Earthquake Research Advances最新文献

Temporary seismic network deployments often suffer from incorrect timing records and thus pose a challenge to fully utilize the valuable data. To inspect and fix such time problems, the ambient noise cross-correlation function (NCCF) has been widely adopted by using daily waveforms. However, it is still challenging to detect the short-term clock drift and overcome the influence of local noise on NCCF. To address these challenges, we conduct a study on two temporary datasets, including an ocean-bottom-seismometer (OBS) dataset from the southern Mariana subduction zone and a dataset from a temporary dense network from the Weiyuan shale gas field, Sichuan, China. We first inspect the teleseismic and local event waveforms to evaluate the overall clock drift and data quality for both datasets. For the OBS dataset, NCCF using different time segments (3, 6, and 12-h) beside daily waveforms data is computed to select the data length with optimal detection capability. Eventually, the 6-h segment is the preferred choice with high detection efficiency and low noise level. For the land dataset, higher drift detection is achieved by NCCF using the daily long waveforms. Meanwhile, we find that NCCF symmetry on the dense array is highly influenced by localized intense noise for large interstation distances (>1 ​km) but is well preserved for short interstation distances. The results have shown that the use of different segments of daily waveform data in the OBS dataset, and the careful selection of interstation distances in the land dataset substantially improved the NCCF results. All the clock drifts in both datasets are successfully corrected and verified with waveforms and NCCF. The newly developed strategies using short-segment NCCF help to overcome the existing issues to correct the clock drift of seismic data.

In a conventional base isolation system, minimizing the seismic responses of the superstructure is always at the cost of increasing the isolator's response. The semi-active control of the isolator has been considered an effective solution to such a dilemma. It tunes the real-time properties of the isolator according to preset rules to further reduce the superstructure's seismic responses without increasing that of the isolator or vice versa. However, the number of ground motion records used to design and validate the controller, i.e., the preset rules, in existing studies is usually very small and therefore is suspectable if it is adequate to address the significant uncertainty in the shaking of future earthquakes. This paper critically reviews the performance of the proportional-integral-derivative (PID), linear-quadratic regulator (LQR), and fuzzy controllers in semi-active base isolation systems with magnetorheological (MR) dampers subjected to highly uncertain ground motion inputs through numerical simulations. The results show that the control performance of the controllers varies significantly with the increasing number of input records, suggesting the necessity of using at least 50 ground motion records to appropriately assess the performance uncertainty of semi-active base isolation systems. More importantly, the superior performance of the optimized controllers is not guaranteed if the system is subjected to ground motions that are new to the controller, even if the controller has been optimized for thousands of existing ground motions. It highlights the need of improving the adaptability of the semi-active systems for uncertain ground motion inputs.

The traces left by earthquakes in lacustrine sediments are studied to determine the occurrence of ancient earthquakes by identifying seismically induced soft-sediment deformation structures (SSDS). Dating can help reconstruct the relative frequency of earthquakes. Identifying seismically induced seismites, which carry abundant seismic information from numerous SSDS, is both critical and challenging. Studying the deformation mechanism of SSDS and learning about the common criteria of seismically induced SSDS improve the identification of earthquake triggers. With better research into SSDS, seismic events can be effectively captured, and temporal constraints can be carried out by ¹⁴C dating and optically stimulated luminescence (OSL) dating to identify and date the occurrence of ancient earthquakes. The present contribution primarily addresses the meaning and mechanism of SSDS and their relationship with earthquake magnitude as well as the common criteria of the SSDS induced by earthquakes.

At 12:52, September 5, 2022, an M_S 6.8 earthquake occurred in Luding, Sichuan. The earthquake caused serious casualties and property loss, and was determined to have an epicenter intensity of IX degree. In this study, we used three earthquake intensity rapid assessment methods (i.e. WFM, BPM and ASM) to evaluate the intensity of this earthquake. Then, we comparatively analyzed the three methods based on strong ground motion observation data and actual intensity maps. The results show that: (1) The earthquake is associated with a southeast-oriented single-sided rupture. The WFM method can only evaluate earthquakes with two-sided ruptures, which has some limitations; (2) The intensity of BPM and ASM was overestimated on the southwest and north sides of the epicenter, but other high-intensity zones were similar to the intensities measured by actual surveys; (3) The residuals of the three intensity assessment methods were all between −0.5 and 1. Although a small number of stations were underestimated, the overall residuals were good, and the residuals gradually approached 0 with the increase of distance; (4) The number of towns and villages evaluated by the three methods in the earthquake area was almost all lower than the field survey results. One exception is the area of VIII degree, where the BPM and ASM were higher than the survey results; (5) The area of the earthquake area evaluated by the three methods was low in VI and VII degree, moderate in VIII degree, and low in IX degree (the area from ASM is similar to the area measured by actual survey). Overall, ASM is applicable to this earthquake intensity assessment.

The report summarizes the observed damage to a variety of buildings near the epicenter of the M6.8 Luding earthquake in Sichuan Province, China. They include base-isolated buildings, multi-story reinforced concrete (RC) frame buildings, and masonry buildings. The near-field region is known to be tectonically highly active, and the local intensity level is the highest, that is, 0.4g peak ground acceleration (PGA) for the design basis earthquake, in the Chinese zonation of seismic ground motion parameters. The extent of damage ranged from the weak-story collapse that claimed lives to the extensive nonstructural damage that suspended occupancy. The report highlights the first observation of the destruction of rubber bearings and viscous dampers in the isolation layer of Chinese seismically isolated buildings. It also features the rare observation of the brittle shear failure of RC columns in moment-resisting frames in a region of such a high seismic design requirement. Possible reasons that may have attributed to the reported damage are suggested by providing facts observed in the field. However, careful forensic analyses are needed before any conclusive judgment can be made.

The long-term earthquake prediction from 2021 to 2030 is carried out by researching the active tectonic block boundary zones in the Chinese mainland. Based on the strong earthquake recurrence model, the cumulative probability of each target fault in the next 10 years is given by the recurrence period and elapsed time of each fault, which are adopted from relevant studies such as seismological geology, geodesy, and historical earthquake records. Based on the long-term predictions of large earthquakes throughout the world, this paper proposes a comprehensive judgment scheme based on the fault segments with the seismic gap, motion strongly locked, sparse small-moderate earthquakes, and apparent Coulomb stress increase. This paper presents a comprehensive analysis of the relative risk for strong earthquakes that may occur in the coming 10 years on the major faults in the active tectonic block boundary zones in the Chinese mainland. The present loading rate of each fault is first constrained by geodetic observations; the cumulative displacement of each fault is then estimated by the elapsed time since the most recent strong earthquake.

The Ningdu basin, located in southern Jiangxi province of southwest China, is one of the Mesozoic basin groups which has exploration prospects for geothermal energy. A study on the detailed velocity structure of the Ningdu basin can provide important information for geothermal resource exploration. In this study, we deployed a dense seismic array in the Ningdu basin to investigate the 3D velocity structure and discuss implications for geothermal exploration and geological evolution. Based on the dense seismic array including 35 short-period (5 s-100 ​Hz) seismometers with an average interstation distance of ∼5 ​km, Rayleigh surface wave dispersion curves were extracted from the continuous ambient noise data for surface wave tomographic inversion. Group velocity tomography was conducted and the 3D S-wave velocity structure was inverted by the neighborhood algorithm. The results revealed obvious low-velocity anomalies in the center of the basin, consistent with the low-velocity Cretaceous sedimentary rocks. The basement and basin-controlling fault can also be depicted by the S-wave velocity anomalies. The obvious seismic interface is about 2 ​km depth in the basin center and decreases to 700 ​m depth near the basin boundary, suggesting spatial thickness variations of the Cretaceous sediment. The fault features of the S-wave velocity profile coincide with the geological cognition of the western boundary basin-controlling fault, which may provide possible upwelling channels for geothermal fluid. This study suggests that seismic tomography with a dense array is an effective method and can play an important role in the detailed investigations of sedimentary basins.

Earthquake-triggered liquefaction deformation could lead to severe infrastructure damage and associated casualties and property damage. At present, there are few studies on the rapid extraction of liquefaction pits based on high-resolution satellite images. Therefore, we provide a framework for extracting liquefaction pits based on a case-based reasoning method. Furthermore, five covariates selection methods were used to filter the 11 covariates that were generated from high-resolution satellite images and digital elevation models (DEM). The proposed method was trained with 450 typical samples which were collected based on visual interpretation, then used the trained case-based reasoning method to identify the liquefaction pits in the whole study area. The performance of the proposed methods was evaluated from three aspects, the prediction accuracies of liquefaction pits based on the validation samples by kappa index, the comparison between the pre- and post-earthquake images, the rationality of spatial distribution of liquefaction pits. The final result shows the importance of covariates ranked by different methods could be different. However, the most important of covariates is consistent. When selecting five most important covariates, the value of kappa index could be about 96%. There also exist clear differences between the pre- and post-earthquake areas that were identified as liquefaction pits. The predicted spatial distribution of liquefaction is also consistent with the formation principle of liquefaction.

It is critical to determine whether a site has potential damage in real-time after an earthquake occurs, which is a challenge in earthquake disaster reduction. Here, we propose a real-time Earthquake Potential Damage predictor (EPDor) based on predicting peak ground velocities (PGVs) of sites. The EPDor is composed of three parts: (1) predicting the magnitude of an earthquake and PGVs of triggered stations based on the machine learning prediction models; (2) predicting the PGVs at distant sites based on the empirical ground motion prediction equation; (3) generating the PGV map through predicting the PGV of each grid point based on an interpolation process of weighted average based on the predicted values in (1) and (2). We apply the EPDor to the 2022 M_S 6.9 Menyuan earthquake in Qinghai Province, China to predict its potential damage. Within the initial few seconds after the first station is triggered, the EPDor can determine directly whether there is potential damage for some sites to a certain degree. Hence, we infer that the EPDor has potential application for future earthquakes. Meanwhile, it also has potential in Chinese earthquake early warning system.

Timely response to earthquake characterization can facilitate earthquake emergency rescue and further scientific investigations. On June 1, 2022, M_W 5.9 earthquake occurred in the southern area of the Longmenshan fault zone. This event also happened at the south end of the Dayi seismic gap and is the largest earthquake that has occurred in this seismic gap since the 1970 M 6.2 event. The slip-distribution model constrained by the seismic waveforms suggests a thrust-dominated faulting mechanism. The main slip occurs at a depth of ∼14 ​km, and the cumulative energy is released in the first 6 ​s. The variations of Coulomb stress caused by the mainshock show a positive change in the southwest area of the Dayi seismic gap, indicating possible activation of future earthquakes. In addition, we emphasize the importance of rapid estimation of deformation for near-field hazard delineation, especially when interferometric radar fails to image coseismic deformation in a high relief terrain.