In this study, 8071 focal parameters of small and moderate earthquakes from January 2019 to December 2023 in the Sichuan-Yunnan region were calculated. The temporal and spatial variation trends of stress drop in the focal areas of the May 21, 2021 Yangbi M_S6.4 earthquake, the September 5, 2022 Luding M_S6.8 earthquake, and key observation areas (Longmenshan fault zone and the intersection area of the Honghe fault and Xiaojiang fault) were analyzed. According to the variation trends of stress drop, significant precursor changes were observed in the 2021 Yangbi M_S6.4 focal area one year before the earthquake. The stress drop time series of the 2022 Luding M_S6.8 earthquake shows a rapid rise and decline in the short term after the main earthquake; meanwhile, the stress drop has no obvious upward trends at present. The stress drops in the intersection area of the Honghe fault and Xiaojiang fault at the southern end of the Sichuan-Yunnan rhombohedral block and the northeast section of the Longmenshan fault zone are relatively high. Consequently, the future risk of strong earthquakes deserves attention, and the stress drop changes in these two areas should be continuously observed.

Using ambient noise correlation and the moving window cross spectrum method, we detected the variations in relative seismic velocity over approximately one year before and after the eruption of the Mt. Ontake volcano in Japan on September 27, 2014, and Kilauea volcano in Hawaii, USA, on May 4, 2018, respectively, using continuous seismic data collected from the Hi-net network and IRIS. The measurement results in the 0.4~0.8 Hz frequency band for the Mt. Ontake volcanic area show that the average relative seismic velocity decreased by about 0.1% during the 10 days before the eruption and then gradually recovered after the eruption. In the Kilauea volcanic area, the measurement results in the 0.5~1.0 Hz frequency band show that the average relative seismic velocity decreased by about 0.5% during the 10 days before the large-scale eruption and then gradually recovered after the eruption ended on 4 August 2018. Combined with the results of ground tilt, GPS, and focal mechanism solutions of the two volcanic areas, it is shown that the changes in relative seismic velocity before and after the volcanic eruptions are a response to shallow magmatic inflation and deflation processes in the volcanic areas.

The Sichuan-Yunnan region is located at the southeastern margin of the Qinghai-Xizang Plateau, where strong earthquakes have occurred frequently in recent years, drawing much attention to the study of strong earthquake activity trends in this area. This paper calculates the spatial distribution of M≥5.0 seismic activity rates caused by Coulomb stress perturbations resulting from 8 strong M_W≥6.5 earthquakes that occurred in the Sichuan-Yunnan region from 1976 to 2019, using the rate-state friction law and regional earthquake catalogs. The results indicate that the calculated seismic activity rates based on the rate-state friction criterion is generally consistent with the spatial distribution of M≥5.0 earthquakes that occurred between 2020 and 2023. Earthquake activity in the Sichuan-Yunnan region is jointly influenced by stress perturbations caused by strong earthquakes and seismogenic environments in different regions. The impact of strong earthquake stress perturbation fields on subsequent seismic activity is mainly concentrated in areas near strong earthquakes; while the higher seismic activity rates in some regions are related to the higher background seismic activity in the region. The areas with higher M≥5.0 seismic activity rates in the Sichuan-Yunnan region are located at the northern and southern ends of the Longmenshan fault, the Lijiang-Xiaojinhe fault, the Ruili-Longling fault, the Lancang River fault, and the Changning area. The results of this study provide new insights into the spatial and temporal distribution characteristics of moderate to strong earthquakes in the Sichuan-Yunnan region and serve as a reference for regional seismic hazard assessment.

In this study, we utilized the adjoint-state traveltime tomography based on eikonal equation to invert the surrounding area of M_S7.3 Landers earthquake by time-evolving method. The inversion obtained high-resolution three-dimensional P-wave and S-wave velocity structures for different time windows. The correlation among the geological structures and velocity structures of the study area and seismic activity were analyzed. The results indicated that the velocity structure in the Landers earthquake source area and its surrounding area exhibited significant lateral heterogeneities, which was well consistent with the geological structure near surface, basins and faults showing relatively low velocity anomalies, and major mountain ranges showing relatively high velocity anomalies. The occurrence and distribution of earthquakes in the region were closely related to the lateral heterogeneity of the velocity structure, with most earthquakes occurring within high-velocity anomalies or transition zones between high- and low-velocity anomalies. There are significant differences for the velocity structure near large earthquakes in different time windows. For example, in the second time window, the velocities near the Landers and Anza earthquakes became slow down, possibly due to the changes in the geological structure nearby after the large earthquakes, which in turn caused changes in velocity.

Ionospheric precursors are crucial indicators for short-term earthquake preparation, and abundant observations of them have been accumulated. Meanwhile, developments concerning the formation mechanisms of seismology ionospheric anomalies have led to increasing interest in the LAI coupling process, in which the AGW-agent hypothesis has been intensively discussed. Based on the BDS TEC data collected by CMONOC GNSS stations, this paper explores the spectral characteristics and spatial-temporal variations of the TEC perturbations from 14 hours before to 2 hours after the Jishishan M_W6.0 earthquake on December 18, 2023, in Gansu Province, China. According to the results, the pre-earthquake AGW-induced perturbation originated from points close to the epicenter and then dispersed outward as an arc-like structure. In addition, the background signal MSTIDs played the role of a carrier in the propagation of the perturbation, while the other two external signals exerted an interference effect on it. Finally, two promising candidates for the excitation and origination of the surface AGW signal are reviewed. Nevertheless, the connection between earthquake preparation and AGW signals needs further validation and investigation.

The M_S6.2 earthquake occurred in Jishishan County, Gansu Province, on December 18, 2023. Within a 300 km radius of the epicenter, there were 9 fixed geo-electrical resistivity observation stations. This study preprocessed the geo-electric resistivity observation data from 2 to 4 years before the earthquake, then analyzed the anomalous changes before the earthquake after eliminating annual and trend changes. It showed a declining trend in ground resistivity and a reduction in the annual variation amplitude before the earthquake at Linxia Station, Dingxi Station, and Tongwei Station, with decreasing magnitudes of 4.9% (44 km), 1.2% (164 km), and 0.6% (232 km) respectively. Earthquakes occurred during the declining reversal period. These anomaly patterns are consistent with statistical results from a large number of earthquake cases. Moreover, the closer the distance to the epicenter, the greater the magnitude of the anomaly change. This indicates that the changes in geo-electrical resistivity at these three stations are related to the M_S6.2 earthquake in Jishishan. It was also found that there was no obvious pre-seismic anomaly at the Jinyintan seismic station, which is 219 km away from the epicenter of the earthquake. Further analysis will be conducted in conjunction with the station’s actual electricity structure and fault distribution.

Hot spring water has the characteristics of deep circulation, fast-rising speed, and little human influence, and its chemical and isotopic composition carries the information of deep environment changes, it is becoming an important content of earthquake precursor monitoring. Based on domestic and foreign relevant literature, this article emphasizes the superiority of hot spring water monitoring in earthquake prediction in areas with harsh natural conditions and sparse populations, such as the Qianghai-Tibet Plateau and Xinjiang, where strong earthquakes are active. It summarizes the precursory response of the chemistry and isotope of hot spring water to earthquakes and the mechanism of abnormal response and proposes that identifying the sources of hot spring water and solute, the hydrogeochemical processes, and the seismic precursory signals during the process of earthquake breeding and occurrence are the key questions to answer how hot spring water responds to earthquakes. It is recognized that seismic prediction based on big data analysis and machine learning can play an important role in the analysis of the monitoring data of hot spring water. In addition, it is expected that the eastern margin of the Qinghai-Tibet Plateau could be the best research area to further study the mechanism of hydrochemical response to earthquakes. The purpose of this paper is to promote the development of chemical and isotopic monitoring of hot spring water for earthquake prediction and to improve the ability of earthquake prevention and disaster reduction.

The focal mechanism of the 2017 Jiuzhaigou M_S7.0 earthquake, inverted through seismic wave and InSAR observations, was mainly strike-slip, but the coseismic displacement observed by near-field GPS showed significant dip-slip characteristics in the northern section of the seismic fault. In view of this, we combines GPS and InSAR observation data to obtain rich coseismic deformation. Based on the Bayesian inversion of the geometric model of the fault, it compares and analyzes the differences in the coseismic slip distribution inverted from three data sources: GPS only, InSAR only, and fused GPS/InSAR. Thereby, it gives the optimal slip distribution model of this earthquake. The results show that the optimal model has a strike of 150° for the seismic fault, an inclination of 56°, a maximum slip of about 1.3 m, located at a depth of 5.3 km underground, and a moment magnitude of M_W6.5. Especially after adding the coseismic displacement of near-field GPS, the results show that in addition to the left-lateral strike-slip, there is also a dip-slip component in the northern section of the seismic fault. Based on the spatial distribution of the main active faults in the epicenter area, such as the Huya Fault and the Tazang Fault, this article speculates that the dip-slip property in the northern section of the seismic fault may be caused by maintaining the motion balance in the intersection area of the Tazang Fault and the Huya Fault.

The source parameters characterize the main physical processes of an earthquake, while the velocity model is an approximate parameter representation of the real underground structure. Both are coupled in various ways, affecting the recording of seismic phases. In the past, when fitting the waveforms of a large number of regional earthquakes to invert for source parameters, low-computational-consumption one-dimensional velocity models were often used to model the seismic waveforms, and there was a lack of systematic and quantitative assessment of the absolute error in the source mechanism solution caused by the velocity model. This study takes the Longmenshan fault zone as an example, using a high-resolution three-dimensional velocity model obtained by wave imaging to accurately perform three-component broadband waveform synthesis for 212 representative regional earthquakes (M_S 3.5~5.7) after the Wenchuan earthquake, and based on this, multiple representative regional one-dimensional velocity models are used for source parameter CAP waveform inversion tests. By statistically analyzing the source parameters obtained from the waveform inversion of different one-dimensional models and comparing them with the representative seismic source parameters, the study systematically evaluates the impact of the accuracy of one-dimensional velocity models on the precision of the source parameter waveform inversion results. In this paper, under the filtered parameters for P-waves (0.01~0.18 Hz) and S-waves (0.03~0.10 Hz), the four sets of one-dimensional velocity model inversion mechanism solutions obtained are all quite reliable, with the number of events with an error Kagan angle less than 30° accounting for more than 97%. However, the CAP inversion depth error depends on the velocity model, and it is found that the inaccurate shallow structure will severely affect the inversion depth of the event. In the case of unknown accuracy of the velocity model, the normalized cross-correlation coefficient NCC of the seismic event can be used as a key indicator for the accurate inversion of the source depth. The velocity model accuracy assessment method and ideas proposed in this paper can be extended to the source inversion research of other complex tectonic areas and different one-dimensional velocity models.

Aiming at the problem that the traditional seismic evaluation of buildings time-consuming and the difficulty in a large-scale implementation, this paper proposes a seismic capacity evaluation model for buildings based on U-Net++. The model takes U-Net++ as the backbone network, integrates multiple information sources, such as high-resolution remote sensing images, building construction age, height, use and structural types. Taking the Yucheng District of Ya’an City, Sichuan Province, as the study area, 17 comparative experiments were designed to explore the degree of influence that different features have on the seismic resilience of buildings. This work provides robust technical support for refined assessments of earthquake disaster risks on a broad scale.

This paper briefly reviews the scientific issues, analytical methods, main features, and results of years of real-time earthquake tracking practice on impending strong earthquake microfluctuations. The main characteristics of impending earthquake microfluctuations are summarized as follows: ① The dominant frequency is 11~16 Hz, and the spectrum shape is relatively neat; ② It may appear 2~24 days before the earthquake, and can be recorded by stations within a radius of 70 km of the epicenter; ③ It is reproducible and appears before multiple strong earthquakes; ④ It may be related to the magnitude of the earthquake. The greater the magnitude, the greater the possibility of impending earthquake microfluctuations before the earthquake. This paper introduces the new results of microfluctuations observed during the aftershock activity of the 2021 Yangbi M6.4 earthquake and the 2021 Maduo M7.4 earthquakes. It is inferred that the microfluctuations of imminent strong earthquakes may originate from the hypocentral area or the earthquake rupture zones.

Using high precision data processing software GAMIT/GLOBK, we obtain co-seismic displacement of the 14 earthquakes above M_W6.0 from 2011 to 2015, based on the CMONOC GPS continuous stations. Combining the tectonic background and the focal mechanism, we research the spatial distribution characteristic of co-seismic displacement field. The results show that the larger magnitude, the shallower source, the closer epicentral distance, the more obvious the co-seismic displacement can be observed by GPS stations. For the shallow source earthquakes, the observable range of co-seismic deformation effects is within 50 km for the M_W6.0~6.5 earthquakes, within 100 km for the M_W6.5~7.0 earthquakes, and exceeds 200 km for the earthquakes with magnitudes above M_W7.0.

To clarify the temporal changes in ground deformation and their causes in the Yucheng District of Ya’an City, this study used 36 scenes of Sentinel-1A satellite data from January 2019 to December 2021 and applied PS-InSAR technology to monitor ground deformation in the Yucheng District of Ya’an City. The accuracy was evaluated using concurrent GNSS observation data. By combining geological structures, precipitation, underground resource extraction, seismic activities, and other factors, the characteristics and mechanisms of deformation in the study area were analyzed. The results showed that the root mean square error (RMSE) between the PS-InSAR monitoring results and the GNSS monitoring results was 3.97 mm. The average deformation rate in the study area ranged from -28.00 to 30.12 mm/a. Under the influence of geological structures, there were significant differences in subsidence rates on both sides of the fault zones, with the maximum difference reaching 25.68 mm/a. Under the same structural control, subsidence rates had a certain relationship with human activities, mineral resource extraction, construction projects, transportation, and dense high-rise buildings all accelerated ground subsidence. Seasonal changes in groundwater levels due to rainfall had seasonal effects on ground subsidence; taking the 2019 precipitation and ground subsidence study as an example, the minimum subsidence in summer, which reached -0.14 mm.

Hot springs are closely related to tectonics and earthquakes. There is a consensus that hot spring geochemistry can be used for tectonic research and earthquake prediction. However, there is little disclosure on how to select continuous observation points for hot springs. Based on the correlation analysis between the hot springs in Fujian and the earthquakes in Taiwan, China from September 2020 to September 2023, this paper summarizes the methods for selecting hot spring observation sites and determining the sensitive components of seismic reflection. Based on this, a fluid geochemical observation network was constructed and applied to prediction practice, successfully predicting the M_L6.8 earthquake in Taiwan, China on September 18, 2022. The core of the method is to use helium, neon, and carbon isotopes from hot springs to explore hot springs with deep circulation and rich deep information. The outstanding characteristics of these hot springs are the large contribution of mantle source fluid in hot spring gas, reflected in the high ratio of mantle source helium and the mean value of the δ13C_CO2 double high region, the significant deviation of δ13C_CO2 measured value from the fitting line with CO₂ volume percentage, the intersection of structural fault zones, and the fact that most faults reach deep into the Moho plane. Water samples were collected from these hot springs for continuous observation of water chemical major ions, and the gas flow rate of Nancheng spontaneous spring with abundant escaping gas was continuously observed. The correlation analysis between the observation results and the earthquakes above M6 in the Taiwan, China was carried out by using the threshold analysis method. The seismic mapping capability of each observation point and each measurement item was calculated, and the R-value evaluation method was applied to evaluate prediction efficiency. Those with high evaluation results and high seismic mapping efficiency could be finally selected as potential effective fluid geochemical seismic monitoring points. The results can be used as a reference for selecting sites for hot spring geochemical monitoring stations and effective earthquake precursor observation projects in the earthquake industry.