Earthquake Research Advances最新文献

{"title":"A spatial forecast of some MW≥6.5 earthquakes in California and Nevada","authors":"John E. Ebel","doi":"10.1016/j.eqrea.2025.100359","DOIUrl":"10.1016/j.eqrea.2025.100359","url":null,"abstract":"<div><div>This paper presents a prospective forecast of the locations of the next <em>M</em>_W ​≥ ​6.5 earthquakes in California and Nevada based on the locations and rates of occurrence of <em>M</em> ​≥ ​4.0 earthquakes during the past 30 years, called here preshocks. The time period of the forecast is arbitrarily set at 33 years. The forecast faults are the Anza section of the San Jacinto Fault, the Calaveras Fault, the creeping section of the San Andreas Fault, the Maacama Fault, the San Bernardino section of the San Jacinto Fault, and the southern San Andreas Fault, all strike-slip faults in California, and the normal-faulting Wassuk Range Fault in Nevada. The suspected preshocks have occurred randomly along the expected future fault ruptures at rates of at least 0.5 events per year. The temporal history of preshocks for past <em>M</em> ​≥ ​6.5 earthquakes in California do not indicate when the future mainshock will occur. Outside of California, preshock activity was observed before the 2016 <em>M</em>_W 7.0 Kumamoto, Japan earthquake, the 2023 <em>M</em>_W 7.8 Kahramanmaras, Turkey earthquake, and the 2017 <em>M</em>_W 6.5 Jiuzhaigou, China earthquake, all strike-slip events, as well as the 2008 <em>M</em>_W 7.9 Wenchuan, China thrust earthquake. The two mainshocks in China had preshock rates less than 0.5 events per year. By publishing this spatial earthquake forecast, seismologists in the future can evaluate whether or not this forecast was a total success, a total failure, or a partial success. The probability of just one of the forecast events actually taking place during the forecast time period is less than 2%.</div></div>","PeriodicalId":100384,"journal":{"name":"Earthquake Research Advances","volume":"5 3","pages":"Article 100359"},"PeriodicalIF":0.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144907816","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-resolution satellite imagery analysis of coseismic landslides and liquefaction induced by the 2024 MW 7.4 Hualien earthquake, Taiwan, China","authors":"Lingyun Lu ,&nbsp;Yueren Xu ,&nbsp;Jiacheng Tang ,&nbsp;Guiming Hu","doi":"10.1016/j.eqrea.2024.100356","DOIUrl":"10.1016/j.eqrea.2024.100356","url":null,"abstract":"<div><div>Rapidly obtaining spatial distribution maps of secondary disasters triggered by strong earthquakes is crucial for understanding the disaster-causing processes in the earthquake hazard chain and formulating effective emergency response measures and post-disaster reconstruction plans. On April 3, 2024, a <em>M</em>_W 7.4 earthquake struck offshore east of Hualien, Taiwan, China, which triggered numerous coseismic landslides in bedrock mountain regions and severe soil liquefaction in coastal areas, resulting in significant economic losses. This study utilized post-earthquake emergency data from China's high-resolution optical satellite imagery and applied visual interpretation method to establish a partial database of secondary disasters triggered by the 2024 Hualien earthquake. A total of 5 348 coseismic landslides were identified, which were primarily distributed along the eastern slopes of the Central Mountain Range watersheds. In high mountain valleys, these landslides mainly manifest as localized bedrock collapses or slope debris flows, causing extensive damage to highways and tourism facilities. Their distribution partially overlaps with the landslide concentration zones triggered by the 1999 Chi-Chi earthquake. Additionally, 6 040 soil liquefaction events were interpreted, predominantly in the Hualien Port area and the lowland valleys of the Hualien River and concentrated within the IX-intensity zone. Widespread surface subsidence and sand ejections characterized soil liquefaction. Verified against local field investigation data in Taiwan, rapid imaging through post-earthquake remote sensing data can effectively assess the distribution of coseismic landslides and soil liquefaction within high-intensity zones. This study provides efficient and reliable data for earthquake disaster response. Moreover, the results are critical for seismic disaster mitigation in high mountain valleys and coastal lowlands.</div></div>","PeriodicalId":100384,"journal":{"name":"Earthquake Research Advances","volume":"5 3","pages":"Article 100356"},"PeriodicalIF":0.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144907820","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":"A comprehensive earthquake source database for China’s strong-motion flatfile (2007–2020)","authors":"Hongwei Wang ,&nbsp;Hongrui Li ,&nbsp;Yefei Ren ,&nbsp;Ruizhi Wen","doi":"10.1016/j.eqrea.2024.100346","DOIUrl":"10.1016/j.eqrea.2024.100346","url":null,"abstract":"<div><div>The National Strong-Motion Observation Network System of China has collected over 12 000 strong-motion recordings from 2007 to December 2020. This study assembled the source-related metadata of 1 920 earthquakes associated with assembled well-processed recordings of China. The earthquake basic information, focal mechanisms, and the fault geometry were collected from various institutes and literature. We recommended the <em>M</em>_W values for 900 earthquakes, the fault types for 1 064 earthquakes, and the fault geometries for 18 large earthquakes. We also performed the statistical analysis for establishing the empirical conversions of <em>M</em>_W-<em>M</em>_S, and <em>M</em>_L, and providing the empirical relationships between <em>M</em>_W and ruptured area, aspect ratio, respectively. Moreover, the ruptured fault geometries of large earthquakes were used to preliminarily divide all earthquakes considered into 1 141 mainshocks, and 779 aftershocks. The finite-fault distances (<em>R</em>_JB and <em>R</em>_rup) of strong-motion recordings from the 18 large earthquakes were calculated, and then used to yield the statistic relationships between the point-source distances (<em>R</em>_epi and <em>R</em>_hyp) and finite-fault distances. We finally provided the earthquake source database freely accessible at website. The source-related metadata can be directly applied to develop the ground motion prediction equations of China.</div></div>","PeriodicalId":100384,"journal":{"name":"Earthquake Research Advances","volume":"5 2","pages":"Article 100346"},"PeriodicalIF":0.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143868886","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":"Physical mechanisms of earthquake nucleation and foreshocks: Cascade triggering, aseismic slip, or fluid flows?","authors":"Zhigang Peng ,&nbsp;Xinglin Lei","doi":"10.1016/j.eqrea.2024.100349","DOIUrl":"10.1016/j.eqrea.2024.100349","url":null,"abstract":"<div><div>Earthquakes are caused by the rapid slip along seismogenic faults. Whether large or small, there is inevitably a certain nucleation process involved before the dynamic rupture. At the same time, significant foreshock activity has been observed before some but not all large earthquakes. Understanding the nucleation process and foreshocks of earthquakes, especially large damaging ones, is crucial for accurate earthquake prediction and seismic hazard mitigation. The physical mechanism of earthquake nucleation and foreshock generation is still in debate. While the earthquake nucleation process is present in laboratory experiments and numerical simulations, it is difficult to observe such a process directly in the field. In addition, it is currently impossible to effectively distinguish foreshocks from ordinary earthquake sequences. In this article, we first summarize foreshock observations in the last decades and attempt to classify them into different types based on their temporal behaviors. Next, we present different mechanisms for earthquake nucleation and foreshocks that have been proposed so far. These physical models can be largely grouped into the following three categories: elastic stress triggering, aseismic slip, and fluid flows. We also review several recent studies of foreshock sequences before moderate to large earthquakes around the world, focusing on how different results/conclusions can be made by different datasets/methods. Finally, we offer some suggestions on how to move forward on the research topic of earthquake nucleation and foreshock mechanisms and their governing factors.</div></div>","PeriodicalId":100384,"journal":{"name":"Earthquake Research Advances","volume":"5 2","pages":"Article 100349"},"PeriodicalIF":0.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143868888","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":"Frontiers in Chinese seismology: Synthesizing innovations from the 18th Seismological Society of China Conference (SSC 2023)","authors":"Xiangli He ,&nbsp;Tao Li ,&nbsp;Qinxia Wang ,&nbsp;Ziyue Wang ,&nbsp;Zhaoning Chen ,&nbsp;Chong Xu","doi":"10.1016/j.eqrea.2024.100351","DOIUrl":"10.1016/j.eqrea.2024.100351","url":null,"abstract":"<div><div>The 18^th Academic Conference of the Seismological Society of China was held in Guiyang, China, on August 7, 2023, fostering academic exchanges on the latest advancements in earthquake science. The conference featured 170 abstracts and nearly 300 academic presentations. In this paper, we classify and summarize the scholars' presentations, analyzing the current state and progress of earthquake science in China from four key perspectives: crustal structure dynamics, earthquake mechanisms, seismic resilience of urban and rural infrastructure, and innovative earthquake services. The presentations reveal that research primarily focuses on detecting crustal structures in southwest China, with seismic imaging technology and magnetotelluric detection being the most commonly used methods. Studies on earthquake mechanisms are centered on recent destructive events, such as the 2023 <em>M</em>_W 7.8 and <em>M</em>_W 7.6 Türkiye earthquakes, the 2022 <em>M</em>_W 6.7 Luding earthquake, and the 2021 <em>M</em>_W 7.4 Madoi earthquake. Regarding seismic resilience, the focus is on shock resistance and seismic isolation experiments involving large-scale hybrid structures, as well as the formation mechanisms and risk assessments of earthquake-triggered disaster chains. Additionally, significant progress has been made in smart earthquake services, particularly in rapid disaster assessment, earthquake disaster information extraction technology, the China Seismic Experimental Site, and the strong-motion Flatfile database for mainland China. Overall, this conference highlighted that earthquake science in China has reached a new level of development. However, numerous scientific challenges and critical technologies remain to be addressed, such as acquiring higher-resolution crustal structures and applying big data and artificial intelligence to diverse seismic models and earthquake services, which requires the continued collaboration of researchers in the field.</div></div>","PeriodicalId":100384,"journal":{"name":"Earthquake Research Advances","volume":"5 2","pages":"Article 100351"},"PeriodicalIF":0.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143868890","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":"Estimating the final fatalities using early reported death count from the 2023 Kahramanmaraş, Türkiye, MS 8.0–7.9 earthquake doublet and revising the estimates over time","authors":"Yan Liu,&nbsp;Zitao Wang,&nbsp;Xuemin Zhang","doi":"10.1016/j.eqrea.2024.100331","DOIUrl":"10.1016/j.eqrea.2024.100331","url":null,"abstract":"<div><div>Earthquakes can cause significant damage and loss of life, necessitating immediate assessment of the resulting fatalities. Rapid assessment and timely revision of fatality estimates are crucial for effective emergency decision-making. This study using the February 6, 2023, <em>M</em>_S 8.0 and <em>M</em>_S 7.9 Kahramanmaraş, Türkiye earthquakes as an example to estimate the ultimate number of fatalities. An early Quick Rough Estimate (QRE) based on the number of deaths reported by the Disaster and Emergency Management Presidency of Türkiye (AFAD) is conducted, and it dynamically adjusts these estimates as new data becomes available. The range of estimates of the final number of deaths can be calculated as 31 384–56 475 based on the \"the QRE of the second day multiplied by 2–3″ rule, which incorporates the reported final deaths 50 500. The Quasi-Linear and Adaptive Estimation (QLAE) ​method adaptively adjusts the final fatality estimate within two days and predicts subsequent reported deaths. The correct order of magnitude of the final death toll can be estimated as early as 13 ​hr after the <em>M</em>_S 8.0 earthquake. In addition, additional earthquakes such as May 12, 2008, <em>M</em>_S 8.1 Wenchuan earthquake (China), September 8, 2023, <em>M</em>_S 7.2 Al Haouz earthquake (Morocco), November 3, 2023, <em>M</em>_S 5.8 Mid-Western Nepal earthquake, December 18, 2023, <em>M</em>_S 6.1 Jishishan earthquake (China), January 1, 2024, <em>M</em>_S 7.2 Noto Peninsula earthquake (Japan) and August 8, 2023, Maui, Hawaii, fires are added again to verified the correctness of the model. The fatalities from the Maui fires are found to be approximately equivalent to those resulting from an MS 7.4 earthquake. These methods complement existing frameworks such as Quake Loss Assessment for Response and Mitigation (QLARM) and Prompt Assessment of Global.</div></div>","PeriodicalId":100384,"journal":{"name":"Earthquake Research Advances","volume":"5 2","pages":"Article 100331"},"PeriodicalIF":0.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143868884","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":"Reexamination confirming additional seismic evidence for the 12 May 2010 low-yield nuclear test","authors":"Miao Zhang ,&nbsp;Lianxing Wen","doi":"10.1016/j.eqrea.2024.100350","DOIUrl":"10.1016/j.eqrea.2024.100350","url":null,"abstract":"<div><div>This study examines event location and source discrimination for the May 12, 2010 possible nuclear event in North Korea, using seismic data recorded in the Dongbei Broadband Seismic Network in China. Using highly similar Pg waveforms between the events, we locate the event within 2 ​km of the 2009 nuclear test site. For event classification, we first build a group of reference earthquakes and explosions through a machine-learning phase picker and an event association/location process, with open-access satellite image verification; we then classify the event based on the Pg/Lg spectral ratios and Pg waveform similarity comparisons with past nuclear tests. The event is classified as a small explosion reaffirming the findings of Zhang and Wen (2015a). Along with independent scientific evidence from radionuclide studies and infrasound signal analysis, the May 12, 2010 event can be reasonably attributed to a low-yield nuclear test. Our study shows that explosion discriminants are dependent on event magnitudes and seismic noises, and vary from station to station. Accordingly, event classification should be performed on a station-by-station basis. The approach presented here is useful for seismic monitoring of low-yield nuclear tests.</div></div>","PeriodicalId":100384,"journal":{"name":"Earthquake Research Advances","volume":"5 2","pages":"Article 100350"},"PeriodicalIF":0.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143868885","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":"Automatic location of surface-monitored microseismicity with deep learning","authors":"Zhaolong Gan ,&nbsp;Xiao Tian ,&nbsp;Xiong Zhang ,&nbsp;Mengxue Dai","doi":"10.1016/j.eqrea.2024.100355","DOIUrl":"10.1016/j.eqrea.2024.100355","url":null,"abstract":"<div><div>Accurate and rapid determination of source locations is of great significance for surface microseismic monitoring. Traditional methods, such as diffraction stacking, are time-consuming and challenging for real-time monitoring. In this study, we propose an approach to locate microseismic events using a deep learning algorithm with surface data. A fully convolutional network is designed to predict source locations. The input data is the waveform of a microseismic event, and the output consists of three 1D Gaussian distributions representing the probability distribution of the source location in the <span><math><mrow><mi>x</mi></mrow></math></span>, <span><math><mrow><mi>y</mi></mrow></math></span>, and <span><math><mrow><mi>z</mi></mrow></math></span> dimensions. The theoretical dataset is generated to train the model, and several data augmentation methods are applied to reduce discrepancies between the theoretical and field data. After applying the trained model to field data, the results demonstrate that our method is fast and achieves comparable location accuracy to the traditional diffraction stacking location method, making it promising for real-time microseismic monitoring.</div></div>","PeriodicalId":100384,"journal":{"name":"Earthquake Research Advances","volume":"5 2","pages":"Article 100355"},"PeriodicalIF":0.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143868887","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":"IonKit-NH: A MATLAB-based toolkit for ionospheric detection of earthquake, tsunami and volcanic eruption","authors":"Long Tang","doi":"10.1016/j.eqrea.2024.100353","DOIUrl":"10.1016/j.eqrea.2024.100353","url":null,"abstract":"<div><div>In recent years, GNSS-derived total electron content (TEC) measurements have emerged as an effective method for detecting natural hazards through their ionospheric manifestations. Seismo-atmospheric disturbances generated by earthquakes, tsunamis, and volcanic eruptions propagate as traveling ionospheric disturbances (TIDs) that modify ionospheric electron density. Despite this potential, specialized open-source tools for such analyses remain limited. We present IonKit-NH, a MATLAB-based toolkit enabling systematic processing of multi-GNSS data (GPS, GLONASS, Galileo, BDS) through dual-frequency combination analysis for TEC derivation. The software implements automated generation of time-distance diagrams and 2D TEC perturbation maps, enabling quantitative characterization of TID propagation parameters associated with natural hazards. This toolkit enhances standardized analysis of ionospheric precursors and co-seismic signals across global navigation satellite systems.</div></div>","PeriodicalId":100384,"journal":{"name":"Earthquake Research Advances","volume":"5 2","pages":"Article 100353"},"PeriodicalIF":0.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143868883","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":"Summary of environmental effect and seismic activity in Qinghai-Xizang Plateau","authors":"Yanyun Zhang ,&nbsp;Yu Zhang ,&nbsp;Huazheng Su ,&nbsp;Ruidong Li ,&nbsp;Bingbing Han","doi":"10.1016/j.eqrea.2024.100354","DOIUrl":"10.1016/j.eqrea.2024.100354","url":null,"abstract":"<div><div>This paper focuses on the Qinghai-Xizang Plateau. It systematically reviews its seismic activity characteristics and extensive environmental effects under extreme climatic conditions in dry and cold seasons. Firstly, through detailed data analysis and literature review, it is revealed how the seasonal significant rainfall and temperature changes in the plateau establish potential links with key parameters such as the frequency and intensity of seismic activity. This process deeply analyzes how natural conditions such as extreme rainfall and temperature changes directly or indirectly affect the mechanism of earthquake preparation and triggering, which may promote or inhibit the occurrence of seismic activity. The close relationship between cold and dry seasons and seismic activity is emphasized, and the unique influence of these special climatic conditions on seismic activity patterns is discussed. In addition, the regional distribution characteristics of seismic activity in the plateau area are also analyzed, including key data such as annual occurrence number and magnitude distribution, which provides strong data support for formulating regional earthquake disaster response strategies. In addition, the characteristics of various secondary disasters that may be caused by earthquakes, such as landslides, debris flows, barrier lakes, etc., are analyzed, which deepens the understanding of the complexity of the earthquake disaster chain. The aim is to provide a scientific basis for future earthquake disaster prevention and control work and to promote the improvement of earthquake science research and disaster management levels in the Qingzang Plateau and even the world.</div></div>","PeriodicalId":100384,"journal":{"name":"Earthquake Research Advances","volume":"5 2","pages":"Article 100354"},"PeriodicalIF":0.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143868889","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}