We investigate the relationship between the cumulative number of earthquakes and ground uplift at the Campi Flegrei caldera (South Italy) during the ongoing unrest (2005-present). While previous studies have explored this correlation, we propose a nonlinear epidemic model that captures new features of the caldera system. Our model describes earthquakes’ occurrence as a cascading process driven by ground deformation. The nonlinearity reflects the reduced efficiency of the triggering mechanism, which contributes to the short duration of seismic swarms. This mechanism may represent a general framework for understanding the occurrence of volcanic earthquakes worldwide.

In this study, the factors that drive the Yigong earthquake swarm in the southeastern part of the Tibetan Plateau are investigated. By analyzing the temporal and spatial characteristics of the earthquake swarm, the Xixingla fault is identified as the primary agent in driving the genesis of the earthquake swarm and the seasonal variations in seismic activity. As a significant branch of the southeastern Jiali fault, the Xixingla fault is subjected to high stress stemming from the northward compressive forces of the eastern Himalayan syntaxis. Additionally, climate variations amplify freeze-thaw cycles in glaciers and increase riverine erosion, leading to increased topographical steepness and greater fracturing of rock masses. During the monsoon season, elevated temperatures and heavy precipitation result in substantial glacial melt, causing rapid accumulation of meltwater and rainfall in Yigong Lake. This phenomenon increases the surface load acting on the fault zone, whereas infiltrating water increases pore pressure along rock fractures and faults. The stress accumulated along the fault ultimately triggers rupture, resulting in the formation of an earthquake swarm. Furthermore, the increased stress on the fault due to the 2017 Milin earthquake contributed to a higher frequency of seismic events in the Yigong region. Understanding the hydrogeological and tectonic conditions in Yigong and its vicinity is essential for predicting future seismic activity and developing effective disaster prevention strategies.

Intense earthquake swarms had been observed on the Noto Peninsula in north-central Japan since December 2020. We report data obtained by periodical groundwater sampling and helium isotope measurements in the epicentre area starting July 2022 for investigating the cause of this swarm. The data show mantle-derived helium reaching a maximum of 5 Ra where Ra is the atmospheric 3He/4He ratio of 1.39 × 10-6. This value indicates that the swarm was caused by fluids rising from the mantle. Time-series analysis show an anomalous drop in helium isotopic ratio prior to the 1 January 2024 Noto earthquake (M7.6), which seriously damaged the region. This decrease in helium isotopic ratio is possibly due to the degassing of radiogenic helium via the deformation of the rocks constituting the groundwater aquifer, which is fundamental and valuable data for predicting inland earthquakes in subduction zones. Periodical observation of helium isotopic ratios in deep groundwater is desirable in regions where a large earthquake is expected.

Abstract The earthquake swarms that occurred before Mt. Sinabung’s largest eruption on February 19, 2018, were concentrated between Mts. Sinabung and Sibayak at -1 to 5 km depth. We present an interdisciplinary analysis of travel time tomography, satellite-derived Global Gravity Model plus (GGMplus), Synthetic Aperture Radar (SAR), and optical satellite multispectral data to investigate the origin of the earthquake swarms. The earthquakes were categorized into five clusters based on residual anomaly. The origins of earthquake swarms in Z1, Z2, and Z4 were clearly defined, while this study focused on analyzing the origins of Z3 and Z5. The lineament derived from the mSTA method reveals northwest-southeast fault traces that intersect with the river in zones Z3 and Z5. We found a river with the largest lateral shift of 384 m, located within an earthquake cluster in Z3, suggesting the existence of a blind fault. The tomography in Z3 showed a high Vp (+ 7.76%) and low Vp/Vs (1.62) from a depth of 0 to 2 km, which possibly represents dense volcanic rock. Southeast of the Z3 anomalies, a low Vp (− 3.45%) and high Vp/Vs (1.71) that continues to Mt. Sinabung at depths of 0–1 km are revealed, suggesting a porous rock. Therefore, we thought the earthquake swarm at Z3 indicates fault reactivation influenced by tectonic stress and magma migration of Mt. Sinabung, which may have caused the rocks to slip.

Abstract The b ‐value from the Gutenberg‐Richter law is a crucial parameter in the assessment of seismic hazard. Its temporal variations may also bring useful insights on the processes driving seismicity at depth, even if not yet fully understood. In this paper, we focus on the temporal evolution of the b ‐value in the Ubaye Region (French Western Alps) which was hit by seismic swarms (2003–2004) and complex sequences with several mainshocks (2012–2015). The swarm‐like sequences show a common temporal behavior of b ‐value characterized by an increase and then a return to the initial level. The temporal b ‐value pattern for the mainshock‐aftershock‐like sequences is quite different. After a drop in the b ‐value that may follow the mainshock, the b ‐value increases above the background level before going back to it. Moreover, no precursory pattern can be identified before the mainshock. Fluid processes are recognized to play a crucial role in the driving mechanisms of these seismic sequences. Drawing parallel between swarms and aftershock sequences suggests that the b ‐value depicts fluid‐processes in the Ubaye Region seismicity. We propose that b ‐value shows a complex behavior, with variations due to Coulomb stress‐transfer from the mainshock and fluid‐pressure processes. Therefore, even with a catalog made at the French national scale, the b ‐value variations may help to monitor the on‐going processes at depth.

Seismic energy, like that released by earthquakes, can fracture rock and thereby alter subsurface fluid flow paths, release substrates from inclusions, and expose fresh mineral surfaces capable of reacting with water. However, it is unclear how such seismic-induced changes influence microbial communities. Volcanically active areas experience frequent seismic activity and thus represent ideal locations to examine the influence of seismic-induced geochemical change on subsurface microbial communities. Here, we demonstrate that energy released in an earthquake swarm in 2021 correlated with extensive temporal change in the geochemical and microbial composition of aquifer fluids sampled from ∼100 m depth in a borehole in Yellowstone National Park. Increased energy absorbed at the borehole over time was correlated with increased concentrations of hydrogen, dissolved organic carbon, and sulfide and was associated with depletion of δ13C in dissolved organic carbon, increased concentrations of cells, and increased abundances of chemolithotrophic, putative hydrogen-oxidizing Dethiobacteraceae and Desulfotomaculum bacteria. Dissipation of the earthquake swarm was associated with decreased concentrations of hydrogen, sulfide, and cells. These results suggest the subsurface biosphere dynamically responds to seismic-induced geochemical change at the level of activity and growth. Laboratory mechanical comminution of rhyolite, the primary bedrock in Yellowstone, released organic carbon and hydrogen and generated hydrogen when exposed to water. This indicates the presence of a large subsurface reservoir of organic carbon and hydrogen that can be released or generated by seismic induced bedrock fracturing. Taken together, these data indicate seismic-induced generation of chemical disequilibria can support the persistence of complex subsurface microbiomes.

The earthquake swarm that occurred in Ambarawa, Central Java, from 23 October 2021 to 5 November 2021 recorded 42 earthquakes with a magnitude of less than 5 and were at shallow depths. Even though the earthquake shaking did not cause damage to strong buildings, the community could feel the shaking on II-III MMI. Ambarawa is flanked by 4 active faults, namely the Ungaran-1 fault in the north, the Ungaran-2 fault in the north, the Merapi-Merbabu fault in the south, and the Baribis-Kendeng Fold Thrust Zone in the east. Determination of the b-value is carried out to determine the level of stress and heterogeneity in the crust of Ambarawa, and the determination of the a-value is carried out to determine the frequency of earthquakes that occur in Ambarawa. The method used is the Least Squares Method (LSM) concerning the Gutenberg-Richter Law and using earthquake data with magnitudes above Mc (Magnitude of Completeness). The b-value obtained is 1.6 ± 0.15, which indicates that Ambarawa has a crust with low stress and high heterogeneity. The a-value obtained is 5.8, which indicates a high level of seismic frequency in Ambarawa, so that the earthquake return period is short.

Abstract The 15‐s‐long weak initial rupture of the 2024 M W 7.5 Noto earthquake overlapped with a fluid‐rich region of a preceding earthquake swarm and was accompanied by enhanced high‐frequency seismic radiation. To understand the radiation and related source processes, we investigate rupture behaviors of four nearby M5+ events. We find that the 5 May 2023 M W 5.7 event exhibits similar characteristic radiation, resulting in a relatively low source spectral decay rate. Apparent moment‐rate functions and dynamic rupture simulations, constrained from near‐source waveform data, consistently suggest a northeastward rupture with multiple asperities. Such rupture heterogeneities under a fluid‐rich condition can explain the weak, long seismic radiation but with enhanced high‐frequency signals in the M W 5.7 event and the initial rupture of the 2024 M W 7.5 Noto earthquake. The multi‐asperity model also holds implications for other observations, including the depth dependence of high‐frequency radiation and the low spectral falloff rates observed for low‐frequency earthquakes.

An intense earthquake swarm lasting ~3 years ultimately led to the 2024 Mw (moment magnitude) 7.5 earthquake in the Noto Peninsula, Japan. The spatial complexities in swarm evolution and earthquake rupture have been observed, but the factors controlling these complexities remain unclear. Using high-resolution subsurface imaging with dense seismic observation, we identified a high-velocity body collocated with the major slip zone, which the preceding swarm avoided. The spatial distribution and absolute velocity of the high-velocity body and the adjacent ring-shaped swarm cluster indicate that the high-velocity body is a solidified ancient magma. It initially acted as an impermeable barrier to the fluid migrations that triggered swarm earthquakes, eventually rupturing as an asperity of the 2024 earthquake. Our observation suggests that the heterogeneity in fault zone permeability, originating from ancient volcanic activity (>15 million years ago), controlled the present-day swarm evolution and the large earthquake generation.

Understanding the role of aseismic slip in earthquake cycles is essential for assessing seismic hazards and short-term forecasting. Eastern Taiwan’s double-vergence suture zone, where the Philippine Sea Plate subducts beneath the Eurasian Plate, experiences frequent M ≥ 6 earthquakes and widespread aseismic slip, making it an ideal natural setting to study earthquake triggering processes. Here we demonstrate how aseismic deformation contributed to the April 3, 2024 Mw7.3 Hualien earthquake by analyzing a 24-year catalog of repeating earthquake sequences (RESs) and earthquake swarms. We find that six out of nine swarms in the epicentral area, northern Longitudinal Valley, were accompanied by increasing aseismic slip rates, as revealed by RESs on the west-dipping Central Range Fault (CRF). A notable aseismic slip episode in 2021 indicated by GNSS signals, the accelerated RESs-derived slip rate, and a four-month-long swarm sequence with high diffusivity (~5.2 m²/s), suggests joint contributions from over-pressured fluids and deep fault creep. Following this episode, a sequence of M6+ events occurred in 2022, and both seismicity and aseismic slip gradually increased again starting in 2023. Coulomb stress modeling indicates that cumulative aseismic and seismic slips since 2021 generated up to ~30 kPa positive stress on the eventual 2024 rupture, promoting fault weakening and shallower seismicity. This study provides compelling evidence for aseismic-slip-induced stress triggering of a major earthquake and highlights the importance of integrating aseismic processes into earthquake hazard models for collisional fault systems.

Aggregate masonry buildings in historic urban centers constitute tangible testimony of collective identity and historical continuity. They encompass both simple terraced configurations and more intricate clusters, which are inherently vulnerable to earthquake-induced damage, due to their typological features and the transformations that occurred in the course of time. Strategies aimed at the protection and valorization of such typical architectural heritage should be based on the recognition of their peculiarities, so that the intangible values embedded within the historic fabric can be preserved. A simplified approach able to identify the effect of facade layout on the vulnerability of terraced buildings was validated on a historical center struck by the Central Italy earthquake. It is based on the evaluation of vulnerability factors derived by the application of a multi-level procedure on a large scale, which integrates data on typological and structural aspects, as well as on the condition state and previous interventions. In the center in question, the evidence of prevalent shear damage in the continuous frontage of the buildings facing the main street suggested the in-depth analysis of the facade’s characteristics, and its relationship with the main direction of the seismic swarm. Starting from a preliminary abacus of twelve vulnerability factors, 16 archetypes of facades at increasing vulnerability defined by a combination of the most significant geometrical features of building aggregates were identified. These virtual models encompass typical features that can be found in similar buildings in different contexts, thus enabling preventive actions based on parametric assessment.

Abstract We conducted a systematic search for earthquake swarms in Eastern Indonesia (2012–2021) using BMKG’s (Badan Meteorologi, Klimatologi, dan Geofisika) finalized catalog, identifying 14 swarms across Bali, Lombok, Nusa Tenggara, Banda, Seram, Papua, Sulawesi, Maluku, and Halmahera. Swarms were detected based on distinct spatio-temporal clustering without preceding or subsequent M > 6 events. From this process, we identified 14 potential earthquake swarms located sporadically in eastern Indonesia. Seismic swarm activity in eastern Indonesia provides critical insight into diverse crustal stress-release mechanisms within this complex tectonic setting. Analysis of multiple swarms across five regions—Lombok-Nusa Tenggara, Sulawesi, Molucca Sea-Halmahera, Banda-Seram, and Papua—reveals consistent patterns: swarms occur at shallow depths (<20 km), exhibit tight magnitude ranges without a dominant mainshock, and are driven by varied triggers including volcanic unrest, tectonic faulting, subduction dynamics, and fluid migration. Key controls include subductionrelated crustal stretching, strike-slip fault activation, and magmatic-fluid interactions. These swarms amplify local seismic hazards due to their shallow, prolonged nature and occurrence on previously unidentified secondary faults. The findings emphasize the necessity of continuous monitoring and refined hazard assessments to address region-specific risks associated with swarm-induced ground shaking and their potential triggering by larger tectonic events.

Soil carbon dioxide diffuse emission during a volcano-tectonic seismic Swarm at Laguna del Maule volcanic field

Abstract The Noto Peninsula, extending northward into the Sea of Japan, features a narrow, elongated shape, complex coastal topography, and numerous active faults along its coastline. Since December 2020, intense earthquake swarms accompanied by crustal deformation have occurred in the northeastern peninsula, likely caused by fluid upwelling from deep underground. The largest event, a Magnitude 7.6 earthquake, struck on January 1, 2024, with aftershock distributions indicating multiple faults ruptured over approximately 150 km. This study aimed to clarify the temporal and spatial variation in seismic wave radiation and investigate the source process of the M7.6 event using the back-projection method. This method estimates the origin of wave packets recorded by a seismic array. In Japan, seismic networks operated by local governments often include densely distributed stations to evaluate seismic intensity. We used these dense sites as a seismic array complemented by strong ground motion data from NIED K-NET and KiK-net. The analysis assumed three fault planes, based on previous studies. Velocity waveforms in two frequency bands (0.05–2.0 Hz and 0.5–5.0 Hz) were used to estimate areas of strong radiation intensity, representing the sources of seismic waves. In the low-frequency band, strong radiation intensity was observed near the rupture initiation point and in shallow regions of the northern Noto Peninsula, corresponding to large fault slips that caused the uplift of the coastline. In contrast, no strong radiation intensity was detected off the northeast coast of the Noto Peninsula in the low-frequency band, suggesting the absence of a significant slip. High-frequency analysis revealed distributions of strong radiation intensities complementary to those in the low-frequency band. A subevent occurring around 20 s after the rupture initiation was found to originate near the northern coast of the Noto Peninsula. Graphical Abstract

The article is of a review nature, where the results of deep geological and geophysical studies carried out in the south of Kamchatka and in the nearest water area of the Pacific Ocean are presented. A description of the volumetric density model and its analysis in combination with other data are given. Information on the structural position of the Tolmachоva active magmatic center (TAMC) and its origin is supplemented. As a result of the studies, a mantle protrusion was revealed, which has closed contours and was formed in the Nachikinsky zone of transverse dislocations (NZTD) no later than the Early Miocene. The sizes of the major and minor axes of the protrusion are ~ 123 and 84 km, respectively. In the lower part of the mantle protrusion, at a depth of 35–45 km, local areas of decompression are identified, which are associated with centers of melting. The formation of the ledge may be caused by the pressure of ultrabasic magma from the upper mantle and its subsequent intrusion into the lower layers of the Earth’s crust. The intrusion occurred along a weakened zone formed at the initial stage of shear dislocation that occurred in the Miocene-Pliocene time. Differentiation of magma entering the earth’s crust from melting centers, as well as heat flows from the same sources, form areas of focal melting and, as a consequence, lead to the formation of an intrusive massif of medium to medium acidic composition. Periodic movement of magma along a weakened zone in the TAMC area is accompanied by a swarm of weak earthquakes. TAMC is genetically related to the mantle ledge and is an integral part of it.Inflection zones of the subducting oceanic lithosphere are areas of accumulation of tectonic stress and its periodic unloading in the form of earthquakes. The highest density of seismic events with magnitude M ≥ 5 is observed in the seismic lineament located closest to the coastline – in the zone of maximum slab bending in the depth range of ~ 30–50 km.

The Hungarian National Seismological Network has experienced significant advancements in its monitoring capabilities due to the increasing density of seismic stations across the country, leading to improved earthquake detection and localization. This paper presents an analysis of the noise characteristics, detection capabilities, and seismic events registered by the Hungarian National Seismological Network, utilizing data from both permanent and temporary stations, including those from international projects such as AlpArray, PACASE, and AdriaArray. The noise characteristics of the network were analyzed through probabilistic power spectral densities, highlighting the diverse noise conditions across Hungary. The stations were grouped based on their installation dates and geographical locations, revealing significant differences in noise levels due to geological conditions, anthropogenic influences, and seasonal variations. Noise conditions at high frequencies, crucial for detecting low‑magnitude local earthquakes, were particularly influenced by both geological factors and human activity. The study also investigated the horizontal‑to‑vertical spectral ratios and found correlations between sediment thickness, resonance frequencies, and noise levels at different stations. The paper assesses the detection capability of the seismic network, focusing on its ability to identify earthquakes of varying magnitudes. We estimated the maximum background noise displacement, providing insights into the detection thresholds of the network. The results showed that the network is capable of detecting events as small as magnitude ML = 0.5 during the night in northern Hungary and events larger than ML = 1.25 throughout the country during all day. A case study of the Szarvas cluster in 2023, a notable seismic swarm demonstrates the network’s ability to accurately localize earthquake sequences using advanced localization algorithms. This event highlighted the enhanced seismic monitoring capability of the expanded network and its ability to capture small local seismic events that were previously undetectable. The paper concludes with an overview of ongoing research and future developments, including studies on the crust and mantle structure of the Pannonian Basin and wider region, advancements in seismic hazard mapping, and the role of the AdriaArray stations in refining earthquake localization. The continuous development of the Hungarian National Seismological Network and its integration into international cooperations are expected to further enhance high quality seismological structural research and contribute to a more detailed understanding of regional seismicity.

On 2 December 2020, an earthquake with a magnitude of Mw 4.5 occurred near the city of Thiva (Greece). The aftershock sequence, triggered by ruptures on or near the Kallithea fault, continued until January 2021. Seven months later, new seismic activity began a few kilometers west of the initial events, with the swarm displaying a general trend of spatiotemporal migration toward the east–southeast until the middle of 2022. In order to understand the physical and statistical pattern of the swarm, the seismicity was relocated using HypoDD, and the magnitude of completeness was determined using the frequency–magnitude distribution. In order to define the existence of spatiotemporal seismicity clusters in an objective way, the DBSCAN clustering algorithm was applied to the 2020–2022 Thiva earthquake sequence. The extracted clusters permit the analysis of the spatiotemporal scaling properties of the main clusters using the Non-Extensive Statistical Physics (NESP) approach, providing detailed insights into the nature of the long-term correlation of the seismic swarm. The statistical pattern observed aligns with a Q-exponential distribution, with qD values ranging from 0.7 to 0.8 and qT values from 1.44 to 1.50. Furthermore, the frequency–magnitude distributions were analyzed using the fragment–asperity model proposed within the NESP framework, providing the non-additive entropic parameter (qM). The results suggest that the statistical characteristics of earthquake clusters can be effectively interpreted using NESP, highlighting the complexity and non-additive nature of the spatiotemporal evolution of seismicity. In addition, the analysis of the properties of the seismicity clusters extracted using the DBSCAN algorithm permits the suggestion of possible physical mechanisms that drive the evolution of the two main and larger clusters. For the cluster that activated first and is located in the west–northwest part, an afterslip mechanism activated after the 2 September 2021, M 4.0 events seems to predominately control its evolution, while for the second activated cluster located in the east–southeast part, a normal diffusion mechanism is proposed to describe its migration pattern. Concluding, we can state that in the present work the application of the DBSCAN algorithm to recognize the existence of any possible spatiotemporal clustering of seismicity could be helping to provide detailed insight into the statistical and physical patterns in earthquake swarms.

SUMMARY Seismic activity induced by underground engineering projects often involves complex causal mechanisms, and represents significant hazards, including ground subsidence, disruption of surface and underground water systems, ecological damage, structural damage to buildings and even casualties. Consequently, induced seismicity has become an important topic in the risk assessment and protective measures for underground engineering projects. During the construction of the Hongtu Tunnel on the Dafenghua Expressway in Guangdong, China, a series of earthquakes occurred nearby, with the biggest of magnitude ML = 3.7, alongside significant water inflows at multiple locations. This study analysed seismic network data from 2017 to 2022 around the tunnel area to investigate the potential relationship between the seismic swarm and tunnel construction and uncover the underlying mechanisms. After velocity model corrections and double-difference relocation, the earthquakes were primarily distributed at depths of 1∼4 km. Three concealed, steeply dipping NE-trending faults, each 3∼7 km in length, were identified based on the earthquake distribution. The swarm began about one month after the onset of water inflows in the tunnel and grew significantly after the peak daily inflow, culminating in the ML 3.7 main shock. A strong spatiotemporal correlation was observed between the seismic swarm and the water inflows. During the first year of the swarm, the seismicity displayed migration characteristics consistent with pore pressure diffusion, with an initial diffusion depth of approximately 2 km and a diffusion rate of 0.0039∼0.0446 m² s−1, and best fit by the classical parabolic diffusion model (α = 0.5). After 2021, the earthquakes occurred more consistently, mainly exhibiting stress-triggering characteristics. Over time, the seismicity gradually extended to greater depths, with focal mechanisms changing from normal faulting to strike-slip faulting. The local stress field shifted from extensional to shear, which reflected the sustained influence of pore pressure diffusion on fault activation. Fluid diffusion not only initially activated the faults but also promoted repeated fault slip during the seismic swarm, indicating that prolonged water inflow significantly altered fault activity patterns and the regional stress field. This study is the first to reveal the phenomenon of long-distance induced seismicity caused by tunnel water inflow and the role of pore pressure diffusion in triggering such events, which offers new insights into the safety of underground construction and the study of fluid-related geological processes.

Abstract Taupō is an active caldera volcano lying beneath Lake Taupō in the central North Island, Aotearoa New Zealand. It last erupted 1,800 years ago, and today has background seismicity interspersed with unrest episodes, most recently in 2019 and 2022–2023. It presents challenges in monitoring due to the lake and consequent limited control on volcano‐related earthquake locations. Using national seismometer network data and 13 temporary broadband seismometers, we detected and located earthquakes near Taupō between October 2019 and September 2022. We refined the locations with relative relocation, and calculated magnitudes along with selected focal mechanisms. Seismicity beneath the northern part of the lake was related to the volcano's magmatic system: seismicity rates increased during the unrest and varied focal mechanisms demonstrate a lack of tectonic control. An arcuate shape in the seismicity at 6 km depth resulted from the interaction of the magmatic system with a caldera ring fault. The arcuate shape was visible in the background seismicity before the start of the 2022–2023 unrest episode but was particularly active during the first months of unrest, reflecting intrusive episodes into the rhyolitic magma reservoir. In contrast, earthquakes north of the lake, as well as around and beneath the southern part of the lake, demonstrated tectonic controls, with rift‐aligned focal mechanisms and seismic swarms. Improvements that could be made to routine earthquake characterization at Taupō and allow detailed interpretation of activity in near‐real‐time include: a volcano‐specific velocity model, a lower threshold to identify earthquakes, routine relative relocation, and enhanced seismic instrumentation.

Abstract Earthquake swarms and strong shocks have frequently occurred in Noto Peninsula, Japan, for decades, resulting in a seismicity pattern characterized by a mixture of background earthquakes, swarms, and foreshock/aftershock sequences. Using an improved version of the space‐time Epidemic‐Type Aftershock Sequence model, we extract statistical features of the aftershocks hidden within earthquake sequences from 2000 to 2024. The aftershock productivity density patterns in the source regions of the 2007 Mw6.7, 2023 Mw6.2, and 2024 Mw7.5 earthquakes exhibit strong spatial heterogeneity, with high productivity density values extending from surface to depths of 15 km, 15 km, and 27 km, respectively. More importantly, the model parameters which characterize productivity and decay rates of aftershocks vary significantly in both space and time, as demonstrated by the results obtained from stochastic reconstruction. Two regions, located in the southwest and northeast of the Noto Peninsula, where the 2024 Mw7.5 mainshock has ruptured and earthquake swarms constantly occur, are characterized by higher , lower , relatively low and high values. Temporal variations in the parameters indicate that these anomalies are primarily observed between 2021 and 2023 in the swarm activated region. We attribute the statistical characteristics of seismicity in these two local regions—such as a larger proportion of indirectly triggered aftershocks, a slower decay rate of aftershock numbers, and a relative higher proportion of small events—to the presence and migration of fluids in the lower crust or upper mantle beneath the Noto Peninsula.