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This study emphasizes the role of active faults as seismogenic sources in probabilistic seismic hazard assessments (PSHA) in the United Arab Emirates (UAE). An extensive PSHA analysis has been carried out in this study, which incorporates faults alongside area seismic sources within a logic tree-oriented framework. Seismicity is evaluated in terms of spectral acceleration (SA) and Peak ground acceleration (PGA) for return periods of 2,475, 975, and 475 years at 5 % damping. The results are compared with seismic hazard projections derived from previous PSHA studies that utilized only area sources. A key observation is the pronounced impact of the Dibba and Oman range frontal faults on the UAE's northeastern region due to the proximity of the faults. This contributes to higher seismic hazard in this region, with some return periods showing greater hazard levels than those documented in earlier studies. In order to aid seismic hazard design in the UAE, contour maps depicting the SAs at 0.2 and 1.0 s, along with PGA, are developed. The analysis reveals that the highest seismic hazard is predicted along the northeastern borders of the UAE, particularly the coastal area of Ras-Al Khaimah, with a PGA of 0.22 g for a return period of 2,475 years.

The low-frequency content of seismic waves in exploration is of substantial value as it can benefit imaging and inversion by providing deeper penetration, broader-band energy, and wavelet stability. However, characterizing the factors contributing to low frequencies (the seismic source, response of the receiver, and spectral signal-to-noise) and their effects may be complicated. The Hussar, Alberta survey, conducted by the CREWES Project at the University of Calgary and used here, addresses this challenge with a range of sources and receiver types. We further analyze the low-frequency content of the Hussar data using surface waves - because of their significant coherent low-frequency energy. The multichannel analysis of surface waves (MASW) method is used. To improve accuracy, a nonlinear approach is applied to extract dispersion properties, overcoming the limitations of conventional methods at low frequencies. This allows for precise phase velocity measurements across frequencies and assesses the frequency content of different source-receiver type combinations based on surface-wave coherence. The extracted dispersion properties were validated by comparing the dispersion curves estimated using Vs from traveltime tomography and well-logging data. The survey tested 2 kg dynamite in addition to vibroseis sources with low-dwell and linear sweeps. The receivers evaluated included Vectorseis accelerometers, as well as 10 and 4.5 Hz geophones. Our dispersion results indicate that all source-receiver combinations contain considerable surface-wave energy down to about 2 Hz. The inverted 1-D Vs models provide Vs estimates to about 800 m, consistent with results from S-wave tomography and shear logging. Dynamite produced more low-frequency energy in surface waves than vibroseis sources, extending below 1.5 Hz. Low-dwell sweeps showed clearer coherence in surface waves at low frequencies than linear sweeps. Of the receivers tested, the 4.5 Hz geophone showed higher sensitivity to low frequencies than both the Vectorseis accelerometer and the 10 Hz geophone. Although the Vectorseis accelerometer recorded more coherent low-frequency surface waves than the 10 Hz geophone, its signals were affected by some instrument noise. Analyzing surface-wave energy and coherency to assess low-frequency content can complement other types of spectral analysis.

We investigate the utility of the P/S amplitude discriminant for small seismic events recorded at local distances on surface seismic networks using (1) mining-related events from within the Kloof gold mine in South Africa; and (2) mining-related events and earthquakes within and adjacent to the Kiruna iron ore mine in northern Sweden. For the Kloof mine, seventy-five source mechanisms characterized by moment tensor solutions obtained using high-frequency in-mine seismic data are used to evaluate three mine-related source types, isotropic (crush), compensated linear vector dipole (crush-slip), and double-couple (DC; pure slip). For the Kiruna mine region, 270 events are used to evaluate earthquake sources, chemical explosions, and mine-related seismic events (primarily isotropic). For the Kloof mine events, we find that average P/S amplitude ratios measured in the 2-6 Hz frequency band discriminate between isotropic and DC events, and if only pure-slip events with a DC component of >60% are considered, the effective frequency band can be extended from 2 to 8 Hz. For the Kiruna region events, P/S amplitude ratios effectively discriminate earthquakes from chemical explosions in the 4-6 Hz and 10-28 Hz frequency bands. Our findings further show that average P/S amplitude ratios for mine-related events and earthquakes separate at frequencies of 10 Hz and higher. A comparison of amplitude ratios for crush and pure-slip events located within a depth range of 1 km in the Kloof mine, and a comparison of amplitude ratios of shallow (<10 km depth) and deep-focus (>20 km depth) earthquakes in the Kiruna region, indicate that the P/S amplitude discriminant is not influenced significantly by source depth. These findings thus suggest that the P/S amplitude discriminant, originally developed for larger events recorded at regional and teleseismic distances, can be extended to smaller events recorded at local distances. [ABSTRACT FROM AUTHOR]

On December 18, 2023, an Ms 6.2 earthquake occurred in Jishishan, Gansu Province, China. This earthquake happened in the eastern region of the Qilian Orogenic Belt, which is situated at the forefront of the NE margin of the Tibetan Plateau (i.e., Qinghai–Tibet Plateau), encompassing a rhombic-shaped area that intersects the Qilian–Qaidam Basin, Alxa Block, Ordos Block, and South China Block. In this study, we analyzed the deep tectonic pattern of the Jishishan earthquake by incorporating data on the crustal thickness, velocity structure, global navigation satellite system (GNSS) strain field, and anisotropy. We discovered that the location of the earthquake was related to changes in the crustal structure. The results showed that the Jishishan Ms 6.2 earthquake occurred in a unique position, with rapid changes in the crustal thickness, Vp/Vs, phase velocity, and S-wave velocity. The epicenter of the earthquake was situated at the transition zone between high and low velocities and was in proximity to a low-velocity region. Additionally, the source area is flanked by two high-velocity anomalies from the east and west. The principal compressive strain orientation near the Lajishan Fault is primarily in the NNE and NE directions, which align with the principal compressive stress direction in this region. In some areas of the Lajishan Fault, the principal compressive strain orientations show the NNW direction, consistent with the direction of the upper crustal fast-wave polarization from local earthquakes and the phase velocity azimuthal anisotropy. These features underscore the relationship between the occurrence of the Jishishan Ms 6.2 earthquake and the deep inhomogeneous structure and deep tectonic characteristics. The NE margin of the Tibetan Plateau was thickened by crustal extension in the process of northeastward expansion, and the middle and lower crustal materials underwent structural deformation and may have been filled with salt-containing fluids during the extension process. The presence of this weak layer makes it easier for strong earthquakes to occur through the release of overlying rigid crustal stresses. However, it is unlikely that an earthquake of comparable or larger magnitude would occur in the short term (e.g., in one year) at the Jishishan east margin fault.

Measurements of magnetic fields near seismic sources during solar flares are vital for understanding the dynamics of solar activity. We used spectropolarimetric observations of the X17.2/4B solar flare on 28 October 2003, over a wavelength interval of 43 Å, including the D3, D2, D1, and Ni I 5892.88 Å lines, to analyze the Stokes I ± V profiles. Effective magnetic fields within 0.5–1.5 kG were measured in the D1, D2, and D3 lines at different flare locations, with the photospheric Ni I 5892.88 Å line showing a weaker field of below 0.5 kG. The D3 line showed rapid plasma descents of up to 11 km/s, in contrast to the slower velocities within 2.3 km/s observed in other lines. The differing amplitudes in the I + V and I − V profiles indicated potential non-Zeeman polarization effects. Secondary Stokes V peaks were also detected up to 8 Å from the D3 emission core. Significant altitudinal inhomogeneity in the magnetic field strengths was detected, possibly indicating the local magnetic collapse, facilitating the Lorentz-force driven mechanism of the seismic source excitation.

Aceh is justified as one of the Indonesian provinces with a high level of seismicity. This high seismicity certainly has a severe negative impact on various aspects of human life in Aceh and the surrounding areas. Various types of efforts must be carried out to solve and mitigate the problem caused by each earthquake in Aceh and the surrounding areas. One aspect that can be carried out to minimize the hazards of seismic activity is the characterization of the source of the earthquake. This characterization can be used for various purposes for further seismic-related studies, including for studying seismic hazard analysis using the probabilistic seismic hazard analysis (PSHA) method. This research aims to determine the characteristics of the seismic source zones for Aceh and the surrounding areas. Based on the geological setting and seismicity catalog data of Aceh and the surrounding areas, a new model of seismic source zones was developed. This new model proposed for Aceh and the surrounding areas is divided into four zones: shallow background seismic source zones (divided into two source zones), two deep background seismic source zones, two megathrust source zones, and one fault zone, namely the Sumatra fault zone. The results of this study suggest that Zone I and Zone II of shallow background seismic source zones have a-values of 2.36 and 4.7, b-values of 0.545, and Mmax of 7.7 and 6.8. Deep background seismic source zone I has an a-value of 4.43 and a b-value of 0.9 with a maximum magnitude of 7 Mw. Meanwhile, deep background seismic source zone II has an a-value of 3.28 and a b-value of 0.755 with a maximum magnitude of 6.1 Mw. Megathrust seismic source zone I has an a-value of 3.53 and a b-value of 0.691 with a Mmax of 7.7 Mw. Meanwhile, the megathrust seismic source zone II has an a-value of 3.81 and a b-value of 0.702 with a Mmax of 7.1 Mw. Sumatra fault seismic source zone has an a-value of 2.88 and a b-value of 0.615 with a Mmax of 6.7 Mw.

Archaeoseismological research often deals with two unresolved questions: the magnitude and level of damage caused by past earthquakes, and the precise location of the seismic source. We propose a comprehensive review of an integrated approach that combines site effects with the analysis of geochemical data in the field of archaeoseismology. This approach aims to identify active buried faults potentially related to the causative seismic source and provide insights into earthquake parameters. For each integrated method, we report the foundational principles, delineation of theoretical field procedures, and exemplification through two case studies. Site effects analysis in archaeoseismology assumes a pivotal role in unraveling historical seismic occurrences. It enables estimating the earthquake magnitude, assessing the seismotectonic patterns, and determining the resulting damage level. Valuable data related to earthquake parameters can be extracted by analyzing vibration frequencies and acceleration measurements from structures within archaeological sites. This information is instrumental in characterizing seismic events, evaluating their impact on ancient structures, and enhancing our understanding of earthquake hazards within the archaeological context. Geochemical investigations supply indispensable tools for identifying buried active faults. The analysis of fluids and gases vented in proximity to faults yields valuable insights into their nature, activity, and underlying mechanisms. Faults often manifest distinctive geochemical imprints, enabling the differentiation between tectonically active and volcanically related fault systems. The presence of specific gases can further serve as indicators of the environmental conditions surrounding these fault networks. Integrating site effects analysis and geochemical investigations within archaeoseismological research is crucial to improving our understanding of unknown past earthquakes. Moreover, it enhances the seismic hazard assessment of the region under study.

Tunnel seismic advanced prediction method is essential for detecting abnormal bodies ahead of the tunnel face and minimizing risks during tunnel construction. Selecting the seismic source plays a crucial role in influencing the precision and effectiveness of data acquisition. At present, tunnel seismic data is usually collected using explosive and sledgehammer sources. Nevertheless, the various sources are located in different positions within the tunnel excavation zone, resulting in distinct characteristics observed on the surface and reflected waves in the acquired tunnel seismic data. The explosive source has minimal surface wave interference, but it is expensive. However, the sledgehammer source is economical yet plagued by inadequate energy and substantial surface wave disruption. Regrettably, there is a lack of research on seismic sources in tunnels, which impairs the precise interpretation of forecasting conclusions from these sources. This paper seeks to investigate how various sources impact tunnel seismic prediction and suggests a new method that integrates data acquisition and processing from these sources. The explosive source is used once, while the sledgehammer source is used 24 times. Cross-correlation calculations are conducted to enhance the resolution of sledgehammer source data, reducing surface wave interference, based on seismic data obtained from the explosive source. Extensive numerical simulations and tunnel experiments support the validity of this method, highlighting its potential to lower data acquisition expenses and enhance tunnel seismic prediction accuracy.

Abstract A minequake of magnitude ML 4.1 occurred on 18 May 2020 early in the morning at the LKAB underground iron ore mine in Kiruna, Sweden. This is the largest mining‐induced earthquake in Scandinavia. It generated acoustic signals observed at three infrasound arrays at 9.3 (KRIS, Sweden), 155 (IS37, Norway), and 286 km (ARCI, Norway) distance. We perform full‐waveform focal mechanism inversion based on regional seismic data and local infrasound data. These independently highlight that this event was dominated by a shallow‐depth collapse in agreement with in‐mine seismic station data. However, regional infrasound data cannot inform the inversion process without an accurate model of atmospheric winds and temperatures. Yet, our numerical simulations demonstrate a potential of using local and regional infrasound data to constrain an event's focal mechanism and depth.

Two sets of predictive models are developed based on the machine learning (ML) and general orthogonal regression (GOR) approaches for predicting the seismic source parameters including rupture width, rupture length, rupture area, and two slip parameters (i.e., the average and maximum slips of rupture surface). The predictive models are developed based on a compiled catalog consisting of 1190 sets of estimated source parameters. First, the Light Gradient Boosting Machine (LightGBM), which is a gradient boosting framework that uses tree-based learning algorithms, is utilized to develop the ML-based predictive models by employing five predictor variables consisting of moment magnitude (Ww), hypocenter depth, dip angle, fault-type, and subduction indicators. It is found that the developed ML-based models exhibit good performance in terms of predictive efficiency and generalization. Second, multiple source-scaling models are developed for predicting the source parameters based on the GOR approach, in which each functional form has one predictor variable only, that is, Mw. The performance of the GOR-based models is compared with existing source-scaling relationships. Both sets of the models developed are applicable in estimating the five source parameters in earthquake engineering-related applications. [ABSTRACT FROM AUTHOR]