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Central America is a seismically active region located in a tectonic setting dominated by the subduction zone between the Cocos and Caribbean plates, transform boundaries between the North American and Caribbean plates, and local or crustal faulting with some of the most important fault systems aligned with the volcanic arc. Combining seismic data from various Central American seismic agency catalogs covering the period from 1520 to 2020, we present an updated regional earthquake catalog for the region. Fourteen databases containing seismic events from local and regional agencies were collected for different time periods, homogenized to moment magnitude (Mw), and subsequently unified using a prioritization criteria approach. We analyzed to the data to identify and remove duplicate earthquakes, prioritizing records with the lowest RMS value, depth consistent with their location based on the region's crustal thickness, and magnitudes in accordance with historical reports or bibliographic sources. Additionally, significant seismic events (Mw ≥ 6.0) were carefully reviewed based on their epicentral locations and magnitudes, according on reliable publications. The earthquake catalog compiled includes a total of 260 548 earthquakes, for which we conducted a descriptive, spatiotemporal statistical analysis, as well as estimations of the magnitude of completeness (Mc) and declustering. Among the most important results, we highlight recent completeness periods for magnitudes Mw < 5.0. Geographically, seismic zones with better Mc are directly related to either good seismic network coverage or high seismicity rates in the region. As regards declustering, the Reasenberg declustering method considers several main shocks with ~ 76% of the earthquakes compared to the initial catalog and the Uhrhammer method considers ~ 51% as main shocks. [ABSTRACT FROM AUTHOR]

This research aims to comprehensively estimate seismicity parameters and create seismotectonic and isoseismal maps for the state of Meghalaya, located in the North-East (NE) region of India using an earthquake catalog collected between 1861 and 2022. The seismic influence zone considered for the study is a circular area with a radius of 350 km around Shillong city (latitude 25.57° N and longitude 91.88° E). Distinct magnitude classes, such as 3.50–3.99, 4.00–4.99, 5.00–5.99, 6.00–6.99, and ≥ 7.00, are considered for analysis, and corresponding completeness periods are obtained as 40, 60, 100, 160, and 130 years, respectively. The study area seismicity parameters a and b values of the Gutenberg–Richter (G–R) relationship are obtained with values ranging from 5.50 to 6.23 and 0.70 to 0.75, respectively. This study further estimates earthquake magnitude occurrence probabilities for 1, 50, and 100 years, as well as the associated return periods. Additionally, seismotectonic maps are developed to provide crucial insights into seismic hazards within the study area. These maps delineate fault lines, active tectonic structures, and seismic zones, facilitating the assessment of potential seismic risks. Intensity-based isoseismal maps are generated to assess the influence of the past five major earthquake occurrences within the study area. It is observed that, if a recurrence of past seismic events occurs at or near the same region, a maximum intensity XI on the Medvedev–Sponheuer–Karnik (MSK) intensity scale might be felt in the study area. The outcome of this study will serve as a valuable resource for seismic hazard assessment specific to the Meghalaya region. [ABSTRACT FROM AUTHOR]

The 1755 Lisbon earthquake holds significant historical importance in Portuguese history. The subsequent tsunami resulted in extensive destruction and damage, affecting not only Lisbon but also other regions of Portugal, Spain, and North Africa. This significant and hazardous event led to an increase in awareness about earthquake and tsunami risks, not only within Portugal but throughout Europe. This heightened awareness facilitated advancements in scientific developments, including design codes, standards, and earthquake engineering. However, recent studies focusing on hazard assessment for Lisbon are limited. For this reason, this paper aims to present a comprehensive probabilistic seismic hazard analysis (PSHA) for the Lisbon metropolitan area. The first stage of PSHA involves defining applicable and active seismic source models (area and line sources) within the study area. Subsequently, historical and instrumental earthquake records are collected to build a homogenized earthquake catalog, utilizing both global and local earthquake databases. Following this, the completeness level of the earthquake catalog is tested. By incorporating suitable ground motion models to the region and local soil characteristics, seismic hazard maps for various return periods and hazard curves in terms of peak ground acceleration (PGA) are developed. The findings based on the area source model agree with existing literature, indicating PGA values ranging from 0.3 g to 0.9 g, 0.2 g to 0.7 g, 0.2 g to 0.5 g, and 0.1 g to 0.3 g for return periods of 2475, 975, 475, and 50 years, respectively.

Knowledge regarding earthquake hazards and seismicity is crucial for crisis management, and the occurrence of foreshocks, seismic activity patterns, and spatiotemporal variations in seismic activity have been studied. Furthermore, the estimation of the region-time-length (RTL) parameter has been proposed to detect seismic quiescence before the occurrence of a large earthquake. In addition, the time-to-failure method has been used to estimate the time occurrence of large earthquakes. Hence, in this study, to gain deeper insight into seismic activity in the southern Zagros region, we utilized the RTL algorithm to identify the quiescence and activation phases leading to the Fin doublet earthquakes. Temporal variations in the RTL parameter showed two significant anomalies. One corresponded to the occurrence time of the first earthquake (2017-12-12); the other anomaly was associated with the occurrence time of the second event (2021-11-14). Based on a negative value of the RTL parameter observed in the vicinity of the Fin epicenters (2021), seismic quiescence (a decrease in seismicity compared to the preceding background rate) was identified. The spatial distribution of the RTL prognostic parameters confirms the appearance of seismic quiescence surrounding the epicenter of the Fin doublet earthquakes (2021). The time-to-failure method was designed using precursory events that describe the acceleration of the seismic energy release before the mainshock. Using the time-to-failure method for the earthquake catalog, it was possible to estimate both the magnitude and time of failure of the Fin doublet. Hence, the time-to-failure technique can be a useful supplementary method to the RTL algorithm for determining the characteristics of impending earthquakes.

The 1755 Lisbon earthquake holds significant historical importance in Portuguese history. The subsequent tsunami resulted in extensive destruction and damage, affecting not only Lisbon but also other regions of Portugal, Spain, and North Africa. This significant and hazardous event led to an increase in awareness about earthquake and tsunami risks, not only within Portugal but throughout Europe. This heightened awareness facilitated advancements in scientific developments, including design codes, standards, and earthquake engineering. However, recent studies focusing on hazard assessment for Lisbon are limited. For this reason, this paper aims to present a comprehensive probabilistic seismic hazard analysis (PSHA) for the Lisbon metropolitan area. The first stage of PSHA involves defining applicable and active seismic source models (area and line sources) within the study area. Subsequently, historical and instrumental earthquake records are collected to build a homogenized earthquake catalog, utilizing both global and local earthquake databases. Following this, the completeness level of the earthquake catalog is tested. By incorporating suitable ground motion models to the region and local soil characteristics, seismic hazard maps for various return periods and hazard curves in terms of peak ground acceleration (PGA) are developed. The findings based on the area source model agree with existing literature, indicating PGA values ranging from 0.3 g to 0.9 g, 0.2 g to 0.7 g, 0.2 g to 0.5 g, and 0.1 g to 0.3 g for return periods of 2475, 975, 475, and 50 years, respectively. [ABSTRACT FROM AUTHOR]

Knowledge regarding earthquake hazards and seismicity is crucial for crisis management, and the occurrence of foreshocks, seismic activity patterns, and spatiotemporal variations in seismic activity have been studied. Furthermore, the estimation of the region-time-length (RTL) parameter has been proposed to detect seismic quiescence before the occurrence of a large earthquake. In addition, the time-to-failure method has been used to estimate the time occurrence of large earthquakes. Hence, in this study, to gain deeper insight into seismic activity in the southern Zagros region, we utilized the RTL algorithm to identify the quiescence and activation phases leading to the Fin doublet earthquakes. Temporal variations in the RTL parameter showed two significant anomalies. One corresponded to the occurrence time of the first earthquake (2017-12-12); the other anomaly was associated with the occurrence time of the second event (2021-11-14). Based on a negative value of the RTL parameter observed in the vicinity of the Fin epicenters (2021), seismic quiescence (a decrease in seismicity compared to the preceding background rate) was identified. The spatial distribution of the RTL prognostic parameters confirms the appearance of seismic quiescence surrounding the epicenter of the Fin doublet earthquakes (2021). The time-to-failure method was designed using precursory events that describe the acceleration of the seismic energy release before the mainshock. Using the time-to-failure method for the earthquake catalog, it was possible to estimate both the magnitude and time of failure of the Fin doublet. Hence, the time-tofailure technique can be a useful supplementary method to the RTL algorithm for determining the characteristics of impending earthquakes. [ABSTRACT FROM AUTHOR]

This study uses complete earthquake catalog data and spatio-temporal analysis to construct a reliable model to forecast the potential seismogenic earthquake or earthquake fault zones. It integrates models developed based on different researchers’ methods and earthquake catalogs from different periods. It constructs and compares models - Model-1, Model-2, and Model-3 - from the complete shallow earthquake catalog between 1963-1999 and 1963-2006. The δAIC is used to evaluate the reliability of the models, with Model-3 emerging as the most reliable in all tests in this study. The model is constructed based on the product of the normalized model of the combined smooth seismicity model of a relatively small to moderate complete earthquake catalog data with a relatively uniform background model and weighted by the normalized seismic moment rate derived from the surface strain rate. It is suggested that a more extended observation period and using a complete, albeit relatively small-to-moderate, earthquake catalog leads to a more reliable and accurate model. Implementation of the Probabilistic Seismic Hazard Function (PSHF) window using the b-value of a 5-year window length with a 1-year sliding window prior to a significant seismic event proved successful, and the methodology demonstrates the importance of the temporal "b-value" in conjunction with the reliable seismicity rate and spatial probabilistic earthquake forecasting models in earthquake forecasting. The results showed large changes in the PSHF prior to giant and large earthquakes and the finding of a correlation between decreased b-value time window length and earthquake magnitude. The results have implications for the implementation of seismic mitigation measures.

Abstract—As part of the international collaboration of several research groups from Russia, France, and Germany, 77 temporary seismic stations were installed in the summer of 2015 for one-year period to conduct a detailed study of the deep structure of the Earth's crust and upper mantle in the region of the Klyuchevskoi Volcano Group (KVG), Kamchatka Peninsula. One of the results of the KISS experiment (Klyuchevskoi Investigation –Seismic Structure of an extraordinary volcanic system) was the final catalog based on the joint data from the temporary stations and the permanent network of the Kamchatka Branch of the Geophysical Survey of the Russian Academy of Sciences (KB GS RAS). The catalog comprises 2136 events, including 560 for which the permanent network catalog lacked sufficient data for correct processing. The catalog in.xlsx format and the station bulletin in.isf format are presented in the supplementary material to the paper. A comparative analysis is performed of joint solutions of two catalogs, one obtained solely from the data of the KB GS RAS permanent network stations and another from a denser seismic network integrated with KISS stations. [ABSTRACT FROM AUTHOR]

This article is the continuation of a study by authors to create the most complete and representative earthquake catalogs with a unified magnitude scale. The catalog created of the Ossetian sector of the Greater Caucasus (the territory of the Republic of North Ossetia–Alania and adjacent areas) was formed by the aggregation of all available data from Soviet, modern Russian, and Georgian catalogs, as well as the data from the International Seismological Centre. The integration was carried out using the author's approach based on the modified nearest neighbor method. The integrated catalog of the Ossetian sector of the Greater Caucasus contains 16,285 events for the period 1962–2022. For all events, magnitude estimates are reduced to a unified "proxy-MW" scale. The integration of data from various sources made it possible to significantly replenish the beginning of the aftershock sequence of the Racha earthquake with MW = 7.0, which occurred on 29 April 1991. There has been a change in the level of registration over time. Thus, there is a significant lack of events for the periods 1967–1970 and 1988–1991; starting from 1995, the catalog is complete for magnitude 3.2, and since 2005 for magnitude 2.2. The integration of Soviet and modern Russian and Georgian catalogs made it possible to significantly increase the completeness and representativeness of seismic events in the studied Ossetian sector of the Greater Caucasus. This once again demonstrates both the fundamental importance of merging seismic data from global, national, and regional catalogs and the effectiveness of the author's developed method. [ABSTRACT FROM AUTHOR]

The article analyzes the development of ideas about the seismicity of the western sector of the Russian Arctic, which is directly related to the peculiarities of development of instrumental observations in the region. The current ideas about the seismicity of the western sector of the Russian Arctic are generalized. Throughout the 20th century, the development of instrumental observations in the Eurasian Arctic, of which the western sector of the Russian Arctic is a part, has been both temporally slow and spatially uneven. In the Eurasian Arctic, seismically active regions, such as mid-ocean ridges, the Svalbard archipelago, the Laptev Sea shelf, and the Taimyr Peninsula, have become the object of study. Conversely, the central and eastern parts of the Barents–Kara region, which are part of the western sector of the Russian Arctic, have always had poor instrumental completeness and, accordingly, the extent of seismic knowledge has been poor. The intensive development of instrumental observations in the Eurasian Arctic in the 21st century has made it possible to significantly expand understanding of the seismicity of the western sector of the Russian Arctic. The greatest seismicity is manifested within the continent–ocean transition zone and Kvitøya (Bely) Island, and the Novaya and Severnaya Zemlya archipelagos. The shelf of the Barents and Kara seas itself is characterized by rare and scattered seismicity. However, the existing seismic network is insufficient for detailed studies of sp-atiotemporal variations in the seismicity of individual seismically active zones and a more correct understanding of its relationship with the geological structure of the region and geodynamic processes developing therein. Long-term studies with bottom seismometers are needed. [ABSTRACT FROM AUTHOR]

In the frame of the DAMAST (Dams and Seismicity) project, we deployed a dense high-fidelity seismological real-time network to investigate in detail the spatio-temporal seismicity distribution around the Enguri high dam, situated in the greater Caucasus in western Georgia. We aim at recording the weak seismicity in a 10 km distance around the dam structure. To lower the detection threshold by reducing the ambient background noise, we installed four seismic stations in shallow (ca. 20 m) and deep boreholes. From these stations, KIT1 with a depth of ca. 250 m is the deepest seismological station in Georgia. In this paper, we characterize the seismicity recorded by the local seismic network from October 2020 to July 2022. To have a better historical picture of the seismic activity, especially since the dam construction and initial operations, re-processing of the old seismological catalogs was carried out. This required digitizing the paper-only catalog copies prior to relocation. We finally obtain a uniform catalog for the Enguri region to characterize the seismicity and start investigating its possible relationship with the exploitation of the dam reservoirs. [ABSTRACT FROM AUTHOR]

Due to its geographical conditions, our country regularly faces the reality of natural disasters, especially earthquakes. Considering that most of the loss of life and property is caused by earthquakes and this region is shaken by a devastating earthquake in an average of five years, earthquake disaster comes first in terms of precautions to be taken. It is of great importance to be able to predict earthquakes in order to determine the precautions that can be taken for earthquakes. In this context, earthquake prediction studies with machine learning have gained momentum in recent years. In this study, earthquake predictions were made using an earthquake catalog and a data set combining geological and geodetic data. This data set is divided into test and training data in order to train the algorithm models used in the study and to measure the performance of the trained models. By using random forest, extreme gradient boosting, decision tree and k nearest neighbor regression algorithms, the models were trained with the training set and the trained models were tested with the test data. Analysis results were compared and evaluated. According to the analysis results, random forest and extreme gradient increment regression algorithms were the algorithms with the most successful results. When the mean square error (MSE) values are examined, the best results are observed in the data set consisting of earthquake information, strains and fault information. This study contributed to the literature by bringing a different perspective to the data set used in earthquake prediction studies with machine learning. [ABSTRACT FROM AUTHOR]

Waveforms of seismic events, extracted from January 2019 to December 2021 were used to construct a test dataset to investigate the generalizability of PhaseNet in the Shandong region. The results show that errors in the picking of seismic phases (P- and S-waves) had a broadly normal distribution, mainly concentrated in the ranges of −0.4–0.3 s and −0.4–0.8 s, respectively. These results were compared with those published in the original PhaseNet article and were found to be approximately 0.2–0.4 s larger. PhaseNet had a strong generalizability for P- and S-wave picking for epicentral distances of less than 120 km and 110 km, respectively. However, the phase recall rate decreased rapidly when these distances were exceeded. Furthermore, the generalizability of PhaseNet was essentially unaffected by magnitude. The M4.1 earthquake sequence in Changqing, Shandong province, China, that occurred on February 18, 2020, was adopted as a case study. PhaseNet detected more than twice the number of earthquakes in the manually obtained catalog. This further verified that PhaseNet has strong generalizability in the Shandong region, and a high-precision earthquake catalog was constructed. According to these precise positioning results, two earthquake sequences occurred in the study area, and the southern cluster may have been triggered by the northern cluster. The focal mechanism solution, regional stress field, and the location results of the northern earthquake sequence indicated that the seismic force of the earthquake was consistent with the regional stress field.

From 10 May 2018 to 1 November 2022 (time of writing), an unprecedented seismic activity is observed east of Mayotte Island (France), related to the largest submarine eruption ever recorded with offshore geophysical studies. Using signals from regional and local seismic stations, we build a comprehensive catalog of the local seismicity for the first ten months of the sequence. This catalog includes a total of 2874 events of magnitude (Mlv) ranging from 2.4 to 6.0, with 77% of them relocated using a double difference location procedure. The hypocentral locations over this period are highly dependent on the small seismic network available. Therefore we compare the locations of later events using a similar network and those estimated from a local ocean bottom seismometer (OBS) network installed since March 2019. Based on the time space evolution and characteristics of the seismicity, five distinct phases can be identified, corresponding to the successive activation of two deep seismic swarms, related to the lithospheric-scale magma ascent up to the seafloor, along with progressive deepening of the seismicity interpreted as decompression of a 40 km deep reservoir.

A reliable and standardized estimation of earthquake size is a fundamental requirement for all tectonophysical and engineering applications. Several investigations raised questions about the determinations of smaller and intermediate earthquakes using Mw scale. Recent investigations (Das et al. in Bull Seismol Soc Am 108(4):1995–2007, 2018b) show that the moment magnitude scale Mw is not applicable for lower and intermediate ranges throughout the world and does not efficiently represent the seismic source potential due to its dependence on surface wave magnitudes; therefore, an observed seismic moment (M0)-based magnitude scale, Mwg, which smoothly connects seismic source processes and highly correlates with seismic-radiated energy (Es) compared to the Mw scale is suggested. With the goal of constructing a homogeneous data set of Mwg to be used for earthquake-related studies, relationships for body wave (mb) and surface wave magnitudes (Ms) toward Mwg have been developed using regression methodologies such as generalized orthogonal regression (GOR) (GOR1: GOR relation is expressed in terms of the observed independent variable; and GOR2: GOR relation is used inappropriately in terms of theoretical true point of GOR line) and standard least-square regression (SLR). In order to establish regression relationships, global data have been considered during 1976–2014 for mb magnitudes of 524,790 events from the International Seismological Centre (ISC) and 326,201 events from the National Earthquake Information Center (NEIC), Ms magnitudes of 111,443 events from ISC along with 41,810 Mwg events data from the Global Centroid Moment Tensor (GCMT). Scaling relationships have been obtained between mb and Mwg for magnitude range 4.5 ≤ mb ≤ 6.2 for ISC and NEIC events using GOR1, GOR2 and SLR methodologies. Furthermore, scaling relationships between Ms and Mwg have been obtained for magnitude ranges 3.0 ≤ Ms ≤ 6.1 and 6.2 ≤ Ms ≤ 8.4 using GOR1, GOR2 and SLR procedures. Our analysis found that GOR1 provides improved estimates of dependent variable compared to GOR2 and SLR on the basis of statistical parameters (mainly uncertainty on slope and intercept, RMSE and Rxy) as reported in Das et al. (2018b). The derived global scaling relationships would be helpful for various seismological applications such as seismicity, seismic hazard and Risk assessment studies. [ABSTRACT FROM AUTHOR]

Earthquakes are a severe natural phenomenon that require continuous monitoring, analysis, and forecasting to mitigate their risks. Seismological data have long been used for this purpose, but geodynamic data from remote sensing of surface displacements have become available in recent decades. In this paper, we present a novel information technology for monitoring, analyzing seismogenic fields, and predicting earthquakes using Earth remote sensing data presented as a time series of surface displacement points for systematic regional earthquake prediction. We demonstrate, for the first time, the successful application of this technology and discuss the method of the minimum area of alarm, which was developed for machine learning and systematic earthquake prediction, as well as the architecture and tools of the GIS platform. Our technology is implemented as a network platform consisting of two GISs. The first GIS automatically loads earthquake catalog data and GPS time series, calculates spatiotemporal fields, performs systematic earthquake prediction in multiple seismically active regions, and provides intuitive mapping tools to analyze seismic processes. The second GIS is designed for scientific research of spatiotemporal processes, including those related to earthquake forecasting. We demonstrate the effectiveness of platform analysis tools that are intuitive and accessible to a wide range of users in solving problems of systematic earthquake prediction. Additionally, we provide examples of scientific research on earthquake prediction using the second GIS, including the effectiveness of using GPS data for forecasting earthquakes in California, estimating the density fields of earthquake epicenters using the adaptive weighted smoothing (AWS) method for predicting earthquakes in Kamchatka, and studying earthquake forecasts in the island part of the territory of Japan using the earthquake catalog and GPS. Our examples demonstrate that the method of the minimum area of alarm used for machine learning is effective for forecasting both catalog and remote sensing data. [ABSTRACT FROM AUTHOR]

Abstract—The paper presents the results of many years of research on the compilation of a consolidated, refined, unified earthquake catalog for the western sector of the Russian Arctic for the entire instrumental observation period, in particular for the period from 1908 to 2020. The catalog includes data on recent seismicity in areas previously unavailable for detailed seismic monitoring. Based on the results of the study, we were able to more accurately determine the spatial distribution of seismicity in the region and compare the instrumental data with parameters of lineament-domain-focal (LDF) models of the General Seismic Zoning maps (GSZ, from Russian term abbreviated as OSR)—OSR-97 and OSR-2016. In the western sector of the Russian Arctic, the highest seismicity is observed in the continent-ocean transition zone, in the Belyi (Kvitøya) Island, Novaya Zemlya and Severnaya Zemlya archipelagos. The very shelf of the Barents and Kara Seas is characterized by rare and scattered seismicity. The configuration, the maximum possible magnitudes, and the depths of the seismogenic layers in the LDF models of OSR-97 and OSR-2016 maps are not always consistent with the instrumental data and need a correction. The consolidated refined earthquake catalog can be used as a basis for the further research aimed at seismic hazard assessment of the territory, construction of geodynamic models, and study of the stress-strain state of the Earth's crust. [ABSTRACT FROM AUTHOR]

Foreshock analysis promises new insights into the earthquake nucleation process and could potentially improve earthquake forecasting. Well‐performing clustering models like the Epidemic‐Type Aftershock Sequence (ETAS) model assume that foreshocks and general seismicity are generated by the same physical process, implying that foreshocks can be identified only in retrospect. However, several studies have recently found higher foreshock activity than predicted by ETAS. Here, we revisit the foreshock activity in southern California using different statistical methods and find anomalous foreshock sequences, that is, those unexplained by ETAS, mostly for mainshock magnitudes below 5.5. The spatial distribution of these anomalies reveals a preferential occurrence in zones of high heat flow, which are known to host swarm‐like seismicity. Outside these zones, the foreshocks generally behave as expected by ETAS. These findings show that anomalous foreshock sequences in southern California do not indicate a pre‐slip nucleation process, but swarm‐like behavior driven by heat flow. Plain Language Summary: Many studies have observed that large earthquakes are preceded by smaller events, called foreshocks. If they have distinctive characteristics that make them recognizable in an ongoing sequence in real time, they can significantly improve the forecasting capability of large earthquakes. To investigate the nature of foreshocks, we compare actual seismicity with the expectation of the most skilled earthquake forecasting model, which assumes that foreshocks are not different from other earthquakes. We find that discrepancies between reality and expectation mostly affect foreshock sequences that anticipate moderate mainshocks with magnitudes below 5.5. We find that those anomalous foreshock sequences tend to occur more often where the heat flow is high. Those zones are already known for the occurrence of swarm‐like sequences, which are prolonged episodes of seismicity without a dominant event. Outside these zones, the observed foreshock activity is explained well by the forecasting model. These findings indicate that anomalous foreshock sequences are not indicating impending large earthquakes but are influenced by the heat flow. Key Points: We compare the foreshock activity in southern California with the expectation of the best‐performing class of earthquake clustering modelsSequences with an anomalous excess of foreshocks are associated mostly with moderate mainshocks and preferentially with high heat flowWe neither find evidence against the cascade nucleation hypothesis nor in favor of the pre‐slip nucleation hypothesis [ABSTRACT FROM AUTHOR]

A unique, consistent, and uniform earthquake catalog is crucial for assessing seismic hazards in any locality. This study aims at compiling and processing a better uniform earthquake catalog, using this catalog to identify the probable subduction zone, and assessing seismicity parameters for Bangladesh. The study area is bounded by the geographical limits 16-29°N and 86-96°E. It includes a sum of 48,342 events which are compiled as 1.0 to 8.5 magnitudes (MW) and time period from 1548 to 2020 yrs. Uniformization is made between the body, surface wave, and moment magnitude scales to unify the catalog in terms of MW. For seismic hazard assessment or prediction studies, this catalog comprises earthquake events from Bangladesh and adjoining regions. The assessed MC obtained is around 4.0-5.0, which leads to a, b value varying between 0.71-1.12 and an a value varying between 4.85-7.12. The findings show that the MC is lower at the border of the Chittagong-Sylhet through Hill tracts than the northern part of the area with an MC 4.5-5.0 and a, b value close to 1.00. The results indicate that the study area is a seismically highly active zone in the context of seismicity parameters. Finally, the compiled catalog, seismicity of the area and a probable deformation front are presented and are recommended for use in assessing seismic hazard analysis in Bangladesh. [ABSTRACT FROM AUTHOR]

As an important model for explaining the seismic rupture mode, the asperity model plays an important role in studying the stress accumulation of faults and the location of earthquake initiation. Taking Qilian-Haiyuan fault as an example, this paper combines geodetic method and b-value method to propose a multi-source observation data fusion detection method that accurately determines the asperity boundary named dual threshold search method. The method is based on the criterion that the b-value asperity boundary should be most consistent with the slip deficit rate asperity boundary. Then the optimal threshold combination of slip deficit rate and b-value is obtained through threshold search, which can be used to determine the boundary of the asperity. Based on this method, the study finds that there are four potential asperities on the Qilian-Haiyuan fault: two asperities (A1 and A2) are on the Tuolaishan segment and the other two asperities (B and C) are on Lenglongling segment and Jinqianghe segment, respectively. Among them, the lengths of asperities A1 and A2 on Tuolaishan segment are 17.0 km and 64.8 km, respectively. And the lower boundaries are 5.5 km and 15.5 km, respectively; The length of asperity B on Lenglongling segment is 70.7 km, and the lower boundary is 10.2 km. The length of asperity C on Jinqianghe segment is 42.3 km, and the lower boundary is 8.3 km.

• We constructed a high-precision catalog of 3539 events for the Daliangshan block. • We unveil multiple previously unmapped faults in the Daliangshan block. • The Zemuhe Region and Lianfeng Fault are in high stress status and there is a risk of large earthquakes in the future. • The differences in fault structure within the Daliangshan block are related to the blocking and compression of the South China block. The Daliangshan block is located between the Tibetan Plateau and the South China block and has accommodated several M > 6.5 damaging earthquakes in the past ∼600 years, as well as intense tectonic deformation and complex fault structures. In this study, we analyze more than two years of continuous seismic data recorded by a recently deployed dense seismic array. We used a recently developed machine learning-based earthquake location workflow (ESPRH) to construct a high-precision earthquake catalog for the region and obtained 3539 earthquakes, which is approximately three times as many as the National Earthquake Data Center (NEDC) catalog contains. The seismicity distribution not only confirms the nature of the faults marked on the map but also delineates the detailed geometry of the unmapped faults, including the en échelon faults at the northern end of the Zemuhe Fault and the "V"-shaped conjugate fault within the Mabian Fault Zone. The Zemuhe Fault and Lianfeng Fault are prone to hosting large earthquakes according to the derived low b-value. The western side of the Daliangshan block is dominated by strike-slip faults. Combining the fault geometry presented in this paper, we observed that the fault properties on the eastern side are complex. This tectonic phenomenon is attributed to the fact that during the lateral extrusion of the southeastern edge of the Chuandian fragments, the northeastern part of the Daliangshan block was squeezed by the South China block more strongly than its southwestern part. We provide the first precise earthquake catalog for Daliangshan block, which can be used as important seismological data for regional hazard assessment and research on the southeastern (SE) margin of the Tibetan Plateau. [ABSTRACT FROM AUTHOR]

This article is the continuation of a study by authors to create the most complete and representative earthquake catalogs with a unified magnitude scale. The catalog created of the Ossetian sector of the Greater Caucasus (the territory of the Republic of North Ossetia–Alania and adjacent areas) was formed by the aggregation of all available data from Soviet, modern Russian, and Georgian catalogs, as well as the data from the International Seismological Centre. The integration was carried out using the author’s approach based on the modified nearest neighbor method. The integrated catalog of the Ossetian sector of the Greater Caucasus contains 16,285 events for the period 1962–2022. For all events, magnitude estimates are reduced to a unified “proxy-MW” scale. The integration of data from various sources made it possible to significantly replenish the beginning of the aftershock sequence of the Racha earthquake with MW = 7.0, which occurred on 29 April 1991. There has been a change in the level of registration over time. Thus, there is a significant lack of events for the periods 1967–1970 and 1988–1991; starting from 1995, the catalog is complete for magnitude 3.2, and since 2005 for magnitude 2.2. The integration of Soviet and modern Russian and Georgian catalogs made it possible to significantly increase the completeness and representativeness of seismic events in the studied Ossetian sector of the Greater Caucasus. This once again demonstrates both the fundamental importance of merging seismic data from global, national, and regional catalogs and the effectiveness of the author’s developed method.

Epicenter locations are generally adjacent to active faults and past seismicity regions. Past earthquake catalogs and the geometry of the active faults can provide key prior knowledge concerning earthquake forecasts. In this study, we first introduce two straightforward dedicated models, the proximity-to-past-earthquakes (PPE) and proximity-to-mapped-faults (PMF) models, to fit the seismicity in the Sichuan-Yunnan region, China. The hybrid proximity-to-known-sources (PKS) model with the optimized model parameters is then used to estimate the probability of earthquake occurrence. Second, to compare the PKS forecast efficiency to those of different models, retrospective tests are applied to a dataset located in the Sichuan-Yunnan region. The results show that the probability maps derived from PPE, PMF, and PKS have non-uniform Poisson distribution features and that there is forecasting significance for past cases of moderate earthquakes in the test region. Finally, using Molchan error diagram tests, we find that the hybrid PKS model performs better than the other models in the testing region. The unsatisfactory performance of the PMF model for earthquake forecasting may lie both in the incompleteness of the fault database and the lack of consideration of co-seismic ruptures. Therefore, one of the three models can be used as a base model for comparing and evaluating earthquake forecast strategies.

Abstract Foreshock analysis promises new insights into the earthquake nucleation process and could potentially improve earthquake forecasting. Well‐performing clustering models like the Epidemic‐Type Aftershock Sequence (ETAS) model assume that foreshocks and general seismicity are generated by the same physical process, implying that foreshocks can be identified only in retrospect. However, several studies have recently found higher foreshock activity than predicted by ETAS. Here, we revisit the foreshock activity in southern California using different statistical methods and find anomalous foreshock sequences, that is, those unexplained by ETAS, mostly for mainshock magnitudes below 5.5. The spatial distribution of these anomalies reveals a preferential occurrence in zones of high heat flow, which are known to host swarm‐like seismicity. Outside these zones, the foreshocks generally behave as expected by ETAS. These findings show that anomalous foreshock sequences in southern California do not indicate a pre‐slip nucleation process, but swarm‐like behavior driven by heat flow.

The data on seismic activations (SAs) in Italy, Greece, and Turkey for the 17th–19th centuries are analyzed to clarify the common patterns of SA occurrence in the different seismically active regions associated with similar geodynamic conditions. The time clustering of strong earthquakes (М ≥ 5.6, I ≥ IX) in Italy, Greece, and Turkey in the 17th–19th centuries has made it possible to identify a number of SAs of various durations both in each country and in the whole region. However, the revealed recurrences are extremely uneven in the time range, the number of earthquakes, and the intervals between the individual SAs. Italy is recorded to have had 12 SAs; the 17th and 18th centuries are characterized by the maximum seismic activity, declining gradually by the 19th century. Nine and eight SAs were detected in Greece and Turkey, respectively, with seismic activity increasing strongly in these countries in the 19th century. The periods of common seismic activation for the entire region are also defined: 1658–1680, 1694–1743, 1766–1791, and 1846–1867. [ABSTRACT FROM AUTHOR]

Paleoseismic evidence from the late‐interseismic Alpine Fault suggests key section boundaries conditionally inhibit rupture. We utilize a year of data from a two‐part seismometer network (Dense Westland Arrays Researching Fault Segmentation) to characterize ∼7,500 earthquakes (−0.7 ≤ MLv ≤ 4.2) and ∼800 focal mechanisms, producing high‐resolution structural images of these boundaries to study effects of material and structural heterogeneities on mode‐switching rupture behavior. Lithologically‐controlled frictional behavior and crustal strength appear to influence lateral and vertical on‐fault seismicity distributions. Ultramafic hanging‐wall serpentinite and serpentinite‐related fault core minerals along the South Westland (SW) boundary, result in a locally shallow seismogenic cuttoff (∼8 km) and abundant on‐fault seismicity. Maximum horizontal compressive stress rotations (14° anti‐clockwise and 20° clockwise near the SW and North Westland (NW) boundaries, respectively, relative to the Central Section), coupled with spatially variable fault frictional properties, are more important than geometry alone in controlling Sections' relative frictional stability. Whereas the SW and Central Sections are well‐oriented for failure, the NW Section is severely misoriented compared with favorably oriented faults of the Marlborough Fault Zone, which possibly facilitate a preferred rupture route. Geometrically, a 40° dip change at the SW boundary may be accommodated either by a single through‐going fault plane ‐ a difficult geometry across which to obtain multi‐segment earthquakes when considering rupture dynamics ‐ or by a deeper vertical fault strand truncated by a shallower listric plane. Our new observations have implications for Alpine Fault rupture scenarios and highlight the need to consider a range of spatially heterogeneous, interdependent physical factors when evaluating controls on rupture segmentation. Plain Language Summary: New Zealand's Alpine Fault last ruptured in 1717 AD and the likelihood of it producing a major earthquake in the next 50 years is estimated to be 75%. The magnitude of the next earthquake will be strongly determined by the area of fault rupture. Two key localities along the fault, which correspond to the boundaries between sections of the fault with differing geometry, slip rate and frictional behavior, have been proposed to sometimes, but not always, act as barriers to fault rupture, limiting the sizes of the resulting earthquakes. However, it remains unclear what physical properties control this process. Using seismic data collected from dense seismometer networks, we construct detailed catalogs of small earthquakes occurring near these localities, at Martyr River and Inchbonnie, and precisely map the distribution of active seismicity near the fault. From these data we improve estimates of (a) the subsurface geometry of the fault and how it changes along length, (b) how seismicity is distributed with depth, to understand possible maximum depth of rupture in conjunction with observations of crustal temperatures and structure, and (c) the orientation of the stresses acting on the fault, to understand its stability to tectonic loading and its frictional behavior. Key Points: Dense microseismicity catalogs constrain fault structure, seismogenic depths and the stress field bookending the fault's Central SectionOn‐fault seismicity, a 40° dip change and a shallow, rheologically controlled cutoff depth are observed at the South Westland boundaryStress analyses indicate South and North Westland Sections are favorably and unfavorably oriented for frictional failure, respectively [ABSTRACT FROM AUTHOR]

Probabilistic seismic hazard analysis, as the most prevalent approach to evaluate earthquake hazard, is commonly based on earthquake catalogs. Although previous studies show that the recurrence time of large-magnitude (Mw> 7.0) events in Iran is more than ~ 1000–2000 years, the available instrumentally recorded earthquakes are limited to less than 100 years. With the idea of having another proxy for seismicity rates, we propose a methodology to evaluate activity rates from strain rates in a combination of regional estimates of β and m max . Considering the comprehensive deformation model of the Iranian Plateau, we found that the deformation-based occurrence rates are more than the catalog-based occurrence rates in all seismotectonic provinces in the Iranian Plateau. The ratios of the deformation-based to the catalog-based occurrence rate are between 1.34 and 2.35. For the first time, a probabilistic deformation-based seismic hazard model for the Iranian plateau is also developed and Peak Ground Acceleration (PGA) values for 10% and 2% POEs in 50 years are estimated. The highest levels of PGA are found in the Azerbaijan and Alborz seismotectonic provinces, where the highest value of strain rates is located. For all provinces, except the Zagros region, the spatial averages of PGA with 10% POE in 50 years from the deformation-based model are up to ~ 23% higher than those from a traditional probabilistic seismic hazard. [ABSTRACT FROM AUTHOR]

Earthquakes are a severe natural phenomenon that require continuous monitoring, analysis, and forecasting to mitigate their risks. Seismological data have long been used for this purpose, but geodynamic data from remote sensing of surface displacements have become available in recent decades. In this paper, we present a novel information technology for monitoring, analyzing seismogenic fields, and predicting earthquakes using Earth remote sensing data presented as a time series of surface displacement points for systematic regional earthquake prediction. We demonstrate, for the first time, the successful application of this technology and discuss the method of the minimum area of alarm, which was developed for machine learning and systematic earthquake prediction, as well as the architecture and tools of the GIS platform. Our technology is implemented as a network platform consisting of two GISs. The first GIS automatically loads earthquake catalog data and GPS time series, calculates spatiotemporal fields, performs systematic earthquake prediction in multiple seismically active regions, and provides intuitive mapping tools to analyze seismic processes. The second GIS is designed for scientific research of spatiotemporal processes, including those related to earthquake forecasting. We demonstrate the effectiveness of platform analysis tools that are intuitive and accessible to a wide range of users in solving problems of systematic earthquake prediction. Additionally, we provide examples of scientific research on earthquake prediction using the second GIS, including the effectiveness of using GPS data for forecasting earthquakes in California, estimating the density fields of earthquake epicenters using the adaptive weighted smoothing (AWS) method for predicting earthquakes in Kamchatka, and studying earthquake forecasts in the island part of the territory of Japan using the earthquake catalog and GPS. Our examples demonstrate that the method of the minimum area of alarm used for machine learning is effective for forecasting both catalog and remote sensing data.

An approach is proposed for analysis of seismic sequences in the Southern Kuril Islands using the Load/Unload Response Ratio (LURR) method. For our calculations, the optimal parameters were chosen for a circular area, the center of which was the epicenter of the Shikotan earthquake of October 4, 1994. The calculations were also carried out for two more earthquakes of August 11, 1969, and March 24, 1978, which were the strongest in the past century. In all cases, anomalies of the LURR parameter have been detected several years before the earthquakes. To test the stability of the anomalies, several zones were investigated near the epicenters of the events tested. The anomalies were inferred to be unstable; that is, they could emerge at different times or disappear completely. The prediction efficiency was tested in the epicentral region of the Shikotan earthquake for the time period of 1965–2020. Six anomalies were recorded during that time, five of which preceded earthquakes with a magnitude of mb ≥ 6.5 that either occurred in close proximity to or fell within the calculated area. In addition, one false alarm was revealed and a missed target was detected. [ABSTRACT FROM AUTHOR]

We describe source and path attributes of the Next Generation of Ground-Motion Attenuation for Subduction zones (NGA-Sub) project relational database. The database contains 991 earthquakes between 1937 and 2016 that meet quality assurance standards and have assigned event types (mostly interface or intraslab). Data curation emphasized large magnitudes: 73% of events have M > 5 and 13 events have M > 8. Event attributes in the database can be broadly divided into those related to the moment tensor, those related to rupture surface geometry (referred to as finite-fault parameters), and categorizations by type (e.g. interface, intraslab) and sequence classification (mainshock, aftershock). Earthquake information and moment tensor parameters compiled from earthquake catalogs include event date and origin time, hypocenter location, seismic moment, and the strike, dip, and rake angles of nodal planes. Finite-fault parameters include along-strike length, down-dip width, and depth to top-of-rupture for one or more rectangles used to parameterize rupture surface geometry. These are modified from models in literature where available, and otherwise are simulated using procedures customized for subduction earthquakes. Rupture distance and other metrics are computed using finite-fault representations of sources, and (as applicable) are partitioned into forearc and backarc components. Forearc and backarc regions are defined based on volcano locations, and are assigned to events and sites. [ABSTRACT FROM AUTHOR]

Earthquake catalogs are essential to analyze the evolution of active fault systems. The background seismicity rate, or rate of earthquakes that are not directly triggered by other earthquakes, directly relates to the stressing rate, a crucial quantity for understanding the seismic hazards. Determining the background seismicity rate is challenging because aftershock sequences may dominate the seismicity rate. Classifying these events in earthquake catalogs—known as catalog declustering—is a common practice and most declustering solutions rely on spatiotemporal distances between events, such as the nearest‐neighbor‐distance algorithm, widely used in various contexts. This algorithm assumes that the nearest‐neighbor distance (NND) follows a bimodal distribution related to the background seismicity and to the aftershocks. Constraining these two distributions is crucial to distinguish the aftershocks from the background events accurately. Recent work often uses linear splitting based on the NND, ignoring the potential overlap between the two populations and resulting in a biased identification of background earthquakes and aftershock sequences. We revisit this problem with machine‐learning algorithms. After testing several popular algorithms, we show that a random forest trained with various synthetic catalogs generated by an Epidemic‐Type Aftershock Sequence model outperforms approaches such as k‐means, Gaussian‐mixture models, and support vector machine classification. We apply our model to two different earthquake catalogs: the relocated Southern California earthquake center catalog and the GeoNet catalog of New Zealand. Our model capably adapts to these two different tectonic contexts, highlighting the differences in aftershock productivity between crustal and intermediate‐depth seismicity. Plain Language Summary: Earthquakes rupture seismic faults when the fault can no longer support the stress built up by tectonic motion. Earthquake catalogs are thus a window into the tectonic processes that occur at depth. Background earthquakes occur spontaneously from tectonic stresses, creating a stress perturbation that generally triggers aftershocks. These aftershocks can also trigger other aftershocks, creating aftershock sequences that may dominate earthquakes catalogs. The accurate determination of the background earthquakes' occurrence is crucial, as it directly relates to the fault's stress state and consequently favors a better understanding of the seismic hazard. To solve this problem, we develop and train a machine‐learning model to classify background earthquakes and aftershocks in earthquake catalogs. After training our model on synthetic earthquakes catalogs, we apply it to several real cases from New Zealand and Southern California to show the effectiveness of our approach. Our results suggest that our method is adaptable to any region, independent of the style of seismicity or the catalog duration. Key Points: The nearest‐neighbor distance metric is a suitable representation of an earthquake catalog for machine‐learning modelsBoth supervised and unsupervised learning algorithms can separate aftershocks from background seismicity in synthetic catalogsA random forest classifier most efficiently declusters real earthquake catalogs in different tectonic contexts [ABSTRACT FROM AUTHOR]

Catalogs of weak seismic events (M ≤ 4) in Turkey and Iran were analyzed to identify signs of their contamination with blasts. A well-pronounced predominance of the number of seismic events and a decrease in their average magnitude in the period from 10:00 to 17:00 LT were found. The epicenters of seismic events that occurred in this time interval at depths of less than 3 km are located much more compactly than other seismic events. Such indications can be considered as an evidence of contamination of the earthquake catalogs with road, mine, and quarry blasts. The presence of such an anthropogenic effect in the earthquake catalogs is also confirmed by the presence of a well-defined weekly periodicity of seismic events. It manifests in the form of a significant weakening of the discussed daytime extremum on Saturday and Sunday in Turkey and on Friday in Iran. Using the example of Turkey, where the observation service attempted to separate blasts and earthquakes in the seismic catalog, it is shown that in an earthquake catalog, which was purified this way, the prevalence of seismic events in the daytime over their number in the nighttime is still observed. The opposite effect was also revealed, namely, the presence of earthquakes in the blast catalog; i.e., there is a mutual contamination of the catalogs of earthquakes and blasts. However, it cannot be excluded that the relative increase in the number of earthquakes in the daytime is only partially caused by the presence of undetected explosions due to imperfect algorithms for discriminating between blasts and earthquakes. The daytime extremum in the number of earthquakes can be partially generated by the occurrence of additional weak earthquakes triggered by relatively strong blasts (i.e., by the triggering effect of explosions on the natural process of seismogenesis). The obtained results show that even in case of earthquake catalogs that are claimed to be cleared of blasts, it is necessary to carry out preliminary study these catalogs in order to assess their contamination with blasts. [ABSTRACT FROM AUTHOR]

From 10 May 2018 to 1 November 2022 (time of writing), an unprecedented seismic activity is observed east of Mayotte Island (France), related to the largest submarine eruption ever recorded with offshore geophysical studies. Using signals from regional and local seismic stations, we build a comprehensive catalog of the local seismicity for the first ten months of the sequence. This catalog includes a total of 2874 events of magnitude (Mlv) ranging from 2.4 to 6.0, with 77% of them relocated using a double difference location procedure. The hypocentral locations over this period are highly dependent on the small seismic network available. Therefore we compare the locations of later events using a similar network and those estimated from a local ocean bottom seismometer (OBS) network installed since March 2019. Based on the time space evolution and characteristics of the seismicity, five distinct phases can be identified, corresponding to the successive activation of two deep seismic swarms, related to the lithospheric-scale magma ascent up to the seafloor, along with progressive deepening of the seismicity interpreted as decompression of a 40 km deep reservoir. [ABSTRACT FROM AUTHOR]

This study presents a procedure for compilation of earthquake catalog for southern Pakistan (spreading over Sindh and Balochistan provinces) and frontal offshore area of Arabian Sea. The active tectonic plate margins of Indian, Eurasian and Arabian Plates and their associated fault lineaments are dominant seismic sources in study area. These seismotectonic sources are extending beyond the terrestrial boundaries of southern Pakistan and diversified in their seismic potential, accumulation of stresses and earthquake generating mechanism. We have compiled earthquake datasets for pre-instrumental period (325 B.C. to 1900) and instrumental observations during January 1901 to August 2020. The seismological datasets are gathered from open source agencies including ISC, GCMT, USGS, PMD and published catalogs. Since earthquake magnitude has a crucial role in seismological studies, the catalog has been thoroughly processed for magnitude homogenization to Mw scale. We have developed magnitude conversion correlations for Mb and Ms to Mw by orthogonal and least square regression analyses. The comparison of these correlations with previously developed regression equations by other authors in similar environments helped us to determine the validity of derived correlations for the study area. The best correlated relations are used for converging multimagnitude types in compiled catalog to Mw scale. Further the catalog is processed for removal of foreshocks- and aftershocks by Reasenberg declustering algorithm. The declustered catalog is used for integrated analysis of various parameters such as completeness analysis in time and magnitude, histograms of depth and magnitude, estimation of GR parameters. It is observed that declustered catalog has completeness period (1960–2020) which is significant for appropriate seismicity analysis. [ABSTRACT FROM AUTHOR]

Based on Matlab，the phase file generated by MSDP software seismic analysis is read，and the GUIDE function in Matlab is used to achieve a highly integrated applet. One-click background automatically generates and outputs earthquake catalogs，so that，there is no need to export earthquakes from the library after seismic events analysis. The catalog is convenient for statistics and research of seismic data.

The Raton Basin has been an area of injection induced seismicity for the past two decades. Previously, the reactivated fault zone structures and spatiotemporal response of seismicity to evolving injection have been poorly constrained due to sparse publicly available seismic monitoring. The application of a machine‐learning phase picker to 4 years of continuous seismic data from a local array enables the detection and location of ∼38,000 earthquakes. The events from 2016 to 2020 are ∼2.5–6 km below sea level and range from ML < −1 to 4.2. Most earthquakes occur within previously identified ∼N‐S zones of seismicity, however our new catalog illuminates that these zones are composed of many short faults with variable orientations. The two most active zones, the Vermejo Park and Tercio zones, are potentially linked by small intermediate faults. In total, we find ∼60 short (<3 km long) basement faults with strikes from WNW to NNE. Faulting mechanisms are predominantly normal but some variability, including reverse dip‐slip and oblique‐slip, is observed. The Trinidad fault zone, which previously hosted a Mw 5.3 earthquake in 2011, is quiescent during 2016–2020, likely in response to both slow accumulation of tectonic strain after the 2011 sequence, and the significant decrease (80% reduction) in nearby wastewater injection from 2012 to 2016. Unlike some other regions, where induced seismicity was triggered in response to higher injection rates, the Raton Basin's frequency‐magnitude and spatiotemporal statistics are not distinguishable from tectonic seismicity. The similarity suggests that seismicity in the Raton Basin is predominantly releasing tectonic stress. Plain Language Summary: The Raton Basin, located on the Colorado‐New Mexico border, has a low level of historical seismicity but experienced a significant increase of earthquakes in the past two decades, coinciding with increased wastewater injection and coal‐bed methane production. We use four years of continuous local seismic data to detect ∼38,000 earthquakes from 2016 to 2020. We find that the previously identified 10–20 km long zones of seismicity are composed of many shorter faults, <3 km long, with variable orientations and slip mechanisms. We observed very little seismicity in the zone that previously hosted the largest earthquake (Mw 5.3 in 2011) in the basin and attribute this finding to both the slow accumulation of tectonic strain following the 2011 sequence and the significant decrease (80% reduction) of wastewater injection to this zone from 2012 to 2016. Overall, the frequency‐magnitude and spatial‐temporal earthquake behavior of the Raton Basin is not distinguishable from tectonic seismicity. This statistical similarity suggests Raton Basin seismicity predominantly releases tectonic stress accumulated over geologic time. Key Points: Seismicity is hosted by short, <3 km long, reactivated basement faults with variable strikes and faulting stylesThe fault zone that hosted a Mw 5.3 event in 2011 exhibits low seismicity following an 80% reduction of the wastewater‐injection rateSimilarity of spatiotemporal‐magnitude basin statistics to tectonic sequences suggests earthquakes mainly release stored tectonic stress [ABSTRACT FROM AUTHOR]

We constructed a catalog of deep low‐frequency (DLF) earthquakes beneath 52 volcanic regions in Japan to investigate their seismicity based on three analyses: relocation, classification, and detection. Relocation and classification analyses were based on waveform correlation, and detection analysis was conducted using the matched filter technique. We detected a total of 105,327 DLF earthquakes and found that DLF earthquakes in many regions are spatially clustered with a spatial spread of only 1–2 km with approximately 5 km intervals between the lower limit of crustal earthquakes and Moho discontinuity. Based on temporal seismicity patterns, DLF earthquake groups in each region can be classified into episodic and non‐episodic types. Episodic groups consist of seismic swarms and quiescence. In some episodic groups, DLF earthquakes have constant recurrence interevent times or increasing interevent times as a function of time. Swarms of DLF earthquakes sometimes are associated with volcanic activities at the surface, which are crustal deformations of Meakan volcano, 2007 and 2014 eruptions of Ontake volcano, and the 2015 magma intrusion of Sakurajima volcano. The spatiotemporal characteristics of DLF earthquake groups may be linked to the movement of magmatic fluids. The discrete vertical separation of DLF earthquake groups may reflect small‐scale heterogeneities, such as injected magma. Periodic activity patterns may be caused by volcanic mechanisms, such as intermittent magma flow. The variety of DLF earthquake patterns may suggest that multiple mechanisms, including magma cooling and intermittent magma flow in complex magma supply systems, may trigger DLF earthquakes rather than a single mechanism. Plain Language Summary: In volcanic regions, deep low‐frequency (DLF) earthquakes are observed, which have lower dominant frequencies than regular earthquakes. We constructed a catalog of volcanic DLF earthquakes in 52 regions in Japan to investigate their distributions and temporal patterns. The catalog was constructed based on relocation, classification, and detection. Relocation and classification were conducted using waveform correlation based on the existing catalog and detection using the template‐matching method. The catalog shows that DLF earthquakes are divided into groups separately, with vertical intervals of approximately 5 km in many regions. The temporal patterns of DLF earthquakes in each group can be classified as episodic (i.e., associated with swarms) and non‐episodic. Some episodic DLF earthquakes have constant or increasing interevent times. In some volcanic regions, episodic activities of DLF earthquakes occurred with volcanic activity at the surface, such as eruptions or crustal deformations. The distribution of the groups of DLF earthquakes may reflect small‐scale heterogeneities beneath volcanoes, and multiple mechanisms may control the occurrence of the two types of DLF earthquakes. Key Points: Deep low‐frequency earthquakes beneath many volcanoes in Japan are clusteredThe temporal activity patterns of the earthquakes are classified into episodic type associated with seismic swarms and non‐episodic typeSpatiotemporal characteristics of deep low‐frequency earthquakes may be interpreted by magmatic fluid movement [ABSTRACT FROM AUTHOR]

The current study analyses the earthquake catalog of Southern Pakistan from 1973 to 2016. The magnitude of completeness (Mc) is 4.9. The b-value and seismic moment release of the Chaman fault system have been calculated and compared with slip rates. The results demonstrate that both seismic moment releases and b-value estimation are consistent with the geodetic slip rates inferred from the InSAR (i.e., lower moment release and higher b-value were estimated on the creep section of the Chaman fault system). The b-value is estimated approximately 1.2 in the northern (i.e., >200 km) and southern (i.e., between 25 and 100 km) portions of Ghazaband fault, which likely depicts the partially creep sections and could not generate large earthquakes. Similarly, the southern Ornach-Nal fault section between 25 and 100 km shows higher b-value (> 1.5), which reflects the creeping nature of the fault. b-value are varied from 0.65 to 1.0 in the region where historic large earthquakes occurred, whereas the b-value is estimated 1.68 for the partial creep section between 110 and 140 km and 2.0 for the creeping section between 210 and 310 km of the Chaman fault. Moreover, b-value of 0.7–1.0 has been found for the central section of both Ornach-Nal and Ghazaband faults. Results reveal that Chaman fault system is likely to host large earthquakes on the section of the faults, which estimate b-value in the range 0.65–1.1 and moderate size earthquakes where b-value is estimated between 1.1 and 1.5. Moreover, faults, which estimate b-value >1.5, are most likely the safe regions from moderate to large earthquakes. In short, estimated b-value clearly depicts the mechanical properties of fault, so that combination of mechanics of fault from geodetic studies and estimated b-value from homogenized earthquake catalog improve the earthquake forecasting models. [ABSTRACT FROM AUTHOR]

Abstract The Ethiopian rift which is part of East African Rift system passes through the middle of the country making it one of the most seismically active regions in the world. Thus, significant and damaging earthquakes have been reported and recorded in the past in this region. A homogeneous earthquake catalog is of basic importance for studying the earthquake occurrence pattern in space and time and for many engineering applications including assessment of seismic hazard, estimation of peak ground accelerations and determination of long-term seismic strain rates. The first earthquake catalogue for Ethiopia was prepared by Pierre Gouin and later, different authors attempted to compile a catalogue using different time period intervals and different earthquake magnitude scales. The b-value mapping and its implication never done for Ethiopia and its environs. The main purpose of the study is therefore first compile and homogenize earthquake catalog of Ethiopia including Read Sea and Gulf of Aden regions into Moment magnitude Mw scale through completeness analysis in time and magnitudes. Secondly, mapping b-values for different Seismgenic regions and understand its implications for magma induced Seismicity in the regions. During the present study, a new homogenized earthquake catalog in moment magnitude scale (Mw), covering about 3814 events is prepared for Ethiopia including Red sea and Gulf of Aden regions. The present study area is bounded within Latitude (40N − 200)N and Longitude (340N − 480)N E and have a magnitude range of Mw (3.0–7.1) with a total coverage period of 56 years (1960 to 2016). The catalog has been analyzed for magnitude completeness (Mc) using Gutenberg’s Frequency Magnitude Distribution law and it is found to be complete respectively for Mc ≥ 4.6 ± 0.03, Mc ≥ 4.6 ± 0.03, Mc ≥ 3.2, Mc ≥ 3.1 and Mc ≥ 5.1 for Afar including red sea and Gulf of Aden, Afar rift and Dabbahu Volcano, Northern, Central, and Southern Main Ethiopian Rifts. Further, the corresponding average b-value of the regions Afar including Red Sea and Gulf of Aden, Afar and Dabbahu Volcano separately, Northern Main Ethiopian Rift, Central Main Ethiopian Rift and Southern Main Ethiopian Rift respectively are estimated to be 1.17 ± 0.05, 1.15 ± 0.05, 0.843, 0.826 and 1.03 with respective period of completeness from 2003 to 2014, 2005 to 2014, 2001 to 2003, 2001 to 2003 and 1960 to 2016 for the regions. Later, mapping of the b-values in the Gutenberg-Richter relation from the newly developed catalog was performed by binning the regions into minimum of 0.050x0.050 for Afar and Dabbahu region, 0.10x0.10 for Main Ethiopian rifts and 0.20x0.20 for the other regions. Thus, the b-value characteristics of various seismogenic zones within the area have been discussed. Hence, in this study, we clearly observed that magma chamber movement including mapping of volcanic centers and magmatic segments are mapped using b-values.

The epidemic-type aftershock sequence (ETAS) model is the most widely used statistical model to describe earthquake catalogs. ETAS is an R package for fitting the space-time ETAS model to an earthquake catalog using the stochastic declustering approach introduced by Zhuang, Ogata, and Vere-Jones (2002). The package provides two classes and several functions to facilitate data preparation, model fitting and some simple diagnostic checks. The present paper is a description of the package and illustrates modeling earthquake data using the space-time ETAS model.