Kemal Onder Cetin, Erol Kalkan, Aysegul Askan, Marco Bohnhoff, Semih Ergintav, Ali Özgün Konca, Tuncay Taymaz, Yeşim Çubuk Sabuncu, Zeynep Gulerce
The Pazarcik and Ekinozu earthquakes in Kahramanmaras, Türkiye, with moment magnitudes M7.8 and 7.6 (U.S. Geological Survey), occurred on 6 February 2023 in southeastern Türkiye, on the East Anatolian fault zone (EAFZ), at local times of 04:17 and 13:24, respectively. The moment tensor solution indicates that both events were characterized by purely left‐lateral strike‐slip movements. The fault rupture of the first event originated on the Narli fault, located at the northern end of the Dead Sea fault zone, and extended along the Pazarcik, Erkenek, and Amanos segments of the EAFZ. Bilateral propagation occurred in the northeast and southwest directions, resulting...
{"title":"Preface for the Focus Section on the 6 February 2023, Kahramanmaraş, Türkiye, Earthquakes","authors":"Kemal Onder Cetin, Erol Kalkan, Aysegul Askan, Marco Bohnhoff, Semih Ergintav, Ali Özgün Konca, Tuncay Taymaz, Yeşim Çubuk Sabuncu, Zeynep Gulerce","doi":"10.1785/0220240006","DOIUrl":"https://doi.org/10.1785/0220240006","url":null,"abstract":"The Pazarcik and Ekinozu earthquakes in Kahramanmaras, Türkiye, with moment magnitudes M7.8 and 7.6 (U.S. Geological Survey), occurred on 6 February 2023 in southeastern Türkiye, on the East Anatolian fault zone (EAFZ), at local times of 04:17 and 13:24, respectively. The moment tensor solution indicates that both events were characterized by purely left‐lateral strike‐slip movements. The fault rupture of the first event originated on the Narli fault, located at the northern end of the Dead Sea fault zone, and extended along the Pazarcik, Erkenek, and Amanos segments of the EAFZ. Bilateral propagation occurred in the northeast and southwest directions, resulting...","PeriodicalId":21687,"journal":{"name":"Seismological Research Letters","volume":"34 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139924017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Allison M. Shumway, Mark D. Petersen, Peter M. Powers, Gabriel Toro, Jason M. Altekruse, Julie A. Herrick, Kenneth S. Rukstales, Jessica A. Thompson Jobe, Alexandra E. Hatem, Demi L. Girot
As part of the U.S. Geological Survey’s 2023 50‐State National Seismic Hazard Model (NSHM), we make modest revisions and additions to the central and eastern U.S. (CEUS) fault‐based seismic source model that result in locally substantial hazard changes. The CEUS fault‐based source model was last updated as part of the 2014 NSHM and considered new information from the Seismic Source Characterization for Nuclear Facilities (CEUS‐SSCn) Project. Since then, new geologic investigations have led to revised fault and fault‐zone inputs, and the release of databases of fault‐based sources in the CEUS. We have reviewed these databases and made minor revisions to six of the current fault‐based sources in the NSHM, as well as added five new fault‐based sources. Implementation of these sources follows the current NSHM methodology for CEUS fault‐based sources, as well as the incorporation of a new magnitude–area relationship and updated maximum magnitude and recurrence rate estimates following the methods used by the CEUS‐SSCn Project. Seismic hazard sensitivity calculations show some substantial local changes in hazard (−0.4g to 1.1g) due to some of these revisions and additions, especially from the addition of the central Virginia, Joiner ridge, and Saline River sources and revisions made to the Meers and New Madrid sources.
{"title":"Earthquake Rupture Forecast Model Construction for the 2023 U.S. 50‐State National Seismic Hazard Model Update: Central and Eastern U.S. Fault‐Based Source Model","authors":"Allison M. Shumway, Mark D. Petersen, Peter M. Powers, Gabriel Toro, Jason M. Altekruse, Julie A. Herrick, Kenneth S. Rukstales, Jessica A. Thompson Jobe, Alexandra E. Hatem, Demi L. Girot","doi":"10.1785/0220230294","DOIUrl":"https://doi.org/10.1785/0220230294","url":null,"abstract":"As part of the U.S. Geological Survey’s 2023 50‐State National Seismic Hazard Model (NSHM), we make modest revisions and additions to the central and eastern U.S. (CEUS) fault‐based seismic source model that result in locally substantial hazard changes. The CEUS fault‐based source model was last updated as part of the 2014 NSHM and considered new information from the Seismic Source Characterization for Nuclear Facilities (CEUS‐SSCn) Project. Since then, new geologic investigations have led to revised fault and fault‐zone inputs, and the release of databases of fault‐based sources in the CEUS. We have reviewed these databases and made minor revisions to six of the current fault‐based sources in the NSHM, as well as added five new fault‐based sources. Implementation of these sources follows the current NSHM methodology for CEUS fault‐based sources, as well as the incorporation of a new magnitude–area relationship and updated maximum magnitude and recurrence rate estimates following the methods used by the CEUS‐SSCn Project. Seismic hazard sensitivity calculations show some substantial local changes in hazard (−0.4g to 1.1g) due to some of these revisions and additions, especially from the addition of the central Virginia, Joiner ridge, and Saline River sources and revisions made to the Meers and New Madrid sources.","PeriodicalId":21687,"journal":{"name":"Seismological Research Letters","volume":"80 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139952011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
SSA would like to acknowledge the following individuals for their service as peer reviewers during 2023. As experts in our field, these volunteers provide valuable insight and constructive feedback to our authors. Thank you to each of you for your time and support of our journals. Your contributions are a critical element that ensures SSA continues to publish the highest quality research and helps us further our mission to advance earthquake science worldwide.John TownendChair of SSA Publications CommitteeElizabeth AbbottRobert AbbottNorman AbrahamsonRafael AbreuMateo AcostaKasey AderholdAlbert AguilarSean AhdiRaed AhmadEleanor Ainscoe...
{"title":"2023 In Recognition","authors":"","doi":"10.1785/0220240010","DOIUrl":"https://doi.org/10.1785/0220240010","url":null,"abstract":"SSA would like to acknowledge the following individuals for their service as peer reviewers during 2023. As experts in our field, these volunteers provide valuable insight and constructive feedback to our authors. Thank you to each of you for your time and support of our journals. Your contributions are a critical element that ensures SSA continues to publish the highest quality research and helps us further our mission to advance earthquake science worldwide.John TownendChair of SSA Publications CommitteeElizabeth AbbottRobert AbbottNorman AbrahamsonRafael AbreuMateo AcostaKasey AderholdAlbert AguilarSean AhdiRaed AhmadEleanor Ainscoe...","PeriodicalId":21687,"journal":{"name":"Seismological Research Letters","volume":"213 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139956146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pablo Letelier, Rodban Acuña, Ignacio Garrido, Jorge López, Guillermo Sanhueza, Caren Seguel, Ismael Riquelme, Neftalí Guzmán, Alfonso H Hernández
Background: Establishing reference intervals (RIs) in clinical laboratories is essential, as these can vary due to inter-individual variability as well as the analytical methods used. The purpose of this study was to determine RIs for markers and ratios biochemical in apparently healthy Chilean adults.
Methods: A sample of 1,143 data was selected from the Universidad Católica de Temuco, Clinical Laboratory database, La Araucanía Region, Chile, which were analysed by sex. The Tukey's Fences was used to detect outliers and the RIs were established using the non-parametric method.
{"title":"Reference intervals of biochemical parameters in Chilean adults.","authors":"Pablo Letelier, Rodban Acuña, Ignacio Garrido, Jorge López, Guillermo Sanhueza, Caren Seguel, Ismael Riquelme, Neftalí Guzmán, Alfonso H Hernández","doi":"10.5937/jomb0-44156","DOIUrl":"10.5937/jomb0-44156","url":null,"abstract":"<p><strong>Background: </strong>Establishing reference intervals (RIs) in clinical laboratories is essential, as these can vary due to inter-individual variability as well as the analytical methods used. The purpose of this study was to determine RIs for markers and ratios biochemical in apparently healthy Chilean adults.</p><p><strong>Methods: </strong>A sample of 1,143 data was selected from the Universidad Católica de Temuco, Clinical Laboratory database, La Araucanía Region, Chile, which were analysed by sex. The Tukey's Fences was used to detect outliers and the RIs were established using the non-parametric method.</p>","PeriodicalId":21687,"journal":{"name":"Seismological Research Letters","volume":"52 1","pages":"133-143"},"PeriodicalIF":2.0,"publicationDate":"2024-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10943462/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89610431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Sichuan–Yunnan block is located at the southeastern margin of the Tibetan Plateau, which is the key area as a transition belt from the active plate extrusion zone to the stable Yangtze Craton. Using a semiautomatic measuring method based on a graphical interface, we pick 81,585 precise travel times from 449 local earthquake records and finally obtain a crustal 3D P-wave velocity model of the Sichuan–Yunnan block. The model reveals an unexpected velocity contrast between the shallower and deeper crusts. It is summarized as weakly perturbed low-velocity belts encircling a high-velocity zone in the upper crust and strongly perturbed low-velocity anomalies in the mid-lower crust, respectively. The weak low-velocity anomalies are revealed along the major strike-slip faults, and their small perturbations may imply a slip-driven mechanism. The strong low-velocity anomalies are distributed extensively in the Sichuan–Yunnan block, and their great perturbations may be related to the partial melting of weak material extruded from Tibet. Besides, our result shows noticeable high-velocity anomalies in the core zone of the Emeishan Large Igneous Province (ELIP), which may be an indication of magma solidification from the ancient mantle plume. The result further exhibits an interesting pattern that the strong low-velocity anomalies are partially separated by the high-velocity anomalies in the ELIP. Such a specific pattern probably reflects that the stable zone in the ELIP leads to the bifurcation of weak Tibetan material.
川滇地块位于青藏高原东南缘，是活跃板块挤压带向稳定的长江克拉通过渡的关键区域。利用基于图形界面的半自动测量方法，我们从 449 条当地地震记录中选取了 81585 个精确走时，最终得到了川滇地块的地壳三维 P 波速度模型。该模型揭示了较浅地壳和较深地壳之间意想不到的速度对比。它分别概括为环绕上地壳高速带的弱扰动低速带和环绕中下地壳的强扰动低速异常带。弱低速异常沿主要的走向滑动断层揭示，其微小的扰动可能意味着滑动驱动机制。强低速异常广泛分布于川滇地块，其较大的扰动可能与西藏挤出的弱物质部分熔化有关。此外，在峨眉山大火成岩带的核心区，我们还发现了明显的高速异常，这可能是古代地幔羽流岩浆凝固的迹象。该结果还显示了一个有趣的模式，即在峨眉山大火成岩带中，强烈的低速异常与高速异常部分分离。这种特殊的模式可能反映了ELIP中的稳定区导致了西藏弱物质的分叉。
{"title":"Crustal Velocity Structure of the Sichuan–Yunnan Block Revealed by High-Quality Crustal Phase Travel Time","authors":"Liya Hu, Fengxue Zhang, Yu Li","doi":"10.1785/0220230181","DOIUrl":"https://doi.org/10.1785/0220230181","url":null,"abstract":"\u0000 The Sichuan–Yunnan block is located at the southeastern margin of the Tibetan Plateau, which is the key area as a transition belt from the active plate extrusion zone to the stable Yangtze Craton. Using a semiautomatic measuring method based on a graphical interface, we pick 81,585 precise travel times from 449 local earthquake records and finally obtain a crustal 3D P-wave velocity model of the Sichuan–Yunnan block. The model reveals an unexpected velocity contrast between the shallower and deeper crusts. It is summarized as weakly perturbed low-velocity belts encircling a high-velocity zone in the upper crust and strongly perturbed low-velocity anomalies in the mid-lower crust, respectively. The weak low-velocity anomalies are revealed along the major strike-slip faults, and their small perturbations may imply a slip-driven mechanism. The strong low-velocity anomalies are distributed extensively in the Sichuan–Yunnan block, and their great perturbations may be related to the partial melting of weak material extruded from Tibet. Besides, our result shows noticeable high-velocity anomalies in the core zone of the Emeishan Large Igneous Province (ELIP), which may be an indication of magma solidification from the ancient mantle plume. The result further exhibits an interesting pattern that the strong low-velocity anomalies are partially separated by the high-velocity anomalies in the ELIP. Such a specific pattern probably reflects that the stable zone in the ELIP leads to the bifurcation of weak Tibetan material.","PeriodicalId":21687,"journal":{"name":"Seismological Research Letters","volume":"66 26","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139385599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
P-wave microseisms are useful for understanding ocean waves. Resolving and locating multiple P-wave source regions using seismic data can provide valuable information about ocean waves. The resolvability of multiple microseismic P-wave source regions depends on the location accuracy and resolution, which can be improved using multiple large seismic arrays. In this article, we investigate the source locations of P-wave microseisms at the period of 5–10 s by combining the backprojection results from two large dense seismic arrays located in China (ChinArray) and the United States (USArray). We independently process data recorded by ChinArray and USArray during a two-year period (2014–2015) that border both the North Pacific and North Atlantic. Then the results are normalized and summed or intersected in the source region to improve the accuracy of the P-wave microseism source locations by reducing the deviation from the velocity structure model and the array response function. The results show that we can resolve two to three sources with a scale of ∼500–1000 km within one large P-wave source region. We also investigate how array parameters such as aperture, interstation spacing, and geographic position affect the detectability and accuracy of the P-wave microseism sources. The discrepancy in P-wave microseism source locations between backprojection observation and ocean model predictions in source number, source scale, and source region scope imply that the ocean model needs to be improved.
P 波微地震有助于了解海洋波。利用地震数据解析和定位多个 P 波源区可提供有关海浪的宝贵信息。多个微地震 P 波源区的可分辨性取决于定位精度和分辨率，而使用多个大型地震阵列可以提高定位精度和分辨率。在本文中，我们结合位于中国（ChinArray）和美国（USArray）的两个大型密集地震台阵的反投影结果，研究了周期为 5-10 秒的 P 波微地震的震源位置。我们独立处理了 ChinArray 和 USArray 在北太平洋和北大西洋边界两年（2014-2015 年）内记录的数据。然后对结果进行归一化处理，并在震源区域求和或相交，通过减少与速度结构模型和阵列响应函数的偏差来提高 P 波微地震震源位置的准确性。结果表明，我们可以在一个大型 P 波源区内分辨出两到三个尺度为 500-1000 公里的源。我们还研究了阵列参数（如孔径、站间距和地理位置）如何影响 P 波微震源的可探测性和精度。反投影观测和海洋模式预测的 P 波微地震源位置在震源数量、震源规模和震源区域范围方面存在差异，这意味着海洋模式需要改进。
{"title":"Resolvability of Multiple Microseismic P-Wave Source Regions with Two Large Seismic Arrays in China and the United States","authors":"Qiaoxia Liu, Yong Zhou, Sidao Ni, Min Xu, Yong Qiu, Yayun Zhang, Chuanhai Yu, Risheng Chu","doi":"10.1785/0220230265","DOIUrl":"https://doi.org/10.1785/0220230265","url":null,"abstract":"\u0000 P-wave microseisms are useful for understanding ocean waves. Resolving and locating multiple P-wave source regions using seismic data can provide valuable information about ocean waves. The resolvability of multiple microseismic P-wave source regions depends on the location accuracy and resolution, which can be improved using multiple large seismic arrays. In this article, we investigate the source locations of P-wave microseisms at the period of 5–10 s by combining the backprojection results from two large dense seismic arrays located in China (ChinArray) and the United States (USArray). We independently process data recorded by ChinArray and USArray during a two-year period (2014–2015) that border both the North Pacific and North Atlantic. Then the results are normalized and summed or intersected in the source region to improve the accuracy of the P-wave microseism source locations by reducing the deviation from the velocity structure model and the array response function. The results show that we can resolve two to three sources with a scale of ∼500–1000 km within one large P-wave source region. We also investigate how array parameters such as aperture, interstation spacing, and geographic position affect the detectability and accuracy of the P-wave microseism sources. The discrepancy in P-wave microseism source locations between backprojection observation and ocean model predictions in source number, source scale, and source region scope imply that the ocean model needs to be improved.","PeriodicalId":21687,"journal":{"name":"Seismological Research Letters","volume":"1 4","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139387388","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Aser Abbas, Brady R. Cox, Khiem T. Tran, Isabella Corey, Nishkarsha Dawadi
This article documents a comprehensive subsurface imaging experiment using seismic waves in a well-studied outdoor laboratory at Newberry, Florida, which is known for significant spatial variability, karstic voids, and underground anomalies. The experiment used approximately two kilometers of distributed acoustic sensing (DAS) fiber-optic cable, forming a dense 2D array of 1920 horizontal-component channels, and a 2D array of 144 SmartSolo three-component nodal seismometers, to sense active-source and passive-wavefield seismic waves. The active-source data were generated using a powerful, triaxial vibroseis shaker truck (T-Rex) and impact sources (accelerated weight drop and an eight-pound sledgehammer) that were simultaneously recorded by both the DAS and nodal seismometers. The vibroseis truck was used to excite the ground in three directions (two horizontal and one vertical) at 260 locations inside and outside the instrumented array, whereas the impact sources were used at 268 locations within the instrumented array. The passive-wavefield data recorded using the nodal seismometers comprised 48 hr of ambient noise collected over a period of four days in four 12-hour time blocks, whereas the passive wavefield data collected using DAS consisted of four hours of ambient noise recordings. This article aims to provide a comprehensive overview of the testing site, experiment layout, the DAS and nodal seismometer acquisition parameters, and implemented raw data processing steps. Although potential use cases, such as surface-wave testing, full-waveform inversion, and ambient noise tomography, are discussed relative to example data, the focus of this article is on documenting this unique data set and presenting its initial data quality rather than on generating subsurface imaging results. The raw and processed data, along with detailed documentation of the experiment and Python tools to aid in visualizing the DAS data set, have been made publicly available.
这篇文章记录了在佛罗里达州纽伯里一个经过充分研究的室外实验室利用地震波进行的综合地下成像实验，该实验室以显著的空间变化、岩溶空洞和地下异常而闻名。实验使用了约两公里长的分布式声学传感（DAS）光纤电缆，形成了一个由 1920 个水平分量通道组成的密集二维阵列，以及一个由 144 个 SmartSolo 三分量节点地震仪组成的二维阵列，以感知主动源和被动波场地震波。主动源数据是通过一台大功率三轴振动台车（T-Rex）和冲击源（加速重物下落和八磅大锤）生成的，同时由 DAS 和节点地震仪记录。振动车用于在仪器阵列内外的 260 个位置从三个方向（两个水平方向和一个垂直方向）激发地面，而冲击源用于仪器阵列内的 268 个位置。使用节点地震仪记录的被动波场数据由 48 小时的环境噪声组成，这些噪声在四天内分四个 12 小时的时间段收集，而使用 DAS 收集的被动波场数据由四小时的环境噪声记录组成。本文旨在全面概述试验场地、试验布局、DAS 和节点地震仪采集参数以及实施的原始数据处理步骤。虽然讨论了与示例数据相关的潜在用例，如面波测试、全波形反演和环境噪声层析成像，但本文的重点是记录这个独特的数据集，并介绍其初始数据质量，而不是生成地下成像结果。原始数据和处理过的数据，以及详细的实验文档和帮助可视化 DAS 数据集的 Python 工具，均已公开发布。
{"title":"An Open-Access Data Set of Active-Source and Passive-Wavefield DAS and Nodal Seismometer Measurements at the Newberry Florida Site","authors":"Aser Abbas, Brady R. Cox, Khiem T. Tran, Isabella Corey, Nishkarsha Dawadi","doi":"10.1785/0220230216","DOIUrl":"https://doi.org/10.1785/0220230216","url":null,"abstract":"\u0000 This article documents a comprehensive subsurface imaging experiment using seismic waves in a well-studied outdoor laboratory at Newberry, Florida, which is known for significant spatial variability, karstic voids, and underground anomalies. The experiment used approximately two kilometers of distributed acoustic sensing (DAS) fiber-optic cable, forming a dense 2D array of 1920 horizontal-component channels, and a 2D array of 144 SmartSolo three-component nodal seismometers, to sense active-source and passive-wavefield seismic waves. The active-source data were generated using a powerful, triaxial vibroseis shaker truck (T-Rex) and impact sources (accelerated weight drop and an eight-pound sledgehammer) that were simultaneously recorded by both the DAS and nodal seismometers. The vibroseis truck was used to excite the ground in three directions (two horizontal and one vertical) at 260 locations inside and outside the instrumented array, whereas the impact sources were used at 268 locations within the instrumented array. The passive-wavefield data recorded using the nodal seismometers comprised 48 hr of ambient noise collected over a period of four days in four 12-hour time blocks, whereas the passive wavefield data collected using DAS consisted of four hours of ambient noise recordings. This article aims to provide a comprehensive overview of the testing site, experiment layout, the DAS and nodal seismometer acquisition parameters, and implemented raw data processing steps. Although potential use cases, such as surface-wave testing, full-waveform inversion, and ambient noise tomography, are discussed relative to example data, the focus of this article is on documenting this unique data set and presenting its initial data quality rather than on generating subsurface imaging results. The raw and processed data, along with detailed documentation of the experiment and Python tools to aid in visualizing the DAS data set, have been made publicly available.","PeriodicalId":21687,"journal":{"name":"Seismological Research Letters","volume":"26 5","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139390662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Real-time classification of volcano seismicity could become a useful component in volcanic monitoring. Supervised learning provides a powerful means to achieve this but often requires a large amount of manually labeled data. Here, we build supervised learning models to discriminate volcano tectonic events (VTs), long-period events (LPs), and hybrid events in Kilauea by training with pseudolabels from unsupervised clustering. We test three different supervised models, and all of them achieve >93% accuracy. We apply the model ensemble to the six-day seismicity during the eruption in 2018 and show that they were mainly VTs (62%), in comparison with the dominance of LPs prior to the eruption (68%). The success of our method is aided by the accuracy of the majority of pseudolabels and the consistency of the three models’ performance. Using Shapley additive explanations, we show that the frequency contents at 1–4 Hz are the most important to differentiate volcano seismicity types. This work, together with our previous clustering analysis, provides an example of bridging unsupervised and supervised learning to construct potential real-time seismic classifiers from scratch.
{"title":"Bridging Supervised and Unsupervised Learning to Build Volcano Seismicity Classifiers at Kilauea Volcano, Hawaii","authors":"Xin Cui, Yanlan Hu, Shang Ma, Zefeng Li, Guoming Liu, Hui Huang","doi":"10.1785/0220230251","DOIUrl":"https://doi.org/10.1785/0220230251","url":null,"abstract":"\u0000 Real-time classification of volcano seismicity could become a useful component in volcanic monitoring. Supervised learning provides a powerful means to achieve this but often requires a large amount of manually labeled data. Here, we build supervised learning models to discriminate volcano tectonic events (VTs), long-period events (LPs), and hybrid events in Kilauea by training with pseudolabels from unsupervised clustering. We test three different supervised models, and all of them achieve >93% accuracy. We apply the model ensemble to the six-day seismicity during the eruption in 2018 and show that they were mainly VTs (62%), in comparison with the dominance of LPs prior to the eruption (68%). The success of our method is aided by the accuracy of the majority of pseudolabels and the consistency of the three models’ performance. Using Shapley additive explanations, we show that the frequency contents at 1–4 Hz are the most important to differentiate volcano seismicity types. This work, together with our previous clustering analysis, provides an example of bridging unsupervised and supervised learning to construct potential real-time seismic classifiers from scratch.","PeriodicalId":21687,"journal":{"name":"Seismological Research Letters","volume":"120 17","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139391509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this study, we analyze the existing ground-motion models (GMMs) applicable in Albania for horizontal peak ground acceleration (PGA) and spectral acceleration (SA) using instrumental ground motions, and also incorporate online citizen responses from “Did you feel it?” (DYFI) to compensate for the sparse distribution of strong-motion stations and provide better constraints for near-fault motions. Our evaluation focuses primarily on the damaging 26 November 2019 Mw 6.4 Durres earthquake, incorporating 1360 DYFI online citizen responses collected after the Durres mainshock event, along with two significant September foreshocks and two large November aftershocks with a moment magnitude Mw>5.0. In general, the DYFI intensities exhibit higher values than instrumentation data, and we find that SA at 0.3 s better represents the observed macroseismic intensities for all events. In the meantime, the reversible relationships between macroseismic intensities and PGA/SA, as established by Oliveti et al. (2022) based on a dataset from the European region (Italy), show a better fit for the converted DYFI observations when compared to instrumental data, in contrast to the fit of the converted DYFI observations by Worden et al. (2012). This underscores the importance of regional characterization when considering the datasets from online citizen responses. The extensive DYFI intensities set, particularly in near-fault regions, significantly improves the evaluation of GMMs due to the sparse distribution of instrumentation data. Moreover, we account for data variance, and applied the log-likelihood approaches to select and rank a candidate set of GMMs. In addition to recommending a set of GMMs suitable for the Albania region, our study highlights the valuable applications of using online citizen responses like DYFI for ground-motion estimations, which are crucial in regions with limited instrumental station coverage. These online citizen response datasets contribute to better constraining the selection of GMMs, although careful consideration is necessary when relating intensity to ground motion for regional characterization. Our study makes a significant contribution to GMM selection and provides a valuable reference for the logic tree structure in subsequent seismic hazard assessments on both national and regional scales.
{"title":"On the Use of Instrumental and Macroseismic Data to Evaluate Ground-Motion Models: The 2019 Mw 6.4 Durres, Albania, Earthquake Sequence","authors":"Edlira Xhafaj, Kuo-Fong Ma, Chung-Han Chan, Jia-cian Gao","doi":"10.1785/0220230205","DOIUrl":"https://doi.org/10.1785/0220230205","url":null,"abstract":"\u0000 In this study, we analyze the existing ground-motion models (GMMs) applicable in Albania for horizontal peak ground acceleration (PGA) and spectral acceleration (SA) using instrumental ground motions, and also incorporate online citizen responses from “Did you feel it?” (DYFI) to compensate for the sparse distribution of strong-motion stations and provide better constraints for near-fault motions. Our evaluation focuses primarily on the damaging 26 November 2019 Mw 6.4 Durres earthquake, incorporating 1360 DYFI online citizen responses collected after the Durres mainshock event, along with two significant September foreshocks and two large November aftershocks with a moment magnitude Mw>5.0. In general, the DYFI intensities exhibit higher values than instrumentation data, and we find that SA at 0.3 s better represents the observed macroseismic intensities for all events. In the meantime, the reversible relationships between macroseismic intensities and PGA/SA, as established by Oliveti et al. (2022) based on a dataset from the European region (Italy), show a better fit for the converted DYFI observations when compared to instrumental data, in contrast to the fit of the converted DYFI observations by Worden et al. (2012). This underscores the importance of regional characterization when considering the datasets from online citizen responses. The extensive DYFI intensities set, particularly in near-fault regions, significantly improves the evaluation of GMMs due to the sparse distribution of instrumentation data. Moreover, we account for data variance, and applied the log-likelihood approaches to select and rank a candidate set of GMMs. In addition to recommending a set of GMMs suitable for the Albania region, our study highlights the valuable applications of using online citizen responses like DYFI for ground-motion estimations, which are crucial in regions with limited instrumental station coverage. These online citizen response datasets contribute to better constraining the selection of GMMs, although careful consideration is necessary when relating intensity to ground motion for regional characterization. Our study makes a significant contribution to GMM selection and provides a valuable reference for the logic tree structure in subsequent seismic hazard assessments on both national and regional scales.","PeriodicalId":21687,"journal":{"name":"Seismological Research Letters","volume":"22 3","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139389786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Matthew C. Gerstenberger, Allison L. Bent, P. Martin Mai, John Townend
The recent completion of a fundamental revision of the New Zealand National Seismic Hazard Model (New Zealand NSHM) provided the catalyst for a joint BSSA Special Issue and SRL Focus Section on seismic hazard models worldwide. The approaches to NSHMs in different locations are varied and driven by different expertise, different philosophies, different tectonic environments, and different needs of the local communities. Despite the large number of countries facing risks from earthquakes, the community of researchers working on NSHMs is small, and it is to our benefit as a community to learn from each other and to understand approaches other...
{"title":"Introduction to the BSSA Special Issue and SRL Focus Section on Seismic Hazard Models","authors":"Matthew C. Gerstenberger, Allison L. Bent, P. Martin Mai, John Townend","doi":"10.1785/0220230422","DOIUrl":"https://doi.org/10.1785/0220230422","url":null,"abstract":"The recent completion of a fundamental revision of the New Zealand National Seismic Hazard Model (New Zealand NSHM) provided the catalyst for a joint BSSA Special Issue and SRL Focus Section on seismic hazard models worldwide. The approaches to NSHMs in different locations are varied and driven by different expertise, different philosophies, different tectonic environments, and different needs of the local communities. Despite the large number of countries facing risks from earthquakes, the community of researchers working on NSHMs is small, and it is to our benefit as a community to learn from each other and to understand approaches other...","PeriodicalId":21687,"journal":{"name":"Seismological Research Letters","volume":"35 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139582701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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