Earthquake Research Advances最新文献

{"title":"Leveraging the DeepSeek large model: A framework for AI-assisted disaster prevention, mitigation, and emergency response systems","authors":"Chenchen Xie ,&nbsp;Huiran Gao ,&nbsp;Yuandong Huang ,&nbsp;Zhiwen Xue ,&nbsp;Chong Xu ,&nbsp;Kebin Dai","doi":"10.1016/j.eqrea.2025.100378","DOIUrl":"10.1016/j.eqrea.2025.100378","url":null,"abstract":"<div><div>We proposes an AI-assisted framework for integrated natural disaster prevention and emergency response, leveraging the DeepSeek large language model (LLM) to advance intelligent decision-making in geohazard management. We systematically analyze the technical pathways for deploying LLMs in disaster scenarios, emphasizing three breakthrough directions: (1) knowledge graph-driven dynamic risk modeling, (2) reinforcement learning-optimized emergency decision systems, and (3) secure local deployment architectures. The DeepSeek model demonstrates unique advantages through its hybrid reasoning mechanism combining semantic analysis with geospatial pattern recognition, enabling cost-effective processing of multi-source data spanning historical disaster records, real-time IoT sensor feeds, and socio-environmental parameters. A modular system architecture is designed to achieve three critical objectives: (a) automated construction of domain-specific knowledge graphs through unsupervised learning of disaster physics relationships, (b) scenario-adaptive resource allocation using risk simulations, and (c) preserving emergency coordination via federated learning across distributed response nodes. The proposed local deployment paradigm addresses critical data security concerns in cross-border disaster management while complying with the FAIR principles (Findable, Accessible, Interoperable, Reusable) for geoscientific data governance. This work establishes a methodological foundation for next-generation AI-earth science convergence in disaster mitigation.</div></div>","PeriodicalId":100384,"journal":{"name":"Earthquake Research Advances","volume":"5 4","pages":"Article 100378"},"PeriodicalIF":0.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145420155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mainshock rupture properties, aftershock activities and remotely triggered seismicity associated with the 2025 Mw7.7 Sagaing fault earthquake in Myanmar","authors":"Zhigang Peng ,&nbsp;Xinglin Lei ,&nbsp;Dun Wang ,&nbsp;Xu Si ,&nbsp;Phuc Mach ,&nbsp;Qiu Zhong ,&nbsp;Chang Ding ,&nbsp;Yangfan Deng ,&nbsp;Min Qin ,&nbsp;Suqiu Miao","doi":"10.1016/j.eqrea.2025.100413","DOIUrl":"10.1016/j.eqrea.2025.100413","url":null,"abstract":"<div><div>A devastating Mw 7.7 earthquake struck near Mandalay, Myanmar, on March 28, 2025, causing extensive damage and casualties across Myanmar and neighboring regions. The 2025 event occurred in a well-recognized seismic gap along the Sagaing Fault. Here we focus on the mainshock rupture properties based on back-projection of teleseismic P waves and early aftershock locations, analysis of near-field seismic recordings for the mainshock initiation, and remotely triggered seismicity following the Mw7.7 mainshock. We find that the ∼500 ​km mainshock rupture can be revealed by both rapid back-projection of teleseismic P waves from multiple broadband arrays and early aftershock locations within about 3 ​h from the Thai Meteorological Department (TMD) catalog. The rupture speed went supershear in the southward propagation after the initial bilateral subshear ruptures, as expected for large strike-slip earthquakes of such sizes. Clear fault zone head waves that are reflected along a bimaterial fault interface are observed at the only near-fault station GE.NPW on the slower side about 2.6 ​km away from the Sagaing fault, consistent with the preferred direction of a supershear rupture propagating to the south. In addition, aftershocks from the regional TMD catalog appear to be located mostly to the east of the mainshock rupture. While we cannot completely rule out mis-locations from the one-sided station distribution, these off-fault seismicity could also be explained by reactivations of subsidiary faults within the Shan Plateau, or an eastward dipping of the mainshock rupture plane. Although no immediate foreshocks were found from several nearby stations, we identify one sub-event with magnitude ∼6 ​at the beginning of the mainshock with a slightly different focal mechanism about 20–30 ​km south of the hypocenter determined by the United States Geological Survey (USGS). The mainshock also occurred when the tidal stresses reached its maximum on the right-lateral strike-slip fault, likely indicating that the timing of the mainshock is modulated by the solid earth tides. We find a significant increase of seismic activity near the Thailand/Myanmar border, in multiple (geothermally active) regions of Yunnan province in Southwest China, as well as the Xingfengjian reservoir in the Guangdong province in South China. Because static stress changes from the mainshock are small but negative near the Thailand/Myanmar border, the occurrence of microseismicity in this and other regions can be mainly explained by remote triggering from dynamic stress changes of the mainshock rupture. Our analyses demonstrate the importance of rapid analysis on openly available seismic data and catalog to better understand the rupture properties and triggered seismicity following large earthquakes.</div></div>","PeriodicalId":100384,"journal":{"name":"Earthquake Research Advances","volume":"5 4","pages":"Article 100413"},"PeriodicalIF":0.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145420046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rapid report of seismic damage and consequence analysis in the 2025 M 6.8 Dingri earthquake","authors":"Qingxue Shang ,&nbsp;Zhongyi Zhou","doi":"10.1016/j.eqrea.2025.100394","DOIUrl":"10.1016/j.eqrea.2025.100394","url":null,"abstract":"<div><div>On January 7, 2025, a <em>M</em> 6.8 earthquake occurred at Dingri County, Shigatse City, Xizang Autonomous Region, which is the most largest earthquake in this region in the most recent five years. The maximum recorded peak ground acceleration in this earthquake is 0.43 ​<em>g</em>, which is significantly higher than the local design basis earthquake intensity level. This report focuses on the post-earthquake seismic damage investigation of rural self-built houses and local public buildings, which shows quite different seismic performance. Collapse and heavy damage of rural self-built houses without seismic resistant measures were observed, while the masonry houses with seismic resistant measures show good seismic performance against collapse. The structural systems of public buildings with proper seismic design suffered slight seismic damage. Different form slight structural damage, the seismic damages of non-structural components, which resulted in the interruption of public building functionality were highlighted in this report. With the investigation results of seismic damage suffered by local houses and buildings, the casualty distribution and causes were analyzed in detail.</div></div>","PeriodicalId":100384,"journal":{"name":"Earthquake Research Advances","volume":"5 4","pages":"Article 100394"},"PeriodicalIF":0.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145420102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High-performance CPU-GPU heterogeneous computing method for 9-component ambient noise cross-correlation","authors":"Jingxi Wang ,&nbsp;Weitao Wang ,&nbsp;Chao Wu ,&nbsp;Lei Jiang ,&nbsp;Hanwen Zou ,&nbsp;Huajian Yao ,&nbsp;Ling Chen","doi":"10.1016/j.eqrea.2024.100357","DOIUrl":"10.1016/j.eqrea.2024.100357","url":null,"abstract":"<div><div>Ambient noise tomography is an established technique in seismology, where calculating single- or nine-component noise cross-correlation functions (NCFs) is a fundamental first step. In this study, we introduced a novel CPU-GPU heterogeneous computing framework designed to significantly enhance the efficiency of computing 9-component NCFs from seismic ambient noise data. This framework not only accelerated the computational process by leveraging the Compute Unified Device Architecture (CUDA) but also improved the signal-to-noise ratio (SNR) through innovative stacking techniques, such as time-frequency domain phase-weighted stacking (tf-PWS). We validated the program using multiple datasets, confirming its superior computation speed, improved reliability, and higher signal-to-noise ratios for NCFs. Our comprehensive study provides detailed insights into optimizing the computational processes for noise cross-correlation functions, thereby enhancing the precision and efficiency of ambient noise imaging.</div></div>","PeriodicalId":100384,"journal":{"name":"Earthquake Research Advances","volume":"5 3","pages":"Article 100357"},"PeriodicalIF":0.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144907746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Green anchors enhance slope stability: mechanisms and efficacy in reinforcement","authors":"Zhihao Du ,&nbsp;Yu Zhang ,&nbsp;Haifeng Huo ,&nbsp;Sheng Shi ,&nbsp;Ruidong Li ,&nbsp;Bingbing Han","doi":"10.1016/j.eqrea.2025.100372","DOIUrl":"10.1016/j.eqrea.2025.100372","url":null,"abstract":"<div><div>As a primary slope stabilization technique, anchor support encompasses traditional engineering anchors, green anchors, and ecological restoration methods. This review synthesizes two decades of literature to evaluate these approaches. Current research disproportionately focuses on engineering anchors, while green anchor systems remain less studied despite their dual advantages: reduced labor/economic costs and environmental benefits. Notably, most green anchor studies originate from low-altitude plains, with minimal attention to high-altitude cold-arid regions such as plateaus. We therefore identify slope reinforcement using green anchors in plateau environments as a critical emerging research frontier.</div></div>","PeriodicalId":100384,"journal":{"name":"Earthquake Research Advances","volume":"5 3","pages":"Article 100372"},"PeriodicalIF":0.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144907748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Travel-time corrections for stations in the Guangdong seismic network and their impact on earthquake location accuracy","authors":"Ming Liang ,&nbsp;Xuan Yang ,&nbsp;Ce Jiang ,&nbsp;Ping Tian ,&nbsp;Qingxi Lin ,&nbsp;Xijiao Jiang","doi":"10.1016/j.eqrea.2024.100345","DOIUrl":"10.1016/j.eqrea.2024.100345","url":null,"abstract":"<div><div>The travel-time corrections for the primary seismic phases of 72 stations in the Guangdong seismic network, relative to the 1D South China travel-time model, were determined using joint hypocentral determination (JHD) and statistical analysis methods. The travel-time corrections for the Pg phase of 72 stations range between −0.25 ​s and 0.14 ​s, while the corrections for the Sg phase range between 0.27 ​s and 0.35 ​s, and those for the Pn phase are between −0.86 ​s and 0.07 ​s. The spatial distribution of travel-time corrections for Pg, Sg, and Pn phases of 72 stations correlates well with the geological structure in this region. This indicates that the travel-time corrections for Pg and Sg phases are mainly caused by the discrepancy between the actual crustal velocity structure beneath the stations and the 1D South China travel-time model. These corrections empirically compensate for systematic travel-time errors arising from such discrepancies. The primary factor contributing to the travel-time corrections for the Pn phase is the Moho undulations or tilt. These corrections are intended to compensate for systematic errors in travel time caused by variations in the actual Moho. By integrating the obtained travel-time corrections into the HYPO-SAT location algorithm, test results showed an obvious improvement in location accuracy and origin time precision for explosion events. The variation of horizontal distance between repeating earthquake pairs has also improved, with 86% of the repeating earthquake pair spacing being more accurately estimated after correction. This suggests the crucial significance of travel-time correction in earthquake location, and the consideration of travel-time correction exerts a notable impact on enhancing earthquake location accuracy.</div></div>","PeriodicalId":100384,"journal":{"name":"Earthquake Research Advances","volume":"5 3","pages":"Article 100345"},"PeriodicalIF":0.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144907744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Disaster analysis and lessons learned from the July 22, 2024, Ethiopian landslide","authors":"Tao Li ,&nbsp;Junxue Ma ,&nbsp;Yuandong Huang ,&nbsp;Shuhui Zhang ,&nbsp;Huiran Gao ,&nbsp;Chong Xu","doi":"10.1016/j.eqrea.2025.100358","DOIUrl":"10.1016/j.eqrea.2025.100358","url":null,"abstract":"<div><div>Rainfall-induced landslides are often highly destructive. Reviewing and analyzing the causes, processes, impacts, and deficiencies in emergency response is critical for improving disaster prevention and management. From the night of July 21 to the morning of July 22, 2024, the Kencho Shacha Gozdi Village in Gezei Gofa, Southern Nations, Nationalities, and Peoples' Region, Ethiopia, suffered heavy rainfall that triggered two landslides. By July 25, this event had claimed at least 257 lives. This study presents a detailed characterization of the landslides using multi-source data. By analyzing the landslide disaster process, this study summarizes key lessons and provides suggestions for preventing rainfall-induced geological hazards. The results indicate that rainfall has the greatest impact on the occurrence of landslides, while lithology and human activities have promoted and strengthened the landslide disaster. Despite the active disaster response in the local area, many problems were still exposed in the emergency response work. This analysis offers valuable insights for mitigating rainfall-induced geological hazards and enhancing emergency response capabilities.</div></div>","PeriodicalId":100384,"journal":{"name":"Earthquake Research Advances","volume":"5 3","pages":"Article 100358"},"PeriodicalIF":0.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144907819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Seismic response of existing stone masonry structures on soft soil foundations","authors":"Xin Zhao ,&nbsp;Haojiang Shang ,&nbsp;Yingxiong Wu","doi":"10.1016/j.eqrea.2025.100370","DOIUrl":"10.1016/j.eqrea.2025.100370","url":null,"abstract":"<div><div>The coastal region of Fujian contains numerous existing stone masonry structures, many of which are constructed on soft soil sites. Previous studies have shown that the soil-structure interaction (SSI) effect on soft soil foundations can prolong the structure's natural vibration period and enhance its seismic response. We develops a soil-structure interaction system model and a comparative rigid foundation model using the finite element software LS-DYNA to investigate the impact of SSI on the dynamic characteristics and seismic response of stone structures. The results indicate that the SSI effect alters stone structures' dynamic properties and seismic response. This alteration is evident in the extended natural vibration period, which reduces overall stiffness, increases interstory displacement angles, and slightly decreases the acceleration response. Under both SSI and FIX systems, the structural failure mode is characterized by the external collapse of the second-story stone walls, which causes the roof stone slabs to lose support and fall, leading to overall collapse. The FIX system demonstrates better structural integrity and stability with slower crack development. In contrast, the SSI system exhibits cracks that appear earlier and develop more rapidly, causing more severe damage. The research findings provide a theoretical basis for the seismic reinforcement of existing stone structures on soft soil foundations.</div></div>","PeriodicalId":100384,"journal":{"name":"Earthquake Research Advances","volume":"5 3","pages":"Article 100370"},"PeriodicalIF":0.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144907747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Preliminary analysis of emergency production and source parameters of the M 4.7 earthquake on September 18, 2024 in Feidong, Anhui","authors":"Jiajing Xu,&nbsp;Guangjie Han,&nbsp;Nan Xi,&nbsp;Li Sun","doi":"10.1016/j.eqrea.2025.100360","DOIUrl":"10.1016/j.eqrea.2025.100360","url":null,"abstract":"<div><div>At 20:08 on September 18, 2024, Beijing time, an earthquake of magnitude 4.7 occurred in Feidong, Anhui Province (31.98°N, 117.6°E). The China Earthquake Early Warning Network presented the first early warning results 8.9 ​s after the earthquake. The China Earthquake Networks Center (CENC) released the automatic rapid report results 163 ​s after the earthquake and the official rapid report results 8 ​min after the earthquake. At the same time, the CENC reported a series of emergency products, including source parameters, seismic tectonics, historical earthquakes, focal mechanism, instrument seismic intensity and predicted intensity. The results showed that the earthquake was located at the junction of the southern section of the Tanlu Fault and the Feizhong Fault, with aftershocks distributed in the NEE direction. The focal mechanism solution indicates that the earthquake is essentially a strike-slip event. The predicted intensity in the vicinity of the epicenter reaches up to VI, involving 23 towns that cover an area of about 1 359 ​km². Only one station near the epicenter shows a peak acceleration value greater than the fortification standard of the area, which may cause slight damage to some adjacent houses, consistent with the actual damage to buildings.</div></div>","PeriodicalId":100384,"journal":{"name":"Earthquake Research Advances","volume":"5 3","pages":"Article 100360"},"PeriodicalIF":0.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144906886","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deriving focal mechanism solutions of small to moderate earthquakes in Sichuan, China via a deep learning method","authors":"Chen Zhang ,&nbsp;Ji Zhang ,&nbsp;Jie Zhang","doi":"10.1016/j.eqrea.2025.100371","DOIUrl":"10.1016/j.eqrea.2025.100371","url":null,"abstract":"<div><div>As one of the most seismically active regions, Sichuan basin is a key area of seismological studies in China. This study applies a neural network model with attention mechanisms, simultaneously picking the P-wave arrival times and determining the first-motion polarity. The polarity information is subsequently used to derive source focal mechanisms. The model is trained and tested using small to moderate earthquake data from June to December 2019 in Sichuan. We apply the trained model to predict first-motion polarity directions of earthquake recordings in Sichuan from January to May 2019, and then derive focal mechanism solutions using HASH algorithm with predicted results. Compared with the source mechanism solutions obtained by manual processing, the deep learning method picks more polarities from smaller events, resulting in more focal mechanism solutions. The catalog documents focal mechanism solutions of 22 events (<em>M</em>_L 2.6–4.8) from analysts during this period, whereas we obtain focal mechanism solutions of 53 events (<em>M</em>_L 1.9–4.8) through the deep learning method. The derived focal mechanism solutions for the same events are consistent with the manual solutions. This method provides an efficient way for the source mechanism inversion of small to moderate earthquakes in Sichuan region, with high stability and reliability.</div></div>","PeriodicalId":100384,"journal":{"name":"Earthquake Research Advances","volume":"5 3","pages":"Article 100371"},"PeriodicalIF":0.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144907821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}