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China, a mountainous country with developed seismic fault zones, frequently experiences landslides triggered by earthquakes, so it is crucial adjective to explore the movement characteristics of landslides caused by earthquake. Utilizing the Daguangbao landslide as a case study, this paper analyzes movement characteristics of landslide under earthquake magnitude and duration time by means of numerical simulation and control variable methods. Firstly, the original topographic conditions and earthquake magnitude of Daguangbao landslide are restored, and its displacement movement characteristics is studied. Secondly, the landslide movement characteristics under different earthquake magnitudes (VI, VIII, VIII, IX) and duration time (10 s, 20 s, 30 s, 40 s, 50 s, 60 s) are obtained through 27 displacement monitoring points on three sections. Finally, the displacement–time formulas of Daguangbao landslide with different earthquake magnitudes are obtained by linear and nonlinear fitting. The research results show that: (i) The formation process of Daguangbao landslide can be summarized into the following four stages: Stage of earthquake wave shatters slope body; Stage of the formation of main sliding surface; Stage of the sliding of main sliding body; Stage of the sliding accumulation. (ii) In the case of earthquake magnitudes VI, VII and VIII, the landslide displacement increases linearly with the earthquake duration time. (iii) In the case of earthquake IX, the landslide displacement increases first and then decreases with the increase of earthquake duration time. The research reveals the mechanical mechanism of landslide under earthquake action, which provides reference and guidance for the study of the motion characteristics of earthquake landslides, and provides a basis for landslide control and disaster prevention and reduction. [ABSTRACT FROM AUTHOR]

Seismic hazard maps have been developed for the Faizabad region of Uttar Pradesh state of India, utilizing deterministic and probabilistic methodologies. Maximum earthquake magnitudes were meticulously determined for each seismic source within a 500 km radius, considering region-specific seismotectonic parameters and rupture characteristics. Twenty-seven ground motion prediction equations were considered for the studied regions, and through an efficacy test, ground motion prediction equations (GMPEs) were selected for segmented hypocentral distances. The final hazard values were computed by applying varied weighting factors to the chosen GMPEs. The peak ground acceleration (PGA) and spectral acceleration (SA) were computed for 2 and 10% probabilities of exceedance in 50 years. The PGA values for the region were found to range between 0.01 and 0.14 g, as obtained from the deterministic analyses. It was inferred from the PSHA that the PGA values range between 0.05 to 0.20 g and 0.01 to 0.12 g for the 2 and 10% probability of exceedance, respectively, for 50 years. Blocks situated in the southeastern part of the city, encompassing Gonda, Faizabad Sultanpur, and Pratapgarh, have been singled out as particularly vulnerable to seismic hazards, thus warranting heightened attention and strategic planning in urban and infrastructure development. [ABSTRACT FROM AUTHOR]

This study focuses on postdisaster damage assessment operations supported by a set of drones. We propose a multistage framework, consisting of two phases applied iteratively to rapidly gather damage information within an assessment period. In the initial phase, the problem involves determining areas to be scanned by each drone and the optimal sequence for visiting these selected areas. We have adapted an electric vehicle routing formulation and devised a variable neighborhood descent heuristic for this phase. In the second phase, information collected from the scanned areas is employed to predict the damage status of the unscanned areas. We have introduced a novel, fast, and easily implementable imputation policy for this purpose. To evaluate the performance of our approach in real‐life disasters, we develop a case study for the expected 7.5 magnitude earthquake in Istanbul, Turkey. Our numerical study demonstrates a significant improvement in response time and priority‐based metrics. [ABSTRACT FROM AUTHOR]

Fault displacement hazard, along with ground shaking hazard and earthquake-induced geohazard, are the primary forms of disaster in major earthquakes. Buildings located on areas of strong seismic surface displacement are likely to be damaged if anti-displacement design is not carried out. Therefore, a reasonable and targeted active fault classification scheme is helpful for avoidance and anti-displacement hazard of active fault in engineering construction. However, the existing classification schemes are rough, and some have no quantitative classification basis, which makes it difficult to apply these classification schemes in actual work. Also, they did not specify whether all active faults should be avoided. In this paper, considering the physical mechanism of earthquakes, using two activity parameters of active faults, "strong earthquake recurrence period" (TRP) and "strong earthquake elapsed time ratio" (Ret), and referring to the probabilistic seismic hazard analysis method (PSHA), the maximum magnitude of potential earthquake on the fault under different exceedance probabilities (EP) is calculated, and was divided into six levels. The fault displacement hazard level under different exceedance probabilities may be different. For buildings with different importance levels, we recommend six hazard classification schemes with different exceedance probabilities. Standard buildings should avoid active faults with a fault displacement hazard level of Ⅰ ~ Ⅲ (faults that can generate earthquakes of magnitude m0 and above under a 4% exceedance probability over 100 years). Special buildings and key buildings should avoid active faults with a fault displacement hazard level of Ⅰ ~ Ⅳ (faults that can generate earthquakes of magnitude m0-0.5and above under a 1% exceedance probability over 100 years). The fault displacement hazard classification scheme given in this paper takes into account the physical mechanism of earthquake occurrence and the importance of buildings, which makes this classification scheme both scientific and practical, helps provide technical support for the design and construction of buildings. This study is still quite preliminary, and there are many issues that need further study. [ABSTRACT FROM AUTHOR]

Throughout history, several large-magnitude earthquakes have caused damage to the Himalayan region and humanity. To understand the present-day strain rate distribution and associated seismic moment budget, a high-resolution velocity field is an essential component. The present study estimates the contemporary seismic moment budget along three spatial sections over the Nepal Himalaya using the state-of-the-art high-resolution velocity field. For this, (1) we integrate 5 years of InSAR data with 77 available GPS observations over the Nepal Himalaya; (2) we then calculate strain rate distribution (dilatational and maximum shear strain rates) from this integrated velocity field, and (3) at last, we compare the geodetic moment accumulation rate estimated from strain rate tensors with the seismic moment release rate based on an earthquake database of 500 years. The results reveal that: (1) the geodetic strain rate is not homogeneous over the Nepal Himalaya, rather along the main central thrust, a relatively higher strain rate is observed; (2) the geodetic moment rate from west to east across three sections ranges from 23.39 × 10 18 to 16.59 × 10 18 Nm/yr, with the minimum of 8.05 × 10 18 Nm/yr in central Nepal, whereas the seismic moment rate varies between 5.02 × 10 18 and 11.41 × 10 18 Nm/yr, with the minimum of 3.69 × 10 18 Nm/yr in central Nepal; (3) the difference between geodetic and seismic moment rates from west to east provides a moment deficit rate of 18.37 × 10 18 to 5.18 × 10 18 Nm/yr, with the minimum of 4.36 × 10 18 Nm/yr in central Nepal, and more importantly, (4) the inferred moment deficit rate suggests that the western and eastern Nepal have an earthquake potential of magnitude M w 8.5 and M w 8.1, respectively, whereas the central Nepal has energy budget equivalent to an M w 7.9 event. In summary, the present study provides spatial distribution of earthquake potential in Nepal Himalaya using the most updated high-resolution InSAR and GPS velocity field, and the findings inevitably contribute to the time-dependent earthquake hazard analysis of the study region. [ABSTRACT FROM AUTHOR]

The Italian Seismological Instrumental and Parametric Database (ISIDe) is the recipient of earthquake data collected in real-time by the Istituto Nazionale di Geofisica e Vulcanologia (INGV), and used by the studies of earthquake forecasting and seismic hazard assessment in Italy in the last decade. When it went online, following a significant improvement of the seismic acquisition system of INGV, it was including only data since the second fortnight of April 2005. About ten years later, the data since the beginning of 1985 suddenly appeared without any prior notice than the updating of the starting date of the dataset. However, the characteristics of the added data appeared clearly different from the following period both in terms of the numbers of located earthquakes and of types of magnitudes provided. After having analyzed the numerical consistency and the calibration of magnitudes of ISIDe as a function of time from 1985 to 15 April 2005, we can say that such a dataset is incomplete and poorly calibrated compared to other catalogs of Italian seismicity (CSTI, CSI, and HORUS) available for the same period. Hence, we suggest not using it as is for statistical analyses of Italian seismicity. However, it provides some magnitudes that are missed by other catalogs and thus might be used for improving such catalogs. [ABSTRACT FROM AUTHOR]

Radon gas anomalies have been investigated as potential earthquake precursors for many years. In this work, we have studied the possible correlations between radon emissions and the seismic activity rate for a given region to test if the existing correlation may be later used to forecast the occurrence of earthquakes larger than a given magnitude. The Vrancea region (Romania) was chosen as a study area since it is being surveilled by a multidisciplinary real-time monitoring network, and at least seven earthquakes with magnitudes greater than 4.5 Mw have occurred in this area in the period from 2016 to 2020. Our research followed several steps: First, the recorded radon signals were preprocessed (detrended, deseasoned and smoothed). Then, the station's signals were correlated in order to check which stations are recording radon anomalies due to the same regional tectonic process. On the other hand, the seismic activity rate was computed using the earthquakes in the main catalogue of the region that are able to generate radon emissions and can be registered at several stations. The obtained results indicate a significant correlation between the seismic activity rate and the temporal series of radon anomalies. A temporal lag between the seismic activity rate and the radon anomalies was found, which can be related to the proximity to the epicentre of the main earthquake in each of the studied subperiods. Changes in the regional tectonic stress field could explain why the seismic activity rate and radon anomalies are correlated over time. Further research could focus on obtaining a function to forecast the seismic activity rate using the following as dependent variables: the radon anomalies recorded at several stations, the distance from the stations, and tectonic factors such as the fault system, azimuth, type of soil, etc. [ABSTRACT FROM AUTHOR]

On January 1, 2024, an earthquake of magnitude 7.6 struck the Noto Peninsula in Ishikawa Prefecture, Japan. Tsunamis were recorded along nearby coasts following the earthquake, with the early tsunami arrival time at the Toyama tide station—located far from the earthquake epicenter—indicating potential submarine landslides in Toyama Bay. To identify these potential submarine landslides by detecting changes in seafloor depth, we collected new bathymetric data using a multibeam echo sounder in January and February 2024, and then compared them with data collected in 2010. This bathymetric comparison revealed submarine landslides along a submarine canyon off the Jinzu River, covering an area measuring 3.5 km × 1 km at depths of 40–370 m. Slide relief ranged from several meters up to 40 m, with some slides displaying distinct head scarps. Seafloor observations in areas with minor depth changes confirmed the presence of cliffs, disturbed seabed, and a redox boundary on the disturbed oxide layer, indicating recent landslides. Given the slide distribution within the estimated tsunami source area of the 2024 Noto Peninsula Earthquake, it is likely these slides were triggered by the earthquake. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach to extract scientifically valuable information about Earth's physical phenomena from unconventional sources, such as multimodal social media posts. Employing a state-of-the-art large language model (LLM), Gemini 1.5 Pro's, we estimate earthquake ground shaking intensity from these unstructured posts. The model's output, estimated intensity values, aligns well with independent observational data. Furthermore, our results suggest that LLMs, trained on vast internet data, may have developed a unique understanding of physical phenomena. Specifically, Google's Gemini models demonstrate a simplified understanding of the general relationship between earthquake magnitude, distance and intensity, accurately describing observational data even though it is not identical to established models. These findings raise intriguing questions about the extent to which Gemini's training has led to a broader understanding of the physical world and its phenomena. The ability of Generative AI models like Gemini to generate results consistent with established scientific knowledge highlights their potential to augment our understanding of complex physical phenomena like earthquakes. The flexible and effective approach proposed in this study holds immense potential for enriching our understanding of the impact of physical phenomena and improving resilience during natural disasters. This research is a significant step toward harnessing the power of social media and AI for natural disaster mitigation, opening new avenues for understanding the emerging capabilities of Generative AI and LLMs for scientific applications. [ABSTRACT FROM AUTHOR]

The Belt and Road global navigation satellite system (B&R GNSS) network is the first large-scale deployment of Chinese GNSS equipment in a seismic system. Prior to this, there have been few systematic assessments of the data quality of Chinese GNSS equipment. In this study, data from four representative GNSS sites in different regions of China were analyzed using the G-Nut/Anubis software package. Four main indicators (data integrity rate, data validity ratio, multi-path error, and cycle slip ratio) used to systematically analyze data quality, while evaluating the seismic monitoring capabilities of the network based on earthquake magnitudes estimated from high-frequency GNSS data are evaluated by estimating magnitude based on highfrequency GNSS data. The results indicate that the quality of the data produced by the three types of Chinese receivers used in the network meets the needs of earthquake monitoring and the new seismic industry standards, which provide a reference for the selection of equipment for future new projects. After the B&R GNSS network was established, the seismic monitoring capability for earthquakes with magnitudes greater than MW6.5 in most parts of the Sichuan-Yunnan region improved by approximately 20%. In key areas such as the Sichuan-Yunnan Rhomboid Block, the monitoring capability increased by more than 25%, which has greatly improved the effectiveness of regional comprehensive earthquake management. [ABSTRACT FROM AUTHOR]

It has become common in the development of ground-motion models (GMMs), especially using mixed-effects regression with crossed random effects, to calculate standard deviations, referred to as variance components, from sample statistics of the residuals (i.e. random effects and within-group errors) rather than using the variance components reported by a mixed-effects regression program, calculated using the same algorithms used in the mixed-effects regression, or estimated using Bayesian inference. This practice leads to underestimating the standard deviations because it does not account for the uncertainty (i.e. standard errors) associated with fitting the random effects and within-group errors during the regression analysis. In this study, we used a series of ground-motion models for Fourier amplitude spectra developed using mixed-effects regression of an Next Generation Attenuation (NGA)-West2 database to show that residual-based standard deviations can be significantly smaller than regression-based standard deviations. These differences are exacerbated for those variance components with the fewest number of observations or when the residuals are partitioned (e.g. by earthquake magnitude). Using residual-based variance components not only results in smaller standard deviations but can lead to biased inferences when attempting to compare the efficacy of a model based solely on a comparison of the values of the variance components or their related mean square errors. It can also lead to biased fixed-effects coefficients if the variance components are derived from the residuals of a mixed-effects regression rather than estimated during a regression. We show that variance components can be decomposed into various random-effect grouping factors and partitioned into subsets of predictor variables, such as magnitude, from the total residuals of a non-Bayesian mixed-effects regression program using Bayesian inference. This process does not require the development of an entire GMM using Bayesian mixed-effects regression. [ABSTRACT FROM AUTHOR]

On 6 February 2023, a devastating earthquake of magnitude 7.7 struck the southeastern part of Turkey, followed by multiple aftershocks. The sequence of earthquakes caused extensive damage in Southern Turkey and Northern Syria. This study evaluates the destructive potential of ground shaking resulting from the Pazarcik mainshock by developing spatial distribution of inelastic demand spectra across the region by using the recorded ground motions. These spectra provide an additional step toward more realistic estimates of the damage potential of ground shaking than the traditional elastic response spectra. Given the recorded ground motions, we also developed simulated ground-motion time series at numerous un-instrumented sites. We used these recorded and simulated motions to estimate ductility demands across the affected area. Constant-ductility spectra were derived using recording stations within 100 km of the fault rupture. The results indicated that in the near-fault area, and for structural periods of 0.5 and 1.0 s, the yield strength demand at a ductility level of 3 exceeded the levels specified in the local seismic design code for a 475-year return period. Our findings demonstrate that with more refinement and efficiency of the ground-motion simulation approach, the development of near-real-time spatial distribution of ductility demand is a promising approach for rapid seismic damage assessment of earthquakes. [ABSTRACT FROM AUTHOR]

Landslides triggered by seismic activity have led to substantial human and economic losses. Nevertheless, the fundamental physical mechanisms underlying the vibration and rupture of rock slopes during earthquakes remain poorly understood. In this study, finite element method-based numerical simulations were conducted based on the rock slope at Dagangshan Hydropower Station in Sichuan province, China. Firstly, systematic analysis in both the time and frequency domains were performed to examine the seismic dynamic characteristics of the slope. Subsequently, the transfer function method and the multiple stepwise linear regression method were employed to clarify the underlying mechanism and determine critical factors influencing the slope instability during earthquakes. Time-domain analysis reveals that rock slope dynamic response exhibits notable elevation, surface, and local amplification effects. Specifically, the Peak Ground Acceleration (PGA) amplification coefficient (MPGA) is significantly higher at elevated locations, near the slope surface and in areas with protrusions. Moreover, the existence of fracture zones and anti-shear galleries minimally influences the dynamic responses but considerably affect the rupture. Specifically, fracture zones exacerbate rupture, while anti-shear galleries mitigate it. Frequency-domain analysis indicates that the dynamic responses of the slope are closely correlated with the degree of slope rupture. As earthquake magnitude increases, the rupture degree of the slope intensifies, and the dominant frequency of the response within the slope decreases, e.g., its value shifts from 3.63 to 2.75 Hz at measurement point 9 near the slope surface. The transfer function of rock slope, calculated under the excitation of wide flat spectrum white noise can reflect the interrelationships between the inherent properties and the rupture degree. Notably, the peak of the transfer function undergoes inversion as the degree of rupture increases. Furthermore, through multiple stepwise linear regression analysis, four key factors influencing the surface dynamic response of the slope were identified: rock strength, slope angle, elevation, and seismic dominant frequency. These findings provide valuable insights into the underlying mechanisms of rock slope dynamic responses triggered by earthquakes, offering essential guidance for understanding and mitigating seismic impacts on rock slopes. [ABSTRACT FROM AUTHOR]

Significant progress has been made in probing the state of an earthquake fault by applying machine learning to continuous seismic waveforms. The breakthroughs were originally obtained from laboratory shear experiments and numerical simulations of fault shear, then successfully extended to slow-slipping faults. Here we apply the Wav2Vec-2.0 self-supervised framework for automatic speech recognition to continuous seismic signals emanating from a sequence of moderate magnitude earthquakes during the 2018 caldera collapse at the Kīlauea volcano on the island of Hawai'i. We pre-train the Wav2Vec-2.0 model using caldera seismic waveforms and augment the model architecture to predict contemporaneous surface displacement during the caldera collapse sequence, a proxy for fault displacement. We find the model displacement predictions to be excellent. The model is adapted for near-future prediction information and found hints of prediction capability, but the results are not robust. The results demonstrate that earthquake faults emit seismic signatures in a similar manner to laboratory and numerical simulation faults, and artificial intelligence models developed for encoding audio of speech may have important applications in studying active fault zones. Here, the authors apply the Wav2Vec-2.0 self-supervised framework for automatic speech recognition to continuous seismic signals emanating from a sequence of moderate magnitude earthquakes during the 2018 caldera collapse at the Kilauea volcano on the island of Hawai'i. [ABSTRACT FROM AUTHOR]

In this study, uncertainty quantification and parametric sensitivity analysis in Probabilistic Tsunami Hazard Assessment (PTHA) are performed for the South China Sea using a Monte Carlo approach. Uncertainties in parameters such as the magnitude–frequency distribution of the potential tsunami zone, geodetic information used to constrain the maximum magnitude, properties determining the slip distribution, scaling laws and dip of unit sources are considered, each of which is varied separately while the others are fixed. The Coefficient of Variation (COV) of tsunami amplitudes corresponding to a fixed annual probability at different coastal sites is used to represent the uncertainty of each parameter. In addition, the overall tsunami hazard and uncertainty are also presented by simultaneously varying all parameters in a Monte Carlo series. Our results suggest that a major contributor to the uncertainty is the magnitude frequency distribution parameters, especially the maximum magnitude. Geodetic information can be used to solve the problem that the maximum magnitude is underestimated owing to the scarcity of mega earthquakes in the historical earthquake catalog, while it will also lead to a large uncertainty if the parameters in it are not well determined. Among these geodetic parameters, the seismic coupling coefficient is the parameter that most influences the uncertainty as it is difficult to determine an accurate value. The effect of the slope parameter β in the magnitude–frequency relationship is complicated because of its influence in determining the maximum magnitude and the number of earthquake events. In addition, the uncertainty associated with the down-dip width of the seismogenic zone is not remarkable but cannot be ignored, which is similar to that of the annual plate slip rate, while the effect of the rigidity is relatively small because its effect on the average slip of earthquake events will reduce the uncertainty. Compared to the uncertainty in determining the maximum magnitude, the effect of slip distribution properties such as Hurst exponent, correlation length and scaling exponent and the choice of scaling laws is relatively small. The uncertainty in the dip angle of the unit source is moderate and cannot be ignored, especially for sites along the strike of the subduction zone. Tsunami curves for four coastal sites indicate that the tsunami hazard in the South China Sea is subject to large variations when considering all uncertainties in the PTHA, with the COV in 2000 years at different sites being about 0.25, which means that the 95th percentile is about two times of the 5th percentile. [ABSTRACT FROM AUTHOR]

To secure the seismic performance of structures, seismic risk assessment is necessary to quantify safety against beyond-design-based earthquakes and seismic design. For the seismic risk assessment of structures, the input ground motions corresponding to the seismic intensity for evaluation are required as seismic loads, which must reflect the tectonic characteristics and site conditions. In this study, ground motions recorded in regions of low to moderate seismicity were used to generate examples of input ground motions for seismic risk assessment. A uniform hazard spectrum (UHS) was used as the target spectrum for risk assessment, following the guidelines. The magnitude and distance parameters of the scenario earthquake for seismic risk assessment were determined via hazard de-aggregation. The empirical Green's function method (EGFM) was used to match the ground motion recorded at the site with the seismic intensity required for seismic risk assessment. In addition, a spectral matching process was applied to ensure that the input ground motion was compatible with the response spectrum used in seismic risk assessment. In this process, the convergence characteristics of the spectral matching to the target spectrum were analyzed. Consequently, the spectral conditions for selecting the ground motion for the seismic risk assessment were determined. [ABSTRACT FROM AUTHOR]

This study proposes a novel model to quantitatively evaluate functionality loss in railway network systems during earthquakes and assesses its applicability to a hypothetical railway network system. The model combines seismic fragility functions and restoration curves to assess functionality loss, deriving a time-dependent recovery function to propose a functionality loss model based on earthquake magnitude. The proposed model uses a hypothetical railway network to calculate the overall functionality loss of the network under various earthquake scenarios. The hypothetical railway network was designed with three lines, allowing different routes to remain operational depending on the damaged sections and increasing the diversity of network impact scenarios based on the functionality loss. This model provides a framework for analyzing the functionality loss and recovery processes of railway networks during seismic events and assessing the socioeconomic impacts of earthquakes. [ABSTRACT FROM AUTHOR]

Ambient noise cross-correlation has been widely used to observe post-earthquake temporal velocity variations. Comparative studies are essential for assessing seismic hazards and clarifying the relationship between velocity variation and magnitude. However, very few comparative studies by earthquake magnitude have been conducted, particularly for magnitudes smaller than 6. In 2016 and 2017, southeastern Korea experienced the two most damaging earthquakes of the past 250 years: the Pohang earthquake (M 5.4) and Gyeongju earthquake (M 5.8). This study compared the coseismic velocity variations of these earthquakes with those observed in the M 7.3 Kumamoto and M 6.6 Tottori earthquakes, which occurred in Japan in 2016. In this study, the moving window cross-spectral analysis revealed different curves for bidirectional cross-correlations, a difference that has not been addressed in previous studies. This discrepancy was most likely caused by data deficiencies due to prolonged aftershocks or by instability from small-magnitude earthquakes recorded by surface seismometers in Korea. The average velocity decrease between forward and reverse order pairs correlated well with earthquake magnitude, except in the case of the Korean earthquake. Our devised measure based on aftershock activity suggests that the large decrease in the Pohang earthquake was due to non-coseismic noise in addition to instability. [ABSTRACT FROM AUTHOR]

Many practical disaster reports are published daily worldwide in various forms, including after-action reports, response plans, impact assessments, and resiliency plans. These reports serve as vital resources, allowing future generations to learn from past events and better mitigate and prepare for future disasters. However, this extensive practical literature often has limited impact on research and practice due to challenges in synthesizing and analyzing the reports. In this study, we 1) present a corpus of practical reports for text mining and 2) introduce an approach to extract insights from the corpus using select text mining tools. We validate the approach through a case study examining practical reports on the preparedness of the U.S. Pacific Northwest for a magnitude 9 Cascadia Subduction Zone earthquake, which has the potential to disrupt lifeline infrastructures for months. To explore opportunities and challenges associated with text mining of practical disaster reports, we conducted a brief survey of potential user groups. The case study illustrates the types of insights that our approach can extract from a corpus. Notably, it reveals potential differences in priorities between Washington and Oregon state-level emergency management, uncovers latent sentiments expressed within the reports, and identifies inconsistent vocabulary across the field. Survey results highlight that while simple tools may yield insights that are primarily interpretable by experienced professionals, more advanced tools utilizing large language models, such as Generative Pre-trained Transformer (GPT), offer more accessible insights, albeit with known risk associated with current artificial intelligence technologies. To ensure reproducibility, all supporting data and code are made publicly available (DOI: 10.17603/ds2-9s7w-9694). [ABSTRACT FROM AUTHOR]

The Yangsan fault is the most prominent NNE-SSW-striking active right-lateral strike-slip fault crossing the Korean Peninsula, with a continuous trace of ~200 km. It can likely generate large earthquakes; however, the paleoseismic information on slip per event, slip rate, and timing of past ruptures along this fault remains sparse. To explore these parameters for the Yangsan fault, we excavated trenches across the central segment of the fault, which showed evidence for at least five surface-rupturing earthquakes preserved in Quaternary fluvial deposits. The timing of these earthquakes is discussed based on luminescence and radiocarbon ages. A close examination of three-dimensional trench exposures revealed that the most recent event(s) occurred during or slightly after the third century CE (one-event interpretation) or sixth to eighth century CE (two-event interpretation), and it was associated with 4.5 m to 5.3 m of lateral displacement of a paleochannel. The observed lateral displacement indicates that large earthquakes with a magnitude of around Mw 7 have taken place in the recent past, which is the first-ever direct evidence of large-magnitude earthquakes along the Yangsan fault. The penultimate event occurred after 17 ± 1 ka, whereas an earlier late Quaternary event occurred in the late Pleistocene, suggesting a recurrence interval in the range of 10,000 yr, and a consequent slip rate on the order of 0.5 mm/yr. The oldest observed ruptures are preserved below an erosional unconformity that probably dates back to the last interglacial period, based on infrared stimulated luminescence ages. An unknown number of ruptures may have occurred between the unconformity and subsequent sedimentation during the latest Pleistocene to Holocene period. Historical earthquake records indicate clustered behavior of moderate and large earthquakes along the Yangsan fault. Past faulting events and implied recurrence intervals constrain the long-term faulting behavior along the Yangsan fault and will contribute to a better seismic hazard assessment in the southeastern part of the Korean Peninsula. [ABSTRACT FROM AUTHOR]

We investigate temporal and spatial variations of the spectral decay parameter kappa (κ) before and after the 6 April 2009, L'Aquila earthquake (M w 6.1), in Central Italy. We analysed foreshocks 10 days before and aftershocks occurring 10 days and 6 months after this main event. We select earthquakes with magnitudes M w ≥ 3.2 registered by the seismic network of Central Italy within a radius of 20 km from the epicentre of the L'Aquila main shock and having hypocentre distances of less than 170 km. We separate near-source, along-path and near-site contributions of κ for each group of events and we detected temporal variations of this S -wave attenuation parameter. We find that 10 days before the main shock κ along the path has the lowest values, probably due to high tectonic stress accumulated, in agreement with previous investigations performed with other techniques, then κ increases during the main event and remains constant during the first 10 days of aftershocks. The aftershocks that occurred 6 months after show an increase in the regional attenuation probably due to the tectonic stress released during the main shock and the earlier aftershocks. From the spatial point of view, 10 days before the principal event the foreshocks located to the south show an increase in the near-source attenuation towards the northeast, in the direction of the main shock. These spatial variations of κ may be related to the presence of crustal fluids near the rupture area, as evidenced by other previous studies. The first 10 days of aftershocks that concentrate around the main earthquake have high near-source κ , and those located north of the main rupture have lower values. These observations are consistent with previous investigations that show variations of elastic and anisotropic crustal properties during the L'Aquila earthquake sequence due to dilatancy and fluid diffusion processes within the nucleation zone. We conclude that temporal variations of the spectral decay parameter κ provide important clues for the earthquake cycle in Central Italy. [ABSTRACT FROM AUTHOR]

A major event with a magnitude of 7.7 (Mw) located in Pazarcık district of Kahramanmaraş on February 6, 2023. Approximately nine hours later, a second earthquake with a magnitude of 7.6 (Mw) located in the Elbistan region of Kahramanmaraş, approximately 100 km from the first earthquake according to the Disaster and Emergency Management Presidency (AFAD). These two earthquakes and the subsequent aftershocks caused many deaths, destruction and severe damage in areas close to the East Anatolian Fault Zone. The seismological and structural observations applied in the Malatya, one of the provinces affected by earthquakes, are presented in this study. For this purpose, acceleration data recorded at the strong motion station located in Malatya province and operated by the AFAD were examined. The seismic stations located in the Kale, Doğanşehir, and Akçadağ districts, located close to the province of the Malatya, were examined for the peak ground acceleration, the peak ground velocity, and the peak ground displacement for each station. Additionally, the spectral acceleration and the Arias intensities were calculated, also. The highest acceleration among these three stations in the Pazarcık earthquake was observed as approximately 0.16 g at station 4414 in the Kale district, and in the Elbistan earthquake, approximately 0.45 g at station 4406 in the Akçadağ district. Since the accelerations of the main shocks were not recorded at the stations in the Malatya city center, both the peak ground acceleration and the spectral acceleration values were predicted by using the ground motion prediction equations (GMPEs). The largest ground accelerations were predicted between 0.15 and 0.2 g for the Pazarcık earthquake and 0.3–0.4 g for the Elbistan earthquake in the Malatya province, also by using GMPEs, for different soil types. The peak ground acceleration that can be produced by DD-2 (the earthquake with a probability of 10% of exceed in 50 years) earthquakes in the center of the Malatya, is 0.361 g according to the Türkiye Building Earthquake Code 2018 (TBEC 2018). The Kahramanmaraş earthquakes (Mw 7.7 and 7.6) caused heavy damage to the structures in Malatya center because they exceeded the maximum ground acceleration value that could be produced according to the 2018 Türkiye Earthquake Hazard Maps (TEHM 2018). The results of the time-domain analysis applied to a collapsed building in the center of Malatya showed the necessity of obtaining site-specific earthquake spectra and making building designs and performance analyses by taking into account the structure-soil interaction. Taking these situations into consideration, it is expected that the building designs to be made based on the calculation of the largest spectrum acceleration values that may occur due to an earthquake in the worst ground conditions in the center of Malatya will be safer against earthquakes. [ABSTRACT FROM AUTHOR]

A correct understanding of dams' dynamic behaviour can help improve structures' design and safety. The settlement of earth dams caused by earthquake shaking can induce instability and destruction. Using white-box machine learning techniques, including gene expression programming (GEP), a numerical relationship has been tried to estimate the settlement of earth dams under different types of earthquake loading, so that this relationship can be used in the design of earth dams. The main input parameters used in this research include the ratio of the yield acceleration of the dam to the maximum horizontal acceleration of the earthquake (ay/amax), the ratio of the fundamental period of the dam to the predominant period of the earthquake (Td/Tp), the magnitude of the earthquake (Mw) and the settlement ratio (S/H) earth dam as the output parameter. The R, MAE, and RMSE values for the proposed relationship in the research were equal to 0.85, 0.058, and 0.127, respectively. The measurement of statistical parameters shows the acceptable accuracy of the GEP method in predicting S/H. However, developing a database containing other effective parameters can be considered for future research. [ABSTRACT FROM AUTHOR]

The article delves into the intricate relationship between an earthquake swarm beneath the Noto Peninsula in Central Japan and the subsequent 2024 M 7.6 Noto Hanto earthquake sequence. It examines the various physical mechanisms at play, including pre-slip, cascade triggering, aseismic slip, and fluid migration, to understand the evolution process leading to the mainshock. By analyzing seismicity patterns, foreshocks, stress distribution, and rupture propagation, the study sheds light on the complexities of earthquake activity in the region. The research underscores the importance of in-depth investigations utilizing diverse data sources to unravel the connection between earthquake swarms and the initiation of major seismic events, making the Noto earthquake sequence a valuable case study for global earthquake research. [Extracted from the article]

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Copyright of Journal of Natural Hazards & Environment (JNHE) / Doğal Afetler ve Çevre Dergisi (DACD) is the property of Artvin Coruh University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Natural Hazards & Environment (JNHE) / Doğal Afetler ve Çevre Dergisi (DACD) is the property of Artvin Coruh University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Natural Hazards & Environment (JNHE) / Doğal Afetler ve Çevre Dergisi (DACD) is the property of Artvin Coruh University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

On 8 August 2017, a strong earthquake of magnitude 7.0 occurred in Jiuzhaigou, Sichuan Province, China. To assess pre-earthquake anomalies, we utilized variational mode decomposition to preprocess borehole strain observation data and combined them with a graph WaveNet neural network model to process data from multiple stations. We obtained 1-year data from four stations near the epicenter as the training dataset and data from 1 January to 10 August 2017 as the test dataset. For the prediction results of the variational mode decomposition–graph WaveNet model, the anomalous days were extracted using statistical methods, and the results of anomalous-day accumulation at multiple stations showed that an increase in the number of anomalous days occurred 15–32 d before the earthquake. The acceleration effect of anomalous accumulation was most obvious 20 d before the earthquake, and an increase in the number of anomalous days also occurred in the 1 to 3 d post-earthquake. We tentatively deduce that the pre-earthquake anomalies are caused by the diffusion of strain energy near the epicenter during the accumulation process, which can be used as a signal of pre-seismic anomalies, whereas the post-earthquake anomalies are caused by the frequent occurrence of aftershocks. [ABSTRACT FROM AUTHOR]

In recent decades, China has collected extensive strong-motion data from the Loess Plateau, which is valuable for understanding the dynamic characteristics of loess sites and the effects of site conditions on seismic motions. The horizontal-to-vertical Fourier spectrum ratio (HVSR) and the horizontal-to-vertical velocity response spectrum ratio (VRSR) are widely used to study site dynamics. This study analyzes strong-motion data from the Loess Plateau to identify key features of the HVSR and VRSR curves. The results show that these spectral ratio curves effectively capture the dynamic behaviors of loess sites, minimizing the influences of earthquake magnitude and propagation path. While the spectral ratio peaks are less affected by magnitude, epicentral distance, and focal depth, they are significantly influenced by site conditions. Conversely, the dominant periods estimated from these curves are strongly influenced by magnitude, epicentral distance, and focal depth. For sites located on the Loess Plateau, the average amplification factor is approximately 3, with a mean predominant period of 0.4 s. These results provide valuable insights into the dynamic characteristics of loess sites and have practical implications for seismic design in the region. [ABSTRACT FROM AUTHOR]

Electromagnetic (EM) signals from a seismogenic zone a few weeks to a few days before an earthquake are considered as a promising attribute in earthquake precursory studies. EM perturbations, termed as the coseismic electromagnetic perturbations, also occur within the source zone at the onset of an earthquake and at recording sites during the passage of seismic waves. In the present study, we have analyzed the coseismic electromagnetic perturbations of the M 6.4 Nepal earthquake of 2023-11-03 and its main aftershock (M 5.6) of 2023-11-06, recorded at eight long-period magnetotelluric (LMT) sites installed in profile mode in the Ganga Basin about 150 to 250 km south-west of the earthquake epicenter. The time series were detrended, bandpass filtered, and rotated in the radial and transverse directions using back-azimuth. These time series mimic seismograms and show EM inductions corresponding to the arrival of the P, S and surface waves. Amplification of the surface wave at sites in the middle sector of the profile covering the Sharda depression having thick sedimentary succession and decrease in the amplitude at the southernmost site at the edge of the depression highlight the role of geological heterogeneities in controlling the EM induction. The presence of two very low amplitude consistent peaks at most sites, spread over a profile length of about 120 km, preceding the earthquake by 70 s and 43 s, respectively, is enigmatic. These signals arrive at most sites almost simultaneously and have peak-to-peak amplitude in the range of -0.07 to + 0.11 µV/m and −0.04 to + 0.07 µV/m, respectively, at fourth site. This is probably the first reporting of such preseismic electromagnetic signals in EM time series. We infer that these signals are possibly linked to the fast propagating EM waves generated during the final stage of the earthquake source zone preparation just before the initiation of the rupture. These signals need to be explored in the future for understanding of the causative physical processes. The results also reveal on average about 5 times reduction in the amplitude of the surface wave-induced electric fields with the drop in the earthquake magnitude from 6.4 to 5.6. [ABSTRACT FROM AUTHOR]

The Nankai Trough region has a history of devastating earthquakes. The Hyuga-nada region is situated in the westernmost Nankai Trough and has not experienced an earthquake exceeding magnitude 8. It is expected that there is a difference in a coupling between the subducting Philippine Sea Plate and the overriding plate. The region is known for its active region of low-frequency tremors and very low-frequency earthquakes. Several long-term ocean bottom seismometer (LTOBS) networks were deployed to monitor seismic activities in the region to reveal the characteristics of seismicity in the study region. Seafloor seismic observations were conducted on the seafloor in the Hyuga-nada region with periods of 2015–2016, 2017–2018, and 2022. Initially, the hypocenters of regular earthquakes were determined by using a location program that integrated absolute travel times and a 1-D velocity structure. Station corrections for travel times were applied to compensate for structural heterogeneity just beneath individual LTOBS. Subsequently, events were relocated using a double-difference technique to enhance the accuracy of the location. Focal mechanisms were estimated using the polarity data of the first arrivals. Comparison with a plate model indicated that these earthquakes occurred within the subducting Philippine Sea Plate. From the spatial–temporal distribution, hypocenters of earthquakes were concentrated in a small region with a size of a few km and occurred within a few days. We could clearly distinguish swarm activities from regular activities. During the observation period, there were two swarm activities in the study area. Fault plane solutions of regular events except swarms, are dominant with a normal fault type mechanism. On the other hand, swarms had a small number of events with a normal fault type. The swarm activities started slightly later than the very low frequency earthquake (VLFE) activities. The regions of activity for the swarms and the VLFE seemed to generally overlap in consideration of the low spatial resolution of the VLFE locations. [ABSTRACT FROM AUTHOR]

Local magnitude (ML) scales have been developed for Egypt based on 14,453 normalized Wood–Anderson amplitudes from 1670 earthquakes. These events were recorded by at least four seismic stations, with hypocentral depths of less than 40 km and earthquake magnitudes ranging from 0.1 to 6.5 ML. The dataset was processed using recordings from the two horizontal components. Egypt was divided into four sub-tectonic regions: South Egypt, North Egypt, the Red Sea, and the Mediterranean Sea. The decay of amplitudes with distance was examined across the entire dataset, providing attenuation characteristics segmented into three sections, with transition distances at 90 km and 175 km. Within each sub-tectonic region, the coefficients of the distance correction term (− log A0) and the station correction term (S) were determined using a trilinear geometrical scattering model and singular value decomposition, respectively. The newly derived relationship for Egypt has resulted in unbiased ML magnitude estimates over a substantial distance range (10–1000 km), thus ensuring consistent magnitude estimates from the ENSN network. [ABSTRACT FROM AUTHOR]

This study employs a dynamic input–output model to simulate the recovery process of a high-speed railway and the subsequent regional economic recovery following an earthquake. The analysis considers the impact of earthquakes of varying magnitudes on Sichuan Province, its neighboring areas, and the entire nation of China. The simulation is conducted against the backdrop of the restoration and reconstruction efforts in Sichuan Province post-earthquake. The findings reveal that the recovery speed of the high-speed railway transportation sector is influenced not only by the established recovery time, but also by the pace of recovery in adjacent industrial sectors and external inputs. Accelerated recovery in adjacent industrial sectors contributes to a faster recovery of the high-speed railway transportation sector. Furthermore, once the adjacent industrial sectors return to normal levels of recovery, the high-speed railway transportation sector follows suit, reaching the established recovery rate. In terms of regional economic recovery, provinces with smaller economies experience higher rates of economic reduction due to earthquakes. Conversely, provinces with a significant proportion of high-speed railways in their economies witness higher rates of economic reduction following seismic events. The insights derived from this study hold practical significance for guiding regional economic and transportation recovery and reconstruction efforts post-major earthquakes. [ABSTRACT FROM AUTHOR]

Magnitude prediction is a key focus in earthquake science research, and using machine learning models to analyze seismic data, identify pre-seismic anomalies, and improve prediction accuracy is of great scientific and practical significance. Taking the southern part of China's North–South Seismic Belt (20° N~30° N, 96° E~106° E), where strong earthquakes frequently occur, as an example, we used the sliding time window method to calculate 11 seismicity indicators from the earthquake catalog data as the characteristic parameters of the training model, and compared six machine learning models, including the random forest (RF) and long short-term memory (LSTM) models, to select the best-performing LSTM model for predicting the maximum magnitude of an earthquake in the study area in the coming year. The experimental results show that the LSTM model performs exceptionally well in predicting earthquakes of magnitude 5 < ML ≤ 6 within the time window of the test set, with a prediction success rate of 85%. Additionally, the study explores how different time windows, spatial locations, and parameter choices affect model performance. It found that longer time windows and key seismicity parameters, such as the b-value and the square root of total seismic energy, are crucial for improving prediction accuracy. Finally, we propose a magnitude interval-based assessment method to better predict the actual impacts that different magnitudes may cause. This method demonstrates the LSTM model's potential in predicting moderate to strong earthquakes and offers new approaches for earthquake early warning and disaster mitigation. [ABSTRACT FROM AUTHOR]

By leveraging the Okada model, the study makes the first-ever attempt to examine earthquake-induced tsunamis in Lake Sevan, related to the activation of underwater segments of the active Pambak-Sevan-Syunik Fault (PSSF), the largest geological structure in the Republic of Armenia (RA). Situated in the Arabian-Eurasian continental collision zone, the basin of Sevan, the largest freshwater lake in the Caucasus region, is characterized by a variety of geological hazards capable of producing events of inter-related triggering. Among other threats, the lake tsunami hazard has remained unexplored. Two hypothetical earthquake scenarios were computed for the PSSF segments: an Mw 6.9 for the sector of the Vanadzor-Artanish segment as a reverse faulting and an Mw 7.5 for the Dzknaget-Khonarhasar strike-slip. The best-fit solutions, as fault-derived parameters, were calibrated under the proposed seismic scenarios. Based on the fault parameters, a back-analysis was first performed to determine earthquake magnitudes and to develop appropriate scenarios for the subsequent lake tsunami simulation. Finally, potential tsunami wave maps were produced for the tsunami hazard in Lake Sevan. The shores of the Small Sevan were identified as the possibly most impacted zone with maximum wave height (Zmax) of 4 meters estimated under the Mw 6.9 scenario for the sector of the Vanadzor-Artanish segment. [ABSTRACT FROM AUTHOR]

A single precursor is not usually an accurate, precise, and adequate measure to predict earthquake parameters. Therefore, it is more appropriate to combine multiple precursors and exploit parameters extracted from them to reduce the uncertainty of the prediction. The assumption in this study is based on the fact that most Earthquakes happen in active fault zones. The study is about the estimation of Earthquake parameters such as date and magnitude. In this study, remote sensing observations (such as electron and ion density, electron temperature, Total Electron Content (TEC), Land Surface Temperature (LST), Sea Surface Temperature (SST), Aerosol Optical Depth (AOD), and Surface Latent Heat Flux (SLHF)) in different modalities acquired several days before impending earthquakes have been investigated to extract earthquake parameters. In this study, three methods: median, support vector regression (SVR), and random forest (RF) have been used to detect anomalies. Then, by estimating the amount of anomaly deviation from the normal state, the magnitude of the impending earthquake is estimated. The final earthquake parameters (such as date and magnitude) can be obtained by integrating the earthquake parameters extracted from different earthquake precursors using the mean square error (MSE) method. [ABSTRACT FROM AUTHOR]

The traditional field of research has been enriched by discovering and applying several unique approaches for extracting relevant information from a time series of Solid Earth tides for a specific location. This study focused on the impactful Mw 9.1 megathrust earthquake of December 26, 2004, in Sumatra-Andaman, which spans 13 earthquakes within a 75-kilometer radius from 1991 to 2021. Employing the univariate singular spectrum analysis (SSA) on Solid Earth tides (SET), a significant anomalous variation in the sixth component of empirical orthogonal functions (EOF) is identified. It is noted that the eigenvalue corresponding to this component exhibits a correlation with earthquake magnitude. Further, this study is extended to a broader spatial region to perform in-depth spatio-temporal analysis exclusively for the December 26, 2004 earthquake, by expanding spatial analysis to latitudes 2° to 5° N and longitudes 94° to 98° E through a sliding window method. A spatio-temporal analysis from 1995 to 2004 reveals distinct patterns preceding higher magnitude earthquakes, offering valuable insights for long-term forecasting. It has been correlated with foreshocks that occur to the same spatiotemporal extent. In a nutshell, singular spectrum analysis SSA of Solid Earth Tides emerges as a promising precursor for long-term earthquake magnitude prediction. Also, EOF alone is insufficient for accurately forecasting the magnitude, as the results show an inverse relationship with magnitude. Finally, it might be combined with other parameters like foreshocks for reliable earthquake forecasting. [ABSTRACT FROM AUTHOR]

The Mw 7.8 Haida Gwaii earthquake occurred on 28 October 2012, generating up to 13 m tsunami waves and 3 m run-up along the British Columbia coastline. Despite the magnitude of the earthquake and tsunami, damages were minor due to the lack of vulnerable infrastructure in the remote area. Previous finite fault models were derived from GNSS, seismic and tsunami data, but the uncertainty remained high due to the limited number of seismic and GNSS stations near the epicenter. In this study, finite fault models were developed using RADARSAT-2 interferograms and previously published GNSS data. These models defined the location of the fault and provided a detailed slip distribution with a high degree of certainty. The results confirmed that the main slip was located on the subduction fault interface between the Pacific and North American plates, west of the Queen Charlotte Fault. The estimated moment magnitude of 7.88–7.93 is slightly larger than the previously reported moment magnitude of around 7.8, due to the capture of postseismic deformation in the interferograms. Overall, the study provides an improved finite fault slip model for the Haida Gwaii earthquake and highlights the importance of utilizing remote sensing data for studying earthquakes in remote areas. [ABSTRACT FROM AUTHOR]

We estimated the source parameters for local earthquakes near the Idukki reservoir, Kerala. The region falls under seismic zone III, indicating moderate seismicity, and is reported to have witnessed several small to moderate size magnitude earthquakes. Eight local earthquakes with magnitudes ranging between 2 and 3.6 were used during the data analysis of this study. Four key parameters were primarily estimated from the earthquake signals, providing an overall idea about the source characteristics, i.e., seismic moment, stress drop, corner frequency, and source radius. Our estimated moment magnitudes (Mw) range between 2 and 3.4, which are consistent with the reported local magnitude (ML) scale, indicating a minor difference between MW and ML scale. The estimated variations in seismic moment align well with the global model of micro-earthquakes, ranging between 1.2E + 15 and 1.1E + 17 dyn-cm. The source radius mostly varies between 110 and 220 m, with seismic moment exhibiting a linear increase as source size grows. This suggests a clear dependence of seismic moment on the radius of the source. It is likely that the brittle shear-failure mechanism on the fault segment and/or the presence of weak zones would contribute to local earthquakes with smaller source radius. Stress drops for most of the events are relatively low in the study region, ranging from 0.3 to 4.5 bars. The initiation of rupture is evident along an existing fault plane, potentially acting as a contributing factor to the observed lower stress drop values. The stress drop variable with a positive correlation to the seismic moment of the event might indicate a wide range of strength of the crustal rock in the region. Interestingly, both the corner frequency (fc) and maximum frequency (fmax) decrease as seismic moment increases, indicating that both are related to the source process and possibly influenced by the site effects. Finally, we can suggest that the derived source parameters can be utilized to simulate ground motion parameters of historical events, thereby enhancing seismic hazard assessment and facilitating earthquake engineering analyses in future research initiatives. [ABSTRACT FROM AUTHOR]

To enhance the seismicity analysis within a given seismic region, it is crucial to establish a unified earthquake catalog with minimized uncertainties. The preparation of such a unified catalog needs scaling relationships to convert different magnitude types to a homogeneous magnitude. Among the plethora of magnitude types, the moment magnitude (Mw) stands out as a widely utilized metric in modern earthquake risk and recurrence analysis. Hence, the key objective of this study is to expand the Mw earthquake dataset specifically for the Northern Algeria region and its surrounding areas, providing a valuable resource for researchers investigating seismicity in this region and for earthquake magnitudes homogenization. To achieve this objective, surface wave (Ms) and body wave (mb) magnitudes obtained from international agencies were standardized to Mw using newly developed regional empirical relationships based on the general orthogonal regression method (GOR). The use of GOR for magnitude conversions has gained popularity in recent years. However, a critical aspect when employing the GOR method is estimating the standard deviations associated with different magnitude types and subsequently determining the error variance ratio. To address this, the present study leverages recent research works to approximate the standard deviations associated with various magnitudes. By calculating the error variance ratio, derived from the estimation of magnitude uncertainties, the general orthogonal regression method was effectively applied to achieve the desired earthquake magnitude homogenization. Notably, this study fills a significant gap in research conducted in Algeria by developing regional empirical relationships using GOR with appropriate values of the error variance ratio. The expanded Mw dataset serves as a dependable resource used for other earthquake magnitudes homogenization, hence the preparation of a more extensive and unified Mw earthquake catalog for Northern Algeria and its neighboring areas. [ABSTRACT FROM AUTHOR]

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

Sichuan Province, as one of the active seismic regions in China, has historically suffered from strong earthquakes. The Xingwen Ms5.7 earthquake in 2018 and the Changning Ms6.0 earthquake in 2019, two moderate-magnitude earthquakes that occurred in Sichuan Province in recent years, happened in quick succession and triggered numerous landslides under similar geological structural conditions. These events provide a rare case study for researching the distribution characteristics and cumulative effects of landslides triggered by multiple earthquakes. This study aims to explore the distribution characteristics and superposition effects of landslides from these two earthquakes and to reveal the complexity and regularity of landslides triggered by multiple moderate magnitude earthquakes by comparing and analyzing the spatial distribution, scale size, and influence factors of landslides from the two earthquakes. The results show that 455 landslides were triggered by the Xingwen earthquake event and 511 landslides were triggered by the Changning earthquake event. The landslides are all mainly small and medium-sized, covering a total area of about 2.33 km2, with similar area frequency distribution trends. There is a certain correlation between the number and area of landslides and each factor. In addition, the landslides are mainly distributed in the middle and lower slopes of slower slopes, and the landslide H/L values are positively correlated with the slope gradient. This study reveals the spatial distribution characteristics and morphological parameter features of landslides triggered by the two earthquakes and their aftershocks, which provides a reference basis for landslide hazard assessment and risk management, as well as a case study and inspiration for the study of landslides under the action of multiple earthquakes. [ABSTRACT FROM AUTHOR]

The Eastern Anatolia Fault Zone (EAFZ) has caused destructive earthquakes. Kahramanmaraş and Hatay, located on the EAFZ, were hit by devastating earthquakes with magnitudes of 7.7, 7.6, and 6.3, respectively, in February 2023. A tectonic chain of disasters was seen in Hatay in a short time, first on 6 February 2023, with earthquakes centred in Kahramanmaraş and the subsequent intense earthquake series, and lastly on 20 February 2023, with the Hatay earthquake centred in the Yayladağ district. The lithological characteristics of the units in the region increased the destructive effects of the earthquakes. In addition, the location of the study area, where the EAFZ and the Death Sea Fault Zone are close to each other, increases the importance of research. This study aims to monitor the ground displacements caused by the earthquakes in Hatay. Sentinel-1A Synthetic Aperture Radar data was acquired on 29 January, and 10 and 22 February, and the Differential Interferometry Synthetic Aperture Radar method was applied. In addition, the elevation change was determined by using two-month global navigation satellite system data from the Continuously Operating Reference Station points (HAT2 and ONIY) in the study area. Thus, considering regional tectonics, ground movements resulting from the earthquakes on 6 and 20 February were identified and examined using geologic, geodesic, and remote sensing techniques. [ABSTRACT FROM AUTHOR]

The results of modeling the stress–strain state of the epicentral zone of the strong crustal earthquake Aketao, which occurred near Muji (China) on November 25, 2016, with magnitude Mw 6.6, are presented. The finite element method is used to model the stress–strain state in the epicentral zone with subsequent construction of stress intensity maps before and after the earthquake. The possibility to determine the location of the rupture origin and its extent, including estimation of the scalar seismic moment and the earthquake magnitude, is shown. The possibility to calculate the seismic moment rate as a function of time Mo(t) based on the model of the stress–strain state of rupture (earthquake focus) is presented for the first time, which allows obtaining synthetic seismograms and accelerograms of a potential earthquake in the future. [ABSTRACT FROM AUTHOR]

In the northern Andes, partitioning of oblique subduction of the Nazca plate beneath the South American continent induces a northeastward motion of the North Andean Sliver. The strain resulting from this motion is absorbed by crustal faults, which have produced magnitude 7+ earthquakes historically in the Andean Cordillera of Ecuador and southern Colombia. In order to quantify the strain in that area, we derive a high-resolution surface velocity map using InSAR time-series processing. We analyzed 6–8 yr of Sentinel-1 data and combined different satellite line-of-sight directions to produce a reliable velocity map in the east direction. We use interpolated GNSS data to express the velocity map with respect to Stable South America and remove the long-wavelength pattern due to the postseismic deformation following the 2016 Mw 7.8 Pedernales earthquake. The InSAR velocity map finds high east–west shortening strain rates along north–south trending structures within the Western Cordillera and the Interandean valley, with little deformation taking place east of them. This result strengthens the previous proposition of a ∼350 km long Quito-Latacunga tectonic block, forming a restraining bend in the overall right-lateral strike-slip fault system accommodating the northeastward escape motion of the North Andean Sliver. However, the high spatial resolution provided by InSAR indicates that previously proposed boundaries for this block need to be revised. In particular, InSAR results highlight high strain rates (>300 nstrain yr−1) along undescribed active structures, south and west of the proposed limits for the Quito-Latacunga block, respectively, in Peltetec and Ibarra regions. Interestingly, the two areas with the largest strain rates spatially correlate with the proposed areas of large historical earthquakes. Modeling of the InSAR and GNSS velocities in these areas suggests shallow coupling and high slip rates on structures which, previously, were not identified as active. We also demonstrate a slow-down of the shallow aseismic slip on the Quito fault after the Pedernales earthquake, suggesting that stress changes following large megathrust events might trigger transient slip behaviors on crustal faults. The high-resolution strain map provided by this work provides a new basis for future tectonic models in the Ecuadorian and southern Colombian Andes, and will contribute to the seismic hazard assessment in this highly populated area of the Andes. [ABSTRACT FROM AUTHOR]

Earthquakes begin with abrupt shifts along the faults. These movements release seismic waves that propagate through the Earth, shaking the ground as a result of the stored "elastic strain" energy being released. Property loss and human deaths occur due to improper design of structures under the earthquake loading conditions. It is observed that Peninsular India witnessed steady-to-serious earthquakes in the last 50 years. Amaravati is the prospective capital city of Andhra Pradesh State, which is situated on the Coromandel Coast of Peninsular India. The upcoming capital city, Amaravati, requires an earthquake hazard analysis because important engineering structures and infrastructure systems will be constructed in the near future. In this study, a probabilistic approach is used to assess the earthquake hazard for Amaravati City (latitudes: 16∘24 ′ 36 ′ ′ –16∘35 ′ 24 ′ ′ N and longitudes: 80∘24 ′ 25 ′ ′ –80∘36 ′ 18 ′ ′ E), India. The seismic risks of Amaravati City presented in terms of the configuration of ground motion parameters, peak ground acceleration (PGA), and spectral response acceleration ( S a ) at 0.05 s and 1 s for 2% and 10% Risks of Exceedance in 50 years, are produced. The uncertainties involved in seismic risk prediction are accounted for by selecting different attenuation relations developed for globally shallow crustal intraplate earthquakes with a logic tree approach. Additionally, the seismic risk values are disaggregated for Amaravati City (16∘31 ′ 37 ′ ′ N and 80∘29 ′ 46 ′ ′ E) to understand the individual contributions of seismic sources in terms of earthquake magnitude and site distance. The uniform hazard spectra are developed for the important places of the Amaravati Capital City and are compared with the Indian seismic code [IS 1893 (Part 1): Criteria for earthquake-resistant design of structures — Part 1: General provisions and buildings] for the rocky site. It is found that the estimated PGA values for Amaravati City are higher than the values recommended by IS 1893 (Part 1) for the rocky site. The results of this study will be very helpful for the composition of earthquake-resistant infrastructures in Amaravati City. [ABSTRACT FROM AUTHOR]