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Slow earthquakes play a crucial role in understanding stress accumulation and release along plate interfaces in subduction zones. The northern Ryukyu Trench, where the Philippine Sea Plate subducts northwestward beneath the Eurasian Plate, experienced a major earthquake in 1911 and is currently regarded as a low-seismicity area (LSA). Understanding the seismic activity in this region, particularly the relationship between very-low-frequency earthquakes (VLFEs) and regular seismic events, is crucial for understanding subduction zone dynamics. We investigated the spatial and temporal distribution of VLFE activity in the northern Ryukyu Trench using broadband ocean-bottom seismometers deployed around Amami Island between September 2018 and June 2019. Our analysis, employing the envelope correlation method, revealed that VLFE activity is primarily concentrated northeast of Amami Island, an area characterized by low regular earthquake activity, with the distribution of VLFEs spatially segregated from that of regular earthquakes. Furthermore, we observed earthquake swarm activity at the edges of the LSA in the northern Ryukyu Trench following VLFE activity. In November 2018, intense VLFE activity northeast of Amami Island migrated northeastward, which was followed by a regular earthquake swarm at the edge of this LSA. Following VLFE activity in January 2019, additional seismic activity, including foreshocks, occurred at the edges of this LSA approximately 1 month later. The spatial segregation of VLFEs and regular earthquakes suggests that VLFE activity may be influenced by the migration of high-pressure fluids within the subducted slab. This migration appears to trigger related time-delayed seismic activity, similar to mechanisms observed in other subduction zones such as Hikurangi. Understanding these dynamics is essential for assessing the coupling state of subduction zones and associated fluid behaviors, which play a critical role in evaluating seismic hazards in LSAs. [ABSTRACT FROM AUTHOR]

The seismic swarm activity that began and expanded in four separate regions in the northern Noto Peninsula at the end of 2020 was followed by the M6.5 earthquake in May 2023, which cascaded into the M7.6 earthquake on New Year's Day 2024. To this series of earthquake events, we estimate temporal changes in the background intensity of the nonstationary ETAS model by inversion for each region. We then interpret how this series of earthquakes was driven by subsurface fluid motion and slow slip at each stage, based on the correspondence between the background seismicity changes and the temporal changes in oblique distance and elevation differences between nearby GNSS stations, as well as the spatiotemporal earthquake patterns. [ABSTRACT FROM AUTHOR]

The Baihetan Reservoir, the second largest in the world, is located at the intersection of multiple large active fault zones on the eastern boundary of the Sichuan-Yunnan rhombic block. After impoundment on 6 April 2021, many earthquakes occurred around the reservoir area submerged by water. The largest M L 4.7 earthquake in the reservoir area occurred after the water level reached its highest point. But the seismogenic structures and mechanisms of earthquakes in the reservoir area are still unclear. Based on dense array data from the reservoir area, this paper uses the experimental site submodel of USTC-Pickers, transfer learned with 'DiTing' data set of China to obtain a high-precision earthquake catalogue that is twice as large as that the manual catalogue. This study show that earthquakes in the reservoir region primarily occur on secondary faults of pre-existing ones, characterized by a prominent feature of high dip angles trending northwest to southeast. Combined with the spatiotemperal migration characteristics of earthquakes and the relationship between earthquakes and water levels, we infer that most earthquakes are rapid response type and may be induced by rapid increase in elastic stress. Only the spatiotemporal distribution image of the M L 3.2 earthquakes sequence in the dam site-Toudaogou section conforms to the law of pore pressure diffusion, and belongs to the fast response type, which may be induced by the poroelasiticity coupling mechanism. The M L 3.0 earthquake swarm with deep depths in the Heishui River section belongs to the delayed response type and may be induced by the poroelasiticity coupling mechanism. [ABSTRACT FROM AUTHOR]

Recent studies have proposed the contribution of aseismic slip (AS) to earthquake swarms. We investigated the role of AS in earthquake swarms that occurred in 2009, 2015, and 2019 at the Hakone volcano, central Japan, through highly resolved hypocenter distribution analysis, geodetic observation analysis, and identification of similar earthquakes. We observed diffusion-like migration of hypocenters during these swarms. The hydraulic diffusivity varied among the swarms, indicating differing dynamics. The 2015 swarm exhibited rapid hypocenter migration and significant crustal deformation, as revealed by the temporal sequences of tiltmeters near the swarm region. Right-lateral shear dislocation on fault planes could explain the crustal deformation observed in 2015, indicating that AS released approximately 90% of the moment. However, the 2009 swarm lacked evidence of significant AS contribution, indicating that the primary mechanism was fluid pressure diffusion. The substantial contribution of AS to the 2015 swarm might be attributed to increased fluid pressure due to the intrusion of hydrothermal fluid into the shallow part beneath the volcano during volcanic unrest. Our findings imply that the temporal and spatial patterns of seismicity can provide valuable insights into the underlying mechanics of earthquake swarms. [ABSTRACT FROM AUTHOR]

A prolonged earthquake swarm has persisted since June 2018 in northeastern Noto Peninsula (central Japan), with activity focused into distinct southern, western, northern, and eastern clusters. To explore the role of fluids in the occurrence of this swarm, we analyzed the focal mechanisms of the earthquakes occurring from 1 January 2018 to 30 November 2022 and performed stress tensor inversions. The western, northern, and eastern clusters were dominated by a reverse fault-type mechanism with a horizontal P-axis oriented NW–SE. One of the nodal planes of those mechanisms aligns closely with the precisely relocated hypocenter distribution. The stress fields in these three clusters, as determined by stress tensor inversion, have maximum principal stresses oriented horizontally in the NW–SE direction and minimum principal stresses oriented vertically, aligning with the regional stress field. From these focal mechanisms and this stress field, we derived small misfit angles and large slip tendencies. These findings suggest that, in these three clusters, fluids diffused into faults largely aligned with the regional stress field, resulting in earthquakes with compatible focal mechanisms. Conversely, normal and strike-slip fault-type focal mechanisms, which are unfavorable to the regional stress field, dominated in the southern cluster. The estimated stress fields, deviating from the regional stress field, have maximum principal stresses closer to vertical and minimum principal stress oriented horizontally in the ENE–WSW direction. For earthquakes deeper than 15 km, this local stress field results in relatively larger misfit angles and lower slip tendency than the other clusters. These results suggest that those earthquakes in the southern cluster occurred on misoriented fault planes due to elevated pore fluid pressures. These findings provide strong evidence of the ascent of high-pore-pressure fluids from depth in the southern cluster and their subsequent diffusion into a southeast-dipping fault zone. [ABSTRACT FROM AUTHOR]

We propose a new method for real-time uncertainty monitoring of earthquake and volcano source models using data from the global navigation satellite system (GNSS) and explore its application concerning observation station placement. The Geospatial Information Authority of Japan operates two main types of GNSS earth observation network system (GEONET) coordinates for crustal deformation monitoring on different time scales: post-processing analysis values and real-time GEONET analysis system for rapid deformation monitoring (REGARD). REGARD uses the Markov Chain Monte Carlo (MCMC) method termed real-time automatic uncertainty estimation of a coseismic single rectangular model using GNSS data (RUNE) for single rectangular fault model estimation to handle uncertainty. Thus far, no GNSS monitoring system can automatically detect transient crustal deformation events, such as volcanic activity and earthquake swarms, on timescales of a day or less. We extended RUNE and developed a core program for a new monitoring system for earthquake and volcanic source models and their uncertainties. Our program achieved automatic and stable MCMC utilization for rectangular fault, dike, Mogi, and spheroid models by increasing the computational speed, improving search efficiency, and adjusting hyperparameters. The program automatically determines the standard deviation of the likelihood function assuming a normal distribution with weights for each observation station. The calculation time was within 15 s for 1 × 106 samples on a standard 1U server. We assessed the reliability of the developed method using synthetic and observed GNSS data from the 2015 Sakurajima volcanic event. The results were consistent with the assumed model and previous studies and indicated an advantage in automatically quantifying uncertainty in a short computation time. Based on MCMC samples, we developed a new visualization algorithm to indicate areas on a map in which the number of observation stations should be expanded. We assessed the reliability using data from the 2023 Noto Peninsula earthquake [Mj 6.5]. The results indicate that the algorithm is helpful in studying the placement of stations. The above model extensions and their application are essential to achieve a rapid quantitative understanding of disaster events near urban areas and for utilizing this information in emergency response activities. [ABSTRACT FROM AUTHOR]

In this paper, we present numerical modeling aimed to explain Deep Long Period (DLP) events occurring in middle‐to‐lower crust beneath volcanoes and often observed in association with volcanic eruptions or their precursors. We consider a DLP generating mechanism caused by the rapid growth of gas bubbles in response to the slow decompression of H2O–CO2 over‐saturated basaltic magma. The nucleation and rapid growth of gas bubbles lead to rapid pressure change in the magma and elastic rebound of the host rocks, radiating seismic waves recorded as DLP events. The magma and host rocks are modeled as Maxwell bodies with different relaxation times and elastic moduli. Simulations of a single sill‐shaped intrusion with different parameters demonstrate that realistic amplitudes and frequencies of P and S seismic waves can be obtained when considering intrusions with linear sizes of the order of 100 m. We then consider a case of two closely located sills and model their interaction. We speculate on conditions that can result in consecutive triggering of the bubble growth in multiple closely located batches of magma, leading to the generation of earthquake swarms or seismic tremors. Plain Language Summary: Volcano seismology is one of the main geophysical methods used to study volcanic processes and to forecast the eruptions. It is based on analysis of ground motion recorded by seismographs installed in the vicinity of volcanoes. Different seismic signals such as impulsive volcanic earthquakes and nearly continuous volcanic tremors are recorded during periods corresponding to preparation of eruptions. Some of them originate from depths of a few tens of kilometers, that is, from the roots of the system that feeds the magma supply to volcanoes and their eruptions. Therefore, such deep seismic sources are particularly interesting because they may represent early eruption precursors. While we still lack physical understanding of the processes leading to this deep volcanic seismicity, there are several reasons to consider that it is not caused by a sudden slip on faults responsible for the majority of "regular tectonic" earthquakes. In this paper, we use numerical simulations to test another possible mechanism of generation of deep volcanic earthquakes. Namely, we assume that they can be caused by rapid growth of bubbles from the gas that was initially dissolved in the magma. We use numerical simulations to demonstrate that this model predicts main properties of the observed seismic signals. Key Points: Spontaneous bubble nucleation leads to rapid pressure increase in a batch of magmaBubble nucleation in the center of a sill filled with magma results in a propagation of a nucleation front inside the sillExpanding sill generate P and S seismic waves with amplitudes and frequencies close to the observations [ABSTRACT FROM AUTHOR]

The seismicity rate markedly increased in the northeastern Noto Peninsula of Ishikawa Prefecture around the end of 2020, with an Mw6.2 event on 5 May, 2023, followed by many aftershocks. Previous earthquake relocation studies have detected upward migration of microearthquakes via multiple faults and clusters, suggesting the involvement of crustal fluids in this sequence. Since some active faults exist near the source region, there was concern that this sequence could lead to a larger earthquake; it became a reality with the Mw7.5 earthquake on 1 January 2024. This study aims to develop an algorithm to precisely relocate microearthquake hypocenters in quasi-real time for better monitoring. A fine view of seismicity requires relative relocation methods such as the double-difference (DD) method with numerous arrival time difference data precisely measured by the waveform correlation analysis. However, the standard DD method has the disadvantage of huge computational costs when data increase, making it unsuitable for real-time monitoring in such situations. We developed a quasi-real-time algorithm that relocates only new earthquakes using the DD method each time a new time window of data is added. The major improvement is that our method incorporates a traditional simple relative relocation and preserves constraints between different time windows; the relative locations of new events are constrained from reference events that were already relocated in the previous time windows. We tested a daily relocation algorithm on 11,546 events from 19 June, 2022, to 31 May, 2023, in the Noto Peninsula earthquake sequence. We found that our modification substantially reduced artificial hypocenter offsets between different time windows and succeeded in resolving the fine fault structures from the cloud-like distribution of initial hypocenters. If we do not impose constraints between different windows, the relocated hypocenters are scattered and do not show fine planar structures. Our algorithm greatly reduces the computational cost, allowing for quasi-real-time earthquake relocation and monitoring. We hope this algorithm will help monitor the spatio-temporal distribution of future earthquake sequences. [ABSTRACT FROM AUTHOR]

The present research work is primarily carried out to select the suitable and better variants or functions of ETAS models to describe the energetic offshore earthquake swarms following 26 December 2004 (MW 9.1) and 21 March 2014 (MW 6.5) along the Andaman–Sumatra subduction zone. An attempt has also been made to inspect the variability of the selected model parameters from this robust estimation to discuss the physical mechanism differences between the SSE-related and fluid- or magma-related swarm sequences. For this purpose, different variants of ETAS models, such as single ETAS model, combined ETAS model, Boxcar swarm model, and exponential swarm model, are utilized for investigating the seismic anomalies by estimating the model parameters from the earthquake occurrence times using maximum likelihood method. The estimated AIC (Akaike information criterion) values for all these models suggest that the exponential swarm model outperforms the other models in successfully explaining the transient changes of background seismicity for the five energetic earthquake swarms triggered by the volcano-tectonic activities in the Andaman Sea. The reason is undoubtedly related to the localized nature of magmatic intrusion or fluid migration that caused the swarms and the exponential decay patterns of earthquakes after the initiation of the swarms. Although the swarms exhibit the shape of exponential function, the background seismicity shown by the parameter μ increases by one order during the swarm as compared to the pre-swarm period in the sub-catalogue. Therefore, the procedure of identifying improved variants or functions of ETAS models and estimating model parameters using earthquake occurrence times enhances our understanding of earthquake-triggering mechanisms, potential swarm activity patterns, and the intricate interplay between seismicity and volcanic processes in submarine volcanic arcs. While this approach might not facilitate real-time forecasting, it remains instrumental in characterizing seismic patterns and providing essential information for effective hazard assessment and the formulation of mitigation strategies within the coastal areas of the Andaman–Nicobar Islands region. [ABSTRACT FROM AUTHOR]

Making use of the geomagnetic field and the electron density data from the ionosphere observed by the three Swarm satellites that were recorded through 2020, 303 days before and 62 days after the Samos earthquake were investigated, which occurred at 11:51 UTC on Oct 30, 2020, happened in an offshore location around 60 km southwest of Izmir, western Turkey, and 16 km north of Samos Island, Greece 37.897°N 26.784°E. Magnetic and electron density data abnormalities were examined using the Analysis of Magnetic Swarm (AMSW) and the Analysis of Electron Density Swarm (AEDSW) algorithms. The quiet time abnormalities during nighttime within the Dobrovisky region showed exciting results. It showed an enhancement in the cumulative number of tracks (acceleration) approximately 150 days before the mainshock of the earthquake in the magnetic and electron density data. In addition, magnetic and electron density data results matched the ground-based observatory data recorded within the same period and the Dobrovisky region. [ABSTRACT FROM AUTHOR]

In Germany, the highest seismic hazard is associated with the Albstadt Shear Zone (ASZ) in the western Swabian Jura, a low mountain range in southwest Germany. The region is affected by continuous micro-seismic activity with the potential for damaging earthquakes (nine events with ML ≥ 5 in the 20 th century). Within the AlpArray and StressTransfer projects nine temporary seismic stations have been installed in the region of the ASZ to densify the permanent seismic monitoring. In October 2018 and September 2019, the state seismological survey (LED) detected two low-magnitude earthquake sequences with hundreds of events in the area. The temporarily densified local network allows us to systematically analyze these sequences and to search for other sequences by applying a template-matching routine on data from 2018 to 2020. In total, six earthquake sequences could be identified with at least 10 events. The four largest sequences (> 50 events) consist of two fore- and aftershock sequence and two earthquake swarms. Earthquake swarms were so far not observed around the ASZ. Precise relative hypocenter relocations and the determination of fault-plane solutions allow us to propose a seismotectonic model based on the three imaged fault types: (a) The well-known NNE-SSW striking sinistral strike-slip ASZ at depths of 5-10 km, (b) a NW-SE striking dextral strike-slip fault zone at depths of 11-15 km beneath the Hohenzollerngraben (HZG), a shallow, apparently aseismic NW-SE striking graben structure; this NW-SE fault zone possibly is an inherited zone of weakness in the basement and facilitated the development of the HZG and (c) at the intersection of the ASZ with the NW-SE fault zone, complex faulting in form of NNW-SSE striking sinistral strike-slip and normal faulting possibly to accommodate local stresses. [ABSTRACT FROM AUTHOR]

The present study addresses verification of average seismic shear-wave velocity from the surface to a depth of 30 m (VS30) as a suitable proxy for a seismic amplification. For this purpose, we used instrumentally homogeneous and spatially dense seismic network WEBNET (West Bohemia Seismic Network), designed to monitor an intraplate earthquake swarm activity in the West Bohemia/Vogtland region (Czech Republic/Germany). Using a Multichannel analysis of surface waves (MASW) shear-wave velocity models and parameters VS30 and H800 (depth of Vs > 800 m/s) were obtained at 17 WEBNET sites. VS30 were compared with (i) H800 and (ii) determined bedrock densities. To understand the relation between VS30 and site amplification, VS30 values were correlated with amplitudes of two earthquakes: (1) Mw 6.4 Petrinja, Croatia (12/2020) and (2) Mw 4.2 SE of Vienna, Austria (03/2021) both recorded by the WEBNET. The correlation analysis examined four categories of seismic waves in nine frequency windows and described the relation between amplification and VS30 using newly defined regression model. The results show that for the regression model, the frequency window with the highest correlation is in the 1–3 Hz range, and this dependence is statistically best observed in the full wave record. The amplification generally decreases with increasing VS30. However, a large scatter in amplification within Eurocode 8 category B is observed. Based on the observations a new general approach is put forward to finely indicate the relation between amplification and VS30 and the use of other site proxies is discussed. [ABSTRACT FROM AUTHOR]

This study aimed to estimate radon concentrations in groundwater and surface water to evaluate radon (222Rn) contamination in drinking water within the Amreli region of Saurashtra, Gujarat, India. Water samples from 84 sites, covering about 3000 km2, were analyzed using the RAD7 device from Durridge Instruments. Samples were collected in 250 ml radon-tight bottles. Radon concentrations ranged from 0.1 to 13.6 Bq/L, averaging 4.52 Bq/L. At three sites (P9, P29, P35), radon levels exceeded the USEPA limit of 11.1 Bq/L. P9 and P29 are near the Tulsishyam geothermal area, while P35 is close to the Savarkundla fault. Geothermal fluids in Tulsishyam may facilitate radon migration, and swarm-type earthquakes near Savarkundla could also contribute to radon migration. Concurrently, physicochemical parameters like Potential of Hydrogen (pH) and Total Dissolved Solid (TDS) were measured, with no significant correlation found between radon levels and these parameters. Samples were taken from tube wells with depths ranging from 105 to 750 feet, averaging 359 feet. A strong and significant correlation (0.83) was observed between radon concentration and water depth. Health risks from radon exposure were assessed by estimating annual effective dose rates for different age groups through ingestion and inhalation. In some instances, the annual effective dose rate surpassed the WHO-recommended value of 100 µSv/year. However, in most instances, the presence of radon in the water does not indicate a significant radiological risk. [ABSTRACT FROM AUTHOR]

We investigated stress drops during an earthquake swarm in northeastern Noto Peninsula, central Japan, which is characterized by ongoing seismic activity in four clusters. We focused on the spatiotemporal distribution of the static stress drop and its relationship with the source faults of the earthquake swarm. Employing the empirical Green's function method, we estimated static stress drops for 90 earthquakes of MJMA 3.0–5.4. We obtained logarithmic mean stress drops of 13 MPa and 19 MPa from P-wave and S-wave analyses, respectively, which were typical values for crustal earthquakes. We comprehensively analyzed the spatiotemporal distribution of static stress drops in the northern cluster due to the abundance of available data and clarity of fault structures there. We observed larger static stress drops for earthquakes along shallow portions of the source faults, as defined by the hypocentral distribution during a given period. Conversely, we observed smaller static stress drops for earthquakes at medial parts along the faults. These results suggest higher fault strength at shallower parts along the faults and reduced fault strength at medial parts. We attribute the high fault strength at shallow parts to low pore fluid pressure after only limited fluid diffusion near the fault terminus. In contrast, we attribute the reduction in fault strength at medial parts to high pore fluid pressure within the fault following penetration by migrating fluids. [ABSTRACT FROM AUTHOR]

The Saurashtra region, located south of the Kachchh M7.7 (2001) epicentre, has seen a few M5.0 earthquakes with dispersed seismicity over the past two decades. In the Amreli area, a sudden triggering of earthquake activity was noticed in the month of October 2021 - March 2022, and 172 earthquakes of M ≤ 3.0 were recorded within a radius of 10 km. Persistent Scatterer Interferometry (PSI) time-series results of Sentinel 1 A dataset (2017–2022) show the seasonal variation in the displacement and indicate anomalous behaviour with a displacement amplitude, up-to 8 mm, before the earthquake activity. The coefficient correlation (R2) of 0.78 between precipitation and Land Water Storage (LWS) accomplish that the risen displacement amplitude is directly linked with the high LWS which change the pore pressure as well as the stress level of the existing faults in the subsurface and ultimately triggers the earthquake swarm activity in this part of the Indian plate. [ABSTRACT FROM AUTHOR]

Abstract Seismicity in the Los Angeles metropolitan area has been primarily attributed to the regional stress loading. Below the urban areas, earthquake sequences have occurred over time showing migration off the faults and providing evidence that secondary processes may be involved in their evolution. Combining high-frequency seismic attenuation with other geophysical observations is a powerful tool for understanding which Earth properties distinguish regions with ongoing seismicity. We develop the first high-resolution 3D seismic attenuation models across the region east of downtown Los Angeles using 5,600 three-component seismograms from local earthquakes recorded by a dense seismic array. We present frequency-dependent peak delay and coda-attenuation tomography as proxies for seismic scattering and absorption, respectively. The scattering models show high sensitivity to the seismicity along some of the major faults, such as the Cucamonga fault and the San Jacinto fault zone, while a channel of low scattering in the basement extends from near the San Andreas fault westward. In the vicinity of the Fontana seismic sequence, high absorption, low scattering, and seismicity migration across a fault network suggest fluid-driven processes. Our attenuation and fault network imaging characterize near-fault zones and rock-fluid properties beneath the study area for future improvements in seismic hazard evaluation.

Three decades of geodetic monitoring have established slow slip events (SSEs) as a common mode of fault slip, sometimes linked with earthquake swarms and in a few cases escalating to major seismic events. However, the connection between SSEs and earthquake hazard has been difficult to quantify and contextualize beyond regional studies. We aggregate a geodetic record of SSEs from subduction zones in the circum-Pacific region. In aggregate, earthquake rates increase up to threefold concurrent with and proximal to SSEs. The relative amplitude of this increase is correlated with the SSE size and, to a lesser extent, their depth and region. The subdued and coincident earthquake response to SSE stress transfer suggests a more limited role of static stress transfer and a very short relaxation timescale for the triggered seismicity. The observed range of behavior does not support a major connection between SSEs and earthquake hazard. [ABSTRACT FROM AUTHOR]

The 2024 Mw 7.5 Noto Peninsula, Japan, earthquake was initiated within the source region of intense swarm activity. To reveal the mainshock early process, we relocated the earthquake hypocenters and found that many key phenomena, including the mainshock initiation, foreshocks, swarm earthquakes, and deep aseismic slip, occurred at parts of a previously unrecognized fault in intricate fault network. This fault is subparallel (several kilometers deeper) to a known active fault, and the mainshock initiation and foreshocks occurred at the front of a 2‐year westward swarm migration. The initiation location coincides with the destination of the upward migration of a deeper earthquake cluster via several smaller faults. Fluid supply, small earthquakes, and aseismic slip on the fault likely triggered the mainshock, leading to the first major rupture at the western region, propagating further to the west and east sides, resulting in an Mw7.5 event, exceeding 100 km in length. Plain Language Summary: In 2024, an earthquake of magnitude 7.5 happened on the Noto Peninsula, Japan. This earthquake started in an area where many small earthquakes occurred. To reveal how this large earthquake occurred, we precisely determined the hypocenters of the mainshock, foreshocks, aftershocks, and swarm earthquakes. We observed that the mainshock initiation, foreshocks, and some aftershocks occurred on the largest fault in the complex network. Aseismic slip also occurred near the deeper extension. This fault is not a previously known active fault, but small earthquakes migrated westward on it for over 2 years, and the mainshock rupture was initiated at the front. Directly below the mainshock initiation area, small earthquakes moved upward through several small faults. Aseismic slip propagation, fluid supply, and small earthquakes likely triggered the mainshock. The initiated mainshock rupture caused the first major slip in the western region, causing considerable uplift there and further propagating to the east and west. Despite the existence of many minor faults, many key phenomena have occurred on this previously unrecognized fault, which plays a vital role in stress release and tectonic processes in this crust. Key Points: The mainshock initiation, foreshocks, and deep aseismic slip occurred on a previously unknown fault deeper than a known active faultMany swarm earthquakes that appeared to have occurred on different faults actually occurred on different parts of the same faultMainshock rupture was initiated in a westward earthquake migration front where fluid was supplied from depth through several small faults [ABSTRACT FROM AUTHOR]

Abstract—A source of a strong earthquake, as a rule, consists of subsources which are identified by waveform modeling. This modeling does not yield an unambiguous result. In this paper, we show an example when two significantly different focal mechanism solutions are presented for the same earthquake. In one solution, the subsources are characterized by similar faulting type, while in the other solution, the last subsource has an opposite mechanism. In (Vakarchuk et al., 2013), this discrepancy was interpreted as the realization of compensatory motion. The compensatory movements are detected not only in the subsources but also at the scale level of the source zone overall, where these movements manifest themselves in a certain regularity of the aftershock mechanisms discovered in the study of the 1970 Dagestan earthquake by Kuznetsova et al. (1976). In this paper, perhaps for the first time, compensatory movements are detected in a high-magnitude earthquake swarm lacking a pronounced main shock, which occurred in 2023 in Herat Province, Afghanistan. The results are supported by the set of the seismological and satellite interferometric data. [ABSTRACT FROM AUTHOR]

Grabens, or valleys formed during extensional tectonic events, are common but rarely observed during formation. In November 2023, inelastic surface deformation formed abruptly along Iceland's plate boundary in Grindavík. We documented graben formation in real‐time through satellite mapping (InSAR), seismicity, GNSS data, repeated lidar surveys, and field mapping. Five normal faults and ∼12 fissures ruptured the surface delineating two grabens separated by a horst, a context not present in other contemporary case studies. The graben normal faults slipped rapidly (over hours) and maximum surface motions coincided with the occurrence of turbulent seismic swarms in both space and time. Although 3 eruptions took place ∼15 km northeast of Grindavík from 2021 to 2023, attributed to magma intrusions (i.e., dikes), none of these also formed grabens. Thus, the Grindavík grabens shows evidence for tectonic origins. Real‐time monitoring of these phenomena provide insight into graben formation on Earth and potentially on other planets. Plain Language Summary: Valleys known as grabens, typically caused by extensional tectonic events, are a common geological feature, yet their formation is rarely observed. In November 2023, such two grabens suddenly emerged along the boundary between tectonic plates in the town of Grindavík, Iceland. The grabens were shaped by tectonic activity expressed by a swarm of earthquakes and associated ground deformation and resulted in normal faults rupturing the surface and cutting through houses, linear infrastructure including water pipelines and roads within Grindavík. We document the grabens and horst in real time using satellite mapping (InSAR), geodetic GPS data, repeated drone surveys, field mapping, and seismic recordings from a local seismic network. The combination of these data provide unprecedented level of precision in characterizing surface and sub‐surface deformations, especially when maximum surface motions correlate with a turbulent seismic activity in both space and time. Critically, following the formation of the grabens, a series of intensive through short‐lived eruptions happened in December 2023, January 2024, February 2024, March, and May 2024 within the northernmost portion of the grabens. Our observations provide valuable insights into the natural laboratory of Iceland and contribute to the understanding of plate tectonics both on Earth and other planets. Key Points: The 2023 seismic swarm and extension lead to a graben forming that coincides in time and space along Iceland's plate boundaryDuring 2021 to December 2023 only one tectonic graben formed, although 4 eruptions have taken placeThe graben in Grindavík, Iceland is wider at the surface than most recently documented grabens (∼4,500 m vs. <1,000 m) [ABSTRACT FROM AUTHOR]

On New Year's Day 2024, a magnitude 7.6 event struck the Noto Peninsula in central Japan. Prior to this event, an intense earthquake swarm had persisted beneath the northeastern peninsula for more than five years. Geophysical evidence provides insight into the upwelling of deep fluids from the uppermost mantle that triggers the seismic swarm activity. The noble gases and their isotopes have been used as geochemical indicators to determine the origin of the fluids associated with the swarms and their upwelling. Gas samples collected from boreholes around the seismic source region are characterized by anomalously high 3He/4He ratios (∼3.9 RAcor), indicating infiltration of mantle fluids from the subcrustal lithosphere. Using a steady‐state advection model, we calculated mantle helium fluxes of 1.1–2.4 × 10−15 mol cm−2 a−1, similar to those estimated for other representative fault zones, such as the San Andreas and North Anatolian faults. Plain Language Summary: In the Noto Peninsula, central Japan, a long‐lasting, intense earthquake swarm has continued since May 2018. On 1 January 2024, the largest M 7.6 earthquake to date occurred. Geophysical evidence provides insight into the upwelling of deep fluids from the uppermost mantle that triggers the seismic swarm activity. The origin of fluids associated with earthquake swarms and their upward fluxes were determined using noble gases and their isotopes. We collected gas samples from hot spring wells around the seismic source region of earthquake swarms. The observed 3He/4He ratios several times higher than the atmospheric value. This indicates infiltration of mantle fluids derived from the subcrustal lithosphere. In addition, we calculated mantle helium fluxes of ∼2.4 × 10−15 mol cm−2 a−1, which is consistent with estimates for other major fault zones around the world. Key Points: Before the M 7.6 earthquake that occurred in the Noto Peninsula on 1 January, there was a persistent earthquake swarm for over five yearsElevated 3He/4He ratios in gas samples from hot spring wells suggest the emission of mantle‐derived helium from the seismic source regionThe mantle fluids infiltrate the seismogenic crust and then diffuse in the fault zone, triggering the earthquake swarm [ABSTRACT FROM AUTHOR]

On January 1, 2024 at 16:10:09 JST, an Mj 7.6 earthquake struck the Noto Peninsula in the southern part of the Sea of Japan. This location has been experiencing an earthquake swarm for more than three years. Here, we provide an overview of this earthquake, focusing on the slip distribution of the mainshock and its relationship with the preceding swarm. We also reexamined the source areas of other large earthquakes that occurred around the Sea of Japan in the past and compared them with the Matsushiro earthquake swarm in central Japan from 1964 to 1968. The difference between the Matsushiro earthquake swarm and the Noto earthquake swarm is the surrounding stress field. The Matsushiro earthquake swarm was a strike-slip stress field, so the cracks in the crust were oriented vertically. This allowed fluids seeped from the depths to rise and flow out to the surface. On the other hand, the Noto area was a reverse fault stress field. Therefore, the cracks in the earth's crust were oriented horizontally. Fluids flowing underground in deep areas could not rise and spread over a wide area in the horizontal plane. This may have caused a large amount of fluid to accumulate underground, triggering a large earthquake. Although our proposed mechanism does not take into account other complex geological conditions into consideration, it may provide a simple way to explain why the Noto swarm is followed by a large earthquake while other swarms are not. [ABSTRACT FROM AUTHOR]

A devastating earthquake with moment magnitude 7.5 occurred in the Noto Peninsula in central Japan on 1 January 2024. We estimate the rupture evolution of this earthquake from teleseismic P‐wave data using the potency‐density tensor inversion method, which provides information on the spatiotemporal slip distribution including fault orientations. The results show a long and quiet initial rupture phase that overlaps with regions of preceding earthquake swarms and associated aseismic deformation. The following three major rupture episodes evolve on segmented, differently oriented faults bounded by the initial rupture region. The irregular initial rupture process followed by the multi‐scale rupture growth is considered to be controlled by the preceding seismic and aseismic processes and the geometric complexity of the fault system. Such a discrete rupture scenario, including the triggering of an isolated fault rupture, adds critical inputs on the assessment of strong ground motion and associated damages for future earthquakes. Plain Language Summary: On 1 January 2024, a moment magnitude 7.5 earthquake occurred in the northern Noto Peninsula, Japan. The strong ground motion and tsunami associated with the earthquake caused severe damage to buildings and infrastructure, resulting in at least 245 causalities in the affected areas. The Noto Peninsula is affected by northwest‐southeast compression, and active reverse faults are known along the northern coast of the peninsula and its offshore region. Before the 2024 earthquake, the source region experienced long‐lasting earthquake swarm activity, which is a set of seismic events without an obvious mainshock‐aftershock pattern. Our seismological analysis found that there was a 10‐s‐long initial rupture episode around the hypocenter that overlapped with the earthquake swarm region. The initial rupture was followed by a series of three different rupture episodes on differently oriented fault segments. This earthquake highlights a multi‐scale rupture growth across a segmented fault network after a very quiet initial rupture process that was controlled by the preceding earthquake swarms and associated aseismic deformation related to fluid injection from depth. The rupture process advances our understanding of earthquake source physics and can lead to a better assessment of future earthquake hazards. Key Points: The 2024 Mw 7.5 Noto Peninsula earthquake involves a multi‐segmented rupture sequence on differently oriented faultsThe long and quiet initial rupture domain coincides with the preceding earthquake swarm regionFluid‐induced earthquake swarms and a segmented fault network control the complex earthquake rupture growth [ABSTRACT FROM AUTHOR]

An unexpected Mw7.45 earthquake struck the Noto Peninsula on 1 January 2024, preceded by several long‐living earthquake swarms, providing a valuable opportunity to study seismic and aseismic slips, as well as their interactions. We derived coseismic and 19‐day postseismic slip distributions by inverting co‐ and post‐seismic displacements from Global Navigation Satellite System (GNSS) data. The inverted coseismic slip distribution shows two slip patches, with a maximum slip of ∼4 m. The early postseismic afterslip is 0.1–0.25 m within coseismic slip asperity and 0.1–0.6 m northward of the rupture area. The afterslip within the rupture area is accompanied by numerous aftershocks and coincides with a ∼6 MPa stress drop, suggesting that aftershocks are likely driven by the afterslip. The pattern of poroelastic rebound implies a potential effect of fluid flow on aftershock triggering. This study sheds lights on the intricate interplay between seismic and aseismic processes following large earthquakes. Plain Language Summary: A Mw7.45 earthquake hit the northeastern tip of the Noto Peninsula on 1 January 2024. This region has hosted several long earthquake swarms. This unusual earthquake provides a good opportunity to explore the fault behaviors following a major earthquake. The coseismic and early postseismic deformation have been well recorded at the GNSS stations with unprecedentedly high spatial and temporal resolutions. We inverted the coseismic and early postseismic slip distributions from the GNSS data. The coseismic slip distributes mostly in two patches and reaches up to approximately 4 m. The 19‐day postseismic slip distributes mainly in the coseismic slip region as well as to the north of it. The postseismic slip in the rupture area overlapped with the aftershocks. The result suggests that these aftershocks were likely triggered by the afterslip. Additionally, the pattern of poroelastic rebound implies that fluid flow may play a role in triggering these aftershocks. This study helps advance our understanding of earthquake‐triggering mechanisms and fault behaviors following large earthquakes. Key Points: We inverted coseismic and early afterslip distributions of Noto Peninsula earthquake using co‐ and post‐seismic displacements from Global Navigation Satellite SystemThe early afterslip occurred within and to the north of the two main coseismic slip patchesThe occurrence of aftershocks may result from the early afterslip and possible fluid flow [ABSTRACT FROM AUTHOR]

The 2020 Alex storm in southern France led to localized extreme rainfall exceeding 600 mm in less than 24 hr. In the 100 days following the storm, a series of small earthquakes swarm occurred beneath the Tinée valley, a region characterized by a low background deformation. To gain insight into the mechanisms controlling swarm evolution, we used an enhanced seismic catalog to detect 188 events. These events exhibited magnitudes comprised between −1.03 and 2.01, and 78 of them were relocated using relative locations at an average depth of 3–4 km. Additionally, we estimated the directions and velocities of seismicity migration. Our analyses reveal multiple episodes of hypocenter expansion and migration within a fluid‐saturated fault system. Observations provide evidence of a bi‐directional seismicity migration marked by dual velocities within a swarm. The northward seismicity migration aligns with velocities indicative of aseismic slip (∼130 m/hr), while the southward migration corresponds to velocities associated with fluid pressure diffusion (∼5 m/hr). This migration pattern underscores the interplay of multiple physical mechanisms in both triggering and driving earthquakes. A stress‐driven model based on rate‐and‐state friction successfully explains the overall evolution of observed seismicity, whereas a fluid‐driven model fails to reproduce the data. Our observations and models suggest that fluid pressure changes resulting from intense rainfall caused aseismic slip in the shallow portion of the crust. We hypothesize that aseismic deformation serves as the driving force for the earthquake swarms, coupled with the invasion of pressurized fluid due to diffusing rainfall. Plain Language Summary: On 2 October 2020, the Alex storm caused extreme rainfall, exceeding 600 mm in less than 24 hr, in southern France. Subsequently, 188 earthquakes were recorded, and 78 of them were precisely relocated at depths of 3–4 km beneath the Tinée valley in the 100 days following the storm. Such increased seismic activity is unusual in this region characterized by low deformation (<1 mm). Using seismic data, we identified two directions of seismicity migration marked by dual velocities within swarms–one indicative of aseismic slip, and the other corresponding to fluid pressure diffusion. A purely fluid‐driven model fails to accurately reproduce the temporal evolution of seismicity, while observed data are effectively modeled based on intermittent stress changes resulting from a slow aseismic slip. Our investigations lead us to attribute earthquake activity to aseismic deformation, acting as the driving force for the swarms, coupled with the invasion of pressurized fluid due to infiltrating precipitation. Key Points: Multiple activation of small earthquake swarms after an extreme rainstorm in southern French AlpsBi‐directional swarm migration velocities reveal an interplay between fluid diffusion and aseismic stress perturbationsA stress‐driven model explains the overall evolution of seismicity and provides insights into the triggering mechanisms [ABSTRACT FROM AUTHOR]

The earthquake swarm in Palghar, western India, is a natural laboratory to understand long-duration seismogenesis. However, it requires an accurate estimation of the key parameters, such as earthquake locations and the velocity model of the region. Two separate studies performed by two organisations in India, the CSIR-National Geophysical Research Institute (NGRI) and the National Center for Seismology (NCS) reported significantly differing results from the first 8–12 months of earthquake monitoring in Palghar. CSIR-NGRI reported the depth of earthquakes in the range of 4–15 km, whereas NCS reported a much shallower depth down to 7 km only. We investigate the reason for this depth discrepancy by analysing datasets from the networks of both these organisations. We find that no available velocity models are able to reconcile the depth difference between the two datasets. Selection criteria generally adopted to determine a good velocity model, such as travel-time residuals and location errors, also failed to identify a suitable velocity model. Several synthetic tests helped us to identify that the network geometry and source-station separation are contributing factors to the observed depth difference. However, the main reason for the discrepancy was found to be inconsistent velocity models used for location at both networks. The main objective of our work is to estimate a velocity model which minimises the depth discrepancy between both datasets. In this regard, we synthetically generated hundreds of models with different VP and VP/VS ratios, followed by a grid search of VP and VP/VS ratios, which harmonises the location from the two datasets. The best model consists of a VP lying between 5.55–5.85 km/s and a VP/VS ratio between 1.77–1.81. For this velocity model, there is a greater overlap of the hypocentral clouds from both networks, and about 80% of the earthquakes of the CSIR-NGRI network were located within depths ≤ 7 km. We find that location errors vary seasonally, which is also related to the VP/VS of the crust. Since earlier studies have also found a strong correspondence between rainfall and seismicity in this region, we infer that the high VP/VS ratio might have been caused by the rainfall saturation of cracks in the Palghar seismicity zone. [ABSTRACT FROM AUTHOR]

[Objective] This study aims to reveal the distribution patterns and characteristics of co-seismic geological hazards in earthquake swarms, clarify the differences in induced geological hazards by different types of earthquakes, further understand the seismic risks around and within the Bayan Har Block, and provide efficient guidance for the prediction and prevention of secondary geological hazards induced by earthquakes. [Methods] We take the co-seismic geological hazards of the Maerkang Ms 6.0 earthquake swarm in 2022 as the research focus. Through systematic data and results analysis on earthquake swarm sequence, regional tectonic environment, regional crustal deformation, and post- earthquake short-term geological hazard, the regional and deep structural environment of the Maerkang Ms 6.0 earthquake swarm and the main controlling factors of co-seismic geological hazards are revealed. [Results] The results show that the Maerkang Ms 6.0 earthquake swarm is a deep-seated sticky-slip earthquake that occurred on a secondary fault in the active strong earthquake zone within the Bayan Har block, a region with extremely strong peripheral boundary activity. The earthquakes with similar magnitudes may be the result of ruptures of secondary faults of the Songgang fault and the successive ruptures of the barriers between them. The earthquake has resulted in 83 newly discovered geological hazard risks, exacerbating deformation in 106 existing hazard spots and triggering multiple high-altitude landslides and a series of fractured mountain slopes. The areas of extreme, high, and medium geological hazard risk in Caodeng Town, the epicenter area after the earthquake, account for 1.62%, 4.80%, and 12.37%, respectively. The occurrence of secondary geological hazards following earthquakes exhibits a positive correlation with the earthquake magnitude, with the number increasing linearly as the magnitude rises. [Conclusion] The significant differences in the GPS horizontal velocity field and vertical velocity field on both sides of the Darlag-Songgang-Fubianhe fault zone are key factors contributing to the activity of this fault and triggering the recent earthquake. The main controlling factors of co-seismic geological hazards induced by earthquakes are, from primary to secondary, the ruptured fault and its associated faults, seismic magnitude and energy attenuation, terrain slope and altitude difference, and rock mass structure and density of structural surfaces. [Significance] This study predicts a high risk of future strong earthquakes in the intersection area of the Songgang fault, which triggered this earthquake, and the Longriba active fault. The surrounding area of the seismogenic fault and its associated faults are at a high risk of geological hazards during earthquakes. The findings provides a reference for predicting and controlling the risk of co-seismic geological hazards in this area. [ABSTRACT FROM AUTHOR]

The development of a damage scenario following an earthquake swarm event in high-risk areas, such as the inland Sea of Galilee (SoG) in Israel, is critical for significantly increasing public awareness in preparation for a strong earthquake event. Following the earthquake swarms in 2013 and 2020 that occurred near the Dead Sea Fault (DSF) system in the SoG, the present study adopts a conservative approach to damage scenario development, maintaining that these events should be treated as precursory swarms. Accordingly, different damage and loss scenarios were developed using the 2020 Federal Emergency Management Agency software program Hazus and new in-house spatial analysis and postprocessing tools. The results of the scenario analyses confirm that the most intensive damage is expected to be concentrated around the SoG, especially in the adjacent city, Tiberias, if a moderate earthquake (Mw ∼ 6) occurred soon thereafter along the DSF system. In contrast, if a stronger earthquake (Mw ∼ 7) was to occur, the damage may spread to distant cities, such as Beit She'an and Haifa (distances of more than 50 km). Considering the potentially high number of casualties, intensive damage to buildings and essential facilities, high economic loss, blockages of main roads due to slope failures, and weight of debris expected to accumulate near the SoG, we stress the importance of immediate action on the part of civil protection agencies based on the present scenarios to promote the readiness of the population and significantly reduce the anticipated disaster magnitude. [ABSTRACT FROM AUTHOR]

The underlying mechanism of the ongoing seismic swarm in the Noto Peninsula, Japan, which generates earthquakes at 10 times the average regional rate, remains elusive. We capture the evolution of the subsurface stress state by monitoring changes in seismic wave velocities over an 11-year period. A sustained long-term increase in seismic velocity that is seasonally modulated drops before the earthquake swarm. We use a three-dimensional hydromechanical model to quantify environmentally driven variations in excess pore pressure, revealing its crucial role in governing the seasonal modulation with a stress sensitivity of 6 × 10-9 per pascal. The decrease in seismic velocity aligns with vertical surface uplift, suggesting potential fluid migration from a high-pore pressure zone at depth. Stress changes induced by abnormally intense snow falls contribute to initiating the swarm through subsequent perturbations to crustal pore pressure. [ABSTRACT FROM AUTHOR]

Silicic caldera volcanoes present major volcanic and seismic hazards but also host dynamic hydrothermal and groundwater systems and a rich but largely unexplored subsurface biosphere. Many of these volcanoes are hosted in rift settings. The intricate connections and feedbacks among magmatism, rifting, hydrothermal processes, and the biosphere in these complex systems remain poorly understood, necessitating subsurface joint observations that are only enabled by scientific drilling. The CALDERA (Connections Among Life, geo-Dynamics and Eruptions in a Rifting Arc caldera) project workshop funded by the International Continental Scientific Drilling Program (ICDP) gathered multi-disciplinary international experts in January 2023 to advance planning of a scientific drilling project within one of these dynamic, rift-hosted calderas, the Okataina Volcanic Centre (OVC), Aotearoa New Zealand. The OVC's high eruption rate, frequent unrest events and earthquake swarms, location in a densely faulted rapidly extending rift, abundant groundwater–geothermal fluid circulations, and diverse surface hot spring microbiota make it an ideal location for exploring a connected geo-hydro-biosphere via scientific drilling and developing a test bed for novel volcano monitoring approaches. Drilling configurations with at least two boreholes (∼ 200 and ∼ 1000–1500 m deep) were favoured to achieve the multi-disciplinary objectives of the CALDERA project. Decadal monitoring including biosphere activity and composition has the potential to evaluate the response of the hydro-bio system to volcano-tectonic activity. In addition to the OVC caldera-scale datasets already available, site surveys will be conducted to select the best drilling locations. The CALDERA project at the OVC would provide, for the first time, an understanding of volcanic–tectonic–hydrological–biological connections in a caldera–rift system and a baseline for global comparisons with other volcanoes, rifts, and hydrothermal systems. CALDERA would serve as an unprecedented model system to understand how and how quickly the subsurface biosphere responds to geologic activities. Discoveries will improve assessment of volcanic and seismic hazards, guide the sustainable management and/or conservation of groundwater and geothermal resources and microbial ecosystems, and provide a forum for interweaving mātauranga Māori and Western knowledge systems. [ABSTRACT FROM AUTHOR]

This article explores the concept of a "seismic dragon king," which refers to an exceptional earthquake event that deviates from the usual pattern of earthquakes. It focuses on a MW 7.5 earthquake that occurred in 2024 on the Noto Peninsula in Japan, interrupting a previous earthquake swarm in the area. The researchers analyze seismic activity patterns to identify any precursor anomalies and use the Load-Unload Response Ratio (LURR) to assess the likelihood of future large earthquakes. The study suggests that the MW 7.5 earthquake can be considered a significant "dragon king" event. The article also discusses the role of fluids in seismic events, particularly in the formation of the "seismic dragon king" phenomenon. The authors propose that studying the Noto Peninsula earthquake and its aftershocks could enhance our understanding of earthquake precursors and prediction. The article acknowledges the contributions of various scientists and organizations in providing data and opinions related to the earthquake, with support from the National Natural Science Foundation of China. [Extracted from the article]

Mt. Ruapehu is an active andesitic stratovolcano, consisting of several peaks with the summit plateau at 2,797 m, making it the tallest active volcano in New Zealand. The extent of the volcano spreads 40 km across with a series of complex faults encompassing almost the entire base of the volcano. A series of earthquakes occurring 20 km west of the summit of Mt. Ruapehu, near the small town of Erua, which preceded the 1995/1996 major volcanic eruption sequence has been proposed as a medium-term precursor for eruptions at Mt. Ruapehu. We use unsupervised machine learning clustering algorithms HDBSCAN and DBSCAN to define anomalous earthquake swarms in the region and determine whether the Erua swarm was unique by identifying key characteristics in space, time and magnitude distribution. HDBSCAN found six spatial cluster zones to the west of Mt. Ruapehu, which have temporal seismic bursts of activity between 1994 and 2023. DBSCAN identified the seismic swarm that preceded the 1995/1996 major eruption, along with one other similar cluster in the same region, which did not coincide with any documented magmatic unrest, suggesting distal seismic swarms at Mt. Ruapehu may not serve as a reliable eruption precursor when observed in isolation. We instead found that earthquake swarms are relatively common at Mt. Ruapehu and the temporal evolution of the earthquake clusters west of Mt. Ruapehu share similar characteristics to seismic swarms identified in other settings related to fluid migration, typical of fault-valve models. [ABSTRACT FROM AUTHOR]

Magmatism on continental lithospheres induced by mantle plumes is more complex compared to oceanic intraplate volcanism owing to the heterogeneous nature of continental crustal and lithospheric structures. Substantial evidence points to the deep-oriented Hainan mantle plume beneath the Lei–Qiong region, the southernmost of the South China block. In this study, we present a detailed shear wave velocity model of the crust and uppermost mantle in the Lei–Qiong volcanic region, derived from 3-year seismic data (2016–2018) from 34 stations and the use of the ambient noise tomography method. An evident columnar low-velocity anomaly was imaged in the crust and uppermost mantle beneath the Wushi Sag (WSS), Beibu Gulf, potentially suggesting that the center of either one branch or the entirety of the Hainan mantle plume impacts the crust here. This low-velocity anomaly is overlaid by a local Moho deepening, indicative of underplating beneath the existing crust. The Maanling–Leihuling Volcanic Field (MLVF) in northern Hainan Island, previously considered the center of the hotspot, does not exhibit such distinct velocity anomalies. Instead, subtle lower crustal anomalies beneath the MLVF are linked with the upper mantle low-velocity zone beneath the WSS. Additionally, the high-conductivity bodies beneath the MLVF indicate lateral magma transport. Earthquake swarms and deep-seated seismic events beneath the WSS further support the presence of magmatic processes. This study indicates that in the Lei–Qiong region, the interaction of the continental crust with the mantle plume centered in the WSS results in magma exhibiting both vertical ascent and lateral migration, leading to a dual low-velocity shear wave pattern in the upper crust, which significantly influences the surface volcanic activity. [ABSTRACT FROM AUTHOR]

Earthquake swarms are most commonly composed of small‐magnitude earthquakes. However, a recent study by Yoshida, Uchida, et al. (2023, https://doi.org/10.1029/2023GL106023) analyzed a swarm beneath the Noto Peninsula in Japan that, after more than two years of moderate‐magnitude seismicity, triggered the moment magnitude (Mw) 6.2 Suzu mainshock in May 2023. Based on high‐precision earthquake locations and a slip inversion of the mainshock, these authors found that the Mw 6.2 Suzu earthquake occurred on the updip extension of a fault that was active during the swarm, likely driven by increased fluid pressure. After publication of that paper, a much larger and more destructive Mw 7.5 event occurred nearby on 1 January 2024. These events underscore the potential for swarms to be precursors to large, damaging earthquakes. Forecasting the eventual evolution of swarms is currently very challenging but could be aided in the future by new observations and models. Plain Language Summary: Although earthquake swarms often only contain small earthquakes, occasionally they can trigger large, damaging earthquakes. Yoshida, Uchida, et al. (2023, https://doi.org/10.1029/2023GL106023) examined the triggering of a magnitude 6.2 earthquake in Japan, which caused extensive damage, following two years of smaller earthquakes. This sequence, like many swarms, may have been driven by elevated fluid pressure migrating upwards within the crust. After publication of that paper, a much larger and more destructive Mw 7.5 event occurred nearby. Forecasting the eventual evolution of ongoing swarms is currently very challenging but could be aided in the future by new observations and models. Key Points: Earthquake swarms can be precursors to damaging earthquakes, including the 1 January 2024, Mw 7.5 Noto Peninsula, Japan eventFluid pressure changes often drive swarm activity, and their degree of confinement may influence swarm evolutionDirect observations of fluids in fault zones combined with numerical modeling may aid swarm forecasting in the future [ABSTRACT FROM AUTHOR]

The Noto region in Japan has been experiencing earthquake swarm activity since mid-2018, with repeated rises and falls in activity. Crustal deformation (expansion and uplift) observed there since the end of 2020 has been connected to crustal fluids. Studies in other regions have suggested that tides are related to earthquake swarm activities associated with crustal fluids. Therefore, we investigated whether tides are also involved in the Noto earthquake swarm activity. Our results suggest a tidal correlation only at greater depths in the southern part of the analyzed area ('region Sd'). There, we inferred that an increase in pore fluid pressure caused by the inflow of deep fluids may have led to a decrease in fault fracture strength, making the local seismicity relatively susceptible to the effects of tidal forces. The significantly high value in region Sd of the scaling parameter b of the Gutenberg–Richter law (describing the earthquake magnitude–frequency distribution) and observed crustal deformation are consistent with this interpretation. [ABSTRACT FROM AUTHOR]

Seismic activity in the Noto region of Ishikawa Prefecture, central Japan, has increased since August 2020 and has continued as of August 2023. Stress changes due to subsurface sources and increases in fluid pressure have been discussed as the causes of the seismic activity increase. In this study, S-wave polarization anisotropy was investigated by S-wave splitting analysis using temporary and permanent stations located in the epicenter area. We also investigated the seismic wave velocity structure in the source region by analyzing seismic wave velocity tomography. The fast orientations of anisotropy (fast shear wave oscillation direction, FSOD) were generally NW–SE in the southern part of the focal area and east–west in the northern part. The NW–SE anisotropy generally coincides with the direction of the maximum horizontal compression axis, both near the surface and at earthquake depths. Therefore, stress-induced anisotropy can be the cause of the observed NW–SE anisotropy. On the other hand, faults with strike directions generally east–west have been identified, and structural anisotropy may be the cause of the observed east–west anisotropy. We examined the time variation of anisotropy at N.SUZH, one of the permanent stations. No significant time variation was observed in the FSOD. Larger anisotropy was observed, particularly for the activity in the western part of the focal area, from about June–September 2021 compared to the previous period. A high Vp/Vs region was identified beneath the focal area, at a depth of 18 km. This high Vp/Vs region has slightly larger P-wave velocities than the surrounding area. Since Tertiary igneous rocks are distributed in the target area, the high Vp/Vs region may represent a Tertiary magma reservoir, suggesting that fluids released through the old magma reservoir are involved in this seismic swarm. This seismic activity started in the southern part of the area, where relatively immature fault structure exists, where stress-induced anisotropy is distributed, and where high Vp/Vs regions suggestive of fluid at depth are identified. Subsequently, seismicity became more active in the northern part, where structural anisotropy with well-developed fault structures is distributed. [ABSTRACT FROM AUTHOR]

To reveal the deep seismogenic environment and mechanism of earthquakes in Songyuan City, Northeastern China, 59 broadband magnetotelluric sites in the Songyuan area were arranged in this study at a spacing of 5 km. In addition, two intersecting magnetotelluric profiles, with a total of 23 measuring sites and a spacing of 2 km, were established near the Ningjiang earthquake swarm. Using a nonlinear conjugate gradient (NLCG) algorithm, resistivity structures in the lithosphere were obtained at different scales using three-dimensional (3D) inversion. The research results show that: a deep high-conductivity system (<10 Ω·m) was identified at 25–85 km depth in the lithosphere under Songyuan, corresponding closely to a region of high heat flow. It is inferred to be the molten material of mantle upwelling. In addition, a shallow high-conductivity system (<10 Ω·m) was identified beneath the Ningjiang earthquake swarm, which is interpreted to correspond to the Fuyu North fault. It is the main seismo-controlling structure of the Ningjiang earthquake swarm. The deep seismogenic environment and seismogenic mechanism of the Ningjiang earthquake swarm can be described as a deep upwelling of molten mantle material, which provides the power source. The deep magma intruded into the lower crust and accumulated, then intruded along faults and fissures, resulting in the activation of the North Fuyu fault and triggering the Ningjiang earthquake. It is attributed to the activation of shallow faults caused by the upwelling of molten mantle material. [ABSTRACT FROM AUTHOR]

The central part of the Pannonian Basin is characterised by low to medium seismicity. North central Hungary is one of the most dangerous areas of the country in terms of earthquakes, which also includes the area of the Mór Graben where some of the largest earthquakes occurred in Hungary's history. Recent activity has been observed in the Mór Graben. It has been established that earthquake swarms occur quite frequently in the graben. To further study these events, we deployed a temporary seismic network that operated for 20 months. Using the temporary network stations as well as permanent stations from the Kövesligethy Radó Seismological Observatory and the GeoRisk Ltd. networks we registered 102 events of small magnitudes. In this paper, we demonstrate and compare three different event detection methods based on the registered waveforms by the permanent and temporary stations to find the optimal one to collect a complete swarm list in the Mór Graben. After the hierarchical cluster analysis, we relocated the hypocentres using a multiple-event algorithm. Our results demonstrate that the most successful detector in this case is the "Subspace detector." We managed to create a complete list of the events. Our results indicate that the Mór Graben is still seismically active. [ABSTRACT FROM AUTHOR]

The Mj6.5 (Mw6.2) event that occurred on 5 May 2023 near the northern shoreline of the northeastern tip of the Noto Peninsula, central Japan, is the largest event to date in a long‐lasting, intense earthquake swarm. Here we have created a more precise aftershock catalog associated with the 2023 Mj6.5 and the second‐largest 2022 Mj5.4 sequence to understand the rupture process of this largest earthquake. Most of the aftershocks are aligned along a ∼45° SE‐dipping plane. The mainshock initially ruptured the same deep section of the fault zone that had been ruptured by the 2022 Mj5.4 event, before propagating rapidly to shallow depths and to offshore along the ruptured fault plane. The aftershock front migrated at a speed of ∼20 km/hr. This rapid upward migration of the immediate aftershocks might be driven by upwelling of crustal fluids along the intensely fractured and permeable fault zone via mainshock dynamic rupture. Plain Language Summary: Near the northeastern tip of the Noto Peninsula, central Japan, a long‐lasting, intense earthquake swarm has continued since November 2020. On 5 May 2023, the largest Mj6.5 (Mw6.2) event to date occurred. We precisely located the aftershock distribution following the 2023 Mj6.5 and the second‐largest 2022 Mj5.4 sequence and enhanced the catalog by searching events based on waveform similarity to understand the rupture process of this largest earthquake. The 2023 Mj6.5 event initially ruptured the same deep section of the fault that had been ruptured by the 2022 Mj5.4 event, before propagating rapidly to shallow depths and to offshore along the ruptured fault. We can see that the aftershock front moved at a speed of ∼20 km/hr, which is a rare case that constrains the rapid movement of aftershocks. The rapid upward movement of the aftershocks may have been caused by the upwelling of crustal fluids along the permeable fault zone created by the dynamic rupture of the mainshock. Key Points: We constructed a more precise aftershock catalog associated with the two major ruptures during a long‐lasting intense seismic swarmWe identify a rapid migration of early aftershocks following the largest 2023 Mj6.5 earthquake to date during the seismic swarmUpwelling of crustal fluids along the fractured permeable fault zone could drive the rapid migration of early aftershocks [ABSTRACT FROM AUTHOR]

Moderate to strong earthquakes have occurred frequently in the northeast Dabie Orogen recently. From 2014 to 2017, the Guanmiao Earthquake Swarm (GES), with a maximum earthquake magnitude of M3.9, and the Quanjun Earthquake Swarm (QES), with a maximum earthquake magnitude of M3.7, occurred successively in the area near southeast Jinzhai County, where two main Mesozoic E–W‐striking boundary faults, including the Xiaotian–Mozitan and Xinyang–Shucheng faults, are cut by the Cenozoic NNE‐/NE‐trending dextral strike‐slip faulting system. These earthquake swarms occurred within areas of human activities and have the potential to cause more violent geological hazards. However, the tectonic geneses of the earthquake swarms are still unknown due to a lack of sufficient geophysical evidence. Based on terrestrial high‐resolution Bouguer gravity anomaly data, the density structure of the northeast Dabie Mountains is inverted using a 3D linear gravity inversion method. As a result, the occurrence and cutting depth of the reactivated faults near the earthquake swarms are defined, suggesting that the Shangloufang–Xialoufang Fault (F11) may be the seismogenic fault of the GES. The genesis of the QES is possibly associated with the fault termination of the Yingshan–Quanjun strike‐slip fault (F10). More broadly, F10 is one of the major synthetic faults of the NNE‐/NE‐trending dextral strike‐slip faulting system between the Tanlu and Shangcheng–Macheng (F2) faults, which bound the East Dabie Block together. The synthetic and antithetic faults fully cover the Beihuaiyang belt and North Dabie unit topography. These intraplate strike‐slip faults formed to accommodate vertical and lateral movements of the Dabie Mountains, driven by the oblique subduction of the Pacific Plate, were likely responsible for generating earthquakes in both Huoshan and Jinzhai. [ABSTRACT FROM AUTHOR]

Earthquake swarms represent a particular mode of seismicity, not directly related to the occurrence of large earthquakes (e.g., aftershocks) but rather driven by external forcing such as aseismic deformation or fluid migration in fault systems. Sometimes their occurrence overlaps with observable geodetic signals in space and time, indicating a direct link. However, the low resolution of geodetic observations tends to obscure the small scale spatial and temporal dynamics of swarms. In this work, we automatically extract clusters of seismicity related to the 2014 Alto Tiberina swarm sequence (Italy) using an unsupervised clustering approach that exploits space and time information of the seismicity. The quantitative characterization of each cluster indicates that the overall swarm is composed of spatially and temporally confined (sub) swarms each of which could potentially be driven by small‐scale aseismic deformation process. This observation aligns with similar findings during slow slip events in subduction zones. Plain Language Summary: An earthquake swarm is characterized by an elevated rate of earthquake occurrences in a specific region, surpassing the typical seismic activity, without being preceded by a major seismic event. Earthquake swarms are thought to be driven by mechanisms like slow deformation or the migration of fluids. In this study we take a closer look into the seismicity of an earthquake swarm in the Apennines in Italy, exploiting unsupervised machine learning methods. This approach indicates that the swarm sequence consists of a general, smooth increase in seismicity, occasionally punctuated by short accelerations of seismic activity. The subsequent analysis of the accelerated seismicity suggests a connection with several small, slow deformation processes that collectively constitute a large‐scale deformation process, as measured by geodetic data. Key Points: Combining hierarchical and density‐based clustering enables to automatically separate background and clustered seismicityThe quantitative analysis of the extracted clusters reveals a swarm‐like characterThe swarm‐like clusters further indicate relations to aseismic processes [ABSTRACT FROM AUTHOR]

The evolution of fluid injection‐induced seismicity, generally characterized through the number of events or their seismic moment, depends on, among other factors, the injected fluid volume. Migration of seismicity is observed during those sequences and might be caused by a range of mechanisms: fluid pressure diffusion, fluid‐induced aseismic slip propagating along a stimulated fault, interactions between earthquakes. Recent theoretical and observational developments underline the important effect on seismicity migration of structural parameters, like fault criticality, or injection parameters, like flow rate or pressurization rate. Here, we analyze two well‐studied injection‐induced seismic sequences at the Soultz‐sous‐Fôret and Basel geothermal sites, and find that the evolution of the seismicity front distance primarily depends on the injected fluid volume. Based on a fracture mechanics model, we develop new equations relating seismicity migration to injected fluid volume and frictional and structural properties of the fault. We find that the propagation of a fluid‐induced aseismic slip front along the stimulated fault, triggering seismicity, explains well the observations made on the two sequences. This model allows us to constrain parameters describing the seismicity front evolution and explains the diversity of migration patterns observed in injection‐induced and natural earthquake swarms. Plain Language Summary: Injection of fluids at depth may induce earthquakes, which can represent a hazard both for reservoir activities and populations. The magnitude and number of earthquakes depend, at first order, on the injected fluid volume. Induced seismicity has also been observed to migrate away from the injection area, with a diversity of velocities and patterns. Migration has been attributed to several mechanisms like the diffusion of a pore pressure perturbation along the fault, earthquakes triggering each other, or the propagation of a silent aseismic slip. Here, we combine recent theoretical and observational developments to propose a new model to explain the migration of seismicity in two well‐studied induced sequences in France and Switzerland. Our model directly relates migration distance to injected fluid volume and other physical parameters describing the frictional or stress properties of the stimulated faults. This generic model explains seismicity propagation and provides constraints on the relevant physical parameters controlling it. We apply our approach to earthquake swarms occurring in natural context, and reconstruct fluid circulation dynamics during those sequences. Key Points: Induced seismicity front position correlates with cumulative injected fluid volumeAn aseismic crack model driven by fluid injection explains the observed slip distribution and seismicity migrationsOur results enable the reconstruction of a wide range of migration patterns within earthquake swarms and their injection history [ABSTRACT FROM AUTHOR]

This paper reports results from an analysis of swarm seismic events that were recorded in 2018 in the area of the Elbrus Volcanic Center (EVC) by the North Caucasus Seismological Network of the Federal Research Center, Geophysical Survey, Russian Academy of Sciences (FRC GS RAS). The standard location procedure was used to find the hypocenters of recorded events in the EVC area. In the LOS program package, a complex combined location algorithm, methods for minimizing the time residuals at the source, and search over a grid with several trial depth values, were used to relocate the hypocenters of seismic events in swarm sequences. This approach enhances location reliability due to incorporation of the uncertainties related to erroneous onset identification and insignificant deviations of travel times that depend on the earth velocity model used here. A study of earthquake mechanisms for the larger earthquakes has determined the type of slip in agreement with the kinematics in the Elbrus–Mineralnye Vody normal-oblique fault zone. Correlation analysis of waveforms on the vertical component that have been filtered in the frequency range 1‒10 Hz, which includes P and S waves, at the nearest station shows a high agreement among the data under analysis (the correlation coefficient is R ≥ 0.85), thus indicating a high probability of all events having similar sources and propagation paths of seismic waves. Comparison of power spectral densities for individual earthquakes in the swarm sequences also demonstrates a high similarity. [ABSTRACT FROM AUTHOR]

We search for earthquake swarms along the Chilean subduction, from −18° to −39° of latitude, 2003–2020 by developing an objective, model-based method that detects potential swarms as anomalous changes in earthquake rate. A set of 16 swarms is obtained after careful inspection of the candidate swarms; this assessment allows to reject cases for which model errors, rather than 'true' anomalous rate changes, are likely the cause of the detection. Averaging the activity over these 16 episodes, we find indirect evidence for a mostly aseismic driving mechanism, and a mean aseismic to seismic ratio estimated to range between 40 and 90 when using the seismicity rate as a proxy for slip. All the swarms are found in the 20–50 km depth range with the notable exception of one 60–100-km-deep swarm that occurs several days after the 2010 Maule earthquake and downdip of it. The dominant depth range (20–50 km) is in agreement with previous studies that suggest this range to be a transition zone from the shallower, locked part of the subduction, to the freely slipping interface at greater depth and intraslab earthquake activity. The swarms can be separated into three spatial groups, two of which being related to a subducting oceanic ridge. This structural control by fluid-rich geological features is modulated by stress control, that is swarms cluster in time with intermediate to large ruptures, both prior and following them, pointing to a close interplay between seismic slip and aseismic deformation in specific, well separated segments of the Chilean subduction. [ABSTRACT FROM AUTHOR]

An Mw 6.2 earthquake occurred in Suzu, northeastern Noto Peninsula, Japan, on 5 May 2023, followed by many aftershocks. Before this mainshock‐aftershock sequence, an intense earthquake swarm lasted in the vicinity for 2.5 years. Here, we estimated the rupture process of the Mw 6.2 mainshock and relocated >20,000 surrounding small earthquakes. The results show that systematic upward migration occurred via a complex network of faults in the preceding swarm period and that the mainshock rupture was initiated near the shallow end of the swarm earthquakes. The mainshock rupture propagated farther updip, followed by many aftershocks in the shallow extension. Upward fluid movement likely caused systematic upward earthquake migration from a depth of 18–5 km. The present results indicate the importance of monitoring swarm events since large (M > 6) and dangerous earthquakes can occur during such swarms. Plain Language Summary: Growing evidence suggests that fluid movements at depth can cause earthquake swarms in the overriding plates of subduction zones. However, there is less evidence of fluid involvement in the occurrence of large (M > 6) earthquakes, and it has been reported that the generation environments of large earthquakes and swarm earthquakes tend to be different. During intense swarm activity in the northeastern Noto Peninsula, Japan, starting at the end of 2020, an M6.2 earthquake occurred on 5 May 2023, followed by many aftershocks. To clarify the occurrence mechanism of the M6.2 mainshock, we relocated >20,000 small earthquakes and estimated the rupture process. The results showed a systematic upward migration of earthquakes in the preceding swarm period on the deep side of the mainshock fault (depth from 20 to 12 km). The mainshock rupture initiated near the shallow end of the swarm activity and propagated updip (depth from 12 to 9 km). Many aftershocks followed in shallower part of the same fault (depth from 10 to 5 km). Upward fluid migration likely caused the observed systematic upward earthquake migration throughout the sequence. The results indicate that earthquakes as large as M > 6 can be triggered by fluid migration during enhanced seismicity in swarms. Key Points: An Mw 6.2 event initiated near the shallow end of a fault where the preceding earthquake swarm showed systematic upward migrationThe Mw 6.2 rupture propagated farther updip, followed by many shallow aftershocks on the faultUpward fluid migration can trigger earthquakes as large as Mw > 6 [ABSTRACT FROM AUTHOR]

It is of great significance to study the thermal radiation anomalies of earthquake swarms in the same area in terms of selecting abnormal characteristic determination parameters, optimizing and determining the processing model, and understanding the abnormal machine. In this paper, we investigated short-term and long-term thermal radiation anomalies induced by earthquake swarms in Iran and Pakistan between 2007 and 2016. The anomalies were extracted from infrared remote sensing black body temperature data from the China Geostationary Meteorological Satellites (FY-2C/2E/2F/2G) using the multiscale time-frequency relative power spectrum (MS T-FRPS) method. By analyzing and summarizing the thermal radiation anomalies of series earthquake groups with consistency law through a stable and reliable MS T-FRPS method, we first obtained the relationship between anomalies and ShakeMaps from USGS and proposed the anomaly regional indicator (ARI) to determine seismic anomalies and the magnitude decision factor (MDF) to determine seismic magnitude. In addition, we explored the following discussions: earthquake impact on regional thermal radiation background and the relationship between thermal anomalies and earthquake magnitude and the like. Future research directions using the MS T-FRPS method to characterize regional thermal radiation anomalies induced by strong earthquakes could help improve the accuracy of earthquake magnitude determination. [ABSTRACT FROM AUTHOR]

Fractional calculus (FC) has recently received increasing attention due to its applications in many fields involving complex and nonlinear systems. However, one of the key challenges in using FC to deal with fractal or multifractal phenomena is how to relate functions to geometries with fractal dimensions. The current paper demonstrates how fractal calculus can be used to represent physical properties such as density defined on fractal geometries that no longer have the Lebesgue additive properties required for ordinary calculus. First, it introduces the recently proposed concept of fractal density, that is, densities defined on fractals and multifractals, and then shows how fractal calculus can be used to describe fractal densities. Finally, the singularity analysis based on fractal density calculation is used to analyze the depth clustering distribution of seismic frequencies around the Moho transition zone in the subduction zone of the Pacific plates and the Tethys collision zones. The results show that three solutions (linear, log-linear, and double log-linear) of a unified differential equation can describe the decay rate of the fractal density of depth clusters at the number (frequencies) of earthquakes. The spatial distribution of the three groups of earthquakes is further divided according to the three attenuation relationships. From north latitude to south latitude, from the North Pacific subduction zone to the Tethys collision zone, and then to the South Pacific subduction zone, the attenuation relationships of the earthquake depth distribution are generally from a linear, to log-linear, to double log-linear pattern. This provides insight into the nonlinearity of the depth distribution of earthquake swarms. [ABSTRACT FROM AUTHOR]

On June 10, 2022, an earthquake swarm including three major earthquakes with magnitudes of Ms5.8, Ms6.0, and Ms5.2 occurred in Maerkang, Sichuan, China. According to statistics, at least 650 landslides have been triggered by this earthquake, with a total area of 1.2 km2. In this study, the spatial distribution of these landslides and their correlation with seismic, topographic, and geological factors were analyzed based on the coseismic landslide inventory. The results show that landslides are mainly distributed on the northeast side of the Songgang-Fubianhe fault (SG-FBHF), which is a VII intensity area. The closer to the epicenter, the more concentrated the landslide distribution. The landslide density increases significantly with increasing slope. The strata of the Upper Triassic Zhuwo Formation are more prone to coseismic landslide occurrence. Our results, when combined with the focal mechanism solution, precise location of aftershocks, and geological characteristics of the SG-FBHF, suggest that this earthquake is a left-lateral strike-slip earthquake along the SG-FBHF, and the seismogenic fault is slightly tilted to the northeast. In addition, nearly 70% of coseismic landslides are concentrated in the extreme seismic area of ~ 225km2, indicating that the seismic energy release is highly concentrated. This work analyzed the distribution of landslides triggered by a moderately strong earthquake swarm, providing a typical case for researchers to understand the spatial distribution pattern of earthquake-triggered landslides and a scientific support for disaster prevention of coseismic landslides in southwestern Sichuan, China. [ABSTRACT FROM AUTHOR]