Sichuan Earthquake Research Articles

Detecting sub-instability before three Mw > 6.0 earthquakes on Chinese mainland in 2020–2022 with load/unload response ratio

The sub-instability refers to a stress state that exists between the maximum stress the rock can withstand and its final failure. This stress state should be an indicator of impending large earthquakes, as it occurs in the final stage of earthquake nucleation. We apply the Load/Unload Response Ratio (LURR) method to explore sub-instability in the source media before large earthquakes. The earthquake-related observation data such as the groundwater, crustal deformation, electromagnetism and so on were adopted as data input. The load and unload phases at each observation station are discriminated by the change of Coulomb failure stress caused by earth tides along the tectonically optimal sliding direction. Retrospective studies of this approach on the 2020 Mw6.0 Jiashi, Xinjiang, 2022 Mw6.6 Menyuan, Qinghai, and Mw6.6 Luding, Sichuan earthquakes show that the LURR time series derived from the observation stations near the epicenter exceed 2 standard deviations of the mean within several days to years before the mainshocks. Additionally, as the time of mainshock approaches, the distance between the stations detecting LURR anomaly and epicenter decreases. The LURR anomalies indicate the presence of sub-instability prior to a large earthquake, and their spatio-temporal evolution may suggest the weakening processes in the source media.

Seismicity changes and numerical simulation of coseismic deformation following the 2022 Ms6.8 Luding earthquake in Sichuan, China

Seismicity changes and numerical simulation of coseismic deformation following the 2022 Ms6.8 Luding earthquake in Sichuan, China

Improved medium-to-short-term earthquake predictions in China in 2022

Every year, China should determine annual seismic hazard regions for earthquakes of magnitude 5.0 and above in Mainland China in the next year. Meanwhile, the short-term earthquake potential in each seismic hazard region is evaluated by monthly analyzing geophysical observations in the same neighborhood and identifying anomalies therein. In 2022, China improved the strategies for these medium-to-short-term earthquake predictions. The annual seismic hazard regions are produced with the optimal methods selected by rigorous tests whose predictions are integrated through the Bayesian formula. And in short-term earthquake potential evaluation, in addition to tracking crucial anomalies, China pays attention to the changes in the number of observed anomalies. The practice in 2022 shows that more than 80% of earthquakes of magnitude 5.0 and above in Mainland China occurred in annual seismic hazard regions. Besides, the largest (M s 6.9 Menyuan, Qinghai) and the most disastrous (M s 6.8 Luding, Sichuan) earthquakes were predicted in both annual and short terms. Some crucial anomalies were observed before these two earthquakes, whose evolutions correlate well with the earthquake time and location. The statistics of the near-field geophysical observations indicate that, prior to the mainshock, the number of anomalies increased significantly and migrated toward the epicenter.

Rapid determination of seismic influence field based on mobile communication big data-A case study of the Luding Ms 6.8 earthquake in Sichuan, China.

Smartphone location data provide the most direct field disaster distribution data with low cost and high coverage. The large-scale continuous sampling of mobile device location data provides a new way to estimate the distribution of disasters with high temporal-spatial resolution. On September 5, 2022, a magnitude 6.8 earthquake struck Luding County, Sichuan Province, China. We quantitatively analyzed the Ms 6.8 earthquake from both temporal and geographic dimensions by combining 1,806,100 smartphone location records and 4,856 spatial grid locations collected through communication big data with the smartphone data under 24-hour continuous positioning. In this study, the deviation of multidimensional mobile terminal location data is estimated, and a methodology to estimate the distribution of out-of-service communication base stations in the disaster area by excluding micro error data users is explored. Finally, the mathematical relationship between the seismic intensity and the corresponding out-of-service rate of communication base stations is established, which provides a new technical concept and means for the rapid assessment of post-earthquake disaster distribution.

The Social Production and Political Potency of Home: Contentions between Housing Reconstruction and Place Making among the Chinese Qiang after the 2008 Sichuan Earthquake

The Social Production and Political Potency of Home: Contentions between Housing Reconstruction and Place Making among the Chinese Qiang after the 2008 Sichuan Earthquake

Optimal decision-making of post-disaster emergency material scheduling based on helicopter–truck–drone collaboration

In the last decades, natural disasters, such as earthquakes and landslides, have occurred frequently, seriously threatening the safety of people’s lives and property. How emergency material is scheduled and delivered efficiently to the affected sites after a disaster has become a critical issue in emergency management. Current studies on emergency material scheduling mainly focus on truck or helicopter transport. Inspired by the success of employing drones in commercial logistics, this work investigates the emergency material scheduling issue based on the cooperative transport of drones, helicopters, and trucks. Specifically, this paper considers the limited transport capacity, road conditions in the early stage of the disaster rescue, and affected sites restricted by road conditions that can only be served by helicopters or drones. The studied problem is formulated as a mixed integer programming model, and a two-stage heuristic algorithm is developed to solve the model. For the proposed model, instances of different sizes are generated, and extensive experiments are performed to test the efficiency of the proposed algorithm. The comparison between the solutions obtained by the two-stage algorithm and Gurobi Solver for the small instances validates the effectiveness of the proposed heuristic algorithm. Experimental results for the larger instances show that the proposed two-stage algorithm can effectively solve the problem of emergency material scheduling. Sensitivity analysis of ten typical instances is performed to provide managerial insights. Finally, a case study of the Sichuan earthquake and the visualization of transport routes are presented. The model and solving approach proposed in this work can provide essential decision references for emergency management decision-making.

Seismic risk model for regional buildings that considers the influence of temperature and intensity measures

Probability-based seismic risk and random ground motion theories are used to develop high-precision seismic risk functions and models of regional building portfolios. Seismic intensity measures and structural demand parameters are critical in developing seismic fragility models for building clusters. Earthquake damage data indicate that ambient temperature may influence structural fragility, but the effect of temperature on seismic risk is commonly ignored. A method for quantifying seismic intensity is proposed in this study and optimized using 450,000 acceleration records detected by 15 stations during the Luding earthquake in Sichuan, China, on September 5, 2022. Considering the influence of different temperature fields, the proposed seismic intensity quantification method was used to evaluate structural damage during two destructive earthquakes in Xinjiang, China (the Aktao earthquake on September 2, 2003 and the Zhaosu earthquake on December 1, 2003). Three structural empirical seismic risk matrices and cloud maps were developed, and a vulnerability membership curve was generated using fuzzy decision-making, a membership algorithm, and nonlinear regression. A structural seismic risk index function was proposed, and vulnerability cloud diagrams and curves based on actual structural seismic vulnerability datasets were generated. Together, these analyses demonstrated the impact of temperature and intensity measures on the seismic risk to regional buildings. A model was established to evaluate the seismic risk to typical structures and was validated using historical earthquake damage data from China. This method improves the accuracy of earthquake risk and vulnerability assessments for typical building clusters given the influence of temperature. The developed seismic risk prediction model enables the evaluation of vulnerability and resilience of typical structures under low and high temperatures.

Research on emotional tendency of earthquake disaster based on E-Trans model: take the topic of “Sichuan Earthquake” on microblog as an example

Research on emotional tendency of earthquake disaster based on E-Trans model: take the topic of “Sichuan Earthquake” on microblog as an example

Slip Model of the 2022 Mw 6.6 Luding Earthquake from Inversion of GNSS and InSAR with Sentinel-1

Abstract We use surface deformation measurements, including Interferometric Synthetic Aperture Radar data acquired by the Sentinel-1A satellites and Global Navigation Satellite System observations, to invert the fault geometry and coseismic slip distribution of the 2022 Mw 6.6 earthquake in Sichuan, China. The dip of the best-fitting model is 68°. The rupture of the 2022 Luding earthquake is dominated by northwest strike-slip movement, mainly concentrated over a length of about 20 km above a depth of 15 km. The maximum slip is at approximately 4 km depth with the maximum displacement of about 2.1 m. The results indicate that the 2022 Luding earthquake ruptured the shallow layer of the seismic zone. The slip distribution indicates that the Moxi–Shimian fault segment is fully locked from the surface down to 15 km, which is consistent with the estimated locking depth. Based on the Coulomb stress analysis and considering the strong locking state of the Anninghe fault, more attention should be paid to the possibility of earthquakes in the Anninghe fault.

Trauma Clearance Concept of PTSD Help Disaster Victims Avoid from PTSD by volunteering

As we know that trauma means experience that cause intense physical and psychological stress reaction in a big disaster or unfortunate encounter . After disaster, the victims engage in volunteer will get more opportunities to take part in the society and interact with more people. Especially the victims will get a new valuable experience with delight. These experiences will cover-up and clear the trauma experience. Actually through inviting victims involved in volunteer , we can find they re-get the value of life and start a new life career. This article practically shares diverse experiences regarding a lot victims Tzu Chi domestic and international disaster relief activities which include 921 Taiwan Chi-Chi earthquake in 1999, Indian Ocean earthquake and tsunami in 2004, Sichuan (Wenchuan) earthquake of Mainland China in 2008, Morake typhoon of southern Taiwan in 2009, Typhoon Haiyan of Philippine in 2013. We accumulated some examples of victim volunteers how did they quit the invasion of PTSD through the involve of volunteering, Thousands of the victims get a lot of valuable and delightful experiences will invite the other victims to participate the volunteer. This positive action will gradually be spread by victims and set into impetus to the whole disaster area. Except the group type example of disaster victims’ volunteer, there is also the example that a lady who lost husband and two children. How she walked out from the biggest tragedy of her life through volunteering as the interpreter.

Fine Seismogenic Fault Structures and Complex Rupture Characteristics of the 2022 M6.8 Luding, Sichuan Earthquake Sequence Revealed by Deep Learning and Waveform Modeling

AbstractAn approximate 236‐year interval in major seismic activity near the southern Xianshuihe fault terminated on 5 September 2022 until a destructive M6.8 Luding earthquake. The strike‐slip mainshock, accompanied by potent normal‐faulting aftershocks, fell short of the previously anticipated M7+ event. Utilizing deep‐learning and source inversion techniques, we analyzed dense near‐field seismograms to examine detailed fault structures and rupture characteristics. Our high‐quality relocated catalog with 7,388 events revealed that the earthquake ruptured an unmapped multiscale fault network. The analysis of the mainshock and 43 ML ≥ 2.8 aftershocks suggests normal‐faulting events relate to the vertical movement of the Gongga Mountain. The sequence length, seismic gaps, and asperities derived from seismicity and waveform modeling imply that the rupture of the M6.8 quake was incomplete, indicating a high risk of a future M6+ event at the northern Moxi segment. These findings hold crucial implications for assessing future seismic hazards in this region.

Anomalies in Infrared Outgoing Longwave Radiation Data before the Yangbi Ms6.4 and Luding Ms6.8 Earthquakes Based on Time Series Forecasting Models

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.

Determination of most affected areas by earthquakes based on mobile signaling data: a case study of the 2022 Mw 6.6 Luding earthquake, China

Rapid determination of the most-affected areas after an earthquake can help with emergency relief efforts, which is also an essential part of postearthquake relief work. Mobile signaling data contains rich user information, which helps determine the most-affected areas. This study investigated the 2022 Mw 6.6 Luding earthquake in Sichuan, China; the relationship between mobile signaling data and the seismically most-affected area was explored using comparative, regression, and spatial interpolation analysis. The results revealed that mobile signaling data changed abnormally following the earthquake and differed across high- and low-intensity zones. There was a significant correlation between mobile signaling data and intensity. Additionally, the most-affected areas estimated using mobile signaling data were comparable to the actual seismic damage. Therefore, mobile signaling data can provide a reference for determining the most-affected areas and assist in emergency relief efforts after an earthquake.

Considering the Research on The Distribution Priority of Materials at The Disaster-Stricken Points After the Earthquake

After the earthquake, it is necessary to effectively and quickly carry out the distribution of emergency materials. This paper considers the different disaster situations of different disaster areas, selects the attributes that affect the material demand in the disaster area, and uses fuzzy clustering technology to classify the demand points; then, uses the entropy The right method sorts different classifications to obtain the priority of material distribution at disaster-stricken points; determines the material satisfaction requirements of each demand point in the distribution system, and finally takes the Yushu earthquake in Sichuan as an example to verify.

Examining governance of post-earthquake reconstruction planning from an evolutionary resilience perspective

Purpose The politically laden nature of postdisaster recovery calls for more research on its governance, especially at the micro-scale. Apart from engineering-oriented frameworks, researchers need new theoretical underpinnings. This paper aims to review the development of the evolutionary resilience theory and use it as an analytical framework to evaluate the governance of post-earthquake reconstruction planning in China. Design/methodology/approach This paper examines how reconstruction planning is governed in the epicenter town of the 2008 Great Sichuan Earthquake, highlighting three key qualities of evolutionary resilience. The authors draw on site investigations, semistructured interviews and analysis of official and unpublished documents from various sources. Findings This paper finds that despite the absence of specific resilience statements in reconstruction plans of the time, qualities of evolutionary resilience, including social connectedness, flexibility and innovation, were evident in a hybrid and contradictory reconstruction planning system. In this respect, resilience thinking appears in Chinese planning earlier than generally assumed. This paper suggests that this manifestation of resilience was the result of an instrumental utility in addressing socioeconomic uncertainties in the postdisaster environment and, thus, may not be systematic. Originality/value This work enriches the understanding of recovery governance from an evolutionary resilience perspective where existing research is insufficient. It also offers ample practical guidance for similar cases in China and elsewhere.

The 2008 Sichuan Earthquake and Its Impacts on Economy

China, with one of the largest populations and the second-largest gross domestic product (GDP), experiences severe earthquake disasters. The Great Sichuan earthquake, one of the deadliest in Chinese history and the most devastating in China since the 1980s, occurred in 2008. This earthquake is characterized by its massive damage to the economy and the loss of a huge number of human lives. This study primarily focused on summarizing the existing studies related to the economic impacts of the Sichuan earthquake and specifically sought to identify the impacts of the Sichuan earthquake on the economy in the affected area. As a result, the earthquake had a significant long-term negative impact on the overall GDP. The earthquake greatly affected the tourist industry, and it has destructively influenced the development of the tourism industry in the quake-hit area. Also, this earthquake harmed the agricultural output in the damaged areas with different magnitudes in the Sichuan province. In addition, the Sichuan earthquake caused extensive damage to local critical infrastructure. The results implied that agricultural, tourism, and infrastructure inputs were reduced in the affected areas. Finally, it could serve as an important reference for the development program after a major earthquake.

Semantic Segmentation Model for Wide-Area Coseismic Landslide Extraction Based on Embedded Multichannel Spectral–Topographic Feature Fusion: A Case Study of the Jiuzhaigou Ms7.0 Earthquake in Sichuan, China

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.

Rapid assessment of the September 5, 2022 ​MS 6.8 Luding earthquake in Sichuan, China

At 12:52, September 5, 2022, an MS 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.

Research on the Characteristics of Internet Public Opinion and Public Sentiment after the Sichuan Earthquake Based on the Perspective of Weibo

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.

Association Among Negative Life Events, Sense of Security, and Depressive Symptoms in Chinese Adolescents After the 2013 Ya'an Earthquake.

About a fourth of Chinese adolescents developed clinically significant depressive symptoms following a disaster. However, little is known about whether and how post-trauma negative life events and a sense of security are associated with depressive symptoms in this population. This study examined the psychological experiences of Chinese young people who had experienced the 2013 Ya'an earthquake in Sichuan, China. This cross-sectional study was conducted in 2019. A total of 693 Chinese middle school students completed a questionnaire that measured their level of depressive symptoms, trauma exposure, stressful life events, and sense of security. Results of hierarchical multiple-regression analyses showed that the level of life stress from stressful life events was positively associated with the level of depressive symptoms (β = 0.416, P < 0.001) and the level of the sense of security was negatively associated with the level of depressive symptoms (β = -0.352, P < 0.001) when analysis controlled for age, gender, and trauma exposure. These findings highlight the importance of considering the influence of life stressors and the sense of security in devising measures and strategies for the prevention of the manifestation of depression among young people, particularly those who were exposed to disasters.