded in the network to estimate the true instrument orientation relative to geographic north and compare that to station metadata. Of the 45 surface stations, we found that at present, ~ 82% are well oriented (i.e., aligned within 0–15° of true north). However, 8 sites have sensors misoriented by more than 15°, and some stations had a temporal change in sensor orientation during an upgrade to the seismic system with replacement of the sensor. We also evaluated sensor orientations for 26 TMD borehole seismic stations, from 2018 to the 2022. For many of the borehole stations, the actual sensor orientation differs significantly from the TMD metadata, especially at short-period stations. Many of those stations have sensor misorientations approaching 180°, due to errors in the ambient noise analysis calibration techniques used during installation. We have also investigated how this sensor misorientation affects previous seismic studies, such as regional moment tensor inversion of earthquakes sources and receiver function stacking. We have found that the large deviations in sensor orientation can result in erroneous results and/or large measurement errors. A cause of the orientation error for borehole sites could be a combination of strong background surface ambient seismic noise coupled with an incorrect reference instrument response.

Scientists at ETH Zurich from different disciplines are developing a dynamic, harmonised and user-centred earthquake risk framework for Switzerland, relying on a continuously evolving earthquake catalogue generated by the SED using the national seismic networks. This framework uses all available information to assess seismic risk at various stages and facilitates widespread dissemination and communication of the resulting information. Earthquake risk products and services include Operational Earthquake (Loss) Forecasting (OE[L]F), Earthquake Early Warning (EEW), ShakeMaps, Rapid Impact Assessment (RIA), Structural Health Monitoring SHM), as well as Recovery and Rebuilding Efforts (RRE). Standardisation of products and workflows across various applications is essential for achieving broad adoption, universal recognition, and maximum synergies. In the Swiss dynamic earthquake risk framework, the harmonisation of products into seamless solutions that access the same databases, workflows, and software is a crucial component to ensure standardisation. A user-centred approach utilising quantitative and qualitative social science tools like online surveys and focus groups is a significant innovation featured in all products and services. Here we report on the key considerations and developments of the framework and its components. We are developing an interdisciplinary dynamic earthquake risk framework for Switzerland for advancing earthquake risk mitigation. It includes various earthquake risk products and services, such as Operational Earthquake Forecasting and Earthquake Early Warning, and adopts a user-centred approach. Standardisation is crucial for widespread adoption and recognition, and the harmonisation of products into seamless solutions that access the same databases, workflows, and software is a crucial component. [ABSTRACT FROM AUTHOR]

In this work, we perform an evaluation of the coverage of the earthquake monitoring network of Taiwan. The capability of a general network is a function of an adequate number of optimally distributed nodes. For this case study, the evaluation is performed with a statistical approach which includes descriptive spatial statistics in combination with point pattern techniques. The spatial distribution of the nodes of the earthquake monitoring network is analyzed in comparison with the distribution of seismicity, completeness magnitude, active seismogenic sources, seismic hazard, and population distribution. All these data can be put in relationship with the objectives of an earthquake monitoring network; therefore, they can be used, in turn, to retrieve information about the consistency of the network itself. In particular, we investigate the "Real-time Seismic Monitoring Network" and the "Strong-Motion Earthquake Observation Network," each one characterized by its own objectives, and therefore respectively compared with external information related to their purposes such as seismicity, seismogenic sources, seismic hazard, and population distribution. This simple and reliable approach reveals the high quality of the networks established in Taiwan. In general, it is able to provide quantitative information on the coverage of any type of network, identifying possible critical areas and addressing their future development. [ABSTRACT FROM AUTHOR]

We present results of a detailed analysis of data obtained from seismic geodynamic field studies conducted at proposed sites for the development of advanced seismic monitoring stations in the Republic of Armenia. These studies aim to determine the background seismic and geodynamic noise level around such sites. Finally, based on the received data and international standards, nine survey points were classified into respective classes according to their noise level. We also calculated minimum significant earthquake magnitude detectable by the proposed seismic network in different regions of Armenia and mapped it based on recorded regional earthquakes. The resulting map indicates that the proposed seismic monitoring network will provide homogenous initial data for the various seismically active regions of the territory of the Republic of Armenia.

The conjunction of seismic records and site effect parameters can lead to the adequate estimation of seismic indexes in urban areas. In this regard, this study uses the map of soil amplification factors obtained in previous studies and the availability of time history waveforms at different locations throughout Metropolitan Lima and Callao to estimate the geospatial distribution of maximum values of horizontal acceleration after the occurrence of earthquakes. Results for three earthquakes of intermediate magnitude and distinct epicenter locations are publicly available in an online system created within the framework of this study (Amaru Peru) and showed that amplified motions could be mainly observed in the lowlands of populated slopes as well as in the eolian sandy deposits. [ABSTRACT FROM AUTHOR]

The Thai Meteorological Department (TMD) seismic network began development in 2008. There are a total of 71 seismic stations consisting of 26 borehole stations and 45 surface stations currently installed. The three-component data from the TMD seismic network have been widely used in previous seismological studies. In a recent analysis, we have found that sensor orientation as reported in the site metadata is sometimes significantly incorrect, especially for borehole stations. In this study, we analyze P-wave polarization data from regional and teleseismic earthquakes recorded in the network to estimate the true instrument orientation relative to geographic north and compare that to station metadata. Of the 45 surface stations, we found that at present, ~ 82% are well oriented (i.e., aligned within 0–15° of true north). However, 8 sites have sensors misoriented by more than 15°, and some stations had a temporal change in sensor orientation during an upgrade to the seismic system with replacement of the sensor. We also evaluated sensor orientations for 26 TMD borehole seismic stations, from 2018 to the 2022. For many of the borehole stations, the actual sensor orientation differs significantly from the TMD metadata, especially at short-period stations. Many of those stations have sensor misorientations approaching 180°, due to errors in the ambient noise analysis calibration techniques used during installation. We have also investigated how this sensor misorientation affects previous seismic studies, such as regional moment tensor inversion of earthquakes sources and receiver function stacking. We have found that the large deviations in sensor orientation can result in erroneous results and/or large measurement errors. A cause of the orientation error for borehole sites could be a combination of strong background surface ambient seismic noise coupled with an incorrect reference instrument response. [ABSTRACT FROM AUTHOR]

This paper describes all the characteristics of the Guatemalan earthquake catalog and how it has evolved. Over 64,483 earthquakes are included in this paper distributed in some areas of El Salvador, Mexico, Honduras, and Belize, but mainly in Guatemala. Regularly, the earthquake catalogs improve their characteristics over time, however, this is not the case for the catalog of Guatemala. Although earthquake detection improved with the establishment of the national seismic network operated by the National Institute of Seismology, Vulcanology, Meteorology and Hydrology (INSIVUMEH) in 1977, the catalog has not kept a favorable evolution over time. This has led to problems with earthquake detection, large location errors, increasing magnitude of completeness, and others that are going to be discussed later in this paper.

A modern digital seismic network, with many stations optimally distributed on the earthquake causative seismic zone, enables detection of very low magnitude earthquakes and determination of their source parameters. It is essential to associate to such kind of networks procedures to analyze the huge amount of continuously recorded data for monitoring the space-time-magnitude evolution of natural and/or induced seismicity. Hence, the demand for near-real-time, automated data collection and analysis procedures for assisting seismic network operators in carrying out microearthquake monitoring is growing. In response to this need, we designed a computational software platform, TREMOR, for fast and reliable detection and characterization of seismicity recorded by a dense local seismic network. TREMOR integrates different open-source seismological algorithms for earthquake signal detection, location, and source characterizations in a fully automatic workflow. We applied the platform in play-back mode to the continuous waveform data recorded during 1 month at the Japanese Hi-net seismic network in the Nagano region (Japan) and compared the resulting catalog with the Japan Meteorological Agency bulletin in terms of number of detections, location pattern and magnitudes. The results show that the completeness magnitude of the new seismic catalog decreased by 0.35 units of the local magnitude scale and consequently the number of events increased by about 60% with respect to the available catalog. Moreover, the fault plane solutions resulted coherent with the stress regime of the region, and the Vp/Vs ratio well delineated the main structural features of the area. According to our results, TREMOR has shown to be a valid tool for investigating and studying earthquakes, especially to identify and monitor natural or induced micro-seismicity.

The stations from the INCD URBAN-INCERC network are distributed throughout the country, including Bucharest, and are located either in free-field conditions, in small buildings, in medium-height buildings or in boreholes. The interactive map representation of the seismic stations and the automatic monitoring of their operation, based on the analysis of received data, are currently carried out with the SeisComP software. The paper exemplifies, as performance benchmarks, some data processing obtained in 2022 within the permanent seismic monitoring system. [ABSTRACT FROM AUTHOR]

Enceladus is an icy world with potentially habitable conditions, as suggested by the coincident presence of a subsurface ocean, an active energy source due to water-rock interactions, and the basic chemical ingredients necessary for terrestrial life. Among all ocean worlds in our Solar System, Enceladus is the only active body that provides direct access to its ocean through the ongoing expulsion of subsurface material from erupting plumes. Here we present the Enceladus Touchdown aNalyzing Astrobiology (ETNA) mission, a concept designed during the 2019 Caltech Space Challenge. ETNA’s goals are to determine whether Enceladus provides habitable conditions and what (pre-) biotic signatures characterize Enceladus. ETNA would sample and analyze expelled plume materials at the South Polar Terrain (SPT) during plume fly-throughs and landed operations. An orbiter includes an ultraviolet imaging spectrometer, an optical camera, and radio science and a landed laboratory includes an ion microscope and mass spectrometer suite, temperature sensors, and an optical camera, plus three seismic geophones deployed during landing. The nominal mission timeline is 2 years in the Saturnian system and ∼1 year in Enceladus orbit with landed operations. The detailed exploration of Enceladus’ plumes and SPT would achieve broad and transformational Solar System science related to the building of habitable worlds and the presence of life elsewhere. The nature of such a mission is particularly timely and relevant given the recently released Origins, Worlds, and Life: A Decadal Strategy for Planetary Science and Astrobiology 2023–2032, which includes a priority recommendation for the dedicated exploration of Enceladus and its habitable potential.

Featured Application: Earthquake Detection, Earthquake Early Warning System (EEWS), Processing of Seismic data. Earthquake is a major hazard to humans, buildings, and infrastructure. Early warning systems should detect an earthquake and issue a warning with earthquake information such as location, magnitude, and depth. Earthquake detection from raw waveform data using deep learning models such as graph neural networks (GNN) is becoming an important research area. The multilayered structure of the GNN with a number of epochs takes more training time. It is also hard to train the model with saturating nonlinearities. The batch normalization technique is applied to each mini-batch to reduce epochs in training and obtain a steady distribution of activation values. It improves model training and prediction accuracy. This study proposes a deep learning model batch normalization graph convolutional neural network (BNGCNN) for early earthquake detection. It consists of two main components: CNN and GNN. Input to the CNN model is multi-station and three-component waveform data with magnitude ≥ 3.0 were collected from January 2000 to January 2015 for Southern California. The extracted features of CNN are appended with location information and input to GNN model for earthquake detection. After hyperparameter tuning of the BNGCNN, when testing and evaluating the model on the Southern California dataset, our method shows promising results to the baseline model GNN by obtaining a low error rate to predict the magnitude, depth, and location of an earthquake. [ABSTRACT FROM AUTHOR]

In this work, we evaluate the suitability of a new MEMS sensor prototype, called ASX1000 (ADEL s.r.l., Modena, Italy), for the monitoring of distant and moderate seismic events. This device is an inexpensive capacitive accelerometer with a relatively low level of instrumental noise; it can record both local and far seismic events. An experimental network built with ASX1000 MEMS, located in northern Italy, was able to record the Mw 6.3 Petrinja earthquake that occurred in December 2020; it had an epicentral distance of more than 350 km. We retrieved the strong motion parameters (PGA, pseudo-absolute velocity, and pseudo-absolute spectral acceleration) from the acceleration time histories recorded by the MEMS sensors. The obtained parameters were compared with the ones obtained by the closer high-quality seismometers, belonging to the INGV National Seismic Network. The comparison to the highest-quality sensors confirms a reasonable agreement of the inferred parameters. This work suggests that—in the near future—MEMS sensors could be adopted to integrate the existing seismic network. A denser coverage of sensors can sample more accurately the seismic wavefield, taking into account the large spatial variability of local geology and the relative differences in seismic response. [ABSTRACT FROM AUTHOR]

The article discusses the results of processing instrumental and macroseismic observations of the strongest earthquake in Central Baikal in the last 60 years, which occurred on December 9, 2020 (MW = 5.5), as well as its aftershocks. The event was named the Kudara earthquake, after the locality where the maximum intensity of shocks was recorded. The epicenter of the main shock is confined to Proval Bay (Lake Baikal), which formed as a result of the catastrophic Tsagan earthquake of 1862. The sufficiently high density of seismic stations in the region allowed us to obtain reliable estimates of the position of epicenters and source depths for the main shock and aftershocks. In total, more than 70 earthquakes were recorded, located within an area extending in the sublatitudinal direction. The strongest aftershock (KR = 12.6) occurred to the west of the main source on the first day after the main shock. To estimate the seismic moment and focal spectrum of the earthquake, the coda envelope inversion method was tested. The moment magnitudes for the main shock and three aftershocks have been obtained. [ABSTRACT FROM AUTHOR]

Western Anatolia is one of the most seismically active regions in Turkey. The high seismic activity is a result of a complex tectonic deformation dominated by the N-S extensional tectonic regime in Western Anatolia. This tectonic deformation is also a result of the relative movement of the African- Arabian plates towards the north, which causes the Anatolian plate to shift 2.5 cm per year towards W-SW. One of the largest fault zones in the Western Anatolia, Sultandağı Fault Zone (SFZ) has a northwest-southeast trend. SFZ, approximately 120 km long, is an important tectonic structure, which produced three major earthquakes (Mw> 6.0) between the years of 2000 -2002. Therefore, the most significant goals of this study were to monitor the micro-earthquakes along SFZ, to enrich the current seismic network and to increase the earthquake detection threshold in the region (Mc

The paper presents the seismic monitoring network of the TURNKey Project (Towards more Earthquake-resilient Urban Societies through a Multi-sensor-based Information System enabling Earthquake Forecasting, Early Warning and Rapid Response Actions) in Bucharest. TURNkey aims to contribute to the mitigation of earthquake risks through European and global scientific collaborations. To reach its objectives the project brings together a strong multidisciplinary team of experts (geophysicists/seismologists, geologists, engineers, disaster risk managers and sociologists) from 21 partner institutions covering 10 European countries. "Testbed 1" (Bucharest) is described in the paper, with its five monitored locations and the deployed seismic sensors and GNSS. The choice of monitored buildings is based upon the characteristics of the design code used in their construction. The paper considers the possible influence of local conditions at the sites of the monitored buildings. [ABSTRACT FROM AUTHOR]

Abstract In this study, we assess the spectral characteristics of seismic noise at the sites of the Italian Seismic Network and its spatio‐temporal variability. The evaluation of noise is crucial for the assessment of the detection capability of a seismic network. We selected a set of 233 stations, those equipped with broadband velocimeters (with corner period > 40 s) and operating continuously for at least four consecutive years. The analysis was carried out in the frequency band from 0.025 to 30 Hz, in accordance with the seismic sensors bandwidth. We estimated the Power Spectral Density (PSD) of the seismic noise for fixed temporal windows and then we calculated the Probability Density Functions (PDF) at each station. Exploiting the large data set available, we have been able to: (a) describe the characteristics of the noise power at each site; (b) investigate both temporal and spatial variations of the background noise, revealing correlations of the noise levels with natural and anthropogenic noise sources; (c) propose an empirical relationship linking the “microseismic” noise (i.e., 0.12–1.2 Hz) with the geographical features of the site hosting the seismic station; (d) establish the baselines of a new seismic noise model that could be considered as a new reference for the Italian territory.

We analyze the performance of a prototype earthquake early warning system deployed at the National Seismological Network of Costa Rica in collaboration with the Swiss Seismological Service by presenting the real-time performance during six earthquakes (Mw 5.1-6.4) that took place during 2018 and 2019. We observe that, despite only limited efforts to optimize the existing network of 158 stations, for EEW purposes, the network density allows fast determination of source parameters using both the Virtual Seismologist and the Finite Fault Rupture Detector algorithms. Shallow earthquakes on or near-shore are routinely identified within 11–20 s of their occurrence. The warning times for the capital city of San Jose are of 43 s for epicenters located at 220 km, like for the Mw 6.4 Armuelles earthquake. On the other hand, during the time analyzed, the EEW system did not provide positive warning times for earthquakes at distances less than 40 km from San Jose. Even though large (Mw > 7) distant historical earthquakes have not caused heavy damage in San Jose, there is potential for developing an EEW system for Costa Rica, especially for the purposes of rapid earthquake notifications, disaster response management, and seismic risk mitigation.

In this study, we assess the spectral characteristics of seismic noise at the sites of the Italian Seismic Network and its spatio‐temporal variability. The evaluation of noise is crucial for the assessment of the detection capability of a seismic network. We selected a set of 233 stations, those equipped with broadband velocimeters (with corner period > 40 s) and operating continuously for at least four consecutive years. The analysis was carried out in the frequency band from 0.025 to 30 Hz, in accordance with the seismic sensors bandwidth. We estimated the Power Spectral Density (PSD) of the seismic noise for fixed temporal windows and then we calculated the Probability Density Functions (PDF) at each station. Exploiting the large data set available, we have been able to: (a) describe the characteristics of the noise power at each site; (b) investigate both temporal and spatial variations of the background noise, revealing correlations of the noise levels with natural and anthropogenic noise sources; (c) propose an empirical relationship linking the "microseismic" noise (i.e., 0.12–1.2 Hz) with the geographical features of the site hosting the seismic station; (d) establish the baselines of a new seismic noise model that could be considered as a new reference for the Italian territory. Key Points: Background seismic noise from 233 Broad‐Band (BB) seismic stations has been analyzed by means of probability density function of power spectral densityTemporal and spatial variations of noise are ascribable to local geological, environmental, and geographical featuresA noise model of background seismic noise is proposed as a reference for Italy [ABSTRACT FROM AUTHOR]

In recent years, the permanent seismic networks worldwide have largely increased, raising the amount of earthquake signals and the applications using seismic records. Although characterization of the soil properties at recording stations has a large impact on hazard estimates, it has not been implemented so far in a standardized way for reaching high-level metadata. To address this issue, we built an online questionnaire for the identification of the indicators useful for a reliable site characterization at a seismic station. We analysed the answers of a large number of experts in different fields, which allowed us to rank 24 different indicators and to identify the most relevant ones: fundamental frequency (f0), shear-wave velocity profile (VS), time-averaged Vs over 30 m (VS30), depth of seismological and engineering bedrock (Hseis_bed and Heng_bed), surface geology and soil class. Moreover, the questionnaire proposed two additional indices in terms of cost and difficulty to obtain a reliable value of each indicator, showing that the selection of the most relevant indicators results from a complex balance between physical relevancy, average cost and reliability. For each indicator we propose a summary report, provided as editable pdf, containing the background information of data acquisition and processing details, with the aim to homogenize site metadata information at European level and to define the quality of the site characterization (see companion paper Di Giulio et al. 2021). The selected indicators and the summary reports have been shared within European and worldwide scientific community and discussed in a dedicated international workshop. They represent a first attempt to reach a homogeneous set of high-level metadata for site characterization. [ABSTRACT FROM AUTHOR]

Probabilistic earthquake locations provide confidence intervals for the hypocentre solutions such as errors encountered in the position, the origin time, and in magnitude. If the relationship of the parameters relative to the local arrangement of the seismic network is considered, such as the node distance, the number of stations, the seismic gap, and the quality of phase readings), the uncertainties can then provide insights on the location capability of the network. In this paper, we collect the earthquake data recorded from the Italian Seismic Network for a time span of 5 years. The data pertain to three different catalogues according to the progressive refinement phases of the location procedure: automatic location, revised location, and published location. By means of spatial analysis, we assess the distribution of the location-related and network-related estimators across the study area. These estimators are subsequently combined to assess the existence of spatial correlations at a local scale. The results indicate that the Italian network is generally able to provide robust locations at the national scale and for smaller earthquakes, and the elongated shape of Italy (and of its network) does not cause systematic bias in the locations. However, we highlight the existence of subregions in which the performance of the network is weaker. At present, a unique 2D, 3-layer velocity model is used for the earthquake location procedure, and this could represent the main limitation for the improvement of the locations. Therefore, the assessment of locally optimized velocity models is the priority for the homogenization and the improvement of the Italian Seismic Network performance. [ABSTRACT FROM AUTHOR]

Turkey is located in a seismically active region with a complex tectonic history. In order to perform seismic risk assessment precisely, major fault zones (North Anatolian Fault Zone and East Anatolian Fault Zone) that are well defined are monitored continuously. It is a widely known fact that intraplate settings, such as Anatolian Plate, in which devastating earthquakes may occur, need to be observed densely. In this study, we investigate the seismotectonics of Malatya Fault within the Malatya Ovacık Fault Zone (MOFZ), which is one of the major agents responsible for internal deformation acting on Anatolian Plate. Recent geological and paleoseismological studies underline the necessity of comprehending the seismicity and latency of a major earthquake in this fault zone.We applied traditional techniques to investigate data of such a region. Earthquakes that occured in the vicinity of Malatya Fault between the years 2011 and mid-2019 are employed in a detailed analysis. The results of this study are constrained by the distribution of sensor networks in the region, yet allowing to define an active structure which is not included in the active fault map of Turkey, therefore, making a significant contribution to seismic hazard estimation.

Aiming at the present situation of the earthquake instant message and the release of earthquake information in Chongqing seismic network, a software of automatic release of earthquake information is designed based on VB.net technology. The software connects with EarthQuake Instant Messenge (EQIM) and gets the earthquake quick report data from the Mysql database of EQIM. According to the corresponding release rules, the earthquake information can be released automatically, quickly and accurately, relying on the SMS proxy server of telecom operators.

The PLUM (Propagation of Local Undamped Motion) earthquake early warning (EEW) algorithm differs from typical source‐based EEW algorithms as it predicts shaking directly from observed shaking without first deriving earthquake source information (e.g., magnitude and epicenter). Here, we determine optimal PLUM event detection thresholds for U.S. West Coast earthquakes using two data sets: 558 M3.5+ earthquakes (California, Oregon, Washington; 2012–2017) and the ShakeAlert test suite of historic and problematic signals (1999–2015). PLUM computes Modified Mercalli Intensity (IMMI) using velocity and acceleration data, leveraging co‐located sensors to avoid problematic signals. An event detection is issued when the observed IMMI exceeds a given threshold(s). We find a two‐station detection method using IMMI trigger thresholds of 4.0 and 3.0 for the first and second stations, respectively, is optimal for detecting M4.5+ earthquakes. PLUM detected 79 events in the 2012–2017 data set, reporting (not including telemetry or alert dissemination) detection times on par, and sometimes faster than current EEW methods (mean 8 s; median 6 s). As expected, detection times were slower for the older 1999–2015 earthquakes (N = 21; mean 11 s; median 6 s) when station coverage was sparser. Of the 31 PLUM detected M5+ events (10 2012–2017; 21 1999–2015), theoretically 20 (∼65%) could provide timely warnings. PLUM issued no false detections and avoided issuing detections for all calibration/anomalous signals, regional and teleseismic events. We conclude PLUM can successfully identify IMMI 4+ shaking from local earthquakes and could complement and enhance EEW in the U.S. Plain Language Summary: Earthquake early warning (EEW) detection schemes require (1) ample seismic information to identify where large ground motions are underway; (2) determining if these ground motions are significant enough to issue a detection; and (3) detecting large ground motions in a timely fashion. Some EEW methods estimate earthquake source parameters like magnitude and location and then input those parameters into a ground‐motion prediction equation, while other methods use observations of the ground motions to directly forecast shaking. We explore the latter approach using the PLUM (Propagation of Local Undamped Motion) method to detect earthquakes that produce shaking above a target value. In this work, we test PLUM's ability to detect earthquakes using two data sets: 558 earthquakes magnitude 3.5 and above from California, Oregon, and Washington (2012–2017) and a test suite of historic and problematic signals (1999–2015) curated by ShakeAlert. We find a two‐station detection method is preferred over a one‐station method as two‐stations can greatly minimize false detections. The PLUM method is also 100% successful at avoiding non‐earthquake anomalous signals and can successfully differentiate ground shaking from local and distant earthquakes. We conclude that PLUM may be a promising candidate for integration into the U.S. EEW system. Key Points: Propagation of Local Undamped Motion (PLUM) detects offshore events that produce at least moderate onshore ground motions, including an event problematic for other algorithmsPLUM's detection times are as timely, and sometimes faster, than other earthquake early warning detection timesPLUM correctly avoids erroneous detections for all teleseismic, calibration pulses, and anomalous signals in the test suite [ABSTRACT FROM AUTHOR]

Abstract Accurate dating of marine sediments is essential to reconstruct past changes in oceanography and climate. Benthic foraminiferal oxygen isotope series from such sediments record long‐term changes in global ice volume and deep‐water temperature. They are commonly used in the Plio‐Pleistocene to correlate deep ocean records and to construct age models. However, continental margin settings often display much higher sedimentation rates due to variations in regional depositional setting and local input of sediment. Here, it is necessary to create a regional multi‐site framework to allow precise dating of strata. We create such a high‐resolution regional framework to determine the ages of events for the Northwest Shelf (NWS) of Australia, which was cored by International Ocean Discovery Program (IODP) Expedition 356. We employ benthic foraminiferal oxygen and carbon isotopes to construct an astronomically‐tuned age model for IODP Site U1463 (5.16–1.69 Ma). The age model is applied to the IODP Site U1463 downhole‐logging natural gamma radiation (NGR) depth‐series, which was then correlated to NGR depth‐series of several IODP sites and industry wells in the area. This approach allows assigning ages to regional seismic reflectors and the timing of key climate‐related siliciclastic phases in a predominantly carbonate‐rich sequence, like the late Miocene‐Pliocene Bare Formation. This age model is also used to chronologically calibrate planktonic foraminiferal biostratigraphic datums showing that the Indonesian Throughflow (ITF) had shoaled enough in the early Pliocene to act as biogeographical barrier between the Pacific and Indian Ocean.

Earthquake is a major hazard to humans, buildings, and infrastructure. Early warning systems should detect an earthquake and issue a warning with earthquake information such as location, magnitude, and depth. Earthquake detection from raw waveform data using deep learning models such as graph neural networks (GNN) is becoming an important research area. The multilayered structure of the GNN with a number of epochs takes more training time. It is also hard to train the model with saturating nonlinearities. The batch normalization technique is applied to each mini-batch to reduce epochs in training and obtain a steady distribution of activation values. It improves model training and prediction accuracy. This study proposes a deep learning model batch normalization graph convolutional neural network (BNGCNN) for early earthquake detection. It consists of two main components: CNN and GNN. Input to the CNN model is multi-station and three-component waveform data with magnitude ≥3.0 were collected from January 2000 to January 2015 for Southern California. The extracted features of CNN are appended with location information and input to GNN model for earthquake detection. After hyperparameter tuning of the BNGCNN, when testing and evaluating the model on the Southern California dataset, our method shows promising results to the baseline model GNN by obtaining a low error rate to predict the magnitude, depth, and location of an earthquake.

Accurate dating of marine sediments is essential to reconstruct past changes in oceanography and climate. Benthic foraminiferal oxygen isotope series from such sediments record long‐term changes in global ice volume and deep‐water temperature. They are commonly used in the Plio‐Pleistocene to correlate deep ocean records and to construct age models. However, continental margin settings often display much higher sedimentation rates due to variations in regional depositional setting and local input of sediment. Here, it is necessary to create a regional multi‐site framework to allow precise dating of strata. We create such a high‐resolution regional framework to determine the ages of events for the Northwest Shelf (NWS) of Australia, which was cored by International Ocean Discovery Program (IODP) Expedition 356. We employ benthic foraminiferal oxygen and carbon isotopes to construct an astronomically‐tuned age model for IODP Site U1463 (5.16–1.69 Ma). The age model is applied to the IODP Site U1463 downhole‐logging natural gamma radiation (NGR) depth‐series, which was then correlated to NGR depth‐series of several IODP sites and industry wells in the area. This approach allows assigning ages to regional seismic reflectors and the timing of key climate‐related siliciclastic phases in a predominantly carbonate‐rich sequence, like the late Miocene‐Pliocene Bare Formation. This age model is also used to chronologically calibrate planktonic foraminiferal biostratigraphic datums showing that the Indonesian Throughflow (ITF) had shoaled enough in the early Pliocene to act as biogeographical barrier between the Pacific and Indian Ocean. Plain Language Summary: Determining the age of marine sediments is essential to reconstruct past changes in oceanography and climate. The oxygen isotopes of benthic foraminifera record long‐term changes in global ice volume and deep‐water temperature, and are commonly used to construct age models. However, continental margin settings often display much higher sedimentation rates due to regional input by rivers. Here, it is necessary to create a regional framework to allow precise dating of strata. We created such a framework for the Northwest Shelf (NWS) of Australia, which was cored by IODP Expedition 356. We used oxygen and carbon isotopes in benthic foraminifera to construct an astronomically‐tuned age model for IODP Site U1463. The natural gamma radiation (NGR) variations for IODP Site U1463 were then correlated to those of other IODP sites and industry wells in the area. The IODP Site U1463 age‐depth model provides a reference for other archives on the NWS allowing to assign ages to regional seismic reflectors and the timing of sediment input. This age model is also used to determine first and last occurrences of foraminiferal species showing that the Indonesian Throughflow (ITF) blocked the migration of foraminifera from the Pacific to the Indian Ocean after 5 Ma. Key Points: Independent, orbitally tuned age model for IODP Site U1463Correlation of natural gamma radiation and seismic profiling allow a consistent age model for the shelf of northwest AustraliaIndependent age model allows updating planktonic foraminiferal biostratigraphy for the Plio‐Pleistocene [ABSTRACT FROM AUTHOR]

From March to May 2019, a seasonal multidisciplinary scientific expedition on the EV Akademik Tryoshnikov was conducted in the framework of the first stage of the "TransArctica 2019" program. Within the seismological part, six temporary seismic stations were installed at four different locations on a drifted ice floe in the North Barents Sea. The first aim of the experiment was to elaborate technology of installation of the seismic stations on drifting ice floes. The second aim was to check if obtained seismological records could be used for registration of the local and remote earthquakes and provide data to investigate the lithosphere structure in the Arctic regions, as well as processes within the ice floe. After analysis of the recoded data, different types of the seismic signal generated by processes in the ice were observed and several signals from remote and regional earthquakes were detected. Further analysis of the seismograms could be used for investigations of the processes within ice floes. The results of the experiment have shown that seismic sensors installed on the drifting ice could be used for recording of local and remote earthquakes. [ABSTRACT FROM AUTHOR]

Earthquake risk reduction approaches classically apply a top-down model where scientific information is processed to deliver risk mitigation measures and policies understandable by all, while shielding end-users from the initial, possibly complex, information. Alternative community-based models exist but are rarely applied at a large scale and rely on valuable, but non-scientific, observations and experiences of local populations. In spite of risk reduction efforts based on both approaches, changes in behaviour or policies to reduce earthquake risk are slow or even non-existent, in particular in developing countries. Here we report on the initial stage of a project that aims at testing, through a participatory seismology experiment in Haiti—a country struck by a devastating earthquake in January 2010—whether public or community involvement through the production and usage of seismic information can improve earthquake awareness and, perhaps, induce grassroots protection initiatives. This experiment is made possible by the recent launch of very low-cost, plug-and-play, Raspberry Shake seismological stations, the relative ease of access to the internet even in developing countries such as Haiti, and the familiarity of all with social networks as a way to disseminate information. Our early findings indicate that 1) the seismic data collected is of sufficient quality for real-time detection and characterization of the regional seismicity, 2) citizens are in demand of earthquake information and trust scientists, even though they appear to see earthquakes through the double lens of tectonics and magic/religion, 3) the motivation of seismic station hosts has allowed data to flow without interruption for more than a year, including through a major political crisis in the Fall of 2019 and the current COVID19 situation. At this early stage of the project, our observations indicate that citizen-seismology in a development context has potential to engage the public while collecting scientifically-relevant seismological information.

In this work, we propose a statistical approach to evaluate the coverage of a network based on the spatial distribution of its nodes and the target information, including all those data related to the final objectives of the network itself. This statistical approach encompasses descriptive spatial statistics in combination with point pattern techniques. As case studies, we evaluate the spatial arrangements of the stations within the Italian National Seismic Network and the Italian Strong Motion Network. Seismic networks are essential tools for observing earthquakes and assessing seismic hazards, while strong motion (accelerometric) networks allow us to describe seismic shaking and to measure the expected effects on buildings and infrastructures. The capability of both networks is a function of an adequate number of optimally distributed stations. We compare the seismic network with the spatial distributions of historical and instrument seismicity and with the distribution of well-known seismogenic sources, and we compare the strong motion station distribution with seismic hazard maps and the population distribution. This simple and reliable methodological approach is able to provide quantitative information on the coverage of any type of network and is able to identify critical areas that require optimization and therefore address areas of future development. [ABSTRACT FROM AUTHOR]

Western Anatolia is one of the most seismically active regions in Turkey. The high seismic activity is a result of a complex tectonic deformation dominated by the N-S extensional tectonic regime in Western Anatolia. This tectonic deformation is also a result of the relative movement of the African- Arabian plates towards the north, which causes the Anatolian plate to shift 2.5 cm per year towards W-SW. One of the largest fault zones in the Western Anatolia, Sultandağı Fault Zone (SFZ) has a northwest-southeast trend. SFZ, approximately 120 km long, is an important tectonic structure, which produced three major earthquakes (Mw> 6.0) between the years of 2000 -2002. Therefore, the most significant goals of this study were to monitor the micro-earthquakes along SFZ, to enrich the current seismic network and to increase the earthquake detection threshold in the region (Mc <2.5). Within the scope of the study, 3 digital broadband earthquake stations were installed in the region. The analysis of the data obtained in the research indicated that the central and western parts of SFZ are active and there is intense seismic activity especially in the vicinity of Sultandağı, Çay, Çobanlar, and Afyonkarahisar. Fault plane solutions revealed that the earthquakes in the region generally occur with normal faulting with oblique components. Seismic stations installed within the scope of the study contributed positively to the increase of the sensitivity (Mc = 1.3) of the earthquake detection threshold (Mc) in the region and increased the detection capacity. [ABSTRACT FROM AUTHOR]

A systematic study of the physical and mechanical processes of landslide development and evolution is important for forecasting, early warning, and prevention of landslide hazards. In the absence of on-site monitoring data, seismic networks can be employed to continuously record ground seismicity generated during landslides. However, landslide seismic signals are relatively weak and inevitably affected by noise interference. Furthermore, systematic characterization and reconstruction of the landslide evolution process remain poorly reported. An evaluation method to recognize landslide events based on seismic signal characteristics is therefore important. This study analyzes the 2019 "7.23" Shuicheng landslide based on data from nearby seismic stations. A landslide seismic signal recognition method is developed based on short-time Fourier transform (STFT) and band-pass filter (BP-filter) analysis. Data from 14 stations near the landslide were reviewed and the landslide data from one station was selected for analysis. The landslide seismic signal was noise-attenuated by using the empirical mode decomposition (EMD) and BP-filter methods. Fast Fourier transform (FFT), STFT, and power spectral density analyses were applied to the landslide seismic signal with higher signal-to-noise ratio (SNR) to obtain the time–frequency signal characteristics of the landslide process. Finally, combined with landslide field survey data, the dynamic process of the landslide was reconstructed based on the seismic signal, and the landslide was divided into four stages: the fracture-transition stage, the accelerated initiation stage, the bifurcation-scraping stage, and the deposition stage. The dynamic characteristics of each stage of the landslide are presented. The results indicate that the initial fracture point of the landslide is located between the bottom of the sliding source area and the top of the acceleration zone, not as traditionally thought, at the top of the sliding source area; this would be difficult to determine through field survey and analysis only. These results provide theoretical guidance for the study of seismic signal extraction, identification of landslide dynamic parameters, and characterization and reconstruction of landslide processes. [ABSTRACT FROM AUTHOR]