Search

Bayesian network (BN) is an important tool in probabilistic seismic risk analysis (PSRA) due to its holistic nature and powerful probabilistic inference capabilities. However, while the information that can be stored by BN includes variable values, probability distributions, and relationships between variables, it does not involve event quantities. The results obtained from PSRA and probabilistic seismic hazard analysis (PSHA) are commonly frequency‐related (the number of occurrences per unit time), fundamentally describing event numbers. BN assumes a fixed event number relationship between nodes, but the aftershock counts vary for different mainshock magnitudes. This limitation further restricts its effectiveness in lifespan PSRA for structures. Therefore, this study aims to propose an enhanced BN (EBN) for modeling aftershock PSHA (APSHA) considering frequency information. This paper first introduces the modeling method using BN, including PSHA and a simplified model of APSHA using Båth's law. Next, an EBN that can effectively address frequency issues between the mainshock and aftershocks is presented for modeling APSHA considering the modified Omori's law, while the mathematical principles of both forward and backward inferences for the EBN are elaborated in detail. Then, the article carefully analyzes the utilization of the EBN for APSHA modeling under different scenarios where the information regarding the mainshock is known to varying extents, followed by the extension of the EBN in a time domain to obtain time‐dependent aftershock hazard. Finally, an example of APSHA in a specific location in China is illustrated. [ABSTRACT FROM AUTHOR]

Modelling seismic wavefields in complex 3-D elastic media is the key in many fields of Earth Science: seismology, seismic imaging, seismic hazard assessment and earthquake source mechanism reconstruction. This modelling operation can incur significant computational cost, and its accuracy depends on the ability to take into account the scales of the subsurface heterogeneities varying. The theory of homogenization describes how the small-scale heterogeneities interact with the seismic waves and allows to upscale elastic media consistently with the wave equation. In this study, an efficient and scalable numerical homogenization tool is developed, relying on the similarity between the equations describing the propagation of elastic waves and the homogenization process. By exploiting the optimized implementation of an elastic modelling kernel based on a spectral-element discretization and domain decomposition, a fully scalable homogenization process, working directly on the spectral-element mesh, is presented. Numerical experiments on the entire SEAM II foothill model and a 3-D version of the Marmousi II model illustrate the efficiency and flexibility of this approach. A reduction of two orders of magnitude in terms of absolute computational cost is observed on the elastic wave modelling of the entire SEAM II model at a controlled accuracy. [ABSTRACT FROM AUTHOR]

The Lacq area in southwest France has been associated with continuous moderate induced seismic activity since 1969. However, the mechanisms driving this induced seismicity are not fully understood: reservoir depletion has been proposed as the main factor, and more recently wastewater injection has been suggested to play a more important role. The interpretation of these mechanisms relies heavily on the quality of earthquake locations, which we prove to be weak due to a lack of local instrumentation for several years. In order to provide the most complete and reliable induced event catalogue for the studies of the Lacq induced seismicity mechanisms and seismic hazard, we made an exhaustive compilation, analysis and improvement of all available catalogues. We also provided new earthquake detections and relocations in a 3-D velocity model from past and present temporary deployments never used for studying the Lacq area. Important remaining location uncertainties lead us to also carefully sort the events according to their location confidence, defining 3 classes of events (unconstrained location, location constrained within 2–3 km and 1–2 km, respectively). This new harmonized catalogue and the identification of well-constrained events, covering 50 yr of induced seismicity, allow us to propose that wastewater injection is almost certainly the main mechanism driving the seismicity, with (i) most of the constrained events located within the reservoir boundaries and (ii) the released seismic energy variations following variations in injection operations at different scales. In particular, we have also highlighted a change in the injection–seismicity relationship around 2010–2013. From 2013, despite lower injection volumes, seismicity remained persistent and some clusters of earthquakes were detected predominantly in spring, summer and early autumn, except in winter periods. From 2016, we observed a strong temporal relationship between days with higher rate/volume injections (approximately above 400 m3 d−1) and both clustered events and higher magnitude earthquakes (greater than 2.4). [ABSTRACT FROM AUTHOR]

To estimate the connectivity of a road network, it is crucial to evaluate the correlation of hazard intensities among individual bridge locations since the probability of multiple bridges being damaged simultaneously depends on the degree of this correlation. However, research on connectivity assessment of bridge networks considering spatial correlations associated with flood intensities is scarce in the literature. When quantifying the spatial correlation of flood intensities, modeling based on the stream distance rather than the Euclidean distance is required, taking into account that river flow is restricted only within the stream network. To achieve this purpose, a novel methodology is proposed to evaluate the spatial correlation of a stream network based on a geostatistical linear model and stream network covariance models. In addition, this study considers the spatial correlation of seismic hazard intensity. With the proposed method, it is possible to identify which bridges play an important role in ensuring the connectivity of the road network under multiple hazards, i.e. flood and seismic. As an illustrative example, the proposed method is applied to a hypothetical bridge network in Kumamoto Prefecture, Japan. The results demonstrate that improved network connectivity can be achieved by implementing a relevant retrofitting strategy for important bridges. [ABSTRACT FROM AUTHOR]

Recent earthquakes demonstrate that prioritizing the retrofitting of buildings should be of the utmost importance for enhancing the seismic resilience and structural integrity of urban structures. To have a realistic results of the pounding effects in modeling process of retrofitting buildings, the present research provides seismic Probability Factors (PFs), which can be used for estimating collision effects without engaging in intricate and time-intensive analysis. To include the low-, to mid-rise buildings, the 3-Story, 5-Story, and 9-Story adjacent steel and Reinforced Concrete (RC) moment-resisting frames were modeled in OpenSees software capable to take into account the structure in a state of collapse during the analysis, which can provide the real condition of buildings under seismic excitations. Results of analysis confirmed that the impact force can considerably affect the moment–rotation curve of beams and columns, in which, it can affect the structural response of structures during earthquakes. Therefore, seismic PFs proposed to examine the possibility of changes in the performance levels and fragility assessments. Moreover, proposed PFs can be used as coefficient factors to facilitate the retrofitting process of buildings and improve the environmental effects. [ABSTRACT FROM AUTHOR]

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

Applying machine learning to continuous acoustic emissions, signals previously deemed noise, from laboratory faults and slowly slipping subduction‐zone faults, demonstrates hidden signatures are emitted that describe physical details, including fault displacement and friction. However, no evidence currently exists to demonstrate that similar hidden signals occur during seismogenic stick‐slip on earthquake faults—the damaging earthquakes of most societal interest. We show that continuous seismic emissions emitted during the 2018 multi‐month caldera collapse sequence at the Kı̄lauea volcano in Hawai'i contain hidden signatures characterizing the earthquake cycle. Multi‐spectral data features extracted from 30 s intervals of the continuous seismic emission are used to train a gradient boosted tree regression model to predict the GNSS‐derived contemporaneous surface displacement and time‐to‐failure of the upcoming collapse event. This striking result suggests that at least some faults emit such signals and provide a potential path to characterizing the instantaneous and future behavior of earthquake faults. Plain Language Summary: Applications of machine learning have revealed that continuous acoustic emissions from laboratory earthquake experiments contain continuous, hidden signatures that describe the fault slip. In these laboratory studies, the acoustic emissions signals that were previously deemed to be dominantly noise, are found to be rich with details that can describe physical properties such as the fault displacement, friction, and fault thickness. By applying similar machine learning approaches, it was discovered that signatures of surface displacement exist in the seismic emissions from slowly slipping subduction zone faults. However, there has yet to be similar evidence observed during seismogenic stick‐slip on earthquake faults–the damaging earthquakes of most societal interest. Here we study a repeating caldera collapse sequence with short enough repeat times to mimic the experiments performed in the laboratory. We find that seismic emissions from seismogenic fault slip associated with the 2018 caldera collapse at the Kı̄lauea volcano in Hawai'i, also contain hidden signatures informing of instantaneous surface displacement associated with fault slip at depth, as well as time‐to‐failure of the upcoming slip event. These observations suggest that at least some seismogenic faults emit such signals, and provide a potential path to characterizing the instantaneous and future behavior of earthquake faults. Key Points: Features extracted from 30 s of continuous seismic waveforms contain information about contemporaneous GNSS ground displacementsA gradient boosted tree model predicts GNSS ground displacements and timing of the next caldera collapse eventThe observations suggest some seismogenic faults emit precursory signals, providing a potential path to characterize behavior of faults [ABSTRACT FROM AUTHOR]

The existence of back-arc thrust faults along the eastern part of the Sunda Arc, ranging westwards from Flores to the western tip of Java, has been recognised for decades. In contrast, it is still unknown whether such back-arc thrust faults exist in Sumatra, which is located in the western part of the Sunda Arc. To investigate the possible existence of back-arc thrusts in Sumatra, we examine regional earthquake data reported by the Agency for Meteorology, Climatology and Geophysics of Indonesia, as well as global earthquake data reported by the International Seismological Centre and the United States Geological Survey. It appears that back-arc thrusts in the study area are not extensively developed, unlike in the eastern Sunda Arc, which may be caused by oblique subduction beneath the Sumatran forearc. The stress associated with the trench-parallel component of subduction is largely accommodated by the ~ 1650-km-long dextral strike-slip fault zone of the Great Sumatran Fault. The seismicity data from various sources do, however, show that there is a dipping seismogenic zone in several parts of the back-arc region of Sumatra, in the opposite direction to the NNE subduction of the Indo-Australian plate. This new observation may be related to the presence of spatially intermittent back-arc thrust faults in the study area, which may need to be taken into account when improving Indonesia's national earthquake hazard maps. [ABSTRACT FROM AUTHOR]

In this paper, a probabilistic methodology based on image analysis is proposed for earthquake‐induced loss estimation in rectangular reinforced concrete shear walls (RCSWs) in compliance with FEMA P‐58. The methodology is developed using a databank of 285 surface crack patterns gathered from the result of experimental research on 99 rectangular RCSWs with wide‐ranging structural and geometric characteristics. For the complexity extraction, three fractal geometry indices of the damaged specimens are taken into consideration. Fragility functions are generated to determine the probability of exceeding a FEMA P‐58 compliant damage state based on the various methods of repair for specific complexity indices. The fragility functions are obtained using four common probabilistic distributions including lognormal, Weibull, gamma, and beta. The fitness of the fragility curves is examined by two goodness‐of‐fit tests, namely the Kolmogorov–Smirnov test and Lilliefors test. Results show that the Weibull is the best‐fitting distribution for the majority of damage states and succolarity possesses the best results in goodness‐of‐fit tests among fractal geometry indices. Empirical loss indices are also derived in this paper aimed at optimizing the goodness‐of‐fits. Finally, the proposed procedure is utilized for a sample specimen from the databank at various damage levels. [ABSTRACT FROM AUTHOR]

Tsunami inundation maps are crucial for understanding the impact of tsunamis and planning mitigation measures. Our research focuses on creating a database of stochastic tsunami scenarios along the Chilean subduction zone and probabilistic inundation maps for 11 coastal cities. We divided the Chile-Perú subduction zone into four seismic segments based on historical seismicity. Stochastic rupture scenarios, ranging from 8.0 to 9.6 magnitudes, were generated using the Karhunen-Loeve expansion. The Stochastic Reduced Order Model (SROM) helped select representative tsunami scenarios for each segment and magnitude bin. We then used the NEOWAVE model to simulate these scenarios to an inundation level, creating probabilistic tsunami maps for various return periods. Our findings reveal that local geography significantly influences tsunami inundation, with some areas facing high inundation risks while others experience minimal impacts. As a result, a uniform planning and design criterion across the entire country is not advisable; site-specific studies are necessary. These probabilistic scenarios can provide tailored solutions for different Chilean coastal cities, enhancing their resilience. Additionally, this research marks the first comprehensive probabilistic tsunami hazard analysis for the Chilean coast, considering multiple seismic sources, marking a crucial step toward full tsunami risk assessment for coastal communities. [ABSTRACT FROM AUTHOR]

The New Zealand Community Fault Model (NZ CFM) is a publicly available representation of New Zealand fault zones that have the potential to produce damaging earthquakes. Compiled through collaborative engagement between New Zealand earthquake-science experts, this first edition (version 1.0) of the NZ CFM builds upon previous compilations of earthquake-source active fault models with the addition of new and modified information. Developed primarily to support an update of the New Zealand National Seismic Hazard Model, the NZ CFM comprises two principal components. The first dataset is a two-dimensional map representation of the surface traces of 880 generalised fault zones. Each fault zone is assigned specific geometric and kinematic attributes, including uncertainties, supplemented with a subjective quality ranking focused primarily on the confidence in assigned slip rates. The second component is a three-dimensional representation of the fault zones as triangulated mesh surfaces that are projected down-dip from the two-dimensional mapped traces to a geophysically-defined maximum fault rupture depth. This article summarises the compilation and parameterisation of the NZ CFM, along with background on its relation to predecessor datasets, and forward applications to probabilistic seismic hazard assessment and physics-based earthquake models currently being developed for Aotearoa New Zealand. [ABSTRACT FROM AUTHOR]

The Alborz Mountains are among the areas exhibiting high tectonic and seismic activity in northern Iran. Studying key parameters of tectonic structures, including quantitative analysis and observational studies, in such active regions is essential to identify potential active faults and assess the consequent seismic hazards. This study focuses on seismicity and seismotectonics by analyzing seismic parameters, including b-value, mean seismic activity rate, earthquake recurrence time, seismic moment, and fractal dimension derived from micro and teleseismic data. The b-values vary between 0.6 and 1.1 in the tectonically active parts of the study area, corresponding with the reverse/thrust and strike-slip active faults. Large earthquakes might be prone to occur at 10–25 km depth because both catalogues show low b-values (b < 1.0) concentrations at this depth range. The high fractal dimension (> 1.5), high seismic activity rate, large seismic moment parameters, and its continuously increasing trend. Short recurrence periods (20–50 years) of M 6.5 events also emphasize the high seismic activity and high seismic hazard. On the other hand, the prevalence of low b-values is notably observed in areas encompassing densely populated cities such as Rasht, Lahijan, Amol, Babol, Sari, Behshahr, Gorgan, and the megacity of Tehran. Furthermore, we have identified asperities where the Gorgan Plain, the Khazar, and the Alamutrud Fault Zones are located. These findings emphasize the seismic hazard potential in the identified areas and urban centers within the study area. Therefore, particular attention should be directed towards areas exhibiting low b-values when assessing and mitigating seismic hazards. It underscores the necessity for additional focus on seismic hazard assessment and implementation of mitigation strategies in the Alborz region. [ABSTRACT FROM AUTHOR]

Detecting surface deformation associated with low-magnitude ( M w ≤ 5 ) seismicity using interferometric synthetic aperture radar (InSAR) is challenging due to the subtlety of the signal and the often challenging imaging environments. However, low-magnitude earthquakes are potential precursors to larger seismic events, and thus characterizing the crustal displacement associated with them is crucial for regional seismic hazard assessment. We combine InSAR time-series techniques with a Deep Learning (DL) autoencoder denoiser to detect the magnitude and extent of crustal deformation from the M w = 3.4 Gallina, New Mexico earthquake that occurred on 30 July 2020. Although InSAR alone cannot detect event-related deformation from such a low-magnitude seismic event, application of the DL method reveals maximum displacements as small as (±2.5 mm) in the vicinity of both the fault and earthquake epicenter without prior knowledge of the fault system. This finding improves small-scale displacement discernment with InSAR by an order of magnitude relative to previous studies. We additionally estimate best-fitting fault parameters associated with the observed deformation. The application of the DL technique unlocks the potential for low-magnitude earthquake studies, providing new insights into local fault geometries and potential risks from higher-magnitude earthquakes. This technique also permits low-magnitude event monitoring in areas where seismic networks are sparse, allowing for the possibility of global fault deformation monitoring. [ABSTRACT FROM AUTHOR]

The 2016 magnitude (MW) 5.5 Gyeongju earthquake, which occurred in Korea near assumed epicenters of several substantial historical earthquakes and Quaternary fault segments, underscores the importance of seismic hazard assessment in the region. However, uncertainties about potential seismic sources make evaluating the potential for a moderate-to-large earthquake challenging. Microearthquake monitoring through a dense seismic network can provide crucial insights into the regional seismic characteristics. An extensive temporary seismic array known as the Gyeongju Hi-density Broadband Seismic Network (GHBSN) was established to investigate microearthquake activity in the southeastern Korean Peninsula. This included the zone of aftershocks from the 2016 Gyeongju earthquake sequence. The GHBSN comprises 200 broadband stations located at approximately 4.5 km intervals in an area of approximately 60 × 60 km2 around the epicenter of the mainshock. A total of 4,773 events were detected from November 2017 to December 2021, including 3,935 events within the GHBSN. The detected events were categorized into five seismic regions excluding quarry blasting sites, that is, the 2016 Gyeongju earthquake region, eastern part of the Ulsan Fault, 2017 Pohang earthquake region, eastern offshore Gyeongju, and western part of the Miryang Fault. A local magnitude scale was developed for the southeastern Korean Peninsula using events detected through the GHBSN. This reflects the distance attenuation and site conditions of the GHBSN stations for earthquakes. An event catalog was created using two automatic detection methods based on the measurement of the energy ratio. This provided high-resolution hypocenter parameters at a completeness magnitude (MC) of 0.0 despite the seismic environment of the network being exposed to high cultural noise. The Gutenberg-Richter b-value was estimated as 0.82 ± 0.02 for all events and 1.01 ± 0.02 for those inside GHBSN. This implies that the seismicity reflects a representative intraplate seismic environment. Testing the obtainability of the focal mechanism solutions showed that the GHBSN outperformed the regional network. Depending on the relationship between the magnitude and frequency of earthquakes, a relatively large number of small earthquakes can provide detailed information on the geometric properties of the causative faults and the state of the acting stress. High-precision microearthquake observation and analysis through GHBSN could provide an unprecedented opportunity with seismic datasets to understand the seismogenesis of the southeastern Korean Peninsula, including the zone of aftershocks of the 2016 Gyeongju earthquake. [ABSTRACT FROM AUTHOR]

On February 6, 2023, a devastating earthquake with a moment magnitude of MW7.8 struck the town of Pazarcik in south-central Türkiye, followed by another powerful earthquake with a moment magnitude of MW7.6 that struck the nearby city of Elbistan 9 h later. To study the characteristics of surface deformation caused by this event and the influence of fault rupture, this study calculated the static coseismic deformation of 56 stations and dynamic displacement waveforms of 15 stations using data from the Turkish national fixed global navigation satellite system (GNSS) network. A maximum static coseismic displacement of 0.38 m for the MW7.8 Kahramanmaras earthquake was observed at station ANTE, 36 km from the epicenter, and a maximum dynamic coseismic displacement of 4.4 m for the MW7.6 Elbistan earthquake was observed at station EKZ1, 5 km from the epicenter. The rupture-slip distributions of the two earthquakes were inverted using GNSS coseismic deformation as a constraint. The results showed that the Kahramanmaras earthquake rupture segment was distinct and exposed on the ground, resulting in significant rupture slip along the Amanos and Pazarcik fault segments of the East Anatolian Fault. The maximum slip in the Pazarcik fault segment was 10.7 m, and rupture occurred at depths of 0-15 km. In the Cardak fault region, the Elbistan earthquake caused significant ruptures at depths of 0-12 km, with the largest amount of slip reaching 11.6 m. The Coulomb stress change caused by the Kahramanmaras earthquake rupture along the Cardak fault segment was approximately 2 bars, and the area of increased Coulomb stress corresponded to the subsequent rupture region of the MW7.6 earthquake. Thus, it is likely that the MW7.8 earthquake triggered or promoted the MW7.6 earthquake. Based on the cumulative stress impact of the MW7.8 and MW7.6 events, the southwestern segment of the East Anatolian Fault, specifically the Amanos fault segment, experienced a Coulomb rupture stress change exceeding 2 bars, warranting further attention to assess its future seismic hazard risk. [ABSTRACT FROM AUTHOR]

The seismic b -value in Gutenberg–Richter law is an important parameter in earthquake science research and earthquake risk assessment. People have tried to use b -values for short-term earthquake forecasts, and this requires the premise of estimating reliable b -values for real-time seismic catalogues. However, estimating b -values for real-time catalogues, which are usually of poor qualities, is usually faced with many difficulties and problems. In this study, through a series of numerical tests, we investigate the performance of three methods, including the commonly used maximum-likelihood estimation method and two relatively new b -value estimation methods, namely the b -positive and K–M slope methods, on calculating b -values for real-time seismic catalogues. We also apply these three methods to both observed seismic catalogues (the seismic sequence in the Costa Marchigiana, Italy, and a high-resolution early aftershock sequence of the 2023 two M w ∼7.8 earthquakes in Türkiye) and synthetic real-time seismic catalogues. The results in this study show that it seems difficult to obtain accurate b -values for real-time earthquake catalogues by each of these three methods, but the combination of these methods may give a better judgment—if all three methods suggest that the change in b -value is significant, the probability of making a correct decision is very high. Facing the uncertainty of b -value estimation that always exists, we advocate exploring the effectiveness of standard b -value estimation strategies in practical applications. [ABSTRACT FROM AUTHOR]

Conditional Spectrum (CS), characterized by a conditional mean and conditional standard deviation, serves as a target spectrum linking seismic hazard information to ground motion selection for seismic demand analysis. Current Ground Motion Selection and Modification (GMSM) methods aim to align with this target spectrum but face challenges due to the limited availability of recorded ground motions and potential modifications, leading to difficulties in ensuring selected ground motions accurately reflect site characteristics. Addressing this issue, the study presents an algorithm to select hazard-consistent CS-based records utilizing a stochastic ground motion model with a dual objective: (1) alleviate the need for scaling during the selection process, and (2) select records consistent with the target hazard and the contributing causal scenarios. To achieve both objectives, the study generates a database of hazard-targeted ground motions utilizing the kriging surrogate with scenarios sampled from the disaggregation matrix. Then, a postprocessing step explicitly considers causative parameters in the selection process. The algorithm's potential to select site-specific ground motions is demonstrated using sites in the Western United States, providing insights into the computational cost and accuracy. Additionally, statistical comparisons are conducted to explore circumstances where similar hazard consistency can be achieved without the postprocessing step, reducing the overall computational cost. Finally, the selected ground motions are favorably compared to those selected through traditional conditional spectrum-based approaches based on their spectral shape and ground motion intensity measures. [ABSTRACT FROM AUTHOR]

Pounding between adjacent structures subjected to earthquake actions can cause significant damage. Due to the many uncertainties inherent to the seismic input and the impact phenomenon, a probabilistic assessment of the occurrence of seismic pounding and of its consequences on the structural performance is necessary. This work analyzes the problem of pounding by considering a single-degree-of-freedom benchmark system surrounded by rigid boundaries and subjected to a stochastic earthquake input. Although simplified, the model is representative of several realistic configurations, such as base-isolated systems surrounded by moat walls or bridge decks near the bridge abutments. The problem is cast in non-dimensional form and a parametric study is carried out to evaluate the influence of the identified non-dimensional input parameters on the statistics of the response. A probabilistic demand model is developed for the impact forces via non-linear regression, with the demand expressed as a function of the identified non-dimensional parameters. This model provides an estimate of median pounding force and of its dispersion given the seismic intensity of the input. Finally, global sensitivity analysis is used to rank the model parameters in terms of their influence on the system performance. [ABSTRACT FROM AUTHOR]

Ground motion prediction equations (GMPEs) play a key role in seismic hazard assessment (SHA). Considering the seismo-tectonic, geophysical, and geotectonic characteristics of a target region, all the GMPEs may not be suitable in predicting the observed ground motion effectively. With a fairly large number of published GMPEs, the selection and ranking of suitable GMPEs for the design of logic trees in SHA for a particular target region have become a necessity of late. This paper presents a detailed quantitative evaluation of performance of 16 GMPEs against recorded ground motion data in two target regions, characterized by distinct seismo-tectonic, geophysical, and geotectonical nature. The dataset comprises 465 three-component spectral accelerograms corresponding to 122 earthquake events. The suitability of a GMPE is tested by two widely accepted data-driven statistical methods, namely, likelihood (LH) and log-likelihood (LLH) method. Different suites of GMPEs are shown suitable for different periods of interest. The results will be useful to scientists and engineers for microzonation and estimation of seismic design parameters for the design of earthquake-resistant structures in these regions. [ABSTRACT FROM AUTHOR]

The Himalayan region and its surrounding area are one of the most seismically active zones in the world which have significant economic and societal impact. It governs the seismicity of highly populous countries like India, China, Pakistan, Nepal, Bhutan and Afghanistan which account for more than 40% population of the world. Therefore, the complex interaction between seismic parameters and transient seismic events needs to be thoroughly addressed at the regional scale. This study highlights the spatial distribution of earthquake hazard parameters and the temporal variation in seismicity of the Himalayas and its nearby regions by employing the maximum likelihood approach using historical records as well as instrumentally recorded earthquake data of the years 1900–2021. An empirical relation is developed to convert the body wave magnitude (Mb) and surface wave magnitude (Ms) to moment magnitude (Mw). The seismic parameters, namely maximum regional magnitude (Mmax), b-value, and mean seismicity rate (λ0), are estimated for 13 defined zones. Further, the seismic behaviours of the study area are evaluated through the return periods (RP) of earthquakes and the fractal dimension (Dc) of the individual zone. Considering the temporal variation of seismicity and RP of Mw ≥ 6, a new index , i.e. earthquake susceptibility index (ESI6), is developed to identify the zones which are susceptible to Mw ≥ 6 earthquakes. The zones: Central Himalayas 2 (CH2), Western Himalayas (WH), North of MCT 1 (NMCT1) and South of MCT 2 (SMCT2) are identified to be highly susceptible to earthquakes of Mw ≥ 6. The present analysis will motivate researchers and engineers from government and non-government organizations to collaborate for improved policy making in the seismically active Himalayan region concerning land-use planning, insurance, and catastrophe preparation. [ABSTRACT FROM AUTHOR]

In this study, comprehensive analytical and parametric studies were conducted on seismic performance of concrete structures equipped with self-centered unbonded post-tensioned hybrid wall system in comparison with traditional structural wall system. For this purpose, analytical models were developed and to further study the seismic performance of self centering hybrid wall, parametric analysis was performed considering four parameters: wall aspect ratio, initial stress of post-tensioned (PT) tendons, the total area of PT tendons, the total area of mild bars. The performance of buildings was evaluated under non-linear quasi cyclic and time history method considering two seismic hazard levels, the design-based earthquake (DBE) level and the risk-targeted maximum considered earthquake (MCE) level. Hysteresis response, damage severity and pattern index estimation, energy dissipation ability and damping ratio, relative self-centering efficiency (RSE), residual drift, peak roof drift and inter-story drift ratio, floors acceleration, shear force ratio, column curvature ductility, prestressing and gap opening effect of all buildings were studied. The results of the parametric analysis showed by increasing the prestressing ratio, wall damage severity, residual drift and energy dissipation capacity were decreased and structural seismic demand and RSE increased, while increasing mild bars was the most efficient method for improving the energy dissipation ability. [ABSTRACT FROM AUTHOR]

The Greek National Annex for current Eurocode 8 has adopted the seismic hazard zonation map published in 2003 as part of the modifications to the Greek Seismic Code EAK 2000 (EAK 2003). This map, which followed the catastrophic earthquakes that hit the country between 1978 and 2001, includes three seismic hazard zones with peak ground acceleration (PGA) ranging between 0.16 and 0.36 g. In this paper, following the significant progress that has been made worldwide in the last two decades towards the improvement of the definition of seismic actions and the seismic hazard maps using fully probabilistic models, we make a complete proposal for the Greek National Annex of the ongoing revision of Eurocode 8, which includes a new seismic hazard zonation map for Greece, as well as a novel site categorization scheme and related site amplification factors. To this end, we use the results of the European Seismic Hazard Model, ESHM20, as reported by Danciu et al. (The 2020 update of the European Seismic Hazard Model: Model Overview, 2021) which will be adopted as informative reference for the seismic hazard at European level in the forthcoming revision of Eurocode 8 (CEN/EC8). The herein proposed ground shaking zonation for rock conditions includes five zones with PGA values ranging between 0.13 and 0.37 g. For each zone, two newly proposed ground motion parameters, i.e., Sα,475 and Sβ,475, are provided, which are the two parameters used for anchoring the elastic response spectrum as defined in CEN/EC8, along with all the other necessary parameters for the definition of the elastic response spectrum, including site amplification. The proposal for the new seismic zonation is supported by a preliminary investigation of the impact of its adoption on the seismic design of new structures and on the seismic risk of the current building stock in Greece, to help gain a better insight on how important the differences imposed by the new zonation might be for the end-users and the administration. [ABSTRACT FROM AUTHOR]

To overcome negative effects of traditional masonry infilling walls (MIWs) on the seismic resilience of a self-centering prestressed concrete (SCPC) frame, a novel SCPC frame with sliding infill walls (SCPC-SIW frame) is proposed. This study compares the seismic performance of the SCPC-SIW frame and the SCPC frame with MIWs (SCPC-MIW frame) through quasi-static tests, fragility analysis, and risk assessment. To begin, quasi-static tests on single-story SCPC-SIW and SCPC-MIW frame specimens are performed to compare their failure characteristics, hysteresis response, energy dissipation, and self-centering ability. The numerical simulation methods for SCPC-SIW and SCPC-MIW frame specimens are then presented and validated. Subsequently, two four-story SCPC-SIW frames and two four-story SCPC-MIW frames are designed, and their dynamic response under MCE is preliminary analyzed. Finally, the fragility analysis and risk assessment of these multi-story SCPC-SIW and SCPC-MIW frames are conducted to determine the probability of their peak inter-story drift ratio (PIDR), residual inter-story drift ratio (RIDR), and peak floor acceleration (PFA) exceeding the specified limit states under any intensity earthquake and within 50 years. The results indicate that, except for cracks caused by fatigue damage appearing on the SIW at the end of loading, the SCPC-SIW frame specimen remains undamaged, whereas the SCPC-MIW frame specimen exhibits diagonal step cracks on the MIW. The hysteresis curve of the SCPC-SIW frame specimen exhibits an ideal and repeatable flag shape, whereas the stiffness and strength of the SCPC-MIW frame specimen degrade during the test. Besides, the probability of exceeding the 4% PIDR and exceeding 0.2% and 0.5% RIDRs within 50 years for the SCPC-SIW frame is significantly lower than that for the SCPC-MIW frame. The SCPC25-MIW frame has a higher probability of exceeding the 1 g PFA within 50 years than the SCPC25-MIW frame. In other cases, the SCPC-SIW frame has a lower probability of exceeding 1 g, 2 g, and 3 g PFA within 50 years than the SCPC-MIW frame. [ABSTRACT FROM AUTHOR]

The Bucaramanga seismic nest has the highest concentration in volume of intermediate depth seismic events with light and moderate magnitudes (Mb > 4.8) worldwide. Despite the nest depth (Zhypo ≥ 100 km), these events play a crucial role in the seismic hazard assessment for several cities in northern South America (NoSAm), particularly those situated close to their epicenters. Moreover, these earthquakes are widely felt across the country, even hundreds of kilometers away from the nest. This paper assesses the performance of commonly used subduction intraslab Ground Motion Models (GMMs) in predicting the updated nest database gathered and processed by the Colombian Geological Survey. This analysis confirms the necessity of a partially non-ergodic ground motion model for estimating the spectral accelerations produced by Bucaramanga nest earthquakes in northern South America. The GMM presented herein is the first model developed specifically for seismic nests in the region and is conceived as a regionalization of the recent NGA-Sub Abrahamson and Gülerce (Earthq Spectra 38(4):2638−2681, 2022) GMM. Additionally, we provide estimates of the variance components at both the earthquake and station levels and compare the developed GMM with the spectral accelerations recorded for typical earthquakes, for the highest magnitude earthquake in the database, and for a recent Bucaramanga nest earthquake having a moment magnitude over 5. [ABSTRACT FROM AUTHOR]

Slopes have a significant impact on the ground motion characteristics, which can aggravate the damage degree of building structures during a strong earthquake. However, many studies have focused on the design response spectra under flat site conditions and fewer researchers have investigated the impact of slope topography on the design response spectra. In this study, the numerical simulation is used to obtain the seismic response of slopes and the differential evolution algorithm is used to obtain the standardized response spectra of the acceleration time histories along the ground surface behind the slope crest. The impacts of slope height (H), slope gradient (i), average shear wave velocity in the top 30 m (VS30) and distance from the slope crest (x) on the characteristic parameters of the design response spectra are then investigated. The results show that H, i, VS30 and x have a little influence on the normalized second inflection point period (mean(Tg/Tg,ff)) but a great influence on the normalized plateau value (mean(αmax/αmax,ff)). Specifically, both mean(Tg/Tg,ff) and mean(αmax/αmax,ff) show a trend from increasing first to decreasing and stabilizing finally as x increases; the mean(αmax/αmax,ff) shows an increasing trend as H increases, but a decreasing trend as i or VS30 increases. Finally, to provide some guidance for the seismic design of building structures near slopes, two approximate relationships are proposed: (1) between mean(Tg/Tg,ff) and x, and (2) between mean(αmax/αmax,ff) and H, i, VS30, x. The main innovation of this paper is that the relationship between the characteristic parameters of the design response spectra and the slope site characteristic parameters is clearly summarized and quantified for the first time. [ABSTRACT FROM AUTHOR]

Several studies have been carried out to assess the building's seismic vulnerability, to mitigate the seismic risk in urban areas, which is one of the most devastating natural hazards causing considerable economic and human losses. These studies must be incorporated to improve the planning of urban areas to have resistant and resilient cities in case of disasters. The seismic feedback has shown that the build-back-better concept has a direct impact on the city's economic growth. In this paper, the existing buildings' resilience is assessed, in order to highlight the capacity of these last to keep the functionality when an earthquake occurs. This building's resilience has been determined for three types of structures: masonry, reinforced concrete and steel, according to the reconstruction time, the reconstruction cost and the damage state. This last has been assessed from empirical fragility curves developed using the log normal distribution for five structures typologies (Unreinforced masonry; reinforced masonry; RC frame; RC shear walls/Mixed RC frame-RC shear walls and steel structures). A seismic resilience scenario was performed using a geographic information system (GIS) and applied for the Blida city (Algeria) classified as a high seismic zone according to Algerian seismic regulations. According to the results found, the old districts of the Blida city, built mainly during the so-called pre-code period, will not be resilient in case of disaster. The other districts built later in the low-code and high-code periods will have, respectively, medium and good functionality. [ABSTRACT FROM AUTHOR]

A five story (G + 4) residential structure is positioned on 15°, 30°, and 45° slopes to be explored in this study in terms of vulnegrability and compared to the same structure resting on flat ground 0°. The RC frame models were constructed in accordance with Eurocode 8 and then subjected through a series of 10 ground motion records. In accordance with Vision 2000 performance limit states (PLS), this research provided the use of nonlinear static analysis (NL-SA) and nonlinear dynamic analysis (NL-DA) methodologies to assess seismic risk performance and vulnerability of structures resting on various slope angles. Incremental Dynamic Analysis (IDA) and Pushover Analysis (POA) capacity curves, as well as the fragility curve and the collapse margin ratio, are generated for the four selected models (M0, M15, M30, M45). The results show that the RC frame model M45, located on a 45°-degree incline, is the most vulnerable to damage. The risk of damage to the RC frame M0 is minimal because it is not elevated off the ground. To this end, the relative degrees of vulnerability among the frames were determined to be as follows: M45 > M30 > M15 > M0. [ABSTRACT FROM AUTHOR]

Probabilistic seismic hazard assessments (PSHAs) provide the scientific basis for building codes to reduce damage from earthquakes. Despite their substantial impact, little is known about how well PSHA predicts actual shaking. Recent PSHA for California, Japan, Italy, Nepal, and France appear to consistently overpredict historically observed earthquake shaking intensities. Numerical simulations show that observed shaking is equally likely to be above or below predictions. This result from independently developed models and datasets in different countries and tectonic settings indicates possible systematic bias in the hazard models, the observations, or both. Analysis of possible causes shows that much of the discrepancy is due to a subtle and rarely considered issue: the conversion equations used in comparing the models--which forecast shaking as peak ground acceleration or velocity--and observations--parameterizations of qualitative shaking reports. Historical shaking reports fill a crucial data gap, but more research is warranted on how qualitative observations relate to instrumental shaking measures for earthquakes. [ABSTRACT FROM AUTHOR]

The paper reports the first results of an experiment in northern Finland during winter 2022–2023 that aimed at studying seismic events caused by seasonal freezing in the so-called critical zone (CZ) of the Earth. These events have attracted public attention recently, as multiple reports about them from local inhabitants in Arctic and sub-Arctic areas appeared on social networks. To make an instrumental study of such events, to reveal the relationship between their occurrence and winter weather conditions, and to evaluate the possible hazard, we installed two high-resolution seismic arrays with co-located soil temperature stations at two sites in Finland, one of them being in the city of Oulu in the sub-Arctic area (65.04° N, 25.61° E) and the other one above the polar circle in the municipality of Sodankylä (67.36° N, 26.63° E). The equipment recorded continuous seismic and soil temperature data during November 2022–April 2023. Based on reports from the inhabitants of Talvikangas (Oulu) about the ground shaking and unusual noises on 6 January 2023 and their observations of new fractures on the roads there, we selected the time interval for the identification of frost quakes that originated during that day from continuous seismic records in Talvikangas and in Sodankylä. During the selected time interval, the extremely rapid air temperature drops of about -1.4 °C h -1 in Talvikangas and -0.88 °C h -1 in Sodankylä were observed. We identified and located two types of seismic events – namely, frost quakes with frequencies of about 10–20 Hz, with waveforms like those of tectonic events, and irregularly shaped frost tremors with frequencies of about 120–180 Hz. The sources of frost quakes in Talvikangas are mainly located on irrigated wetland, while in Sodankylä, about 50 % of registered frost quakes were caused by ice fracturing on the Kitinen River. However, several relatively strong events, with their origin in the wetlands, were also recorded. A significant number of sources of frost tremors are confined to wetland areas cut by irrigation channels and to roads cleaned from snow during winter both in Talvikangas and in Sodankylä. We calculated ground accelerations and ground velocities for the strongest events from both groups and compared them to equivalent properties of other seismic signals, like distant local earthquakes in the area, mining production blasts, and cargo train vibration. Our study shows that high-frequency frost tremors corresponding to surface fracture opening in the uppermost frozen surface layer of a thickness of up to 5 cm can directly damage infrastructure objects like roads and basements of buildings. Surface waves, produced by frost quakes and propagating inside the shallow soil layer, have large enough ground accelerations at epicentral distances of hundreds of metres. Therefore, frost quakes should be considered a phenomenon that can potentially damage infrastructures, and they have to be taken into account in seismic hazard assessments. Our research is the first instrumental study of seismic events originating from wetland areas. These events occur as a result of the interaction between the uppermost layer of the solid Earth's CZ and atmosphere processes that deserves further study. [ABSTRACT FROM AUTHOR]

We applied an interdisciplinary approach to analyze the late Quaternary activity of the Sava Fault in the Slovenian Southern Alps. The Sava Fault is an active strike-slip fault, and part of the Periadriatic Fault System that accommodated the convergence of Adria and Europe. It is one of the longest faults in the Southern Alps. Using high-resolution digital elevation models from lidar and photogrammetric surveys, we were able to overcome the challenges of assessing fault activity in a region with intense surface processes, dense vegetation, and relatively low fault slip rates. By integrating remote sensing analysis, geomorphological mapping, structural geological investigations, and near-surface geophysics (electrical resistivity tomography and ground penetrating radar), we were able to find subtle geomorphological indicators, detect near-surface deformation, and show distributed surface deformation and a complex fault pattern. Using optically stimulated luminescence dating, we tentatively estimated a slip rate of 1.8 ± 0.4 mm/a for the last 27 ka, which exceeds previous estimates and suggests temporal variability in fault behavior. Our study highlights the importance of modern high-resolution remote sensing techniques and interdisciplinary approaches in detecting tectonic deformation in relatively low-strain rate environments with intense surface processes. We show that slip rates can vary significantly depending on the studied time window. This is a critical piece of information since slip rates are a key input parameter for seismic hazard studies. [ABSTRACT FROM AUTHOR]

In probabilistic coastal hazard assessments based on the Joint Probability Method, historical storm data is used to build distribution models of tropical cyclone atmospheric parameters (i.e., central pressure deficit, forward velocity, radius of maximum wind, and heading direction). Recent models have used a range of assumptions regarding the dependence structure between these random variables. This research investigates the performance of a series of joint distribution models based on assumptions of parameter independence, partial-dependence (i.e., dependence between only central pressure deficit and radius of maximum wind), and full dependence (i.e., dependence between each pair of tropical cyclone atmospheric parameters). Full dependence models consider a range of copula models, such as the Gaussian copula and vine copulas that combine linear-circular copulas with Gaussian or Frank copulas. The consideration of linear-circular copulas allows for the characterization of correlation between linear variables (e.g., central pressure deficit) and circular variables (e.g., heading direction). The sensitivity of the results to different joint distribution models is assessed by comparing hazard curves at representative locations in New Orleans, LA (USA). The stability of hazard curves generated using a Gaussian copula considering variation in the selection of the zero-degree convention is also assessed. The tail dependence between large central pressure deficit and large radius of maximum wind associated with various copula models are also compared using estimated conditional probability. It is found that the linear-circular Frank vine copula model improve the stability of hazard curves and maximize tail dependence between large central pressure deficit and large radius of maximum wind. However, the meta-Gaussian copula model exhibits performance within this study region that was generally consistent with the tested vine copulas and have the advantage of being easier to implement. [ABSTRACT FROM AUTHOR]

In order to seismically characterize Chile's northern Coquimbo Region, data from 2003 to 2020 were considered. The region was divided into 30 zones of 0. 5 ∘ latitude and 0. 5 ∘ longitude and non-extensive statistical physics was used. Both, the Sotolongo–Costa–Posadas (SCP) and Mathai models were deployed to analyze the magnitude-frequency distribution. A sub-division into cells of the catalog allowed to demonstrate that systems with value of q ∼ 1 present exponential behavior, while it was expected to obtain q > 1 , by superimposing sub-systems supporting the superstatistical model. Thus, by subdividing the Coquimbo region into south and north, we found that in both zones the entropic index is greater than 1, q > 1 , However, in the southern zone the long-range effects are greater than in the north, according to the value obtained, which means both sectors are well described under a nonextensive statistical model, be it the SCP model or the Mathai one. The entropic index is q > 1 and in both cases R 2 > 0.99 . As the region is considered as a whole, the nonextensive statistical distribution is the more adequate one. With respect to probabilistic seismic hazard assessment, Mathai's model proved to have the better fit. Thus, the frequency-interevent time distribution was used for different limit magnitude values. Our analysis showed that the probability occurrence of a seismic event in the region's north is lower than in the south considering the same period. In the north the behavior is of Poissonian type. [ABSTRACT FROM AUTHOR]

Seismic moment accumulation rate is a fundamental parameter for assessing seismic hazard. It can be estimated geodetically from either fault‐based modeling, or strain rate‐based calculations, where fault‐based models largely depend on the rheological layering and the number of faults. The strain‐rate method depends on an unknown (Kostrov) thickness used to convert strain rate into moment rate. In Part 1 of this study, we use three published fault‐based models from southern California to establish the value of the Kostrov thickness such that the total moment from the strain‐rate approach, calculated from the fault model‐predicted strain rate, matches the fault‐based approach. Constrained thickness estimates of 7.3, 9.7, and 11.5 km (6.4–13.0 km, including uncertainties) suggest that the 11 km value used in previous studies may be too large and a lower value may be more accurate. In Part 2 we use calibrated values of Kostrov thickness, along with the latest compilation of GNSS velocity data, to partition moment rate into on‐fault and off‐fault moment rate, where off‐fault varies from 32%–43% of the total moment rate. The largest uncertainty is related to the method used to interpolate sparse GNSS data. Lastly, we compare our estimates of total moment rate (mean: 2.13 ± 0.42 × 1019 Nm/yr) with the historical seismic catalog. Results suggest that including uncertainties in Kostrov thickness brings fault‐based geodetic moment rate closer to the seismic moment release (particularly when aseismic afterslip is accounted for), while the (uncertain) values of off‐fault moment rate push geodetic moment rates to be larger than seismic moment rates. Plain Language Summary: One commonly‐used method of evaluating the future earthquake potential of a known fault is to estimate the moment rate accumulating along that fault. In other words, one can estimate how much earthquake energy is accumulating over time, caused by the forces that propel plate boundary motion along fault systems. Two ways to do this are: (a) using detailed fault models of plate boundary motion, which are constrained by satellite‐based measurements of surface motion or (b) using those satellite‐based measurements directly through the estimation of regional strain rate. Here, we investigate the uncertainties present in the latter method by comparing previously published estimates of fault‐based moment rate, with their equivalent strain rate‐based versions. We estimate uncertainties related to the strain‐rate based method, which can lead to an over‐ or under‐estimation of earthquake potential on a given fault system. In addition, we explore the off‐fault moment rate accumulation in southern California which can help identify areas of enhanced moment accumulation and thus increased seismic hazard. Key Points: Previously published fault‐based models can constrain a Kostrov thickness range of 6.4–13.0 km, including uncertaintiesDifferences between strain rate moment estimates and fault‐based estimates suggest 32%–43% off‐fault moment rate in southern CaliforniaThe largest uncertainty in estimating moment rate from strain rate is the degree of smoothing used to estimate strain from geodetic data [ABSTRACT FROM AUTHOR]

Coseismic slip on the Patton Bay splay fault system during the 1964 Mw 9.2 Great Alaska Earthquake contributed to local tsunami generation and vertically uplifted shorelines as much as 11 m on Montague Island in Prince William Sound (PWS). Sudden uplift of 3.7–4.3 m caused coastal lagoons along the island's northwestern coast to gradually drain. The resulting change in depositional environment from marine lagoon to freshwater muskeg created a sharp, laterally continuous stratigraphic contact between silt and overlying peat. Here, we characterize the geomorphology, sedimentology, and diatom ecology across the 1964 earthquake contact and three similar prehistoric contacts within the stratigraphy of the Hidden Lagoons locality. We find that the contacts signal instances of abrupt coastal uplift that, within error, overlap the timing of independently constrained megathrust earthquakes in PWS—1964 Common Era, 760–870 yr BP, 2500–2700 yr BP, and 4120–4500 yr BP. Changes in fossil diatom assemblages across the inferred prehistoric earthquake contacts reflect ecological shifts consistent with repeated draining of a lagoon system caused by >3 m of coseismic uplift. Our observations provide evidence for four instances of combined megathrust‐splay fault ruptures that have occurred in the past ∼4,200 years in PWS. The possibility that 1964‐style combined megathrust‐splay fault ruptures may have repeated in the past warrants their consideration in future seismic and tsunami hazards assessments. Plain Language Summary: During the Mw 9.2 1964 Great Alaska Earthquake, both the subduction zone and the crustal faults connected to the subduction zone (called splay faults) slipped, lifting shorelines up to 11 m on Montague Island in Prince William Sound (PWS) and contributing to local tsunami generation. The sudden uplift cut off tidal connection to coastal lagoons on Montague Island's northwest coast, producing a change to a drier, freshwater environment. The sudden environmental change created a clear sedimentary change from pre‐earthquake lagoon silt to post‐earthquake rooted soil in the stratigraphy of a study site known as Hidden Lagoons. Using the stratigraphic evidence of the 1964 uplift as a guide, we investigated deeper into the subsurface of Hidden Lagoons to see if there were previous instances of subduction zone and splay fault activation. We discovered three previous stratigraphic boundaries marking times when earthquakes uplifted the land. Changes in the species of diatoms across these boundaries show that the marine lagoon system was repeatedly drained by earthquakes causing over 3 m of uplift. These uplift events match the timing of four of the eight known prehistoric subduction zone earthquakes in PWS, suggesting that splay faults have slipped with the subduction zone multiple times over the past ∼4,200 years. Key Points: We find widespread stratigraphic evidence for the 1964 M9.2 earthquake and three prehistoric earthquake contacts on Montague Island, AlaskaStratigraphic and diatom analyses suggest ruptures of splay faults may have occurred in conjunction with 4 of 8 documented Alaska‐Aleutian subduction zone earthquakesHazard assessments may want to consider the tsunami potential with possible future 1964‐style combined megathrust‐splay fault ruptures [ABSTRACT FROM AUTHOR]

Precipitation nowcasting (forecasting locally for 0–6 h) serves both public security and industries, facilitating the mitigation of losses incurred due to, e.g., flash floods and is usually done by predicting weather radar echoes, which provide better performance than numerical weather prediction (NWP) at that scale. Probabilistic nowcasts are especially useful as they provide a desirable framework for operational decision-making. Many extrapolation-based statistical nowcasting methods exist, but they all suffer from a limited ability to capture the nonlinear growth and decay of precipitation, leading to a recent paradigm shift towards deep-learning methods which are more capable of representing these patterns. Despite its potential advantages, the application of deep learning in probabilistic nowcasting has only recently started to be explored. Here we develop a novel probabilistic precipitation nowcasting method, based on Bayesian neural networks with variational inference and the U-Net architecture, named DEUCE. The method estimates the total predictive uncertainty in the precipitation by combining estimates of the epistemic (knowledge-related and reducible) and heteroscedastic aleatoric (data-dependent and irreducible) uncertainties, using them to produce an ensemble of development scenarios for the following 60 min. DEUCE is trained and verified using Finnish Meteorological Institute radar composites compared to established classical models. Our model is found to produce both skillful and reliable probabilistic nowcasts based on various evaluation criteria. It improves the receiver operating characteristic (ROC) area under the curve scores 1 %–5 % over STEPS and LINDA-P baselines and comes close to the best-performer STEPS on a continuous ranked probability score (CRPS) metric. The reliability of DEUCE is demonstrated with, e.g., having the lowest expected calibration error at 20 and 25 dBZ reflectivity thresholds and coming second at 35 dBZ. On the other hand, the deterministic performance of ensemble means is found to be worse than that of extrapolation and LINDA-D baselines. Last, the composition of the predictive uncertainty is analyzed and described, with the conclusion that aleatoric uncertainty is more significant and informative than epistemic uncertainty in the DEUCE model. [ABSTRACT FROM AUTHOR]

Earthquake hypocentres are routinely obtained by a common inversion problem of P - and S -phase arrivals observed on a seismological network. Improving our understanding of the uncertainties associated with the hypocentral parameters is crucial for reliable seismological analysis, understanding of tectonic processes and seismic hazard assessment. However, current methods often overlook uncertainties in velocity models and variable trade-offs during inversion. Here, we propose to unravel the effects of the main sources of uncertainty in the location process using techniques derived from the Global Sensitivity Analysis (GSA) framework. These techniques provide a quantification of the effects of selected variables on the variance of the earthquake location using an iterative model that challenges the inversion scheme. Specifically, we consider the main and combined effects of (1) variable network geometry, (2) the presence of errors in the analyst's observations and (3) errors in velocity parameters from a 1-D velocity model. These multiple sources of uncertainty are described by a dozen of random variables in our model. Using a Monte Carlo sampling approach, we explore the model configurations and analyse the differences between the initial reference location and 100 000 resulting hypocentral locations. The GSA approach using Sobol's variance decomposition allows us to quantify the relative importance of our choice of variables. It highlights the critical importance of the velocity model approximation and provides a new objective and quantitative insight into understanding the sources of uncertainty in the inversion process. [ABSTRACT FROM AUTHOR]

For regional hazard analysis or engineering applications, it is necessary to simulate a group of correlated ground motions containing information from given recordings. A new method is presented to conditionally generate ground motions at unobserved points using actual recordings in this localized region. This method is based on an extension of the traditional conditional simulation using a wavelet packet. Utilizing the advantages of wavelet-packet transformation, the time and frequency characteristics of ground motions are effectively identified. Besides by decomposing the signal into non-overlapping sub-frequency bands, it is possible to conditionally simulating stationary, space-time, and Gaussian random fields. These simulated motions are consistent with the actual recordings in terms of temporal variations in the frequency domain and its design spectrum, and their coherence functions satisfy the target coherence values. Two numerical examples have been provided to illustrate the capability of the proposed method: the simulation of ensembles of earthquake accelerograms using actual recordings and blind tests in SMART-1 array. [ABSTRACT FROM AUTHOR]

We present a detailed one-dimensional (1-D) velocity model of the Lake Van Basin and its surrounding region, alongside precise hypocenter locations, utilizing seismic data from the aftershocks of the 23 October 2011 Lake Van earthquake (Mw = 7.1). The 1-D minimum velocity model is computed by the VELEST program by analyzing body wave traveltimes and station corrections. Encompassing a geographical area of 180 x 90 km² centered around Lake Van, the study incorporated seismic data from 10 newly deployed stations, complementing the existing network of the Kandilli Earthquake Research Institute. A comprehensive manual analysis was conducted on a dataset comprising 7643 events occurring between 23 October 2011 and 21 January 2015. Among these, 1193 well-located events recorded by 16 stations were selected, encompassing 48,387 P-wave and 26,913 S-wave arrival times. The iterative simultaneous inversion technique was applied to refine velocity and hypocenter parameters while mitigating the influence of near-surface velocity heterogeneity and station elevation through station corrections. The resulting 1-D velocity model delineates eight distinct layers up to a depth of 39 km, including a 3-km-thick sedimentary layer, while determining the VP/VS ratio for each layer. Rigorous testing procedures were implemented to ensure the stability and accuracy of the velocity structure and aftershock locations. The relocation of the aftershock sequence using the new 1-D velocity model revealed significant shifts in the distribution pattern, notably concentrating relocated events towards the vicinity of the main shock area. This study underscores the efficacy of the VELEST software in deriving a robust 1-D velocity model and refining hypocenter locations for the Lake Van region. The insights gained enhance our understanding of the region's seismotectonic and have implications for seismic hazard assessment and risk mitigation strategies. [ABSTRACT FROM AUTHOR]

For reinforced concrete (RC) column with biaxial eccentricity, the conventional design methods usually use the fixed eccentricity criterion to check its resistance, which may underestimate the variations of column resistance. Based on the load statistics compatible with the codes, the random properties of biaxial eccentricity are analyzed with Monte Carlo simulation (MCS) for representative columns in regular frame structures under both vertical load and wind load. Then, the tested capacity results of 103 relevant column specimen are collected from literatures. The uncertainty of the resistance model is analyzed for the reciprocal load method in code ACI 318-14. Based on the criterion of both random eccentricity and fixed eccentricity, the probability regarding load bearing capacity exceedance is analyzed for columns by MCS with different design parameters (e.g. axial compression ratio, etc.). The results indicate that based on the prescribed load statistics, the random properties of eccentricities along two principal directions are mainly controlled by the stochastic wind load, leading to that the eccentricities along two principal directions show an approximate perfect correlation; the random biaxial eccentricity has a significant influence on resistance variations and the maximum coefficient of variation is as large as 0.73. [ABSTRACT FROM AUTHOR]

The calculation of the spatial distribution of ground motion is one of the most important steps in earthquake scenarios. The advancements in machine learning algorithms and the release of new ground motion data can enable improvements in the reliability and accuracy of this component. We developed an artificial neural network (ANN) ground motion model using a compiled database from two subsets with measured Vs30 from the Pan-European strong motion database and the NGA-West2 database. The ANN model employs five input parameters: moment magnitude (Mw), hypocentral depth, Joyner–Boore distance (Rjb), shear wave velocity in the top 30 m (Vs30), and faulting type. The outputs of the ANN are the RotD50 horizontal components of common intensity measures used in seismic risk assessment: PGA, PGD, PGV, Arias Intensity, and 5% damped spectral acceleration at 27 periods from 0.01 to 4.0 s. A mixed-effects modelling approach was followed to train the ANN and partition the ground motion variability into between-event and between-site terms. The input parameter scaling relationships were studied and demonstrated physically sound trends of the ground motion with respect to Mw scaling, distance attenuation, and site amplification. The predicted median response spectra for several combinations of Mw and Rjb were compared to common ground motion models for Europe, and the results are discussed. The developed ANN is used in a companion study to calculate the hazard footprints for several historical earthquakes in the Balkan region. [ABSTRACT FROM AUTHOR]

Seismic risk assessment of building portfolios has been traditionally performed using empirical ground motion models, and scalar fragility and vulnerability functions. The advent of machine learning algorithms in earthquake engineering and ground motion modelling has demonstrated promising advantages. The aim of the present study is to explore the benefits of employing artificial neural networks (ANNs) in earthquake scenarios for spatially-distributed building portfolios. To this end, several recent major seismic events in the Balkan region were selected to assess damage and economic losses, considering different modelling approaches. For the assessment of the seismic demand, the ANN developed in the companion study and common ground motion models for Europe were adopted. For the vulnerability component, recent ANN models and existing scalar fragility and vulnerability functions for the Balkans were used. The estimates of all modelling cases were compared against the aggregated damage and economic loss data observed in the aftermath of these events. The findings of this study suggest that overall, the ANNs led to damage and economic loss estimates closer to the observations. [ABSTRACT FROM AUTHOR]

This article presents the findings of a study on the directionality effect observed in strong motion records. We set out to establish ratios between several seismic intensity measures that depend on sensor orientation (e.g., GMar, Larger) and others that are orientation-independent (e.g., RotDpp, GMRotDpp, and GMRotIpp), with the intention of proposing multiplicative correction factors. The analysis included an evaluation of the impact of site conditions, ground motion intensity, earthquake magnitude, and hypocentral distance on these ratios. Following a concise overview of the directionality effects and the associated intensity measures, the Costa Rican Strong Motion Database, comprising a total of 4199 horizontal accelerograms (two components), was employed to determine the correction factors. The analysis was carried out for 5% damped response spectra within the 0.01–5 s period range. The study focuses on orientation-independent intensity measures that are derived by combining the maximum values from the recorded motions. In the comprehensive analysis of the complete database, a trend was observed between these intensity measures and the magnitude of the earthquake along with the hypocentral distance. Specifically, records from earthquakes with greater magnitudes exhibited a lower maximum spectral response to the geometric mean of the response spectra of the as-recorded (ar) components ratio (RotD100/GMar), similar to records from earthquakes with larger hypocentral distances. Based on these findings, a proposal was put forth to estimate RotD100 values using GMar values. This ratio can prove useful in transforming data from previous seismic hazard studies, including those applied in many seismic codes, and in defining the maximum anticipated seismic intensity for design purposes in a more straightforward manner. [ABSTRACT FROM AUTHOR]

In the territory of Dushanbe city, the capital of Tajikistan, detailed geological and geophysical data were collected during geophysical surveys in 2019–2020. The data comprise 5 microtremor array measurements, 9 seismic refraction tomography profiles, seismological data from 5 temporary seismic stations for standard spectral ratio calculations, 60 borehole datasets, and 175 ambient noise measurements. The complete dataset for Dushanbe was used to build a consistent 3D geologic model of the city with a size of 12 × 12 km2. The results of the seismological and geophysical surveys were compared and calibrated with borehole data to define the boundaries of each layer in the study area. The Leapfrog Works software was utilized to create a 3D geomodel. From the 3D geomodel, we extracted six 12 km long 2D geological cross-sections. These 2D geological cross-sections were used for 2D dynamic numerical modeling with the Universal Distinct Element Code software to calculate the local seismic response. Finally, the dynamic numerical modeling results were compared with the amplification functions obtained from the seismological and ambient noise data analysis. The 2D dynamic numerical modeling results allowed a better assessment of the site effects in the study area to support seismic microzonation and the determination of local peak ground acceleration changes in combination with regional seismic hazard maps. In addition, our results confirm the strong seismic amplification effects noted in some previous studies, which are attributed to the influence of local topographic and subsurface characteristics on seismic ground motions. [ABSTRACT FROM AUTHOR]

Following the 2016 Chauk earthquake in Bagan (Myanmar), numerous old pagodas and temples suffered severe damage. This research presents a study on the seismic hazard analysis of the Bagan city in Myanmar, based on a probabilistic framework focussing on analysing 43 temples with their associated local soil information. To this end, two seismic source models are developed based on the tectonic setting of the region and information available. Instrumental and historical records are compiled from both literature and international earthquake catalogues while conducting catalogue completeness. This study uses state-of-the-art ground motion models to perform probabilistic seismic hazard analysis and develop seismic hazard maps for different return periods in the region. Results are also expressed for selected temples in the region in terms of site-specific uniform hazard spectra. The findings indicate significant seismic activity, with peak ground acceleration in the region ranging from 0.25 to 0.36 g for a return period of 2475 years, 0.22–0.32 g for a return period of 975 years, and 0.18–0.24 g for a return period of 475 years. The updated hazard levels indicate that the literature slightly underestimates hazard in the region under study. [ABSTRACT FROM AUTHOR]

In past, several ground motion prediction models (GMMs) were developed in Himalayan region. However, there is no comprehensive review available for the developed GMMs. In order to fill the gap, in the present study an attempt has been made to review the existing GMMs for Himalayan region. The study focuses on the seismotectonic setting of the region, source of seismic data, GMMs used for conducting hazard analysis of different locations and various developed GMMs by several researchers. Further, applicability of these generated GMMs was inspected thoroughly using available seismic records of Indo-Himalayan region. For this purpose, predicted peak ground acceleration (PGA) and peak spectral acceleration (PSA) obtained by using the GMMs for different magnitudes and distances are compared with recorded data by computing root mean square error (RMSE) and Chi-square value. Moreover, log-likelihood (LLH) scoring method has been applied and proper weights of the GMMs have been proposed. [ABSTRACT FROM AUTHOR]

In order to avoid the casualties caused by damaged buildings during strong earthquakes, it's important and essential to understand the seismic design specifications of buildings. The motion of a building depends on the interferometry of building and ground motion, the coupling between building and ground, and the mechanical properties of the building. We applied deconvolution technique to the motion recorded to separate the building response and calculated the structural parameters (including traveling wave velocity, resonant frequency and attenuation parameter). Therefore, we can check medium's state by tracking these parameters to avoid damaged building collapse in the next mega-earthquake. We deployed a seismograph array in the building to record the earthquakes and few months of ambient noise data. In addition, we divided the structure into lower and higher floors to calculate the layering velocity. We found that the wave velocities of the lower and higher floors are significantly different but the former exhibit stable variation. For the monitoring phase, we tried different stacking time-lengths and calculated the related traveling wave velocities which are similar to the analysis in earthquakes. From the above results, we concluded that the physical parameters of the building can monitor the healthy condition of structure. Finally, we hope these results would be helpful to build a long-term monitoring of building's healthy status and the assessment of seismic hazard. [ABSTRACT FROM AUTHOR]