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Numerous scholars have used traditional thermal anomaly extraction methods and time series prediction models to study seismic anomalies based on longwave infrared radiation data. This paper selected bidirectional long short-term memory (BILSTM) as the research algorithm after analyzing and comparing the prediction performance of five time series prediction models. Based on the outgoing longwave radiation (OLR) data, the time series prediction model was used to predict the infrared longwave radiation values in the spatial area of 5° × 5° at the epicenter for 30 days before the earthquake. The confidence interval was used as the evaluation criterion to extract anomalies. The examples of earthquakes selected for study were the Yangbi Ms6.4-magnitude earthquake in Yunnan on 21 May 2021 and the Luding Ms6.8-magnitude earthquake in Sichuan on 5 September 2022. The results showed that the observed values of the Yangbi earthquake 15 to 16 days before the earthquake (5 May to 6 May) exceeded the prediction confidence interval over a wide area and to a large extent. This indicates a strong and concentrated OLR anomaly before the Yangbi earthquake. The observations at 27 days (9 August), 18 days (18 August), and 8 days (28 August) before the Luding earthquake exceeded the prediction confidence interval in a local area and by a large extent, indicating a strong and scattered OLR anomaly before the Luding earthquake. Overall, the method used in this paper extracts anomalies in both spatial and temporal dimensions and is an effective method for extracting infrared longwave radiation anomalies. [ABSTRACT FROM AUTHOR]

Several possible lithosphere–atmosphere–ionosphere coupling mechanisms before earthquake occurrence are presented in the literature. They are described by several models with different interaction channels (e.g., electromagnetic, mechanics, chemical, thermal), sometimes in conflict with each other. In this paper, we search for anomalies six months before the Lushan (China) 2013 earthquake in the three geo-layers looking for a possible view of the couplings and testing if one or another is more reliable to describe the observations. The Lushan earthquake occurred in China's Sichuan province on 20 April 2013, with a magnitude of Mw = 6.7. Despite the moderate magnitude of the event, it caused concern because its source was localized on the southwest side of the same fault that produced the catastrophic Wenchuan event in 2008. This paper applies a geophysical multi-layer approach to search for possible pre-earthquake anomalies in the lithosphere, atmosphere, and ionosphere. In detail, six main increases in the accumulated seismic stress were depicted. Anomalous geomagnetic pulsations were recorded in the Chengdu observatory, sometimes following the increased stress. Atmosphere status and composition were found to be anomalous in several periods before the earthquake, and, spatially, the anomalies seem to appear firstly far from the upcoming earthquakes and later approaching the Longmenshan fault where the Lushan earthquakes nucleated. The Formosat-3 data identified interesting anomalies in the altitude or electron content of the ionospheric F2 peak in correspondence with seismic and atmospheric anomalies 130 days before the earthquake. In addition, the total electron content showed high anomalous values from 12 to 6 days before the earthquake. We compared the anomalies and tried to explain their correspondences in different geo-layers by the lithosphere–atmosphere–ionosphere coupling models. In particular, we identified three possible couplings with different mechanisms: a first, about 130 days before the earthquake, with a fast (order of one day) propagation delay; a second, about 40 days before the earthquake occurrence, with a propagation delay of few days and a third from 2.5 weeks until one week before the event. Such evidence suggests that the geo-layers could interact with different channels (pure electromagnetic or a chain of physical-chemical processes) with specific propagation delays. Such results support the understanding of the preparation for medium and large earthquakes globally, which is necessary (although not sufficient) knowledge in order to mitigate their impact on human life. [ABSTRACT FROM AUTHOR]

The rapid and accurate extraction of wide-area coseismic landslide locations is critical in earthquake emergencies. At present, the extraction of coseismic landslides is mainly based on post-earthquake site investigation or the interpretation of human–computer interactions based on remote sensing images. However, the identification efficiency is low, which seriously delays the earthquake emergency response. On the basis of the available multisource and multiscale remote sensing data, numerous studies have been carried out on the methods of coseismic landslide extraction, such as pixel analysis, object-oriented analysis, change detection, and machine learning. However, the effectiveness of coseismic landslide extraction was low in wide areas with complex topographic and geomorphic backgrounds. Therefore, this paper offers a comprehensive study of the factors influencing coseismic landslides and researches rapid and accurate wide-area coseismic landslide extraction methods with multisource remote sensing and geoscience technology. These techniques include digital elevation modeling (DEM) and its derived slopes and aspects. An embedded multichannel spectral–topographic feature fusion model for coseismic landslide extraction based on DeepLab V3+ is proposed, and a knowledge-enhanced deep learning information extraction method integrating geological knowledge is formed. Using the Jiuzhaigou Ms7.0 earthquake (seismic intensity VIII) in Sichuan Province, China, a comparison of landslide extraction models and strategies is carried out. The results show that the model proposed in this paper achieves the best balance in the accuracy and efficiency of wide-area extractions. Using multiple feature data of coseismic landslides, the problem of mixed pixels is solved. The rate of the misidentification of landslides as clouds, snow, buildings, and roads is significantly lower than in other methods. The identified landslide boundaries are smoother and more accurate, and the connectivity is better. Compared with other methods, ours can more accurately eliminate landslides not triggered by the Jiuzhaigou earthquake. While using the image block strategy to ensure extraction efficiency, it also improves the extraction accuracy of wide-area coseismic landslides in complex backgrounds. [ABSTRACT FROM AUTHOR]

In this paper, based on Sina Weibo data, a natural language processing (NLP) analysis method was used to analyze the temporal and spatial sequence characteristics of people's attention and the characteristics of text content with the help of microblogs posted by people within 6 days after the 2022 Lushan M6.1, Maerkang M5.8 and Luding M6.8 earthquakes. Moreover, the same analysis method was used on the content of comments on microblogs posted by official media outlets within 6 days after the earthquakes to analyze the changes in people's sentiments and the differences in the sentiments in various regions, and the influencing factors were also analyzed. The results of this research show the following: In terms of the spatial and temporal distributions, people's attention was affected by the earthquakes themselves and their social impacts, and the first 2 h was often a period of an outbreak of attention, with the publishing areas mainly concentrated in Sichuan and Guangdong. In terms of people's sentiments, the overall microblogging sentiment of the three earthquakes was positive, and the sentiment value of the people in Sichuan was generally low compared with that of the people in the other regions. Not only was the fluctuation in sentiment affected by the influence of the region, but it was also positively related to the sentiment of official microblogs. The results of this research provide reference for guiding people's sentiments after earthquakes in the new media era. [ABSTRACT FROM AUTHOR]

For emergency rescue and damage assessment after an earthquake, quick detection of seismic landslides in the affected areas is crucial. The purpose of this study is to quickly determine the extent and size of post-earthquake seismic landslides using a small amount of post-earthquake seismic landslide imagery data. This information will serve as a foundation for emergency rescue efforts, disaster estimation, and other actions. In this study, Wenchuan County, Sichuan Province, China's 2008 post-quake Unmanned Air Vehicle (UAV) remote sensing images are used as the data source. ResNet-50, ResNet-101, and Swin Transformer are used as the backbone networks of Mask R-CNN to train and identify seismic landslides in post-quake UAV images. The training samples are then augmented by data augmentation methods, and transfer learning methods are used to reduce the training time required and enhance the generalization of the model. Finally, transfer learning was used to apply the model to seismic landslide imagery from Haiti after the earthquake that was not calibrated. With Precision and F1 scores of 0.9328 and 0.9025, respectively, the results demonstrate that Swin Transformer performs better as a backbone network than the original Mask R-CNN, YOLOv5, and Faster R-CNN. In Haiti's post-earthquake images, the improved model performs significantly better than the original model in terms of accuracy and recognition. The model for identifying post-earthquake seismic landslides developed in this paper has good generalizability and transferability as well as good application potential in emergency responses to earthquake disasters, which can offer strong support for post-earthquake emergency rescue and disaster assessment. [ABSTRACT FROM AUTHOR]

Tectonic extrusion bypassing the eastern Himalayan syntaxis results in a significant increase in regional stress instability and the associated frequent occurrence of earthquakes in southern Yunnan, China. However, the stress field, and the relationship between the focal mechanism of earthquakes and stress evolution in southern Yunnan, remain enigmatic. In this paper, using a modified grid point test method, we calculated the focal mechanism of ML ≥ 2.5 earthquakes in southern Yunnan (22–25° N, 100–104° E) from January 2009 to June 2023. Utilizing the solutions of historical earthquake focal mechanisms, we obtained the present-day regional tectonic stress field in southern Yunnan via inversion. The results indicate complex and diverse seismic focal mechanisms, and the main types of earthquakes are strike-slip events, followed by normal fault and reverse fault events. The orientations of the maximum and minimum principal stress axes rotate in a clockwise direction from northeast to southwest. The internal stress orientation distribution of the rhombic Sichuan–Yunnan block in the study area is consistent, and the block boundary zone is the site where stress deflection occurs, and the regional tectonic stress field is influenced by the interaction among different blocks. The distribution of R-value in the Lamping–Simao block gradually increases from north to south, indicating that the compressive stress required for material transport becomes relatively small. Combined with the geological and tectonic background of the study area, our results suggest that the speed of block movement gradually decreases from north to south; the distribution of R-value in the South China block is significantly smaller than that of the interior of the Sichuan–Yunnan rhombus, and the proportion of compressive stresses is larger, indicating a stronger extrusion in this region, which may be related to the fact that the Sichuan–Yunnan rhombus is strongly resisted by the South China block in the east. [ABSTRACT FROM AUTHOR]

On 5 September 2022, an Ms6.8 magnitude earthquake occurred in Luding County, Sichuan Province, China. Based on Sentinel-1 SAR images, this paper uses the D-InSAR approach to obtain the displacement field of the earthquake, invert the coseismic sliding distribution, and then calculate the static coulomb stress changes of the coseismic deformation on the aftershock distribution and surrounding faults. Further, the seismic structure is analyzed and discussed. The InSAR coseismic deformation field demonstrates that the maximum LoS displacement of the surface deformation caused by the Luding earthquake is about 15 cm. The Luding Ms 6.8 earthquake is dominated by the Moxi fault, which is a left-lateral strike-slip fault that ruptures along the NNW-SSE trend at about 160.3°, and the dip is 81°. The fault depth is mainly 5~15 km, the maximum sliding amount is about 174.8 cm, and the corresponding depth is 8.5 km. The seismic moment tensor obtained by inversion is 1.06 × 1019 Nm, Mw = 6.65. The Coulomb stress generated by the Luding earthquake on the northern end of the Anninghe fault zone exceeded the trigger threshold. The risk of the Anninghe fault's future earthquake was greater, and continuous monitoring and risk assessment were required. [ABSTRACT FROM AUTHOR]

Seismic landslides are the most common and highly destructive earthquake-triggered geological hazards. They are large in scale and occur simultaneously in many places. Therefore, obtaining landslide information quickly after an earthquake is the key to disaster mitigation and relief. The survey results show that most of the landslide-information extraction methods involve too much manual participation, resulting in a low degree of automation and the inability to provide effective information for earthquake rescue in time. In order to solve the abovementioned problems and improve the efficiency of landslide identification, this paper proposes an automatic landslide identification method named improved U-Net model. The intelligent extraction of post-earthquake landslide information is realized through the automatic extraction of hierarchical features. The main innovations of this paper include the following: (1) On the basis of the three RGB bands, three new bands, DSM, slope, and aspect, with spatial information are added, and the number of feature parameters of the training samples is increased. (2) The U-Net model structure is rebuilt by adding residual learning units during the up-sampling and down-sampling processes, to solve the problem that the traditional U-Net model cannot fully extract the characteristics of the six-channel landslide for its shallow structure. At the end of the paper, the new method is used in Jiuzhaigou County, Sichuan Province, China. The results show that the accuracy of the new method is 91.3%, which is 13.8% higher than the traditional U-Net model. It is proved that the new method is effective and feasible for the automatic extraction of post-earthquake landslides. [ABSTRACT FROM AUTHOR]

In recent years, the rapid expansion and development of the shale gas industry in the Sichuan Basin has coincided with a series of unexpected moderate-sized earthquakes. Given that the Sichuan Basin is situated within a stable interior block, the focal mechanism of the 2019 earthquake sequence (ML4.7, ML5.4, and ML5.2) in the Weiyuan-Rongxian area remains a subject of debate. In this study, we propose a joint InSAR- and PCA- based inversion method utilizing the distributed Mogi model to investigate the spatial-temporal characteristics of a gas reservoir and evaluate the induced Coulomb stress change. The surface deformation derived from Sentinel-1 data between 2015 and 2021 was consistent with the spatial distribution of production wells, and it correlated with the temporal changes in reservoir volume associated with the shale gas operating process. The Coulomb stress loading on the regional faults suggests that human activities associated with shale gas operation likely triggered the three moderate earthquakes. Furthermore, our results indicate Coulomb stress loadings of 10 kPa, 15 kPa, 5 kPa, 3 kPa, and 87 kPa on the Dongxingchang fault, Gaoqiao fault, Dayaokou fault, Niujingao fault, and Lijiachang fold, respectively. Consequently, fluid injection and extraction during shale gas development could be contributing to the elevated seismic activity in the Weiyuan-Rongxian area. [ABSTRACT FROM AUTHOR]

On 5 September 2022 (BJT), Luding, located in southwestern Sichuan Province, China, experienced an MS 6.8 earthquake. This earthquake occurred within the historical rupture zone of the 1786 MS 7.75 event, part of the southern section of the Xianshui He Fault belt. Given the average 155-year recurrence interval for strong earthquakes in this area, the 236 years since the last event made this earthquake somewhat expected. However, prior to this event, we did not detect any anomalies indicating low surface b-values, which are often indicative of a high-stress state in the source area before strong earthquakes, as highlighted by numerous studies. Our research focused on the northern section of the eastern boundary of the Sichuan–Yunnan sub-block, encompassing the Xianshui He, Anning He, Zemu He, and Daliang Shan fault belts. We meticulously located earthquakes of ML ≥ 1.5 from 2009 to May 2022. The catalog was divided into two periods: 2009–2014 and 2015–May 2022. Using an AIC-constraint method, we analyzed the changes in b-values (Δb) in the latter period compared to the former. Our findings revealed a significant abnormal Δb zone (Δb < −0.3), with a radius of approximately 50 km, when ΔAIC ≥ 2 was selected. Intriguingly, the epicenter of the recent Luding MS 6.8 earthquake fell within this abnormal zone. Furthermore, we calculated the b-value cross-section for the southern section of the Xianshui He fault belt using a directory of precisely located small earthquakes. This revealed that the location, scale, and shape of the abnormally low-b-value area corresponded with the large displacement co-seismic area of the main earthquake, affirming the b-value's effectiveness in identifying asperities. The b-value's temporal evolution prior to the mainshock exhibited a nearly decade-long continuous decrease, signifying a long-term stress-loading process akin to that observed before many strong earthquakes. The b-value anomalies observed from different profiles before the Luding earthquake underline the necessity of a comprehensive, multi-dimensional analysis of such anomalies. Finally, our analysis indicates that nine earthquakes with MS ≥ 6.5, including the Luding MS 6.8 event, have contributed to increased Coulomb Failure Stress change (ΔCFS) in the Daofu (DF)–Kangding (KD) section of the Xianshui He fault belt and the northern section of the Anning He fault belt south of Shimian (SM), with amplitudes surpassing the 0.01 MPa threshold. This suggests the potential for strong earthquakes in these zones. [ABSTRACT FROM AUTHOR]

On 1 June 2022, a magnitude 6.1 earthquake struck the southern segment of the Longmenshan fault zone on the eastern edge of the Tibetan Plateau, once again causing casualties and economic losses. Understanding the deep-seated dynamic mechanisms that lead to seismic events in the Lushan earthquake area and assessing the potential hazards in seismic gap areas are of significant importance. In this study, we utilized 118 magnetotelluric datasets collected from the Lushan earthquake area and employed three-dimensional electromagnetic inversion with topographic considerations to characterize the deep-seated three-dimensional resistivity structure of the Lushan earthquake area. The results reveal that the Shuangshi–Dachuan fault in the Lushan earthquake area can be divided into two relatively low-resistivity zones: a western zone dipping southeastward and an eastern zone with a steeper slightly northwestern dip. These two zones intersect at a depth of approximately 20 km, forming an extensional pattern resembling a "Y" shape. The epicenters of both the 2013 and 2022 Lushan earthquakes are primarily located in the upper constricted portion of the pocket-like low-resistivity body at depth. The distribution of seismic aftershocks is confined within the region enclosed by the high-resistivity body, following the pattern of the Y-shaped low-resistivity zone. [ABSTRACT FROM AUTHOR]

By deploying a magnetic monitoring network in the earthquake-prone areas of Sichuan, China, and conducting long-term observations, processing, and analysis of real-time geomagnetic data, it can be observed that the pre-earthquake geomagnetic anomalies are highly correlated with the occurrence time of earthquakes. We propose a novel algorithm that obtains a new quantity by accumulating geomagnetic anomaly energy to eliminate external environmental interference and take its gradient as a measure for predicting the occurrence time of an earthquake. Through observations of a large amount of geomagnetic data, it is confirmed that the proposed method can be used to predict the occurrence time of earthquakes with about 75% to 85% accuracy. Conclusions: The geomagnetic anomaly phenomenon can be accurately observed and recorded before an impending earthquake, and it has been confirmed by data that using this observation makes imminent earthquake prediction a practical prediction method. [ABSTRACT FROM AUTHOR]

An Mw 6.8 earthquake occurred in Luding County, Ganzi Tibetan Autonomous Prefecture, Sichuan Province, on 5 September 2022. This seismic event triggered numerous coseismic geohazards in the seismic zone. In this study, the ascending- and descending-track synthetic aperture radar (SAR) images observed by the Sentinel-1A satellite are utilized to extract the coseismic surface deformation of the Luding earthquake. Subsequently, a faulting model is estimated based on the elastic dislocation theory, under the constraint of the InSAR observation. Additionally, the POT technique was employed to detect coseismic geohazards. High-spatial-resolution optical remote sensing images served to validate the reliability of the detection results. The coseismic interferometric synthetic aperture radar (InSAR) deformation field indicated a maximum deformation of ~190 mm and ~140 mm along the ascending and descending tracks, respectively. The estimated best-fitting faulting model suggests that the optimal seismogenic fault strike and dip angles are 169.3° and 70°, respectively. The fault slip predominantly exhibits left-lateral strike-slip characteristics and is concentrated at depths of 3–12 km. The estimated maximum fault slip was 2.67 m, occurring at a depth of 7 km. The pixel offset tracking (POT) result derived from the pre- and post-earthquake SAR images found a total of 245 medium- to large-scale coseismic geohazards, with a verification rate from optical images exceeding 64%. The distribution of these geohazards is notably dense within the significant fault rupture segment. Geohazards on the fault hanging wall are densely packed, whereas landslides along the Dadu River's fault footwall are also notably frequent. [ABSTRACT FROM AUTHOR]

The 2008 8.0 Ms Wenchuan earthquake caused serious ecological degradation in the northwest of China's Sichuan Province. Elucidating landscape fragmentation and spatial pattern of post-earthquake landscape is of great interest in order to improve ecological restoration and predict the spatial distribution of damaged ecosystems in earthquake-affected areas. We used four real-time remote sensing images to analyze the landscape pattern characteristics and spatial autocorrelation of the Longxi River Basin before and after the Wenchuan earthquake during the period from 2005 to 2015. In the study period, the degree of landscape fragmentation increased 1 year after the earthquake in 2009 but decreased in 2011 and 2015. The spatial distribution of forest, farmland, and shrub-grassland had significantly positive spatial correlation and the characteristics of spatial aggregation from 2005 to 2015. Construction land had no significant spatial correlation before the earthquake in 2005, but significantly positive spatial correlation after the earthquake, while traffic land had no significant spatial correlation across the study period. Unlike the other landscape types, geological disasters changed from a significantly negative spatial correlation before the earthquake to a significantly positive spatial correlation after the earthquake. However, the positive autocorrelation of all landscape types decreased with the increase of space distance, but in different distance-decay rates. The High-high spatial aggregation areas of geological disasters and construction land clustered gradually upstream of the basin and distributed in Longchi town, respectively; those of farmland distributed in the southeast of the basin increased in 2009 but then decreased, while those of forests had the opposite pattern as the dominant landscape type after the earthquake. Our results elucidated the spatial structure and distribution features of the Longxi River Basin to give a theoretical foundation for assessing the effects of ecological restoration and reconstruction management in earthquake-affected areas. [ABSTRACT FROM AUTHOR]

This study reports the atmospheric electric field (AEF) anomalies associated with seismic-geological activity recorded by the monitoring network in the Sichuan–Yunnan region of China during the 15–30 days prior to the Yangbi earthquake in Yunnan Province, China, on 21 May 2021. Based on the real-time AEF data from continuous observation, this study summarized the characteristics of the anomalous interference of different meteorological factors on the AEF, compared the simultaneous meteorological data of the AEF anomalies, and ruled out the influence of precipitation, wind, fog, and other weather factors on the AEF anomalies in Yangbi County prior to the Yangbi Ms 6.4 earthquake. The AEF anomalies were identified and extracted from the two-month data from 1 April to 1 June, which were from multiple days, stations, and rupture zones near the 100 km radius from the epicenter of the Yangbi Ms 6.4 main earthquake. Using time series and wavelet transform analysis methods, the obvious common features of the anomalies were summarized, and the homology of the anomalies was verified. The main outcome of the investigation in this study will be used to distinguish and characterize the AEF anomalies associated with pre-seismic geologic activity of non-meteorological elements in the near future. [ABSTRACT FROM AUTHOR]

A series of small-magnitude earthquakes (Mw 2.9~Mw 4.9) occurred in Rong County, Sichuan Province, China between 30 March 2018 and December 2020, which threatened the safety of local residents. Determining the surface displacement and estimating the damage caused by these earthquakes are significant for earthquake relief, post-earthquake disaster assessment and hazard elimination. This paper integrates the Generic Atmospheric Correction Online Service (GACOS) with interferometry synthetic aperture radar (InSAR) to accurately detect the displacement of the series of small-magnitude earthquakes in Rong County based on 45 Sentinel-1 ascending/descending images acquired from January 2018 to December 2020. We analyze the influence of some factors involved in surface displacement, including earthquake magnitude, focal depth and the distance from the epicenter to the fault. The above measurement for small-magnitude earthquakes and statistics analysis for the displacement have not been performed before, so this can help better understand the displacement features of small-magnitude earthquakes, which are important for post-earthquake hazard assessment and disaster prevention. [ABSTRACT FROM AUTHOR]

The Ms 7.0 Jiuzhaigou earthquake that occurred on 8 August 2017 triggered hundreds of landslides in the Jiuzhaigou valley scenic and historic-interest area in Sichuan, China, causing heavy casualties and serious property losses. Quick and accurate mapping of post-disaster landslide distribution is of paramount importance for earthquake emergency rescue and the analysis of post-seismic landslides distribution characteristics. The automatic identification of landslides is mostly based on medium- and low-resolution satellite-borne optical remote-sensing imageries, and the high-accuracy interpretation of earthquake-triggered landslides still relies on time-consuming manual interpretation. This paper describes a methodology based on the use of 1 m high-resolution unmanned aerial vehicle (UAV) imagery acquired after the earthquake, and proposes a support vector machine (SVM) classification method combining the roads and villages mask from pre-seismic remote sensing imagery to accurately and automatically map the landslide inventory. Compared with the results of manual visual interpretation, the automatic recognition accuracy could reach 99.89%, and the Kappa coefficient was higher than 0.9, suggesting that the proposed method and 1 m high-resolution UAV imagery greatly improved the mapping accuracy of the landslide area. We also analyzed the spatial-distribution characteristics of earthquake-triggered landslides with the influenced factors of altitude, slope gradient, slope aspect, and the nearest faults, which provided important support for the further study of post-disaster landslide distribution characteristics, susceptibility prediction, and risk assessment. [ABSTRACT FROM AUTHOR]

An Ms 6.8 earthquake struck Luding County, Ganzi Prefecture, Sichuan Province on 5 September 2022, with the epicenter about 10 km away from Hailuogou Glacier. How Hailuogou Glacier was affected by the earthquake was of major concern to society. Sentinel-1 SAR satellite imaging was used to monitor the glacier surface velocity during different periods before and after the Luding earthquake based on pixel offset tracking (POT) technology, which applies a feature-tracking algorithm to overcome the phase co-registration problems commonly encountered in large displacement monitoring. The results indicated that the velocity had a positive correlation with the average daily maximum temperature and the slope gradient on the small-slope surfaces. The correlation was not apparent on the steeper surfaces, which corresponded spatially with the identified ice avalanche region in the Planet images. It was deduced that this may be because of the occurrence of ice avalanches on surfaces steeper than 25°, or that the narrower front channel impeded the glacier's movement. The Luding earthquake did not cause a significant increase in the velocity of Hailuogou Glacier within a large range, but it disturbed the front area of the ice cascade, where the maximum velocity reached 2.5 m/d. Although the possibility of directly-induced destruction by ice avalanches after the earthquake was low, and the buffering in the downstream glacier tongue further reduced the risk of ice avalanches, the risk of some secondary hazards such as debris flow increased. The proposed method in this study might be the most efficient in monitoring and evaluating the effects of strong earthquakes on glaciers because it would not be limited by undesirable weather or traffic blockage. [ABSTRACT FROM AUTHOR]

The Baihetan Reservoir was impounded on 6 April 2021, after which the water level rose significantly. Notably, after one week of impoundment, microseismic activities were prominent around the reservoir area, which was highly associated with the water level change. From 6 April 2021 to 31 December 2021, over 7000 microearthquakes were recorded by the seismic stations in the vicinity of the reservoir, including 12 ML > 3 events. The maximum was the 21 December 2021 ML3.9 earthquake in Qiluogou town, Sichuan. The post-impoundment seismic events were clustered in Hulukou town in the Qiaojia Basin, with an overall "Y-shaped" pattern. In this study, taking advantage of the high-frequency waveform matching approach, the pre- and post-impoundment focal mechanism solutions totaling 207 ML > 2 earthquakes are successfully obtained. The impoundment-induced stress change is analyzed, and the iterative joint inversion method is used to invert the stress field. Major results and conclusions include the following: (1) After impoundment, the number of normal fault earthquakes remarkably increased in the reservoir area; (2) Impoundment has led to a vertical compressive stress field and horizontal tensile stress field in the area where microearthquakes occurred. It is necessary to pay close attention to possible moderate-to-strong earthquakes in the future. [ABSTRACT FROM AUTHOR]

The Changning area is located in the southern Sichuan basin and the western Yangtze Plate and is the most abundant shale gas exploration area in China. In recent years, Changning has experienced frequent earthquakes with moderate magnitudes, attracting extensive interest. To investigate the magnetic characteristics in Changning, 952 land-based stations were employed to establish a magnetic anomaly model with a resolution of 2 km, and the subsurface magnetic basement structure was obtained by an iterative algorithm in the Fourier domain. The magnetic anomaly model shows significant distinctions between the northern salt mine area and the southern shale gas area. The magnetic basement includes the crystalline basement and the Sinian sedimentary rock metamorphic basement, which has strong magnetism. The large intracratonic rift that developed in the Sinian–Early Cambrian plays an important role in the evolution of Changning, which also impacts magnetic anomalies and the magnetic basement structure. Finally, by comparing the seismic wave velocity ratio structure, the deeper magnetic basement that corresponds to the higher seismic wave velocity ratio can be explained. This article implies that magnetic anomalies and magnetic basement depth have a certain correlation with earthquakes in Changning, and it provides a geodynamic reference for Changning and the southern Sichuan basin. [ABSTRACT FROM AUTHOR]

Featured Application: Resource and environmental effects of the Tibetan Plateau. Long-term stress accumulation influenced by coseismic stress changes and postseismic viscoelastic relaxation is considered critical to triggering giant earthquakes. Nevertheless, how the stress increase is interrupted by aftershocks and how it influences the megaseismic cycle remain enigmatic. In this study, based on the Mohr–Coulomb failure criterion at the nucleated segments of the 2008 great Sichuan earthquake, the stress variation associated with four M > 6 aftershocks was calculated for the period from 2010 to 2017. The results show that (1) the spatial distribution of coseismic stress change is correlated with the rupture pattern of large events and has a fundamental impact on triggering subsequent earthquakes and (2) postseismic viscoelastic relaxation leads to increased Coulomb stress accumulation at the northern and southern edges of the seismogenic Longmenshan fault, which results in enhanced fault instability and the potential for future large events. [ABSTRACT FROM AUTHOR]

To investigate the nonlinear spatio-temporal behavior of earthquakes, a complex network has been built using borehole strain data from the southwestern endpoint of the Longmenshan fault zone, Sichuan-Yunnan region of China, and the topological structural properties of the network have been investigated based on data from 2011–2014. Herein, six observation sites were defined as nodes and their edges as the connections between them. We introduced Multi-channel Singular Spectrum Analysis (MSSA) to analyze periodic oscillations, earthquake-related strain, and noise in multi-site observations, and then defined the edges of the network by calculating the correlations between sites. The results of the daily degree centrality of the borehole strain network indicated that the strain network anomalies were correlatable with local seismicity associate with the earthquake energy in the strain network. Further investigation showed that strain network anomalies were more likely to appear before major earthquakes rather than after them, particularly within 30 days before an event. Anomaly acceleration rates were also found to be related to earthquake energy. This study has revealed the self-organizing pre-earthquake phenomena and verified the construction of borehole networks is a powerful tool for providing information on earthquake precursors and the dynamics of complex fault systems. [ABSTRACT FROM AUTHOR]

On 8 August 2017 an earthquake (MS7.0) occurred within Jiuzhaigou County, Northern Aba Prefecture, Sichuan Province, China, triggering 4834 landslides with an individual area greater than 7.8 m2 over a more than 400 km2 region. Instead of correlating geological and topographic factors with the coseismic landslide distribution pattern, this study has attempted to reveal the control from seismic landslide susceptibility mapping, which relies on the calculation of critical acceleration values using a simplified Newmark block model. We calculated the average critical acceleration for each cell of the gridded study area (1 km×1 km), which represented the seismic landslide susceptibility of the cell. An index of the potential landslide area generation rate was defined, i.e., the possible landsliding area in each grid cell. In combination with PGA (peak ground acceleration) distribution, we calculated such indexes for each cell to predict the possible landslide hazard under seismic ground shaking. Results show that seismic landslide susceptibility plays an important role in determining the coseismic landslide pattern. The places with high seismic landslide susceptibility tends to host many landslides. Additionally, the areas with high potential landslide area generation rates have high real landslide occurrence rates, consistent with dominant small-medium scale landslides by this earthquake. This approach can aid assessment of seismic landslide hazards at a preliminary stage. Additionally, it forms a foundation for further research, such as the rapid evaluation of post-earthquake landslides and identifying highly impacted areas to help decision makers prioritize disaster relief efforts. [ABSTRACT FROM AUTHOR]

The occurrence of aftershocks and geohazards (landslides, collapses, and debris flows) decreases with time following a major earthquake. The 12 May 2008 Wenchuan Earthquake in Sichuan, China, provides the opportunity to characterize the subsequent spatiotemporal evolution of geohazards. Following the 12 May 2008 Wenchuan Earthquake, the incidence of geohazards first increased sharply, representing a "post-earthquake effect", before starting to decrease. We compared the spatial distribution of the area affected by vegetation damage (AVD) triggered by large and medium-scale geohazards (LMG). We studied the interval prior to the 12 May 2008 Wenchuan Earthquake (2001–2007), the co-seismic period (2008), and the post-earthquake interval (2009–2016) and characterized the trend of decreasing geohazards at a macro scale. In vegetated areas, geohazards often seriously damage the vegetation, resulting in pronounced contrasts with the surrounding surface in terms of color tone, texture, morphology, and Normalized Difference Vegetation Index (NDVI) which are evident in remote sensing images (RSI). In principle, it is possible to use the strong positive correlation between AVD and geohazards to determine indirectly the resulting vegetation and to monitor its spatiotemporal evolution. In this study we attempted to characterize the process of geohazard evolution in the region affected by the 12 May 2008 Wenchuan Earthquake during 2001–2016. Our approach was to analyze the characteristics of areas with reduced vegetation coverage caused by LMG. Our principal findings are as follows: (i) Before the Wenchuan Earthquake (during 2001–2007), there was no evidence for a linear increase in the number of LMG with time; thus, the geological environment was relatively stable and the geohazards were mainly induced by rainfall events. (ii) The 12 May 2008 Wenchuan Earthquake was the main cause of a surge in geohazards in 2008, with the characteristics of seismogenic faults and strong aftershocks determining the spatial distribution of geohazards. (iii) Following the 12 May 2008 Wenchuan Earthquake (during 2009–2016) the incidence of geohazards exhibited an oscillating pattern of attenuation, with a decreasing trend of higher-grade seismic intensity. The intensity of geohazards was related to rainfall and seismogenic faults, and also to the number, magnitude and depth of new earthquakes following the 12 May 2008 Wenchuan Earthquake. Our results provide a new perspective on the temporal pattern of attenuation of seismic geohazards, with implications for disaster prevention and mitigation and ecological restoration in the areas affected by the 12 May 2008 Wenchuan Earthquake. [ABSTRACT FROM AUTHOR]