Journal of Seismology最新文献

Synthetic aperture radar interferometry (InSAR) is a powerful technique for quantifying the co- and postseismic deformation of large earthquakes at the Earth’s surface. However, surface deformation caused by small- to moderate-sized earthquakes is rarely revealed by InSAR because their coseismic slip occurs mostly at significant depths (> 5 km), with limited deformation on the Earth’s surface. In this work, we investigate the surface deformation associated with the Mw 5.4 May 28, 2016, Mihoub (Algeria) earthquake and its source parameters. Interferograms calculated from Sentinel-1 TOPSAR images of both ascending and descending orbits show that, despite its small size, the earthquake produced evident deformation on the Earth’s surface, suggesting that the coseismic slip took place at a relatively shallow depth. We model the coseismic displacement fields extracted from InSAR time series using Bayesian approaches in two stages: 1) we model the coseismic slip data using uniform slip on a single fault to constrain the fault parameters. 2) We explore a variable slip model with varying rakes on the discretized fault obtained in the first stage. The modelling results indicate that the earthquake was associated with a ~ 0.5 m shallow oblique reverse slip, mostly between depths of 1.5 and 4.5 km, on a NE–SW-trending and SE-dipping thrust fault, which is in good agreement with the focal mechanism solutions of the earthquake deduced from seismology. This study demonstrates that the multitemporal InSAR (MTI) method may constrain surface displacements when the coseismic interferograms of moderate- to small-sized earthquakes are noisy and hence difficult to unwrap. The newly identified seismogenic Mihoub fault has implications for seismic hazard assessment in northern Algeria.

In Germany, the highest seismic hazard is associated with the Albstadt Shear Zone (ASZ) in the western Swabian Jura, a low mountain range in southwest Germany. The region is affected by continuous micro-seismic activity with the potential for damaging earthquakes (nine events with ML (ge ) 5 in the 20(^{th}) century). Within the AlpArray and StressTransfer projects nine temporary seismic stations have been installed in the region of the ASZ to densify the permanent seismic monitoring. In October 2018 and September 2019, the state seismological survey (LED) detected two low-magnitude earthquake sequences with hundreds of events in the area. The temporarily densified local network allows us to systematically analyze these sequences and to search for other sequences by applying a template-matching routine on data from 2018 to 2020. In total, six earthquake sequences could be identified with at least 10 events. The four largest sequences (> 50 events) consist of two fore- and aftershock sequence and two earthquake swarms. Earthquake swarms were so far not observed around the ASZ. Precise relative hypocenter relocations and the determination of fault-plane solutions allow us to propose a seismotectonic model based on the three imaged fault types: (a) The well-known NNE-SSW striking sinistral strike-slip ASZ at depths of 5-10 km, (b) a NW-SE striking dextral strike-slip fault zone at depths of 11-15 km beneath the Hohenzollerngraben (HZG), a shallow, apparently aseismic NW-SE striking graben structure; this NW-SE fault zone possibly is an inherited zone of weakness in the basement and facilitated the development of the HZG and (c) at the intersection of the ASZ with the NW-SE fault zone, complex faulting in form of NNW-SSE striking sinistral strike-slip and normal faulting possibly to accommodate local stresses.

The Central Ionian Islands of Cephalonia and Ithaca belong to the most seismically active Greek region, mainly due to the presence of the dextral Cephalonia-Lefkada Transform Fault Zone. The study area has experienced strong earthquakes in the twentieth century, including the destructive 1953 sequence with maximum intensity 9.0. The Paliki peninsula, western Cephalonia, hosted two strong earthquakes (M_w = 6.1 and 5.8) in 2014, with ground acceleration reaching ~ 560 cm/s² and 735 cm/s², respectively. This study updates the seismic hazard evaluation in Cephalonia and Ithaca using new data and computational techniques to reduce epistemic uncertainties. The probabilistic approach of Cornell and McGuire was used, and the uncertainties are reduced through data variability of the source models, seismicity data, and Ground Motion Prediction Equations using a logic tree approach, sampled by implementing the Latin Hypercube Sampling method. The spatial distribution of Peak Ground Acceleration and Peak Ground Velocity for return periods of 475 and 950 years indicates low variation in the entire study area and that the Paliki peninsula possesses the highest level of seismic hazard. Additionally, site-specific analysis across the three main towns, Lixouri and Argostoli in Cephalonia and Vathi in Ithaca, reveals that Lixouri has the highest level of seismic hazard, while Vathi the lowest.

This paper introduces machine learning-based Turkiye-specific ground motion models for the geometric mean horizontal component of peak ground velocity (PGV). PGV is a significant intensity metric to measure and diagnose potential earthquake damage in structures. Reliable prediction of PGV is of essential importance in precise calculations of seismic hazard. The efficiencies, reliabilities, and capabilities of various machine learning algorithms, including Random Forest, Support Vector Machine, Linear Regression, Artificial Neural Network, Gradient Boosting, and Bayesian Ridge Regression, are evaluated and compared. The most recently compiled Turkish strong motion database, which consists of over 950 earthquakes occurring from 1983 to 2023, is used for shaping the models' ability to learn and make accurate predictions. Three feature selection methods- Least Absolute Shrinkage and Selection Operator, Recursive Feature Elimination, and Pearson’s Correlation- representing embedded, wrapper, and filter approaches, respectively, are applied to determine the most suitable estimator parameters to predict PGV. Residual analyses and statistical evaluation metrics are employed to measure the performance and effectiveness of the machine learning models. Among the algorithms applied, Gradient Boosting demonstrates exceptional success in predicting PGV, particularly when utilizing all estimator parameters (features) collectively. The Gradient Boosting model exhibits superior predictive capabilities compared to existing ground motion models. It is applicable to shallow crustal strike-slip and normal faulting earthquakes with moment magnitude ranging from 3.5 to 7.8 and Joyner and Boore distance up to 200 km.

The Haichenghe fault zone (HFZ), the site of the 1975 M 7.3 Haicheng earthquake, is one of the most seismically active zones in eastern China. To better understand the fault structures in HFZ, we deployed a dense array of 23 broadband seismic stations in 2021, with an average distance interval of ~ 6 km. Utilizing neural network-based phase picking, earthquake association, and relocation methods, we analyzed data from the dense array and the Liaoning Seismic Network from Aug. 9, 2021, to Sep. 8, 2023. The relocations clearly reveal a conjugate fault system within the HFZ, consisting of WNW-striking and NE-striking subvertical faults with different scales. The Haichenghe Fault (HF) appears as a WNW-trending en echelon fault, with a 30-km-long main segment (MHF) to the northwest and a 5-km-long Xiuyan segment (XYF) to the southeast. The MHF is further divided into NW and SE segments by two NE-trending faults. Additionally, our data resolve the asymmetric conjugate rupture area of the Haicheng M 7.3 earthquake and a triangular seismic gap near the intersection of the MHF and the main NE-trending conjugate fault (MCF), indicating a strong heterogeneity of the subsurface medium in this region. Furthermore, we identified new conjugate fault structures with a V-shaped seismicity pattern in the Xiuyan area, extending along WNW and NE directions. Our findings stress the importance of dense array observations in the HFZ, providing essential seismological insights into its complex fault structures and seismogenic environment.

This study investigates the impact of aftershocks on hazard assessment and disaster prevention by examining three main characteristics of strong ground motions: amplitude, spectrum, and duration. A total of 6414 accelerograms were compiled from 26 selected mainshock-aftershock events in the Yalong River Basin, China, Japan, and Turkey. The aim is to investigate the correlation between mainshocks and aftershocks using Copula theory and seven representative intensity measures: peak ground acceleration (PGA), cumulative absolute velocity (CAV), peak ground velocity (PGV), Arias intensity, significant duration, mean frequency and predominant frequency of Fourier amplitude spectrum. The findings reveal a moderate to strong non-linear correlation among the seven intensity measures of mainshocks and aftershocks. This non-linear correlation can be effectively captured using Gumbel, Gaussian, and t-Copula functions. Under the conditions of the optimal Copula joint distribution model among the given intensity measures and the mainshock intensity measures, the Copula conditional prediction model for aftershocks accurately reflects the values of aftershock intensity measures. This approach demonstrates the effectiveness of Copula theory in studying the correlation between mainshock and aftershock intensity measures. It offers a novel method for determining aftershock intensity measures and investigating correlations among multivariate random variables.

Attaining explicit hazard estimates is a challenging task for data sparse regions such as the Peninsular India. Physics based probabilistic seismic hazard analysis (Pb-PSHA) has gained momentum in recent years as a viable solution to this issue. While performing a site-specific analysis in data-sparse regions, instead of incorporating ground motion models (GMMs) from other regions in the hazard methodology, the Pb-PSHA involves obtaining physics-based numerical simulations. In the present study, Pb-PSHA is carried out for the entire southern Peninsular India, with a detailed demonstration for the Kalpakkam site, Tamilnadu. Due to absence of any data on local fault characteristics and past rupture models, simulations are derived using the spectral element method, for several source rupture scenarios. Further, the stochastic seismological model is used to simulate for high frequency (1-100 Hz) ensemble ground motions. Broadband ground motions are then obtained by combining the results from the deterministic model i.e., low frequency (0.01-1 Hz) simulations and the stochastic model. Further, PSHA based on elliptical gridded seismicity is carried out to obtain hazard curves for spectral accelerations. The ensuing uniform hazard response spectra are compared against the outcome of traditional PSHA involving a global GMM. The results indicate that the PGA values obtained from the Pb-PSHA are slightly higher than that of the global GMM-based PSHA.

Studying the source characteristics of doublet or multiple earthquake sequences presents significant challenges in seismology, especially with short time intervals between events. On November 14, 2021, a doublet earthquake (Mw 6.0 and Mw 6.1) occurred near Fin city, southern Iran, within a span of less than two minutes and 10 km apart. We employed the Kinematic Waveform Inversion (KIWI) procedure to determine the point and extended source parameters of these events, using a multistep inversion approach for stable solutions. Our analysis highlighted the directivity of the earthquakes: the first event exhibited bilateral directivity, causing a rupture area that reached the surface, while the second event showed unilateral westward directivity, supported by waveform amplitude differences observed at various stations. This directivity analysis plays an essential role in seismic hazard studies. Our findings regarding the source parameters of these recent doublet earthquakes in the Fin region align well with regional geological trends and fault patterns. However, retrieving the main fault plane for the second earthquake was challenging due to the complexities of the waveform. Moment tensor decomposition revealed significant non-double-couple components for the second event, indicating the complexity inherent in analyzing doublet events. This study underscores the critical role of precise waveform analysis and robust inversion techniques in understanding complex seismic events.

Predicting ground motions due to induced seismicity is a challenging task owing to the scarcity of data and heterogeneity of the uppermost crust. Dealing with this requires a thorough understanding of the underlying physics and consideration of inter-site variability. The most common ground motion model used in practice is the parametric ground motion prediction equation (GMPE), of which hundreds exist in the literature. However, relatively few are developed with a focus on induced seismicity. Developing GMPEs that are specific to an appropriate magnitude-distance range ((R < 30) km; (2 le M le 6)) is important for induced seismicity applications. This paper proposes a framework for the development of physically-based GMPEs to provide more accurate and reliable estimates of the potential induced-seismicity ground motion hazard, allowing for better risk assessment and management strategies. To demonstrate this approach, a new set of GMPEs for the 2018-2019 induced seismicity sequence at the Preston New Road (PNR) shale gas site near Blackpool, United Kingdom, is presented. The physically-based GMPE was developed based on a pseudo-finite-fault stochastic ground motion simulation, calibrated with parameters derived from the spectral analysis of weak-motion records from induced seismic events. An optimization-based calibration technique using the area metric (AM) was subsequently performed to calibrate optimal parameters for simulating ground motion at the PNR site. Finally, using a suite of forward simulations for events with (1 le M le 6) recorded at distances up to 30 km, combined with empirical data, a location-specific GMPE was derived through adjustment of an existing model.

On November 22, 2020, a moment magnitude of Mw 3.5 earthquake struck the highly populated Nile Delta. This event marked the first recorded earthquake in this area. We employed the polarity of P and S wave first motions, as well as SH and SV amplitudes and their respective ratios (SH/P and SV/SH), to constrain the focal mechanism solution. Furthermore, considering Brune's circular source model, kinematic source parameters were estimated through spectral analysis of available and reliable seismic data. The obtained solution reveals an oblique-slip fault mechanism, characterized by strike, dip, and rake angles of 341º, 69º, and -47º, respectively. Additionally, the two fault planes exhibit trends aligned with the E-W and NNW directions. This normal fault mechanism with a strike component aligns with previously identified events in various active areas of Egypt, indicating a dominant extensional stress regime. The trend/plunge of the P and T axes are determined to be 299º/46º and 42º/13º, respectively. Moreover, the NE trending of the T axis agrees well with the current extension stress field prevalent along the eastern border of Egypt. The average seismic moment and moment magnitude values for P and SH waves are estimated to be 1.86 × 10¹⁴ Nm, and 3.5, respectively. Furthermore, the average source values of radius and stress drop are calculated to be 304 m, and 29 bar, respectively. Through a comparative and comprehensive analysis of fault mechanism solutions in the Nile Delta region and its surroundings, we have concluded that the fault structures in the Hinge Zone and Cairo-Suez Shear Zone exhibit similarities. This finding provides evidence that the geodynamic processes and fault style are identical. In conclusion, the provided information contributes to our understanding of the seismotectonic characteristics and earthquake hazard in the epicentral region. Moreover, this study serves as a motivation for future site response and seismic hazard analyses based on a scenario-based approach.