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The Epidemic-Type Aftershock Sequence (ETAS) model is currently the most powerful statistical seismicity model that reproduces the general characteristics of earthquake clustering in space and time. However, its application can be hampered by biased parameter estimations related to earthquake catalogue deficiencies, particularly in regions where the spatial coverage of local recording networks is relatively poor. Here, we systematically investigate the possible influences of the effect introduced by data truncation through the choice of the cut-off magnitude (⁠|${{m}_{\rm cut}})$| and missing events due to heterogeneity of the seismic network on ETAS parameter estimates along the East African Rift System (EARS). After dividing the region into six source zones based on rheological and mechanical behaviours, the ETAS model is fitted to the earthquakes within each zone using the Davidon–Fletcher–Powell optimization algorithm. The fits and variations in parameter estimates are compared for each zone to the others and the seismological implications are discussed. We found that some parameters vary as a function of |${{m}_{\rm cut}}$| primarily driven by changes in catalogue size. Additionally, a systematic regional dependency of ETAS parameters is found across source zones. Furthermore, a median heat flow value for each analysed source zone in the EARS is calculated. In contrast to previous findings in other tectonic settings, the results reveal no significant correlations between the crustal heat flows and the ETAS parameters describing earthquake productivity (⁠|${{K}_0}$|⁠) and the relative efficiency of an earthquake with magnitude M to produce aftershocks (⁠|$\alpha $|⁠). Our findings have significant implications for understanding the mechanisms of earthquake interaction and, therefore, provide tight constraints on the model's parameters that may serve as a testbed for existing earthquake forecasting models in this region where the vulnerability of local buildings and structures exacerbate seismic risk. [ABSTRACT FROM AUTHOR]

We develop and apply a dynamic economic simulation model to analyze the multi-regional impacts of, and mechanisms of recovery from, a major disaster, the HayWired scenario — a hypothetical Magnitude 7.0 earthquake affecting California's San Francisco Bay Area. The model integrates loss pathways: capital stock damage, labor supply shocks due to short-term population displacement and longer-run out-migration from damaged areas, and the exacerbating effects of damage to transportation infrastructure capital, as well as various aspects of static and dynamic economic resilience. With input substitution-based static inherent resilience and dynamic resilience in the form of optimal intertemporal and spatial investment allocation, gross output losses range from 0.5 percent to 6 percent across regions, and welfare losses are 0.4 percent statewide but can be ten times as large in hardest-hit areas. Large-scale reconstruction investment is supported by substantial interregional transfers of resources through intra-state trade. Increased output via firms engaging in the key adaptive resilience tactic of production recapture can alleviate a substantial fraction of losses—but only if upstream and downstream barriers to recovery can be lowered quickly. [ABSTRACT FROM AUTHOR]

A series of undrained cyclic triaxial tests were carried out on loose sand specimens, including encased and non-encased granular columns, to evaluate the cyclic behavior and liquefaction resistance of the ground improved by granular columns. It was found that using geogrid encasements could effectively reduce cumulative settlements and mitigate the liquefaction potential when its tensile stiffness was high enough. Another finding was the inefficiency of flexible geosynthetic encasements to delay and mitigate the liquefaction in granular columns with the possibility of clogging. Findings indicated that the improvement of a loose ground with encased granular columns not only decreased the liquefaction-induced ground deformation but also significantly reduced the effect of earthquake magnitude on the ground deformation. It was also found that using the granular column and encasing it with a high-stiffness encasement not only slowed down the rate of ground softening during the cyclic loading experience but also decreased the dissipation of energy. [ABSTRACT FROM AUTHOR]

With the highly nonlinear relationship between various seismic feature indicators and earthquakes, the researchers can hardly construct an earthquake model. Meanwhile, the lack of samples for destructive earthquakes also leads to inaccurate medium-to-short-term earthquake magnitude predictions. Therefore, this study proposes a novel model for earthquake prediction, named variant detector bagging algorithm (V-detector-bagging). First, we adopt the geological distribution of earthquakes and faults as a criterion to select the appropriate history catalog data area, and the seismic indicators are calculated through the Gutenberg–Richter laws and Panakkat indicators. Then, we propose the V-detector-bagging algorithm, which combines the V-detector algorithm with the bagging method. The proposed algorithm converts the self-tolerance process into a cycle process, during this process, different selves guide samples to spread widely, generate various detectors covering more wide nonself areas, fill holes that are not covered by detectors in nonself areas, and reduce the false negative rate. Thus, the V-detector-bagging algorithm improves the detection performance of the V-detector. Finally, through experimental validation analysis, the proposed algorithm ranked first in the detection rate on Sichuan and Xinjiang catalog data compared to the popular machine learning methods used in predicting earthquakes and the original V-detector algorithm, with Xinjiang yielding the best results. [ABSTRACT FROM AUTHOR]

This research breaks new ground in earthquake prediction for Los Angeles, California, by leveraging advanced machine learning and neural network models. We meticulously constructed a comprehensive feature matrix to maximize predictive accuracy. By synthesizing existing research and integrating novel predictive features, we developed a robust subset capable of estimating the maximum potential earthquake magnitude. Our standout achievement is the creation of a feature set that, when applied with the Random Forest machine learning model, achieves a high accuracy in predicting the maximum earthquake category within the next 30 days. Among sixteen evaluated machine learning algorithms, Random Forest proved to be the most effective. Our findings underscore the transformative potential of machine learning and neural networks in enhancing earthquake prediction accuracy, offering significant advancements in seismic risk management and preparedness for Los Angeles. [ABSTRACT FROM AUTHOR]

Background: The landslide inventory of the western flank of Mount Oku, Cameroon, includes spreads or complex landslides, indicating sudden soil weakening, possibly due to seismic activity or heavy rainfall causing groundwater rise. These landslides were likely triggered between 2009 and 2018 based on the dates of the aerial imagery. Identifying triggers for past landslides remains a major unresolved issue in landslide science. However, understanding these triggers is crucial for accurately assessing future landslide hazards. Methodology: In this paper, we investigate the possibility of earthquakes to precondition landslide development or reactivation during climatic events. By assuming a magnitude 5.2 earthquake, an epicenter of 10 km from this area, and different wetness conditions, the factor of safety (FS) and Newmark displacement (ND) models were calculated for shallow and deep-seated landslides with sliding depths of 3 and 7.5 m. Afterward, the relationship between FS, assumed ND, and observed landslides was analyzed in a cluster analysis, to derive patterns of climatically and seismically triggered landslides. Results: The comparison of FS maps and FS values of the observed landslides revealed that especially for landslides at 7.5 m depth, most sites that are stable during dry conditions become instable under saturated conditions, indicating a climatic trigger. At 3 m depth, however, some landslide sites that are still marginally stable under saturated conditions, display relatively high ND values for the investigated hypothetical earthquake, indicating a possible seismic influence. In the cluster analysis, we clustered the observed landslides according to their distances to rivers and topographic ridges and obtained three clusters. Landslides from cluster 3 with 31% of the landslides display medium to high ND for the assumed earthquake, and were found near ridges and farther away from rivers, suggesting seismic triggering. Cluster 2, with 12% of landslides closer to rivers, suggested climatic origins. Thus, while climate is a critical landslide contributing factor, seismic events may also contribute, either by predisposing to landslides or by reactivating them alongside climatic factors. These results enable the establishment of more precise and effective landslide mitigating measures considering mostly rainfall but also earthquakes as possible triggers. [ABSTRACT FROM AUTHOR]

The Central and South‐Central Andes form a "two‐sided" mountain belt bounded by distinct zones of convergence in the forearc and backarc flanks. Previous geodetic interseismic deformation studies found that the forearc to backarc velocity field is better explained when elastic models allow reverse aseismic slip on the Andes eastern‐flank décollement faults. Here, we extend the earlier interpretation of interseismic motion and argue that normal aseismic creep of the Precordillera décollement is required to explain backarc Global Navigation Satellite System displacements during the co‐ and early postseismic phases of the 2015 Illapel, Chile, earthquake. This model significantly reduces the previously reported overlap between coseismic slip and afterslip on the megathrust of this earthquake, consistent with the expectation that these slip modes are spatially partitioned. These findings have direct implications for estimating recurrence interval and slip rate, and for probabilistic seismic hazard analysis on both sides of the orogen. Plain Language Summary: Between consecutive earthquakes in the Central and South‐Central Andes, during what is known as the interseismic phase, the traditional Nazca‐South America two‐plate model underpredicts the surface Global Navigation Satellite System (GNSS) velocities on the east side of the mountain belt. Previous studies show that adding an "Andean microplate," thus forming a three‐plate model, kinematically explains the observed velocity field on both sides of the Andes. We analyzed the GNSS coseismic displacements caused by the Mw 8.3 2015 Illapel, Chile, earthquake, and found that the traditional two‐plate model also underpredicts GNSS observations in the eastern side of the Andes. We show that adding the Andean microplate to the model, in the same manner as for the interseismic phase, and allowing aseismic slip on the detachment interface beneath it significantly reduces the observed surface displacements misfit. We also show that this holds for the displacements observed 50 days after the main shock, evidencing that the detachment geometry slips before, during, and after a large magnitude earthquake. Using the three‐plate model produces fault slip distributions that decrease overlap between local maxima in coseismic and aseismic slip, consistent with expectations from rate‐ and state‐dependent friction laws. Key Points: Revised co‐ and postseismic slip models account for forearc‐backarc coupling by allowing slip on the Argentine Precordillera décollementObserved continuous and survey Global Navigation Satellite System displacements on both sides of the Andes are better explained by models with a décollementAdding a décollement significantly reduces megathrust coseismic slip and afterslip overlap, compatible with rate and state friction law [ABSTRACT FROM AUTHOR]

On 8 October 2023 (UTC), unique earthquakes occurred in the Izu‐Ogasawara Arc, Japan, in which the P‐ and S‐phases were barely visible and only the T‐phases were evident, followed by tsunamis that reached islands in the Izu‐Ogasawara Arc and a wide area of the Pacific coast of southwest Japan. Our estimated T‐phase source area coincides with the Sofu Seamount, which was previously unrecognized as an active submarine volcano. A bathymetric survey of the seamount conducted 1 month after the event revealed characteristics of the seamount with a caldera and a central cone. Compared to the bathymetry in 1987, the topography in the caldera had changed significantly such as a crater forming in the central cone. This seamount is likely to be an active volcano. The topographic changes on the caldera‐sized scale that occurred at the caldera can be explained as a source of the October tsunami. Plain Language Summary: On 8 October 2023 (UTC), earthquakes were followed by tsunamis in the Izu‐Ogasawara Arc of Japan that were higher than that estimated from the magnitude of the earthquake. The tsunamis were observed on islands in the Izu‐Ogasawara Arc and a wide area of the Pacific coast of southwest Japanese islands. Strong T‐phases that are underwater acoustic waves were observed accompanying that event. We estimated that the T‐phases originated from the area around the Sofu Seamount, which has not been recognized as an active submarine volcano until now. One month after the event, we conducted a bathymetric survey of the seamount and revealed the characteristics of a caldera and a central cone within the caldera. Compared to the bathymetric data obtained in 1987, the caldera and central cone topography have changed significantly, such as a crater forming in the central cone, indicating that this seamount is likely to have been an active submarine volcano. The topographic changes that occurred at the depth of the caldera (∼1,000 m) and its scale (diameter ∼5 km) can be associated with the source of the tsunami on 8 October 2023. Key Points: A bathymetric survey of the Sofu Seamount was conducted after the unique T‐phase dominant earthquakes and tsunamis on 8 October 2023Compared to data in 1987, the caldera and central cone topography have changed, indicating that this seamount is an active submarine volcanoThe observed seafloor displacement at the caldera scale may have contributed to the source of the tsunami on 8 October 2023 [ABSTRACT FROM AUTHOR]

We develop a methodology to compile an objective tremor catalog by utilizing distinctive event features that differentiate tectonic tremors from non‐tremor events, and combining the envelope cross‐correlation method with clustering technique and neural network. This approach enables tremor extraction without subjective criteria, allowing for the detection of previously overlooked short‐duration tremors. The event features employed to distinguish tremors and non‐tremor events are depth, the mean amplitudes at high and low frequencies, the ratio of these two amplitudes, and event duration. The duration is defined as the minimum period that contains 50% of the seismic energy. The application of this method to western Japan detects 1.7 times more tremors than the previous studies, with the durations of 0.3–∼100 s. The events with short durations are considered low‐frequency earthquakes. The relationship between seismic moment and duration of the detected tremors is consistent with the scaling law of slow earthquakes. Plain Language Summary: Slow earthquakes are characterized by very slow underground deformation compared with regular (fast) earthquakes and are important for understanding the preparation period prior to large earthquakes. Tectonic tremors, which are a type of slow earthquakes, radiate tiny seismic waves with frequencies of several Hz, occur episodically and densely in space and time, and may last for long durations of up to several hundred seconds, which is much longer than the durations of fast earthquakes of equivalent magnitude. In this study, we detect and differentiate tectonic tremors from fast earthquakes and anthropogenic events. We do this using a set of event features, without relying on subjective criteria. The durations of the detected tremors range from 0.3 to ∼100 s, and they appear consistent with a previously proposed scaling relationship for slow earthquakes. This result suggests that fast earthquakes and slow earthquakes have different physical mechanisms. Key Points: We compile a more complete tectonic tremor catalog for western Japan using a clustering method based on event featuresEvent duration, newly defined using energy radiation, clearly separates tectonic tremors from fast earthquakesTectonic tremors, ranging in duration from 0.3 to 100 s, are consistent with the scaling law of slow earthquakes [ABSTRACT FROM AUTHOR]

We consider 3-component records of the magnetic field strength with a time step of 1 min at 153 stations of the INTERMAGNET network for 31 years, 1991–2021. Data analysis is based on the calculation of pairwise correlation coefficients between wavelet coefficients in successive time windows 1 day long (1440 min counts). To describe the state of the magnetic field, the maxima of the average values of all pairwise correlation coefficients between stations were chosen, calculated over all detail levels of the wavelet decomposition and over all components of the magnetic field strength vector. The daily time series of such maxima is called wavelet correlation. The division of the network stations into 7 clusters is considered, and a time series of wavelet correlations is calculated for each cluster. In a sliding time window with a length of 365 days, correlation measures of synchronization of wavelet correlations from different clusters are calculated, which are compared with the strongest earthquakes with a magnitude of at least 8.5. For the global time series of wavelet correlations, the method of influence matrices is used to study the relationship between the maximum correlation responses to a change in the length of the day and a sequence of earthquakes with a magnitude of at least 7. As a result of the analysis, precursor effects are identified, and the important role of the Maule earthquake in Chile on February 27, 2010 in the behavior of the response of magnetic field for the preparation of strong seismic events is shown. [ABSTRACT FROM AUTHOR]

This case study evaluated the liquefaction risk and application of vibro-compaction for soil improvement in a construction project site on Saadiyat Island, Abu Dhabi, UAE. Abu Dhabi is designated as Zone 0 according to the Uniform Building Code (UBC-97), and we discuss the design criteria for vibro-compaction that were adopted to mitigate the liquefaction risk, the trials conducted to establish the application criteria for vibro-compaction, and the general practices related to vibro-compaction. Specific studies conducted in Abu Dhabi Emirate indicate that the seismicity in the region is low, and the probability of liquefaction is very limited. However, during the pre-project soil investigation phase, the analysis of potential soil liquefaction indicated that certain examined areas have the potential to undergo liquefaction. The liquefaction potential was assessed based on a combination of safety factors obtained for an earthquake with a magnitude Mw = 6 and the corrected cone tip resistance (qc). The acceptability criteria for improved soil are based on cone penetration test (CPT) results. The target qc is accepted as 2.7 MPa and the treatment depth would be a minimum of − 3.5 m. A field trial was conducted to determine the optimal compaction grid spacing that meets the specified acceptance criteria and aligns with the project's design criteria. Based on the trial evaluation, a vibro-compaction grid spacing of 4 × 4 m was appropriate. Consequently, a total of 4125 points at the construction site underwent vibro-compaction. [ABSTRACT FROM AUTHOR]

This article, published in Frontiers in Earth Science, discusses the fault geometry and kinematics at the intersection of the Zemuhe, Daliangshan, and Xiaojiang Faults in China. The study aims to understand the relationships between these fault intersections and earthquake rupture behavior in the region. Through aerial photographs, field surveys, and analysis of seismic data, the researchers identified the geometric patterns and fault kinematics in the intersection area. The findings suggest that the segmented boundary between the Zemuhe Fault and the Xiaojiang Fault may prevent the propagation of large earthquake ruptures, while the lack of geometric complexity between the Daliangshan Fault and Xiaojiang Fault may hinder earthquake rupture propagation. The study emphasizes the need for different earthquake prevention and disaster reduction measures in different cities in the region. [Extracted from the article]

The East Anatolian fault in Turkey exhibits along-strike rupture segmentation, typically resulting in earthquakes with moment magnitude (Mw) up to 7.5 that are confined to individual segments. However, on 6 February 2023, a catastrophic Mw 7.8 earthquake struck near Kahramanmaraş (southeastern Turkey), defying previous expectations by rupturing multiple segments spanning over 300 km and overcoming multiple geometric complexities. We explore the mechanics of successive single- and multi-segment ruptures using numerical models of the seismic cycle calibrated to historical earthquake records and geodetic observations of the 2023 doublet. Our model successfully reproduces the observed historical rupture segmentation and the rare occurrence of multi-segment earthquakes. The segmentation pattern is influenced by variations in long-term slip rate along strike across the kinematically complex fault network between the Arabian and Anatolian plates. Our physics-based seismic cycle simulations shed light on the long-term variability of earthquake size that shapes seismic hazards. [ABSTRACT FROM AUTHOR]

The purpose of this study is to systematically investigate the segmental seismicity features of the Zhangjiakou-Bohai tectonic belt to understand the characteristics of the seismic activity in this tectonic area and identify potential sources of strong earthquake hazard. From the collected seismic data, we first determined the minimum completeness magnitude by combining qualitative and quantitative methods, such as the detection rate function, maximum curvature (MAXC) method, goodness of fit (GFT) method and magnitude-rank method. We used the stochastic declustering method based on the space-time ETAS model to obtain the background seismicity. We then implemented the accelerating moment release (AMR) model, the Ogata-Katsura 1993 (OK1993) model, the moment ratio (MR) model and the Region-Time-Length (RTL) algorithm. Finally, we analyzed the spatial migration of strong earthquakes. The completeness magnitude of the earthquake sequence does not significantly change with time, with the minimum completeness magnitude being 2.0 for the Zhangjiakou-Bohai tectonic zone. The results provided by the aforementioned seismic activity models allow us to detect some differences between sectors of the tectonic belt. The Zhangjiakou and Tangshan segments show a higher level of seismic hazard compared to the others, which have little chance of a strong earthquake occurring (weak release of seismic energy). The b value of the Zhangjiakou segment shows a stepwise downward trend, reflecting the gradual increase of stress accumulation level, and the hazard of moderate-strong earthquakes is increasing. Compared with the Tangshan and Penglai segments, the Zhangjiakou and Beijing sectors have a slightly higher MR index, which means that the rate of earthquake occurrence is increasing and thus the hazard of moderate to strong earthquakes. According to the RTL value, the deviation of seismic activity in the Zhangjiakou and Tangshan segments is relatively high, and there is a possibility of moderate to strong earthquakes in the future. Based on the results obtained from various seismicity models and the migration law of strong earthquakes, we can say that the overall seismic hazard for each sector of the Zhangjiakou-Bohai tectonic chain is low in terms of qualitative analysis. If anything, the Zhangjiakou segment, which is the section with the relatively high seismic hazard level, should require our attention in the future. [ABSTRACT FROM AUTHOR]

Detection and separation of the subtle post-seismic deformation signals associated with moderate magnitude earthquakes from interferometric synthetic aperture radar (InSAR) time-series is often challenging. Singular spectrum analysis (SSA) is a statistical non‐parametric technique used to decompose and reconstruct signals from complex time-series data. We show that the SSA analysis effectively distinguished the post-seismic signal associated with the 2019 M w 6 Mirpur earthquake from periodic and noise components. The SSA-derived post-seismic deformation signal is smoother and fits better to an exponential model with a decay time of 34 d. The post-seismic deformation is confined to the southeast of the rupture area and lasted for ∼90 d following the main shock. Inversion of the post-seismic deformation suggests an afterslip mechanism with a maximum slip of ∼0.07 m on the shallow, updip portions of the Main Himalayan Thrust. The 2019 Mirpur earthquake and afterslip together released less than 12 per cent of the accumulated strain energy since the 1555 Kashmir earthquake and implies continued seismic hazard in the future. [ABSTRACT FROM AUTHOR]

Seismic and tsunami hazard modelling and preparedness are challenged by uncertainties in the earthquake source process. Important parameters such as the recurrence interval of earthquakes of a given magnitude at a particular location, the probability of multifault rupture, earthquake clustering, rupture directivity and slip distribution are often poorly constrained. Physics-based earthquake simulators, such as RSQSim, offer a means of probing uncertainties in these parameters by generating long-term catalogues of earthquake ruptures on a system of known faults. The fault initial stress state in these simulations is typically prescribed as a single uniform value, which can promote characteristic earthquake behaviours and reduce variability in modelled events. Here, we test the role of spatial heterogeneity in the distribution of the initial stresses and frictional properties on earthquake cycle simulations. We focus on the Hikurangi–Kermadec subduction zone, which may produce M w > 9.0 earthquakes and likely poses a major hazard and risk to Aotearoa New Zealand. We explore RSQSim simulations of Hikurangi-Kermadec subduction earthquake cycles in which we vary the rate and state coefficients (a and b). The results are compared with the magnitude-frequency distribution (MFD) of the instrumental earthquake catalogue and with empirical slip scaling laws from global earthquakes. Our results suggest stress heterogeneity produces more realistic and less characteristic synthetic catalogues, making them particularly well suited for hazard and risk assessment. We further find that the initial stress effects are dominated by the initial effective normal stresses, since the normal stresses evolve more slowly than the shear stresses. A heterogeneous stress model with a constant pore-fluid pressure ratio and a constant state coefficient (b) of 0.003 produces the best fit to MFDs and empirical scaling laws, while the model with variable frictional properties produces the best fit to earthquake depth distribution and empirical scaling laws. This model is our preferred initial stress state and frictional property settings for earthquake modelling of the Hikurangi–Kermadec subduction interface. Introducing heterogeneity of other parameters within RSQSim (e.g. friction coefficient, reference slip rate, characteristic distance, initial state variable, etc.) could further improve the applicability of the synthetic earthquake catalogues to seismic hazard problems and form the focus of future research. [ABSTRACT FROM AUTHOR]

Moderate magnitude earthquakes and seismic sequences frequently develop on fault systems, but whether they are linked to future major ruptures is always ambiguous. In this study, we investigated a seismic sequence that has developed within a portion of the stretching region of the Apennines in Italy where moderate to large earthquakes are likely to occur. We captured a total of 2039 aftershocks of the 2023 September 18, M w 4.9 earthquake occurred during the first week, by using machine-learning (ML) based algorithms. Aftershocks align on two 5–7 km long parallel faults, from a length that exceeds what is expected from the main shock magnitude. The segments are ramping at about 6 km depth on closely spaced N100 striking 70 N dipping planes, at a distance of some kilometres from the main shock hypocentre. Our results indicate that even moderate magnitude events trigger seismicity on a spread set of fault segments around the main shock hypocentre, revealing processes of interaction within the crustal layer. The possibility that larger earthquakes develop during seismicity spread is favoured by pore pressure diffusion, in relation with the closeness to criticality of fault segments. Based on the very rapid activation of seismicity on the entire system and a back-front signal from the hypocentre of the main event, we infer that fluid pressure, initially high within the crustal layer, rapidly dropped after the main shock. Our study reinforces the importance of timely extracting information on fault geometry and seismicity distribution on faults. ML-based methods represent a viable tool for semi-real-time application, yielding constraints on short-time forecasts. [ABSTRACT FROM AUTHOR]

In the present study, a hypothetical earthquake of magnitude 8.5 has been simulated using the modified hybrid technique. Existing hybrid technique, as the name suggests, is the blend of two already existing simulation techniques, i.e. composite source technique and the envelope technique. In the present modified technique, site response functions and high-frequency decay parameter (kappa factor) have also been introduced in the existing hybrid technique. The waveforms have been simulated at more than 430 points using the calculated site response or transfer function estimated at 50 recording stations situated in the central seismic gap (CSG) region of Himalaya. Peak ground acceleration (PGA) and duration parameters have been estimated. Calculated PGA values helped estimating in the corresponding intensity for those PGA values at various stations. With the help of these PGA and intensity values, the scenario hazard map has been prepared for central seismic gap (CSG) region of Himalaya. It has been found that the stations situated close to rupture initiation point is ≥ 1 g. The estimated PGA values have been compared with the PGA values of other studies. The earthquake has been simulated using three different rupture points The station having highest PGA values changed with rupture initiation point. The intensity values are correlated with the damage pattern of region and therefore relatively more useful for agencies involved in the mitigation of seismic hazard of the region. Accordingly, the synthetic intensity maps have been generated in the present study by converting PGA values into MMI values using an empirical relation. The comparison with the other studies shows an agreement with the other studies. This modified technique is independent aftershocks database and velocity-Q structure. This research work will help bringing light on the effect of site response functions and kappa factor. This kind of study can help in mitigate the earthquake hazard and design an earthquake-resistant structures and building for that particular area. [ABSTRACT FROM AUTHOR]

Two massive earthquakes hit Turkey on February 6, 2023. The first occurred at around 4 a.m. local time and the other at around midday. The quakes affected almost ten cities and around thirteen million people. Unfortunately, the number of casualties increased with time. These earthquakes reminded us of the importance of the determination of the magnitude of an earthquake in a couple of minutes with as high accuracy as possible, which is vital for the people who live in the epicenter area. Governmental institutes must announce the magnitude of an earthquake quickly if it is huge to start a response action. This study shows the quality and efficiency of the technique that calculates the P-wave moment magnitude (Mwp) using local (strong-motion records), regional and teleseismic (velocity records) waveforms recorded at seismic stations located at different epicentral distances. The disadvantage of determining the time window for calculations was resolved with this study using calculated P-wave velocity and theoretically determined S-wave arrival times depending on the regional and teleseismic waveforms' onset and epicentral distance. The Mwp magnitude has been calculated as 7.9 using regional and teleseismic waveforms for events one and two, whereas 7.7 and 7.6 with strong-motion waveforms for events one and two, respectively, are compatible with Global Centroid Moment Tensor (GCMT) magnitude 7.8 and 7.7 for events one and two. The results of this study clearly show that an earthquake research institute should evaluate all the seismic waveforms recorded at different epicentral distances to get a confidential magnitude value considering destructive events, which is possible with data sharing through global networks at present. [ABSTRACT FROM AUTHOR]

In November 1815, the deadliest "natural" disaster in Balinese history was caused by the exceptional combination of multiple natural hazards that occurred simultaneously and cascaded in the present-day province of Buleleng. This major disaster, which is thought to have claimed more than 10,000 lives, has never been scientifically analyzed. The study conducts an in-depth analysis of this cascading disaster, from the root causes and chronology of natural hazards to their environmental and societal effects, by thoroughly examining all available written sources about this event, whether colonial or Indonesian. Seven months after the Tambora eruption, a magnitude 7.3 earthquake, which occurred in the Bali Sea off the northern coast of the island, triggered a very large landslide on the northern flank of the Buyan-Bratan caldera. The initial mass movement evolved into a cohesive debris flow that reached the sea after traveling up to twenty kilometers through Banyumala River Valley and Singaraja City downstream. According to historical accounts, fifteen villages were buried or devastated by the debris flow. The large volume of sediment entering the sea triggered a local tsunami along Buleleng's coast. This geohistorical approach offers a comprehensive overview of various sources describing Singaraja's situation before the crisis, the hazard succession, the cascading hazard intensities, and the short- to long-term impacts on Buleleng. Based on the written sources, Bali took around fifteen years to recover from the 1815 disasters. [ABSTRACT FROM AUTHOR]

Surface topographic irregularities can alter ground motion. In this study, we investigated the influence of various topographic factors such as relative elevation, slope angle, and curvature on ground-motion amplification. A finite element analysis with absorbing boundary layer was performed using actual topographic data and ground motion data from earthquakes of magnitude 3.8–9 recorded in Japan. To identify the effect of wave velocity on ground motion amplification, we considered the variability in topography and three sets of shear and longitudinal wave velocities by considering five cross-sectional profiles for the topographic models in the numerical analyses. We demonstrate that the topographic amplification factor, which is the ratio of the estimated spectral acceleration on the surface to the median spectral acceleration within the entire surface domain, is significantly influenced by curvature and relative elevation. Furthermore, we have proposed models that estimate ground-motion amplification using the two topographic factors—curvature and relative elevation—as variables. [ABSTRACT FROM AUTHOR]

Post-disaster recovery modelling of engineering systems has become an important facet of catastrophe risk modelling and management for natural hazards. The post-disaster recovery trajectory of a civil infrastructure system can be quantified using (a) the initial post-disaster functionality level, Qo; (b) rapidity, h (i.e., the rate of functionality restoration); and (c) recovery time, Rt. This study uses a Bayesian estimation approach to derive a set of probabilistic models to estimate Qo, Rt, and h of electric power networks (EPNs) using post-earthquake recovery data from 16 large earthquakes in Japan between 2003 and 2022. The considered predictor (explanatory) variables include earthquake magnitude, year of occurrence, seismic intensity, and exposed population (PEX). Apart from being a simple and efficient stand-alone tool, the proposed data-driven models can be a useful benchmarking tool for simulation-based approaches for EPN recovery modelling. [ABSTRACT FROM AUTHOR]

S-net is a seafloor observation network for earthquakes and tsunamis around the Japan Trench, comprising 150 observatories with seismometers and pressure gauges. The region has been known to experience massive earthquakes, and several magnitude 6 and 7 class earthquakes have occurred after the network was established in 2016. This study constructed ground motion prediction equations (GMPEs) for horizontal peak ground accelerations (PGAs) and peak ground velocities (PGVs) using the S-net data and revealed that the GMPEs can be used to predict the PGAs and PGVs at the land stations where measured S-wave velocities are available. We used a relatively short time window of the S-net records from the viewpoint of earthquake early warning but included S waves. Data from earthquakes of magnitudes between Mw 5.5 and Mw 7.4 were used. The construction of the GMPEs was achieved in two steps. First, regression analysis was conducted for each event data, and mean site residual was obtained over the available records at each S-net site. Second, the data were adjusted by the mean site residuals, and stratified regression analysis, which decouples the source and path factors, was performed. Finally, we applied the GMPEs to predict PGAs and PGVs at the KiK-net sites on land. We determined that the residuals at the KiK-net sites were systematically biased with Vs30 (average S-wave velocity in the upper 30 m). We obtained correction factors for the bias and demonstrated that the PGAs and PGVs at the KiK-net sites could be predicted reasonably well. [ABSTRACT FROM AUTHOR]

The Load/Unload Response Ratio (LURR) is a seismic prediction method based on the dynamic evolution of the stress-strain relationship of rocks. By adopting Benioff strain as the response indicator, an in-depth analysis was conducted on the LURR anomalies within 400 km of the epicenter and its surrounding areas before the Ms7.4 earthquake in Madoi, Qinghai Province, on 22 May 2021. The analysis revealed that the LURR value peaked 1 month before the earthquake and then declined within half a month, indicating that the rock medium in the seismic gestation area was approaching the end of its yielding phase. Further investigation using the Outgoing Longwave Radiation (OLR) data from the National Oceanic and Atmospheric Administration (NOAA) satellite was conducted to study the short-term and imminent anomalous evolution of ground longwave radiation values after the high values declined (from May 14 to 25). The results showed that, spatially, significant and continuous OLR anomalies were observed only in the northern area of the epicenter before the earthquake, and these anomalies exhibited a trend of expanding towards the epicenter. Temporally, the entire anomalous evolution process can be divided into six phases: initial warming, anomaly expansion, peak intensity, anomaly weakening, earthquake occurrence, and anomaly disappearance. To validate this finding, the spatiotemporal evolution characteristics of LURR and OLR within 300 km of the epicenter and its surrounding areas before the Ms6.4 earthquake in Yangbi, Yunnan Province, on 21 May 2021, were analyzed, and similar patterns were found. These results suggest that the high LURR value before its decline may mark the end of the rock medium's yielding phase, and OLR data can reflect, to some extent, the state of tectonic stress accumulation along active faults in a critical condition. A comprehensive study of the anomalous evolution characteristics of these two physical parameters before the earthquake is not only conducive to the continuity from long-term to short-term forecasts but also of great significance for more accurately assessing the trend of seismic activity. [ABSTRACT FROM AUTHOR]

Timely estimation of earthquake magnitude plays a crucial role in the early warning systems for earthquakes. Despite the inherent danger associated with earthquake energy, earthquake research necessitates extensive parameter estimation and predictive techniques to account for uncertain trends in earthquake waveforms when determining earthquake magnitudes using a single station. This study introduces an effective solution to tackle the issue through the automatic magnitude deep network (AMagDN) model. The proposed model includes long short-term memory (LSTM), a bidirectional LSTM, an autocorrelation attention mechanism, and a machine learning block that can capture detailed information from the seismic waveform recorded during an earthquake. The unique feature of this model is the use of multivariate time series waveforms derived from recorded accelerograms specifically tailored to their energy significance with magnitude and seven fusion tabular parameters involving source and geospatial features. The proposed model's training, validation and testing are done using independent 15014, 1287 and 3448 records maintained by the Kyoshin network, Japan, for moderate to great impact earthquakes between 5.5 and 8.0 ( M JMA ). A comparative study shows that the proposed model outperforms recent state-of-the-art models and common linear relations, reducing mean absolute prediction error by 40% from the second-best model. The multi-stations data are also used for successfully forecasting the magnitudes of two significant earthquakes of 7.7 and 7.3 magnitude ( M JMA ) using the proposed model. The reliable prediction capabilities of the proposed model for both single and multi-station data clearly demonstrate its utility in reducing earthquake hazards. [ABSTRACT FROM AUTHOR]

The presence of "ill-posed samples" specifically in low-volume datasets leads to accuracy decrement in the learning procedure and the generalization of neural networks. Such samples can be caused by various reasons such as noise contamination, corrupted sensors, or even, the complex distribution of physical properties governing the problem. The peak ground acceleration (PGA) datasets are definitely among the last mentioned. Focusing on speed and accuracy, a method for calculating earthquake magnitude based on the PGA data recorded at a single station along with hypocentral information has been presented in this research. Here, after training a deep neural network, the regression errors of the training data samples are clustered into two groups, namely well and ill posed using the grey wolf optimization algorithm. Instead of being removed, the data samples with low learning rates are then modified using samples selected from the other cluster in a fusional form. Then, two separate models are used and trained independently for the clusters. Next, in addition to the routine procedure of network generalization, every new sample is first checked whether is more likely to belong to which group of the clustered data, and after processing, the corresponding trained model is used. The results of the experiments show that using the proposed method results in magnitude calculation with an error order of less than 0.212 units of moment magnitude with a probability of more than 99.7%, which is superior to the conventional methods some of which were reviewed in this research. [ABSTRACT FROM AUTHOR]

Hydrological changes in groundwater coupled with earthquakes had been documented in previous studies by global researchers. Although few reports investigate multiple geochemical parameters that respond to earthquakes, trace elements received less attention, whereas they were suggested to be more sensitive to small earthquakes than the commonly used geochemical parameters. Beijing is located in the Zhangjiakou-Bohai(Zhang-Bo) seismic belt of North China, and although the occurrence of small earthquakes is frequent, the great historic earthquake in the Sanhe-Pinggu area M8 in 1679 in the adjoining southeast of Beijing gained widespread public attention. To find effective precursors that are significant for operational earthquake forecasting of the Beijing area, we carried out a one year test research project through weekly collection of groundwater samples during June 2021 to June 2022 from the seismic monitoring well of Wuliying in northwest Beijing. The 41 trace elements chemical compositions were analyzed for each sample. During the project ongoing period, the biggest earthquake with a magnitude of ML3.3 occurred in the Chaoyang District of Beijing on 3 February 2022. The content changes in these trace elements were systematically monitored before and after the earthquake. Through retrospective research, it was found that a few sensitive trace elements were anomalous to be coupled to the earthquake, including Li,Sc, Rb, Mo, Cs, Ba, W, U, Sr, Mn, Ni,andZn. In addition to trace elements, we examined stable isotopes of hydrogen and oxygen and the existing hydrological data on groundwater level, temperature, major ions, and gases to assess the validity of geochemistry as a monitoring and predictive tool. We only found that F(fluorine) ions and He (helium) gas had apparent shifts related to the earthquakes, while no shifts in the groundwater level were observed. Such characteristics of multiple geochemical parameters indicate that trace elements are likely to be more sensitive to crustalstrain than the groundwater level and major ions. We assumed a most likely mechanism of the combination of mixing and water-rock interactions to explain the phenomenon. The probable scenario was that minor stresses caused by the earthquakes might create microcracks in bedrocks, thereby leading to a small volume of chemically distinct water mixing with the original water of the aquifer, and finally, the earthquakeinduced rock fractures enhance the water-rock interactions, resulting in the post-seismic recovery of trace elements and δ180 value migration to the GWML. More testing works to find other sensitive sites to investigate multiple geochemical characteristics aiming at long-term to short-term earthquake prediction in the Beijing area and Zhang-Bo seismic belt are in progress. [ABSTRACT FROM AUTHOR]

Predicting ionospheric Total Electron Content (TEC) variations associated with seismic activity is crucial for mitigating potential disruptions in communication networks, particularly during earthquakes. This research investigates applying two modelling techniques, Autoregressive Moving Average (ARMA) and Cokriging (CoK) based models to forecast ionospheric TEC changes linked to seismic events in Indonesia. The study focuses on two significant earthquakes: the December 2004 Sumatra earthquake and the August 2012 Sulawesi earthquake. GPS TEC data from a BAKO station near Indonesia and solar and geomagnetic data were utilized to assess the causes of TEC variations. The December 2004 Sumatra earthquake, registering a magnitude of 9.1-9.3, exhibited notable TEC variations 5 days before the event. Analysis revealed that the TEC variations were weakly linked to solar and geomagnetic activities. Both ARMA and CoK models were employed to predict TEC variations during the Earthquakes. The ARMA model demonstrated a maximum TEC prediction of 50.92 TECU and a Root Mean Square Error (RMSE) value of 6.15, while the CoK model predicted a maximum TEC of 50.68 TECU with an RMSE value of 6.14. The August 2012 Sulawesi earthquake having a magnitude of 6.6, revealed TEC anomalies 6 days before the event. For both the Sumatra and Sulawesi earthquakes, the GPS TEC variations showed weak associations with solar and geomagnetic activities but stronger correlations with the earthquake-induced electric field for the considered two stations. The ARMA model predicted a maximum TEC of 54.43 TECU with an RMSE of 3.05, while the CoK model predicted a maximum TEC of 52.90 TECU with an RMSE of 7.35. Evaluation metrics including RMSE, Mean Absolute Deviation (MAD), Relative Error, and Normalized RMSE (NRMSE) were employed to assess the accuracy and reliability of the prediction models. The results indicated that while both models captured the general trend in TEC variations, nuances emerged in their responses to seismic events. The ARMA model demonstrated heightened sensitivity to seismic disturbances, particularly evident on the day of the earthquake, whereas the CoK model exhibited more consistent performance across preand postearthquake periods. [ABSTRACT FROM AUTHOR]

We compare Fourier Amplitude Spectra of Fault Normal (FN) and Fault Parallel (FP) seismograms at near‐fault sites for seven strike‐slip earthquakes with moment magnitudes Mw ≥ 6. For all events we find large FN/FP ratios at low frequencies consistent with near‐fault S‐wave radiation patterns for strike‐slip earthquakes. However, the difference diminishes with increasing frequency and FN/FP is about 1 above a transition frequency. The results may reflect small tensile/isotropic components in the earthquake rupture zones that homogenize the high‐frequency radiation in different directions at near‐fault sites. The FN/FP ratios at low frequencies and transition frequencies above which FN ∼ FP vary among the analyzed earthquakes and have no clear correlation with the magnitudes. The lack of correlation may signify a characteristic scale (e.g., process zone size, duration of source time function) controlling the isotropic radiation, and/or wave propagation and other effects that mask the source effects. Plain Language Summary: Earthquake source processes have significant impacts on many topics including generation of frictional heat on the fault and seismic ground motion away from the fault. The classical model with pure shear motion predicts that strike‐slip earthquakes should produce considerably larger fault‐normal motion close to the fault than fault‐parallel motion. Analyzing near‐fault seismic waveforms generated by seven moderate to large earthquakes, we find that larger fault‐normal motion is observed only for relatively low frequencies, and that above a transition frequency the fault‐normal and fault‐parallel motions are very similar. The observations may reflect local dilatational processes in the earthquake rupture zones that modify the directional dependence of the high‐frequency seismic radiation. The transition frequencies do not show clear scaling with the size of earthquakes, which suggests a process with a characteristic length and/or time scale, or a mixture of multiple effects. The results highlight the need to further improve our understanding of earthquake source processes with detailed near‐fault data. Key Points: Near‐fault seismograms of Mw ≥ 6 strike‐slip events show significantly larger fault‐normal than fault‐parallel motion at low frequenciesThe near‐fault seismic motions have similar amplitudes in different directions above certain transition frequenciesThe isotropic high‐frequency radiation suggests that local dilatational processes accompany the overall shear motion in the rupture zones [ABSTRACT FROM AUTHOR]

Earthquake magnitude prediction is an exceptionally challenging task that has been explored through various machine learning approaches. However, the development of prediction models is hindered by redundant features and time series properties. The Elite Genetic Algorithm (EGA) excels in searching for optimal feature subsets; while, Long Short-Term Memory (LSTM) is specialized in processing time series and complex data. Hence, we introduce an EGA feature selection and LSTM model (EGA-LSTM) for time series earthquake prediction. Initially, acoustic and electromagnetic data from our developed AETA system are fused and preprocessed using a roulette-based EGA to search strong correlation indicators. Subsequently, LSTM is employed to perform magnitude prediction with the selected features. Specially, the Root Mean Square Error (RMSE) of LSTM and the ratio of selected features are chosen as fitness components of EGA. Finally, we evaluate the proposed EGA-LSTM on AETA data from four regions from China, considering the influence of data in different time periods (timePeriod) and fitness function weights ( ω a and ω F ) on prediction results. Furthermore, our proposed approach outperforms state-of-the-art methods in evaluation metrics such as EV, MAE, MSE, RMSE, and R2. Nonparametric tests reveal that EGA-LSTM is significantly different from others and outperforms the standard LSTM. [ABSTRACT FROM AUTHOR]

On 26th May 2021, an earthquake with a moment magnitude Mw 5.1 hit the densely populated cities of Gisenyi (Rwanda) and Goma (D.R. Congo) which sit on the active East African Rift System. It was one of the largest earthquakes associated with the 2021 Mount Nyiragongo eruption. Although of moderate magnitude, the earthquake substantially damaged manmade structures. This paper presents field observations on the geotechnical impact, building damage, and factors contributing to the heightened destruction caused by this moderate earthquake. The damage pattern observed in the field indicates that masonry structures with inadequate seismic detailing were the most damaged buildings. In addition, the statistical analysis of the damaged buildings indicates most of the damaged structures were located in plains covered by volcanic soil. The intensity of the waves was estimated using the building damage data based on the European Macroseismic Scale (EMS-98). An intensity distribution map was generated for the surveyed area, suggesting EMS-98 intensity of VIII or IX along the eastern basin boundary fault and VII around the cities of Goma and Gisenyi where the land is composed of black cotton soil of volcanic origin. The higher intensity values along the eastern basin-bounding fault indicate that a reevaluation of the seismic hazard for the region is necessary. Since this is the first-ever such damage survey for the region, the developed intensity map can be used to understand the correlation between the intensity of the ground motion and damage severity which contributed to the seismic hazard assessment of the study area. [ABSTRACT FROM AUTHOR]

The Shanxi Graben is a transitional zone between the Ordos Block and North China Plain with complex structures and frequent earthquakes. Six earthquakes with M ≥ 7.0 have been recorded in the area, including the 1303 Hongtong M 8 and 1695 Linfen M 7.8 earthquakes in the Linfen Basin. Research on these two large earthquakes, closely related in time and space, is lacking. Our objective was to use deep seismic reflection profiles and 3D velocity structure data from previous research, along with seismological observation results, to interpret the geological structure near the source of the two earthquakes. A 3D geometric model of the seismogenic fault was constructed, and the relationships among the deep and shallow structures, deep seismogenic environment, and two large earthquakes were explored. Differences in seismogenic environment between the southern and northern Linfen Basin were identified. The distribution of small earthquakes in the southern Linfen Basin was scattered, and the overall distribution was at depths <25 km. The small earthquakes in the northern part of the basin were dense and concentrated at depths of 25–35 km. Low-velocity layers at an approximate depth of 15–20 km in the southern basin led to differences in seismogenesis between the two regions. Based on the area of the 3D geometric model of the Huoshan Fault, the maximum magnitude of an earthquake caused by fault rupture is Mw 7.7, so the magnitude of the 1303 Hongtong earthquake might be overestimated. Numerical simulation results of Coulomb stress showed that the 1303 Hongtong earthquake had a stress-loading effect on the 1695 Linfen earthquake. The change in Coulomb rupture stress was 1.008–2.543 bar, which is higher than the generally considered earthquake trigger threshold (0.1 bar). We created a new 3D source model of large earthquakes in the Linfen Basin, Shanxi Province, providing a reference and typical cases for risk assessment of large earthquakes in different regions of the Shanxi Graben. [ABSTRACT FROM AUTHOR]

This study was conducted as a qualitative inquiry to deeply explore the thoughts and experiences of nursing students involved in support activities in disaster areas. It was conducted as a qualitative study. Data for the study were collected through face‐to‐face interviews or video conferencing using a Personal Information Form and a Semi‐Structured Interview Form created by the researcher. Data analysis was conducted using the MAXQDA software.The population of this qualitative study consisted of nursing students actively involved in support activities in 11 provinces affected by the magnitude of 7.7 earthquake centered in Kahramanmaraş/Turkey. The sample of the study comprised nursing students who responded to our call shared with nursing student groups and met the inclusion criteria.Through qualitative analysis, three themes were identified: initial emotions experienced during the earthquake, difficulties faced during the earthquake process, and emotions following the earthquake experience.Students participating in support activities in the earthquake‐affected region provided explanations regarding their emotions, encountered ethical dilemmas, infrastructure issues, as well as deficiencies in organization and education. [ABSTRACT FROM AUTHOR]

Kosovo is distinguished by a particularly high degree of seismic activity as a result of its location in the alpine-Mediterranean seismic area. The thickness of the seismic zone in the Earth's crust is a crucial element in seismotectonics, as it affects the design of fault systems, relative fault activity, earthquake size and distribution within a fault system, and the long-term accumulation of tectonic deformation. Kosovo's large depressions and high relief make it challenging geomorphologically. The country of Kosovo is divided into numerous chunks along the fault lines because of the inclinations of these prevalent motions. Normal faults, along which differentiations on the order of 2000 m occurred during the neotectonics period, identify the contacts between these blocks. Understanding Kosovo's seismotectonic characteristics requires an exact analysis of hypocenter parameters when historical earthquakes that have struck the country are reassessed for magnitude. This study deals with the seismicity and tectonics of the territorial space of the Republic of Kosovo. [ABSTRACT FROM AUTHOR]

In this paper, a point cloud extraction method based on the template grid was proposed for deformation analysis. Firstly, coordinate alignment was carried out by a coarse-to-fine strategy to ensure that the point clouds are in a unified coordinate system. Then, the points in the grid are subsequently converted into a universal grid system and the center according to the grid border is carried out to serve as the feature points for deflection detection. The deformation was determined by analyzing the deviation under different working conditions, and the maximum deformation under different earthquake magnitudes was verified in the experiment. [ABSTRACT FROM AUTHOR]

Objectives: Infrequent strong earthquakes which occur on subduction and intraplate faults worldwide can be extremely destructive. The exploration on the reliability and timeliness of high-rate global navigation satellite system(GNSS) continuous stations can help rapid inversion of slip distribution and rapid estimation of earthquake magnitude. Especially for the Anninghe fault with high potential for strong earthquakes, this research has important practical significance for early warning of strong earthquakes in this region. Methods: We adopt a kinematic simulation method to synthesize stochastic rupture scenarios by incorporating the geodetic fault coupling model as prior constraints. For the Anninghe fault, we synthesize 1 100 earthquake events from Mw 6.5 to 7.5 and rupture scenarios, and simulate displacement waveforms by using random noise signals from the existing and newly built GNSS stations. These waveforms are analyzed the reliability of fault slip distribution along the Anninghe fault in combination with the steepest descent method. Results: For these events along the Anninghe fault, the initial inversion magnitude of Mw 6.2 can be determined in about 8 s after the earthquake using the existing GNSS continuous stations. And the magnitude and slip distributions can be obtained within a short time or before the rupture completes. The GNSS continuous stations of the China earthquake science experimental field, which is about to be built, can not only effectively obtain the magnitudes and slip distributions, but also determine the dominant directions of fault rupture. Conclusions: The feasibility and usefulness of the high-rate GNSS data are confirmed in magnitude estimation and finite-fault slip inversion of strong earthquakes along the Anninghe fault. It can provide theoretical basis and technical support for earthquake early warning in this region. [ABSTRACT FROM AUTHOR]

After impounding the Baihetan Water Reservoir in a historically seismically active area, numerous earthquakes occurred, but it is uncertain if they are connected to the impoundment. Based on the dense seismic network, this study used local earthquake tomography to construct high‐resolution VP (P‐wave velocity) and VP/VS models (P‐ to S‐wave velocity ratio) and update earthquake locations after the impoundment of Baihetan reservoir. Our study revealed that the reservoir water spreads from the dam site to the Qiaojia Basin and the Heishuihe branch, and pore pressure diffusion along faults induces many earthquakes. Reservoir water migrates through hidden faults and fractures beneath Hulukou, spreading to both sides and saturating some rocks below 7 km beneath the dam site‐Lianhuatang section, causing multiple magnitude 3.5+ earthquakes. This study reveals that reservoir water migration drives earthquakes in the reservoir area, offering new insights into seismogenesis following the Baihetan reservoir's impoundment, potentially applicable to understanding reservoir‐induced earthquakes in other reservoirs. Plain Language Summary: Numerous earthquakes occurred after the Baihetan reservoir impoundment. It is worth considering whether the significant seismicity was caused by fluid injection. We used the local earthquake tomography to construct high‐precision earthquake locations and high‐resolution 3D VP and VP/VS models of Baihetan reservoir after the impoundment. The 3D VP and VP/VS models reveal the penetration and diffusion range of reservoir water. The relationship between seismic locations and velocity models reveals that microearthquakes are induced by pore pressure diffusion caused by fluid migration, and some of the water‐saturated areas induced bigger earthquakes. Key Points: The highest resolution 3D VP and VP/VS models of the Baihetan reservoir are obtained by using a dense seismic arrayThe relationship between the change of medium structure and seismicity caused by the impoundment of Baihetan reservoir is revealedA new understanding of the seismogenesis of a large number of earthquakes occurred after the Baihetan reservoir impoundment are obtained [ABSTRACT FROM AUTHOR]

The rapid and accurate prediction of earthquake Strong-Shaking Zone (SSZ) is crucial for issuing precise early warnings to regions at high risk of strong ground shaking. Generally, the SSZ is derived from the real-time spatial distribution of observed ground motions. However, during the initial stages of large earthquakes, the SSZ is often underestimated and provide alerts without enough lead-time (the time interval between the alert declaration and the S-wave arrival to the target area). In this study, we propose an innovative approach termed Near-epicenter-based Partial Matching Crossover. Leveraging the characteristic that reliable magnitude estimates for large earthquakes are available earlier than accurate predictions of the peak ground velocity (PGV) distribution, this approach utilizes near-epicenter station data to rapidly estimate the SSZ. It achieves this by matching a segment of the fault, defined by a predetermined length, with the predicted PGV map within a 120 km radius centered at the epicenter. Application of our method to strong motion data from China, Japan and Turkey demonstrates its efficacy in quickly anticipating the post-earthquake intensity distributions for large earthquakes. Specifically, it offers a lead time of 5 s or more for 51.5% (39,354 km2), 43.3% (5772 km2), 31%(47,107 km2) and 75.3% (81,966 km2) of the IMM = V region during the M 8 Wenchuan earthquake, the M 7.3 Kumamoto earthquake, the M 7.8 Syria earthquake and M 7.6 Turkey earthquake, respectively. The presented approach introduces a novel methodology to extend the lead time for earthquake early warnings. [ABSTRACT FROM AUTHOR]

Together with axial and flexural actions, modern-designed reinforced-concrete walls can also be subjected to torsion during rare loading events, such as large-magnitude earthquakes or strong winds. For certain widely used nonplanar open cross-section geometries, this torque is resisted primarily through warping. In some cases, the longitudinal stresses caused by torsional warping can be of the same order of magnitude as those caused by flexure, which postulates a reduction of the in-plane bending moment capacity of the section. This study explores the reduction of bending moment capacity of open reinforced-concrete U-shaped core walls due to the simultaneous application of flexural, axial, and torsional loading. Initial investigations focused on strain gradients through the wall segments of reinforced-concrete U-shaped walls. Using a refined data set from a recent experimental campaign, the commonly assumed linear strain gradient used in the design of reinforced-concrete walls is challenged. Numerical methods that intrinsically rely on the observed strain gradients are then employed to compute, for a range of torque-to-bending-moment ratios, the ultimate bending moment and torque capacities from combined loading scenarios. The numerical results corroborate existing experimental results, indicating a significant reduction (almost half) in ultimate bending moment capacity when a torque equal to approximately 20% of imposed bending is applied. Interaction diagrams between the ultimate torque and bending moment show that it is possible to derive a simple relationship between the two for the purposes of structural design. These results can help formulate guidelines for future international building codes, which in their current form cannot account for the design of open sections governed by warping torsion. [ABSTRACT FROM AUTHOR]

The occurrence of earthquakes is not random, as confirmed by tectonic and geodynamic studies. However, their trigger mechanism, especially for tectonic earthquakes, involves many variables, including, among others, the influence of the Sun. This study presents the collection and discussion of data from 2012 to 2023, which compares solar activity with the occurrence of potentially destructive earthquakes, of magnitude equal to or greater than M6, considered on a global scale. The most significant clue from the study is constituted by the flow of solar protons which, corresponding to significant increases, show a potential relationship between potentially destructive geophysical events. The spatio-temporal analysis of proton increases, based on the discussion of 1567 events, has shown to have a close relationship with seismic events, especially for those of magnitude M6+. [ABSTRACT FROM AUTHOR]

In December 2023, a 6.2 magnitude earthquake struck Jishishan, Gansu Province. This study utilized the Real‐time Earthquake Damage Assessment using City‐scale Time‐history analysis (RED‐ACT) system to analyze the seismic damage caused by the event. The analysis included assessments of strong ground motion records, building damage, and human acceleration feeling. The results indicate the following: (1) The earthquake‐induced significant ground motion. The response spectrum at the 0–1.3 s period range is far above the 7° design‐based and maximum considered earthquake levels, and it also far exceeds the 9° maximum considered earthquake level. How to provide a more scientific and reasonable seismic design standard to ensure the anti‐collapse performance of buildings still requires further in‐depth research. (2) The RED‐ACT analysis results indicate that the destructive power of this earthquake was significant. The strong ground motions recorded near the epicenter could cause a certain number of buildings to collapse, with the collapsed buildings mainly being raw‐earth/wood structures and unreinforced masonry structures. The main damage states of buildings assessed correspond generally with the actual earthquake damage survey results. (3) The RED‐ACT system can provide assessment results of human feeling of acceleration at different locations, and the assessment results take into account the amplification effect of acceleration by different floors, which can provide a reference for post‐earthquake science popularization and for reducing post‐earthquake panic among the population. [ABSTRACT FROM AUTHOR]

Between September 17 and 18, 2022, a series of earthquakes struck the southern Longitudinal Valley of Taiwan, causing severe damage to infrastructure, particularly bridges, railroads, buildings, and highways in Taitung and Hualien. The primary event in this sequence was the Chihshang earthquake, measuring magnitude of M L 6.9, preceded by a significant foreshock of M L 6.4 the day before. Notably, the highest intensity reported in the epicentral region during this earthquake sequence reached 6 + , marking the highest intensity ever recorded since the Central Weather Bureau (CWB) revised its seismic intensity scale. In this study, we examined the strong ground motion data recorded by the low-cost P-alert network to investigate the cause of structural damage to buildings, railway stations, schools, and other structures in the affected area. Our analysis encompassed data from a total of 17 monitoring stations. The observed peak ground acceleration (PGA) ranges from 0.06 g and 0.78 g, the peak spectral acceleration or response spectrum (PSA) spanned from 0.20 g at 0.50 s to 3.87 g at 0.41 s, and site amplification varied from 4 at 0.6 Hz to 12.6 at 5.2 Hz. The reported damage of single storey house at Taitung City is correlated with the higher amplification 4.5 at 0.14 s; Bridge and factory at Chihshang Township is correlated with the higher amplification 5 at 0.17 s; Railway station at Zhuoxi Township with the higher amplification 7.5 at 0.3 s; of three storey building at Yuli Township with amplification 8 at 0.26 s and, also higher PSA 2.83 g at 0.29 s, and several schools at Kaoshiung City with amplification 7.2 at 0.37 s and with high PSA 3.87 g at 0.41 s. Additionally, we studied the static Coulomb stress changes resulting from the coseismic slip of the main shock, which contributed to an increase in aftershock occurrences. The occurrence of a high-intensity earthquake ( M L 6.9) on September 18, 2022, within a region of positive Coulomb stress changes, provides support for the hypothesis of aftershock triggering. Through analysis, we found that stronger foreshock ( M L 6.4) occurred in the rupture area of mainshock foreshock, positioned adjacent to the main fault. [ABSTRACT FROM AUTHOR]

Nepal, identified as one of the world's most disaster-prone areas, has a history of frequent earthquakes. Despite its seismic activity and vulnerability to liquefaction, the Terai region lacks comprehensive studies on site characterization and liquefaction potential. This research focuses on evaluating the liquefaction potential of the Terai region's soil, crucial due to its high population density and the imperative to ensure the safety of engineering structures. In this study, in-situ parameters are utilized to assess the subsurface geology's liquefaction potential, encompassing soil characterization, soil liquefaction factor of safety (FS), and liquefaction potential index (LPI). Data from 284 boreholes, collected at 97 locations within the study area up to a depth of 20 m, offer insights into the Terai region's seismic vulnerability. Considering an earthquake scenario with a magnitude (Mw) of 7.8, liquefaction resistance was assessed at each location using peak ground acceleration (PGA) varying from 0.3 to 0.4 g as specified in NBC 105 (2020) for each district. The results indicate the LPI range of 0–57.85, with 34.02% of the Terai region classified as very high risk, 15.46% as high risk, 23.72% as low risk, and 26.80% as very low risk or liquefaction hazard. A hazard map is generated based on liquefaction potential, offering valuable insights for planning, management, and long-term development in the studied locations. This research addresses the crucial knowledge gap in understanding the seismic vulnerability of the Terai region, providing a basis for informed decision-making and risk mitigation strategies. [ABSTRACT FROM AUTHOR]

Documenting the magnitude of finite strain within ductile shear zones is critical for understanding lithospheric deformation. However, pervasive recrystallization within shear zones often destroys the deformed markers from which strain can be measured. Intensity parameters calculated from quartz crystallographic preferred orientation (CPO) distributions have been interpreted as proxies for the relative strain magnitude within shear zones, but thus far have not been calibrated to absolute strain magnitude. Here, we present equations that quantify the relationship between CPO intensity parameters (cylindricity and density norm) and finite strain magnitude, which we calculate by integrating quartz CPO analyses (n = 87) with strain ellipsoids from stretched detrital quartz clasts (n = 49) and macro‐scale ductile thinning measurements (n = 7) from the footwall of the Northern Snake Range décollement (NSRD) in Nevada. The NSRD footwall exhibits a strain gradient, with Rs(XZ) values increasing from 5.4 ± 1.4 to 282 ± 122 eastward across the range. Cylindricity increases from 0.52 to 0.83 as Rs increases from 5.4 to 23.5, and increases gradually to 0.92 at Rs values between 160 and 404. Density norm increases from 1.68 to 2.97 as Rs increases from 5.4 to 23.5, but stays approximately constant until Rs values between 160 and 404. We present equations that express average finite strain as a function of average cylindricity and density norm, which provide a broadly applicable tool for estimating the first‐order finite strain magnitude within any shear zone from which quartz CPO intensity can be measured. To demonstrate their utility, we apply our equations to published data from Himalayan shear zones and a Cordilleran core complex. Key Point: Quantifying the relationship between crystallographic preferred orientation distribution intensity parameters and finite strain magnitude [ABSTRACT FROM AUTHOR]

As electric vehicle (EV) adoption increases, transportation services will shift dependence from liquid fuel infrastructure to electric power infrastructure. Since transportation plays a major role in disaster response and recovery, this shift in dependence has important implications for coupling electrical grids and transport resilience. The implications for the electrical grid for southwestern British Columbia, Canada are examined, motivated by this region's high EV adoption rate and the potential for a catastrophic magnitude 9.5 earthquake. A comparison of the resilience of the electrical infrastructure compared to the fuel infrastructure is provided and approaches for increasing resilience in the region for EV power supply are discussed. This paper compiles lessons learned from past large earthquakes in Chile, Japan, and New Zealand with consideration given to successes and failures. While this paper was written with a focus on southwestern British Columbia, many of the suggestions for increasing power system resilience could be applied in other seismically active locations during the transition to EVs. This paper also considers integrated disaster resilience planning for the changing transport landscape from fuel vehicles to EVs. [ABSTRACT FROM AUTHOR]

For the last few decades, for the liquefaction susceptibility assessment of a location, Standard Penetration Test (SPT) based methods have been generally practiced. In this research, the liquefaction potential of Dhaka Metropolitan Development Plan (DMDP) area has been analyzed using three existing Cone Penetration Test (CPT) based methods. CPT (CPTu and SCPT) data have been collected from 546 locations of the DMDP region covering 1530 square kilometer area and have been analyzed to assess the liquefaction potential. Bangladesh is located in the junction of Indian and Eurasian plate, which makes this country vulnerable to earthquakes. A magnitude 7.5 earthquakes and Peak Ground Acceleration (PGA) value of 0.21 g at the surface have been used to evaluate the liquefaction susceptibility of the region using the three CPT-based techniques and another CPT-based technique has been employed to evaluate the liquefaction susceptibility of the region using variable surface PGA based on Modhupur scenario. Liquefaction potential maps have been proposed and compared for these four methods. It has been found that more than 60% of the study area falls within the LPI range which indicates moderate to relatively high liquefaction vulnerability. The liquefaction susceptibility of the three methods has been found to be in agreement and possible reasons of deviation in any particular method have been explained. Also, Ishihara 1985 proposed LPIISH has been estimated and compared with Iwasaki's LPI values. It has been observed that the difference in results using LPI and LPIISH are not significant. The seismic microzonation and liquefaction analyses will help engineers, planners and relevant professionals to get prior idea about the seismic vulnerability of any part of the DMDP region and take measures beforehand to avoid any damaging consequences. [ABSTRACT FROM AUTHOR]