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We investigate the global variation of earthquake stress drops using spectra of about 2000 events of mb ≥ 5.5 between 1990 and 2007. We use an iterative least squares method to isolate source displacement spectra from travel path and receiver contributions, based on a convolutional model. The observed P wave source spectra are corrected with a globally averaged empirical correction spectrum and estimates of near‐source attenuation. Assuming a Brune‐type source model, we estimate corner frequencies and compute stress drops. Stress drop estimates for individual earthquakes range from about 0.3 to 50 MPa, but the median stress drop of about 4 MPa does not vary with moment, implying earthquake self‐similarity over the Mw = 5.2 to 8.3 range of our data. A comparison of our results with previous studies confirms this observation over most of the instrumentally observable magnitude range. While the absolute values of our estimated stress drops depend upon the assumed source model, we identify relative regional variations of stress drop that are robust with respect to the processing parameters and modeling assumptions, which includes an inherent assumption of constant rupture velocity. We find a dependence of median stress drop on focal mechanism, with a factor of 3–5 times higher stress drops for strike‐slip earthquakes and also find a factor of 2 times higher stress drops for intraplate earthquakes compared to interplate earthquakes.

Nowadays, the seismological monitoring system in China is a valuable tool in the rockburst risk evaluation for deep coal mines. In the past, only parameters, like source location and energy, are widely used to estimate the risk level of rockburst. Sometimes, it is effective; however, some other important physical parameters, such as apparent stress drop, static stress drop, P‐wave velocity, and moment tensor, should also be included in order to improve the accuracy of risk assessment. In this study, these parameters are calculated using mine tremor signals recorded in the LW35001 workface of Liangbaosi Coal Mine. These calculations provide an overall identification of periodical stress distribution and rock mass energy‐releasing type under high concentrated stress. Via linear moment tensor inversion procedure, the source mechanism of mine tremors and stress state of the rock mass is determined whether it is risk or not to underground roadway. This comprehensive analysis provides a specific guidance for rockburst prevention for coal mine management, that is, knowing when and where measures must be taken to decrease the risk level or induce the occurrence of rockburst under control. A comprehensive evaluation method based on physical parameters, including apparent stress drop, static stress drop, P‐wave velocity, and moment tensor, has been applied to improve the accuracy of rockburst risk assessment at Liangbaosi Coal Mine. These parameters have demonstrated an overall identification of periodic stress distribution and rock mass energy releasing type under high concentrated stress as well as an analysis of the potential for rockburst induced by mine tremors.

The stochastic EXtended finite‐fault ground‐motion SIMulation algorithm (EXSIM) has been widely applied in simulating and predicting broadband strong ground‐motion. However, an increasingly number of researchers have found that EXSIM may overestimate ground‐motions at low frequencies for some large‐magnitude earthquakes and/or thrust earthquakes, for which the far‐field source model has been explained by a double‐corner‐frequency model. Despite controversy, the double‐corner‐frequency model is now being accepted as one of the main categories of the far‐field source model. This study demonstrated the limited applicability of EXSIM to earthquakes explained by the double‐corner‐frequency source model, by presenting the equivalence between motions generated by EXSIM and those generated by EXSIM's point‐source version, SMSIM, which adopts the ω‐square single‐corner‐frequency model. Furthermore, two improvements to EXSIM have been proposed: (a) the incorporation of the asperity‐distributed stress‐drop compound faults model and (b) the hybrid application of EXSIM with the proposed model. The effects of the two improvements have been verified by comparing EXSIM‐generating motions with recorded ground‐motions for the 2013 Mw 6.7 Lushan thrust earthquake. Significantly, consistent simulation accuracy has been achieved across high‐ and low‐frequency bands as well as in far‐ and near‐fields. The consistent accuracy of the improved EXSIM in simulating high‐ and low‐frequency ground motions enables its direct and independent application to broadband ground motion simulations. Moreover, the first validation of this consistent accuracy in both near‐ and far‐field scenarios further enhances its application in earthquake engineering practices. Key Points EXtended finite‐fault ground‐motion SIMulation algorithm (EXSIM) could overestimate the low‐frequency ground motions of earthquakes with double‐corner‐frequency source model characteristics Two improvements to EXSIM were proposed: the asperity‐distributed stress‐drop compound faults model and the hybrid application of EXSIM The improvements have been validated by comparing EXSIM‐generating motions with records for Mw 6.7 Lushan thrust earthquake

Our models and understanding of the dynamics of earthquake rupture are based largely on estimates of earthquake source parameters, such as stress drop and radiated seismic energy. Unfortunately, the measurements, especially those of small and moderate-sized earthquakes (magnitude less than about 5 or 6), are not well resolved, containing significant random and potentially systematic uncertainties. The aim of this review is to provide a context in which to understand the challenges involved in estimating these measurements, and to assess the quality and reliability of reported measurements of earthquake source parameters. I also discuss some of the ways progress is being made towards more reliable parameter measurements. At present, whether the earthquake source is entirely self-similar, or not, and which factors and processes control the physics of the rupture remains, at least in the author's opinion, largely unconstrained. Detailed analysis of the best recorded earthquakes, using the increasing quantity and quality of data available, and methods less dependent on simplistic source models is one approach that may help provide better constraints. This article is part of the theme issue ‘Fracture dynamics of solid materials: from particles to the globe’.

Earthquake stress drops are inferred to be independent of source depth, contradicting linear scaling predictions for earthquakes as frictional stick‐slip instabilities that assume increasing fault normal stress due to overburden. Here, we examine the scaling between averaged stress drops and increasing normal stress for simulated earthquake sequences in continuum rate‐and‐state fault models. The models produce a weaker dependence of stress drop on normal stress than the linearity of simple friction, which can be well‐fit by a sublinear power‐law. This result is more prominent when the fault dimension is much larger than nucleation scales. In such cases, the averaged behavior of ruptures is dominated by rupture propagation conditions, reflecting more heterogeneous shear stress conditions. As natural faults can be considerably larger than the smallest earthquakes they host, such a weaker scaling between averaged rupture conditions and normal stress may partially explain the lack of an inferred depth‐dependence of earthquake stress drops.

Seismic moment and rupture length can be combined to infer stress drop, a key parameter for assessing earthquakes. In natural earthquakes, stress drops are largely depth‐independent, which is surprising given the expected dependence of frictional stress on normal stresses and hence overburden. We have developed a transparent experimental fault that allows direct observation of thousands of slip events, with ruptures that are fully contained within the fault. Surprisingly, the observed stress drops are largely independent of both the magnitude of normal stress and its heterogeneity, capturing the independence seen in nature. However, we observe larger, normal stress‐dependent stress drops when the fault area is reduced, which allows slip events to frequently reach the edge of the interface. We conclude that confined ruptures have normal stress independent stress drops, and thus the depth‐independent stress drops of tectonic earthquakes may be a consequence of their confined nature. Plain Language Summary Seismological stress drop is an important quantity for studying earthquakes that is usually interpreted as the change in frictional stress during an event. Frictional stress is expected to increase with depth in the crust due to the increasing weight of the overlying rocks. However, seismological stress drops of earthquakes do not show this behavior. This observation contradicts decades of lab experiments that show an increasing change in frictional stress with increasing pressure on the fault. We have built a new lab fault made out of transparent rubber, where we can directly observe slip and measure stress drops. We show that we can easily make slip events with seismological stress drops that are independent of the pressure on the fault. Events that do not reach the edge of the laboratory fault naturally keep the same seismological stress drop regardless of the experimental conditions. Conversely, events that reach the edge of the system have seismological stress drops that vary with pressure on the fault, much like the prior rock mechanics experiments that have always created this style of rupture. These new experiments force us to reconsider the appropriate interpretation of seismological stress drops and discourage inferences of friction based on this particular quantity. Key Points Lab stress drops based on moment‐area scaling are normal stress‐independent for confined ruptures, mimicking depth‐independence in nature Experiments use a new laboratory fault with direct imaging of slip, control over normal stress heterogeneity, and fully confined ruptures Seismologically inferred stress drops may not reflect frictional stress changes and finite fault effects are a critical consideration

Brittleness is an important characteristic of rocks, for it has a strong influence on the failure process no matter from perspective of facilitating rock breakage or controlling rock failure when rocks are being loaded. Various brittleness criteria have been proposed to describe rock brittleness. In this paper, the existing brittle indices are summarised and then analysed in terms of their applicability to describe rock brittleness. The analysis demonstrates that the widely used strength ratio or product ( σ c / σ t , σ c · σ t ) of rocks cannot describe rock brittleness properly and that most of the indices neglect the impact of the rock’s stress state on its brittleness. A new evaluation method that includes the degree of brittleness ( B d ) and brittle failure intensity ( B f ) is proposed based on the magnitude and velocity of the post-peak stress drop, which can be easily obtained from the conventional uniaxial and triaxial compression tests. The two indices can accurately account for the influence of the confining pressure on brittleness, and the applicability of the new evaluation method is verified by different experiments. The relationship between B d and B f is also discussed.

Numerous normal‐faulting aftershocks in subduction forearcs commonly follow large megathrust earthquakes. Postseismic normal faulting has been explained by stress changes induced by the stress drop along the megathrust. However, details of forearc stress changes and aftershock triggering mechanisms remain poorly understood. Here, we use numerical force‐balance models combined with Coulomb failure analysis to show that the megathrust stress drop supports normal faulting, but that forearc‐wide aftershock triggering is feasible within a narrow range of megathrust stress drop values and preseismic stress states only. We determine this range for the 2011 Tohoku earthquake (Japan) and show that the associated stress changes explain the aftershock seismicity in unprecedented detail and are consistent with the stress released by forearc seismicity before and after the earthquake. Plain Language Summary Earthquakes release stresses that build up in the Earth due to the motion of tectonic plates. The stress release can cause additional earthquakes called aftershocks. Several thousand onshore and offshore aftershocks followed the great Tohoku subduction earthquake in March 2011. Whether the stress release of the Tohoku earthquake triggered most of the aftershocks is not well understood, because it is largely unknown how the stress field changed following the earthquake. We therefore use a computer model to estimate the stress release and resulting stress change required to explain the aftershock distribution. We find that 78% of the aftershocks occurred in areas where the Tohoku earthquake caused a subsequent stress increase. Our model results are further consistent with the stress release of smaller earthquakes that occurred in Japan before and after the Tohoku earthquake. Our findings provide new insights into aftershock triggering and help to understand where aftershocks occur after great earthquakes at subduction zones. Key Points We show using force‐balance modeling that a megathrust earthquake stress drop can trigger forearc‐wide aftershock seismicity Model results explain the Tohoku earthquake aftershock distribution and reveal spatial variability in forearc stress and strength Most aftershocks occurred in areas that experienced an increase in deviatoric stress

In this paper, the source parameters were determined for 123 small to moderate size earthquakes (1.2 ≤ M L ≤ 4.5) occurred during 1997-2013 in Qinba Mountain and its adjacent area by using the digital seismic data recorded in Shaanxi seismic network. The scaling relations between seismic moment, stress drop, seismic radiated energy with seismic magnitude are determined, the relations between scaled energy E g /M 0 and seismic moment are analyzed. The results show that the seismic stress drop in this area approximately increases with the increase of seismic moment, but the seismic stress drop is generally low. The Zúñiga parameter ε is generally less than 1, indicating partial stress drop mechanism in the region and may be the activity of low strength mature faults. The seismic scaled energy in this area is relatively small, which may be the results of high dynamic friction force or insufficient estimation of seismic radiation energy.

Improving accuracy and reducing uncertainty in ground motion models (GMMs) are crucial for the safe design of infrastructure. Traditional GMMs often oversimplify source complexity, such as stress drop, due to high variability in estimation. This study aims to address this issue by extracting robust spatial variations in stress drop estimates and ground motion residuals. We introduce a non‐ergodic modeling framework using Bayesian Gaussian Process regression to analyze data from over 5,000 earthquakes (M2‐4.5) in the San Francisco Bay area. Our findings reveal consistent spatial patterns in non‐ergodic stress drop and peak ground acceleration (PGA), providing a reliable approach to understanding the spatial distribution of stress drop and its link to regional tectonics. Furthermore, integrating source models derived from the non‐ergodic stress drop into GMMs can effectively account for source effect in ground motions and reduce aleatory uncertainty. This study establishes a framework for utilizing stress drop data sets to enhance seismic hazard assessment. Plain Language Summary Ground shaking is the primary cause of damage during earthquakes, making accurate predictions vital for designing safer buildings. However, traditional models used to predict ground shaking often oversimplify the complex nature of earthquake sources, which may impact the uncertainty of seismic hazard analysis. In this study, we aim to improve source characteristics in ground motions by focusing on a key factor, stress drop, which has a significant influence on ground shaking but is known for its high variability due to measurement methods. To address this, we apply Gaussian Process regression to extract consistent patterns from the highly variable stress drop data before eventually incorporating it into the ground motion model. We analyze data from over 5,000 small earthquakes in the San Francisco Bay area. The extracted repeatable regional stress drop values presented in this study reveal underlying regional tectonic patterns. Additionally, we demonstrate that incorporating these extracted stress drop values reduces the variability in ground motion predictions without adding uncertainty from stress drop estimations. This serves as a potential bridge between stress drop and ground motion data sets, ultimately enhancing seismic hazard analysis and preparedness by leveraging stress drop insights. Key Points We retrieve robust spatial repeatable patterns from stress drop and ground motion data sets of small earthquakes in the Bay Area A strong spatial correlation between stress drop and peak ground acceleration is unveiled by non‐ergodic Gaussian Process regression Our extracted non‐ergodic stress drop can represent regional source effects in ground motion, thus improving ground motion model prediction