Journal of Seismology最新文献

The high-frequency decay parameter (κ) is investigated using the three-component broadband seismograms from 306 earthquakes with M_L 3.1–5.6 recorded at nine Iranian National Broadband Seismic Network (BIN) stations in the Alborz region and adjacent areas. The individual κ values are calculated for both the horizontal and vertical components of each record. The estimated mean horizontal and vertical κ values are 0.051 and 0.035 s, respectively, indicating slightly lower attenuation of high-frequency energy on the vertical component than the horizontal one. The dependence of the kappa values on path and source parameters such as distance, magnitude, and focal mechanism are also investigated. A clear increasing trend is observed for κ values with hypocentral distances for horizontal and vertical components. The zero-distance kappa (κ₀) values for the nine BIN stations are evaluated, and a mean value of 0.013 s is estimated, which is close to the values expected for generic rock sites. The obtained κ values show no significant correlation with the earthquake size in the magnitude range of our events. Furthermore, the κ values are found to be fairly similar for all faulting types, with a slight decrease in κ for strike-slip events; hence, the kappa values are deemed as independent of faulting type.

In 2013 there were reports on exceptionally deep earthquakes in ca. 40 km depth below the intraplate East Eifel Volcanic Field, Germany. Due to this observation the regional seismological monitoring network was improved to better explore this unusual seismicity. In order to acquire the necessary instruments, financial resources, and man power, a close partnership was initiated between the local state seismological service and academic research institutions. As an outcome the seismological field experiment called Deep Eifel Earthquake Project – Tiefe Eifel Erdbeben (DEEP-TEE) was accomplished which measures high-quality ground motion recordings since 2014. These measurements are used to study deep magmatic processes around the Laacher See Volcano (LSV) which was the site of a paroxysmal eruption just 13,079 years ago. As the DEEP-TEE network is located in a region with a high cultural noise and loose sediments, a careful site selection was a major task. Here, the network design is described and its recordings are used to determine 1-D seismic velocity models (vp, vs, and vp / vs) with station delay times to relocate the seismic events. The models include a priori information from active seismic experiments, especially in the mantle, to overcome resolution problems. The new velocity models allow to (re)locate the local earthquakes with horizontal and vertical uncertainties of ca. 0.5 km and 2.0 km, respectively. A special highlight of DEEP-TEE is the frequent observation of deep low-frequency (< 10 Hz) earthquakes whose hypocentres outline an active translithospheric channel, feeding the magmatic-fluid-volatile system underneath the LSV.

In our paper, we propose the most appropriate partition to depict the seismogenic zones of an active seismic region. To do so, the earthquake data considered are the location and magnitude. To determine three ellipsoidal layers of shallow, intermediate, and deep earthquakes, we switch from the geoid to a solid ball model and solve an appropriate multiple concentric sphere detection problem. Considering the Iberian Peninsula region, by using the Mahalanobis incremental algorithm with the help of the Mahalanobis area index and Mahalanobis minimal distance index, we first determine the most appropriate partition of earthquake positions, consisting of as compact and mutually separated clusters as possible. The result shows four clusters representing the main seismogenic zones of that area. In each of these clusters, we analyze some important earthquake properties, notably the hypocentral depths—a less researched property. Furthermore, we show how to generate a smooth surface best fitting the hypocenters in the considered area, and since the data contain many outliers, for that purpose we use the moving least absolute deviation method. In addition, for each cluster of the most appropriate partition, we ponder the question of estimating the Gutenberg–Richter’s b-value. To avoid the known drawbacks mentioned in the literature for estimating the b-parameter in the Gutenberg–Richter law, we propose the estimation of parameters a and b by using the least absolute deviation method. We also found that the hypocenters are notably deeper in the southwestern Iberian Peninsula and the Azores-Gibraltar fault zone, where the largest earthquakes take place. Finally, one should emphasize that the hypocenters study proposed in this research demonstrated that the most hazardous zone encompasses the most deep focuses. The CPU-time required for all calculations has been moderate. The methodology, used in this work, could easily be applied to other seismological areas, for which we list our freely available Mathematica-modules.

We propose a novel kinematic rupture modeling procedure for synthesizing broadband ground motions derived from the frequency-wavenumber integration algorithm. This procedure addresses two key issues in characterizing the rupture processes relevant to broadband seismic radiation: an accurate Green's function and a well-constrained kinematic source model. For the first issue, we derive the theoretical Green's function based on an improved dynamic stiffness matrix approach that effectively handles wave propagation in a 1D crustal velocity structure across a broad frequency band. For the second issue, we generate the hybrid source model that combines asperity slip and random slip over the fault plane to effectively implement constraints on the radiated energy during the whole rupture process. The accuracy and effectiveness of the proposed methodology are verified by comparing with the surface acceleration traces and Fourier spectra calculated by spectral element method. With the hybrid source model and crustal velocity structure applicable to the target area, the broadband (0–10 Hz) ground motion of the 2022 M_S6.9 Menyuan earthquake is synthesized. The amplitude, duration, and frequency content of the synthetic motions are systematically compared with those of the available observed records and ground motion attenuation relationships, as well as the spatial distribution characteristics of the near-field ground motions from the earthquake scenarios are presented. In conclusion, the case study of the Menyuan M_S6.9 earthquake demonstrates that the presented modeling procedure can estimate broadband ground motions rapidly and reliably from a physics-based kinematic rupture perspective.

We use a machine learning approach based on the Extreme Gradient Boosting algorithm to analyze the controlling factors of injection induced earthquakes (IIE) in northeast British Columbia (NE BC), particularly hydraulic fracturing induced seismicity within the Montney unconventional resource play. We compile comprehensive datasets incorporating seismological, operational, and stratigraphic features corresponding to various spatiotemporal grids to rank the controlling factors in terms of their importance. Our results show that, in general, the number of hydraulic fracturing stage is the most important factor controlling IIE, followed by cumulative volume of injected fluid and two depth-related features: depth difference between hydraulic fracturing injection and Montney formation and depth difference between Precambrian basement and Montney formation. Out of 168 datasets with varying spatiotemporal grids, the best model performance is achieved for the dataset with spatial grid of 0.1 degree and temporal grid of 10 days. Based on the Shapley Additive exPlanations values, we observe that a threshold of ~ 2200 in the number of hydraulic fracturing stages significantly encourages the occurrence of IIE while the threshold for cumulative volume of injected fluid is ~ 500,000 m³. Moreover, the occurrence of IIE is mostly encouraged when injections occur within ~ 300 m below the top of Montney formation (associated with the maximum thickness of this formation in NE BC) and at ~ 1700 m above the top of Precambrian basement.

We investigate the possibility of combined interpretation of macroseismic and strong-motion data for recent large earthquakes in the Aegean area. We employ macroseismic information derived from EMSC testimonies, as well as strong-motion information extracted from online sources provided by two Greek institutes (ITSAK and GEIN-NOA). The EMSC testimonies database (https://www.seismicportal.eu/testimonies-ws/) is a widely used inventory for the damage distribution of significant earthquakes. The collected data were first compared with the predicted macroseismic intensities using the empirical relation of Papazachos and Papaioannou (J Seismol 1:181–201, 1997) While the correlation between the observed and modeled data was found to be satisfactory, a systematic bias is evident for very high and very low values intensities derived from the reported EMSC testimonies. A Monte Carlo simulation approach was employed to identify the source of this bias, suggesting that it is a result of the large scatter of the EMSC data and the limits of the macroseismic scale used. To minimize this effect, a spatial grouping and smoothing approach was adopted for the EMSC dataset, resulting in significantly improved correlations with the available independent strong motion estimates, such as PGA and PGV. Using this correlation, we demonstrate through several examples that it is possible to reconstruct the main features of the damage pattern for strong earthquakes in the Aegean. This is achieved by jointly analyzing rapidly crowdsourced EMSC data and strong motion information, after appropriate processing of the raw macroseismic dataset.

Precise site response characterization is essential for understanding lithostratigraphic subsurface properties, seismic site effects, and soil classification within seismic networks. This study addresses the challenge of limited shear-wave velocity data within the upper 30 meters ((V_{S30})) at 39 stations of the Egyptian National Seismic Network (ENSN) in Northern Egypt. We employ the inversion of Horizontal-to-Vertical Spectral Ratio (HVSR) data from single-station ambient noise using an Elitist Genetic Algorithm (EGA) to estimate the shear-wave velocity profile at each station. This algorithm uses an equivalent linear approach based on the viscoelastic Kelvin-Voigt model to compute the theoretical site response of horizontally stratified soil layers. Inversion results from Multichannel Analysis of Surface Waves (MASW) conducted at five ENSN stations were incorporated to refine the input inversion parameters and control the genetic HVSR inversion outcomes. This approach effectively demonstrates the HVSR method’s ability to detect variations in the shear-wave velocity structure with depth and determine the average shear-wave velocity in the upper 30 meters. The obtained site-specific amplification data contributes to a more detailed understanding of site conditions, enabling precise determination of site classification and characterization factors. This facilitates refined Peak Ground Acceleration (PGA) estimations, thereby substantially enhancing the robustness of future seismic hazard assessments in Egypt.

We deconvolved regional seismograms to derive the azimuth-dependent source time functions for the 2019 Xiulin (Taiwan) earthquake. Subsequently, using rupture directivity and multiple-event analyses, we investigated the earthquake’s rupture features. The rupture directivity analysis revealed a rupture length of 11.5 km, a source duration of 7.37 s, and a rupture velocity (Vr) of 1.56 km/s, approximately 0.4 times the crustal S-wave velocity. The multiple-event analysis indicated two sub-ruptures during the earthquake. Notably, the average rupture and the sub-rupture shared the same product of Δσ_SVr³ (Δσ_S: static stress drop), adhering to a specific source-scaling relationship. In summary, the 2019 Xiulin earthquake exhibited a relatively low Vr and a relatively high Δσ_S. Additionally, we observed similarities between the 2018 Hualien and 2019 Xiulin earthquakes by comparing their fault parameters. The rupture directivity analysis revealed that both earthquakes occurred on the same westward-dipping plane, suggesting that the 2019 Xiulin earthquake represented the residual stress release from the 2018 Hualien earthquake. Compared with the Hualien earthquake, the Xiulin earthquake dissipated more energy per unit area to rupture the fault.

The present paper aims to investigate the implications of the seismological factors (strike angle, rake angle, dip angle, focal depth, and magnitude) on the characteristics (inundation depth/wave height and velocity) of earthquake-induced tsunamis. The uniform slip model is used primarily for characterizing the seismic source and exploring how various seismological factors affect tsunami characteristics. The observed tsunami characteristics is physically explained in far and near fields in light of the seismological factors and wave characteristics. Since unidirectional analysis is generally adopted for tsunami design, sensitivity of structural response to orientations is studied in detail. It has been shown that there exists an orientation that can be determined in terms of pure tsunami characteristics in which the structural response achieves its maximum. Simple case studies are illustrated, and it is shown that, for a deterministic tsunami scenario, the maximum values of inter-story drift may be estimated by a single unidirectional analysis resolving velocity components in the orientation defined herein as the most intense orientation. When assessing structural responses, both uniform and non-uniform slip models are considered simultaneously. Interestingly, although the uniform slip model may provide an unconservative estimate of structural response, it can still accurately predict the orientation that corresponds to the maximum response, similar to the non-uniform slip model.

This study offers a comprehensive forecast of conditional earthquake recurrence probabilities in the North Anatolian Fault Zone (NAFZ), utilizing advanced statistical models and temporal analyses, aiming to discern the likelihood of future earthquakes. We sought to contribute insights into seismic hazard assessment by analyzing earthquakes (M_W ≥ 4.0) from 1900–2022, employing Inverse Gaussian (aka Brownian Passage Time) and Lognormal distribution models, categorizing the NAFZ into ten seismic zones. Rigorous model fitness assessments were conducted, including Akaike and Bayesian information criteria, Kolmogorov–Smirnov, and Anderson–Darling tests. Conditional probabilities were calculated across eleven temporal intervals (0–50 years) and eleven residual periods (1–50 years), starting on January 1, 2023, and extending into the future. Results reveal nuanced earthquake probabilities, highlighting a heterogeneous seismic hazard landscape. Probability forecasts surge within the initial five years and continue to rise for another five years, underscoring the spatiotemporal sensitivity and widespread earthquake hazard. The findings enhance the understanding of seismic hazard assessment, extending the future applicability potential to global seismic regions. Acknowledging uncertainties and relying on instrumental data, future research could explore more extensive areas and refined data sources, along with new modeling techniques, to enhance forecasting accuracy. The findings stress the need for earthquake preparedness throughout the study area, not only for the anticipated large earthquakes but especially for medium-magnitude earthquakes. This remark manifestly underscores the necessity to develop strategies to reduce possible damage and loss of life stemming from the collapse of non-engineered and rural building stock unevenly scattered along the NAFZ that remain vulnerable to moderate-magnitude earthquakes.