Accurately defining slab geometry is crucial for unraveling the seismogenic mechanism and subduction dynamics. Guided wave, generated from deep earthquakes with a focal depth greater than 100 km, efficiently propagates along a continuous slab and offers an effective way to image the slab geometry. However, it is challenging to manually identify slab guided waves through a large dataset, hindering their application in determining slab geometry. We propose the use of a deep embedding clustering algorithm for identifying slab guided waves. Using waveform data for deep earthquakes within the northwestern Pacific slab recorded by the F-net in Japan, we first employ spectra clustering analysis to determine three classification types. Subsequently, we perform clustering analysis on the spectrogram, efficiently featuring guided wave characteristics by enhancing the high-frequency energy. Then, using the sampled region by slab guided wave as a proxy, we map out the boundaries of the northwest Pacific slab at different depths, particularly within the depth range of 200–400 km. Our inferred slab boundaries correlate well with those derived from other methods, validating the accuracy and efficiency of our clustering analysis. Evaluation of our proposed workflow on smaller earthquakes with a lower signal-to-noise ratio underscores its great potential in determining slab geometry, particularly in less-studied regions.
准确界定板块几何形状对于揭示地震发生机制和俯冲动力学至关重要。导波由焦点深度大于 100 千米的深层地震产生，可沿着连续的板块有效传播，为板块几何成像提供了有效途径。然而，通过大量数据集手动识别板坯导波具有挑战性，阻碍了其在确定板坯几何形状方面的应用。我们建议使用深嵌入聚类算法来识别板岩导波。利用日本 F 网记录的西北太平洋板块内深层地震的波形数据，我们首先采用频谱聚类分析确定了三种分类类型。随后，我们对频谱图进行聚类分析，通过增强高频能量来有效地显示导波特征。然后，我们以板块导波采样区域为代表，绘制出西北太平洋板块在不同深度的边界，尤其是在 200-400 公里深度范围内。我们推断出的板块边界与其他方法得出的边界有很好的相关性，验证了我们聚类分析的准确性和效率。在信噪比较低的较小地震上对我们提出的工作流程进行评估，凸显了其在确定板块几何形状方面的巨大潜力，尤其是在研究较少的地区。
{"title":"Constraining the Geometry of the Northwest Pacific Slab Using Deep Clustering of Slab Guided Waves","authors":"Guangcan Liu, Daoyuan Sun, Zefeng Li","doi":"10.1785/0220240101","DOIUrl":"https://doi.org/10.1785/0220240101","url":null,"abstract":"\u0000 Accurately defining slab geometry is crucial for unraveling the seismogenic mechanism and subduction dynamics. Guided wave, generated from deep earthquakes with a focal depth greater than 100 km, efficiently propagates along a continuous slab and offers an effective way to image the slab geometry. However, it is challenging to manually identify slab guided waves through a large dataset, hindering their application in determining slab geometry. We propose the use of a deep embedding clustering algorithm for identifying slab guided waves. Using waveform data for deep earthquakes within the northwestern Pacific slab recorded by the F-net in Japan, we first employ spectra clustering analysis to determine three classification types. Subsequently, we perform clustering analysis on the spectrogram, efficiently featuring guided wave characteristics by enhancing the high-frequency energy. Then, using the sampled region by slab guided wave as a proxy, we map out the boundaries of the northwest Pacific slab at different depths, particularly within the depth range of 200–400 km. Our inferred slab boundaries correlate well with those derived from other methods, validating the accuracy and efficiency of our clustering analysis. Evaluation of our proposed workflow on smaller earthquakes with a lower signal-to-noise ratio underscores its great potential in determining slab geometry, particularly in less-studied regions.","PeriodicalId":508466,"journal":{"name":"Seismological Research Letters","volume":"67 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141922585","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}
Lusette Karime Escobar-Rey, David Mencin, Tim Dittmann, Patricia A. Mothes, Héctor Mora-Páez
Colombia and Ecuador sit at one of the most diverse tectonic regimes in the world, located at the intersection of five tectonic plates (Bird, 2003) encompassing many geophysical hazard regimes, multiple subduction zones, and broad diffuse areas of significant deformation. Notably, the subduction of the Nazca plate under South America has produced at least seven large (>Mw 7) and damaging earthquakes since 1900—the largest being the 1906 Mw 8.8 event. Both Colombia and Ecuador have made significant investments in Global Navigation Satellite System (GNSS) networks to study tectonic and volcanic deformation. Earthquake early warning (EEW) systems like the U.S.-operated ShakeAlert system (Murray et al., 2018, 2023) utilize real-time Global Navigation Satellite System (RT-GNSS) to rapidly characterize the largest, most damaging earthquakes in situations where seismic networks alone saturate (Melgar et al., 2015, 2016; Allen and Melgar, 2019; Ruhl et al., 2019). Both Colombia and Ecuador have large vulnerable populations proximal to the coast that may sustain significant damage in these large subduction events (Pulido et al., 2020) and yet farther enough away that an RT-GNSS EEW system could offer significant warning times to these populations and associated infrastructure. We examine the status of the Servicio Geológico Colombiano Geodesia: Red de Estudios de Deformación GNSS network in Colombia and the Escuela Politécnica Nacional GNSS network in Ecuador, their spatial distribution, and the current status of their data streams to determine what augmentations are required to support the real-time detection and modeling of large destructive earthquakes in and near Colombia and Ecuador.
哥伦比亚和厄瓜多尔地处世界上最多样化的构造体系之一，位于五大构造板块的交汇处（Bird，2003 年），包括许多地球物理危险体系、多个俯冲带和广泛的重大变形区域。值得注意的是，自 1900 年以来，南美洲纳斯卡板块的俯冲至少引发了七次破坏性大地震（>Mw 7），其中最大的一次是 1906 年发生的 Mw 8.8 地震。哥伦比亚和厄瓜多尔都对全球导航卫星系统（GNSS）网络进行了大量投资，以研究构造和火山变形。地震预警（EEW）系统，如美国运营的 ShakeAlert 系统（Murray 等人，2018 年，2023 年），利用实时全球导航卫星系统（RT-GNSS），在仅有地震网络饱和的情况下，迅速确定最大、破坏性最强地震的特征（Melgar 等人，2015 年，2016 年；Allen 和 Melgar，2019 年；Ruhl 等人，2019 年）。哥伦比亚和厄瓜多尔都有大量靠近海岸的脆弱人群，他们可能会在这些大型俯冲事件中遭受重大损失（Pulido 等人，2020 年），但距离足够远，RT-GNSS EEW 系统可以为这些人群和相关基础设施提供重要的预警时间。我们研究了哥伦比亚大地测量局（Servicio Geológico Colombiano Geodesia）的现状：我们研究了哥伦比亚的 Servicio Geológico Colombiano Geodesia：Red de Estudios de Deformación GNSS 网络和厄瓜多尔的 Escuela Politécnica Nacional GNSS 网络的现状、空间分布及其数据流的现状，以确定为支持哥伦比亚和厄瓜多尔境内及附近地区大型破坏性地震的实时探测和建模需要哪些增强功能。
{"title":"A Geodetic-Based Earthquake Early Warning System for Colombia and Ecuador","authors":"Lusette Karime Escobar-Rey, David Mencin, Tim Dittmann, Patricia A. Mothes, Héctor Mora-Páez","doi":"10.1785/0220230390","DOIUrl":"https://doi.org/10.1785/0220230390","url":null,"abstract":"\u0000 Colombia and Ecuador sit at one of the most diverse tectonic regimes in the world, located at the intersection of five tectonic plates (Bird, 2003) encompassing many geophysical hazard regimes, multiple subduction zones, and broad diffuse areas of significant deformation. Notably, the subduction of the Nazca plate under South America has produced at least seven large (>Mw 7) and damaging earthquakes since 1900—the largest being the 1906 Mw 8.8 event. Both Colombia and Ecuador have made significant investments in Global Navigation Satellite System (GNSS) networks to study tectonic and volcanic deformation. Earthquake early warning (EEW) systems like the U.S.-operated ShakeAlert system (Murray et al., 2018, 2023) utilize real-time Global Navigation Satellite System (RT-GNSS) to rapidly characterize the largest, most damaging earthquakes in situations where seismic networks alone saturate (Melgar et al., 2015, 2016; Allen and Melgar, 2019; Ruhl et al., 2019). Both Colombia and Ecuador have large vulnerable populations proximal to the coast that may sustain significant damage in these large subduction events (Pulido et al., 2020) and yet farther enough away that an RT-GNSS EEW system could offer significant warning times to these populations and associated infrastructure. We examine the status of the Servicio Geológico Colombiano Geodesia: Red de Estudios de Deformación GNSS network in Colombia and the Escuela Politécnica Nacional GNSS network in Ecuador, their spatial distribution, and the current status of their data streams to determine what augmentations are required to support the real-time detection and modeling of large destructive earthquakes in and near Colombia and Ecuador.","PeriodicalId":508466,"journal":{"name":"Seismological Research Letters","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141921595","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}
Ming-Che Hsieh, Chung-Han Chan, Kuo-Fong Ma, Y. Yen, Chun-Te Chen, Da-Yi Chen, Yi-Wun Mika Liao
Earthquake forecasting, combined with precise ground-shaking estimations, plays a pivotal role in safeguarding public safety, fortifying infrastructure, and bolstering the preparedness of emergency services. This study introduces a comprehensive workflow that integrates the epidemic-type aftershock sequence (ETAS) model with a preselected ground-motion model (GMM), facilitating accurate short-term forecasting of ground-shaking intensity (GSI), which is crucial for effective earthquake warning. First, an analysis was conducted on an earthquake catalog spanning from 1994 to 2022 to optimize the ETAS parameters. The dataset used in this analysis allowed for the further calculation of total, background, and clustering seismicity rates, which are crucial for understanding spatiotemporal earthquake occurrence. Subsequently, short-term earthquake activity simulations were performed using these up-to-date seismicity rates to generate synthetic catalogs. The ground-shaking impact on the target sites from each synthetic catalog was assessed by determining the maximum intensity using a selected GMM. This simulation process was repeated to enhance the reliability of the forecasts. Through this process, a probability distribution was created, serving as a robust forecasting for GSI at sites. The performance of the forecasting model was validated through an example of the Taitung earthquake sequence in September 2022, showing its effectiveness in forecasting earthquake activity and site-specific GSI. The proposed forecasting model can quickly deliver short-term seismic hazard curves and warning messages, facilitating timely decision making.
{"title":"Toward Real-Time Ground-Shaking-Intensity Forecasting Using ETAS and GMM: Insights from the Analysis of the 2022 Taitung Earthquake Sequence","authors":"Ming-Che Hsieh, Chung-Han Chan, Kuo-Fong Ma, Y. Yen, Chun-Te Chen, Da-Yi Chen, Yi-Wun Mika Liao","doi":"10.1785/0220240180","DOIUrl":"https://doi.org/10.1785/0220240180","url":null,"abstract":"\u0000 Earthquake forecasting, combined with precise ground-shaking estimations, plays a pivotal role in safeguarding public safety, fortifying infrastructure, and bolstering the preparedness of emergency services. This study introduces a comprehensive workflow that integrates the epidemic-type aftershock sequence (ETAS) model with a preselected ground-motion model (GMM), facilitating accurate short-term forecasting of ground-shaking intensity (GSI), which is crucial for effective earthquake warning. First, an analysis was conducted on an earthquake catalog spanning from 1994 to 2022 to optimize the ETAS parameters. The dataset used in this analysis allowed for the further calculation of total, background, and clustering seismicity rates, which are crucial for understanding spatiotemporal earthquake occurrence. Subsequently, short-term earthquake activity simulations were performed using these up-to-date seismicity rates to generate synthetic catalogs. The ground-shaking impact on the target sites from each synthetic catalog was assessed by determining the maximum intensity using a selected GMM. This simulation process was repeated to enhance the reliability of the forecasts. Through this process, a probability distribution was created, serving as a robust forecasting for GSI at sites. The performance of the forecasting model was validated through an example of the Taitung earthquake sequence in September 2022, showing its effectiveness in forecasting earthquake activity and site-specific GSI. The proposed forecasting model can quickly deliver short-term seismic hazard curves and warning messages, facilitating timely decision making.","PeriodicalId":508466,"journal":{"name":"Seismological Research Letters","volume":"10 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141801896","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}
Wenfang Shi, Jinhui Yin, S. Mudd, Wei Xu, Yonggang Zheng
The first major (Mw>7) earthquake in the Chinese historical catalog is recorded to have occurred near Qishan, in Shaanxi Province, and is entered for the year 780 B.C., but there is limited field evidence of its effects. Previous satellite images and field surveys have shown that there is a cluster of ancient seismic landslides about 50 km long in the northern margin of the Qinling Mountains, south of Qishan, which is the macroepicenter of the 780 B.C. Qishan earthquake. However, the actual age of the landslide group is debated. To constrain this age, we examined a >1 m thick lacustrine deposit above the landslide gravel of a dammed lake impounded by the largest of several landslides near its inferred macroseismic epicenter and determined these were deposited 758–486 B.C. This date is sufficiently close to the catalog age that we infer that this landslide was triggered by the 780 B.C. historical event. This lends credibility to the historical account and resolves earlier speculation based on disputed dates of surface materials on the landslide. We also re-evaluated the magnitude of the 780 B.C. Qishan earthquake and found that it could plausibly be higher than Ms 7.8 (Mw 7.5). The possible seismogenic structure belongs to the Longxian–Qishan–Mazhao fault. This work updated the damage area of the Qishan earthquake and helped us revise the seismic parameters of the historical earthquake.
{"title":"Field Validation of the First Recorded Historically Major (Mw >7) Earthquake in China Based on the Age of the Landslide-Dammed Lake","authors":"Wenfang Shi, Jinhui Yin, S. Mudd, Wei Xu, Yonggang Zheng","doi":"10.1785/0220240065","DOIUrl":"https://doi.org/10.1785/0220240065","url":null,"abstract":"\u0000 The first major (Mw>7) earthquake in the Chinese historical catalog is recorded to have occurred near Qishan, in Shaanxi Province, and is entered for the year 780 B.C., but there is limited field evidence of its effects. Previous satellite images and field surveys have shown that there is a cluster of ancient seismic landslides about 50 km long in the northern margin of the Qinling Mountains, south of Qishan, which is the macroepicenter of the 780 B.C. Qishan earthquake. However, the actual age of the landslide group is debated. To constrain this age, we examined a >1 m thick lacustrine deposit above the landslide gravel of a dammed lake impounded by the largest of several landslides near its inferred macroseismic epicenter and determined these were deposited 758–486 B.C. This date is sufficiently close to the catalog age that we infer that this landslide was triggered by the 780 B.C. historical event. This lends credibility to the historical account and resolves earlier speculation based on disputed dates of surface materials on the landslide. We also re-evaluated the magnitude of the 780 B.C. Qishan earthquake and found that it could plausibly be higher than Ms 7.8 (Mw 7.5). The possible seismogenic structure belongs to the Longxian–Qishan–Mazhao fault. This work updated the damage area of the Qishan earthquake and helped us revise the seismic parameters of the historical earthquake.","PeriodicalId":508466,"journal":{"name":"Seismological Research Letters","volume":"23 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141802221","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}
Distributed acoustic sensing (DAS) has emerged as a novel technology in geophysics, owing to its high-sensing density, cost effectiveness, and adaptability to extreme environments. Nonetheless, DAS differs from traditional seismic acquisition technologies in many aspects: big data volume, equidistant sensing, measurement of axial strain (strain rate), and noise characteristics. These differences make DAS data processing challenging for new hands. To lower the bar of DAS data processing, we develop an open-source Python toolbox called DASPy, which encompasses classic seismic data processing techniques, including preprocessing, filter, spectrum analysis, and visualization, and specialized algorithms for DAS applications, including denoising, waveform decomposition, channel attribute analysis, and strain–velocity conversion. Using openly available DAS data as examples, this article makes an overview and tutorial on the eight modules in DASPy to illustrate the algorithms and practical applications. We anticipate DASPy to provide convenience for researchers unfamiliar with DAS data and help facilitate the rapid growth of DAS seismology.
分布式声学传感（DAS）因其传感密度高、成本效益高、可适应极端环境等优点，已成为地球物理学领域的一项新技术。然而，DAS 与传统的地震采集技术有许多不同之处：数据量大、等距传感、轴向应变（应变率）测量和噪声特性。这些差异使得 DAS 数据处理对新手来说具有挑战性。为了降低 DAS 数据处理的门槛，我们开发了一个名为 DASPy 的开源 Python 工具箱，其中包含预处理、滤波、频谱分析和可视化等经典地震数据处理技术，以及去噪、波形分解、道属性分析和应变速度转换等 DAS 应用的专门算法。本文以公开的 DAS 数据为例，对 DASPy 中的八个模块进行了概述和教程，以说明算法和实际应用。我们期待 DASPy 能够为不熟悉 DAS 数据的研究人员提供方便，促进 DAS 地震学的快速发展。
{"title":"DASPy: A Python Toolbox for DAS Seismology","authors":"Minzhe Hu, Zefeng Li","doi":"10.1785/0220240124","DOIUrl":"https://doi.org/10.1785/0220240124","url":null,"abstract":"\u0000 Distributed acoustic sensing (DAS) has emerged as a novel technology in geophysics, owing to its high-sensing density, cost effectiveness, and adaptability to extreme environments. Nonetheless, DAS differs from traditional seismic acquisition technologies in many aspects: big data volume, equidistant sensing, measurement of axial strain (strain rate), and noise characteristics. These differences make DAS data processing challenging for new hands. To lower the bar of DAS data processing, we develop an open-source Python toolbox called DASPy, which encompasses classic seismic data processing techniques, including preprocessing, filter, spectrum analysis, and visualization, and specialized algorithms for DAS applications, including denoising, waveform decomposition, channel attribute analysis, and strain–velocity conversion. Using openly available DAS data as examples, this article makes an overview and tutorial on the eight modules in DASPy to illustrate the algorithms and practical applications. We anticipate DASPy to provide convenience for researchers unfamiliar with DAS data and help facilitate the rapid growth of DAS seismology.","PeriodicalId":508466,"journal":{"name":"Seismological Research Letters","volume":"34 20","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141800623","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}
From 23 November 2022 to 30 November 2022, a sequence of earthquakes with a peak magnitude of ML 5.6 occurred ∼46 km away from Peace River—a vibrant rural community in Alberta, Canada. Broadly felt by residents throughout central Alberta, the ML 5.6 earthquake on 30 November 2022, registers as the second-largest earthquake ever reported in the Western Canada Sedimentary basin and possibly the largest Canadian earthquake induced by human activities. On 6 December 2022, 1 week after the mainshock, the University of Alberta and Alberta Geological Survey jointly installed a circular array of nodal geophones surrounding the seismogenic zone. Over the next 4 months, this quick-response array (nicknamed “Peace River Induced Seismic Monitoring” array, for short PRISM) operated at temperatures as low as −30°C and substantially bolstered the seismic data coverage in this previously undersampled region. Our preliminary array data analysis has detected more than 2000 earthquakes with magnitudes ranging from −1.9 to 5.0 since the initial outbreak in late 2022. Investigations based on earthquake location, focal mechanism, and magnitude jointly reveal distinct earthquake clusters distributed along pre-existing faults from earlier tectonic events. The data recovered from this array offer unique and vital constraints on the tectonic histories and seismic risks of the Peace River region.
{"title":"Peace River Induced Seismic Monitoring (PRISM) Nodal Seismic Array","authors":"Yu Jeffrey Gu, Wenhan Sun, Tai-Chieh Yu, Jingchuan Wang, Ruijia Wang, Tianyang Li, R. Schultz","doi":"10.1785/0220240029","DOIUrl":"https://doi.org/10.1785/0220240029","url":null,"abstract":"\u0000 From 23 November 2022 to 30 November 2022, a sequence of earthquakes with a peak magnitude of ML 5.6 occurred ∼46 km away from Peace River—a vibrant rural community in Alberta, Canada. Broadly felt by residents throughout central Alberta, the ML 5.6 earthquake on 30 November 2022, registers as the second-largest earthquake ever reported in the Western Canada Sedimentary basin and possibly the largest Canadian earthquake induced by human activities. On 6 December 2022, 1 week after the mainshock, the University of Alberta and Alberta Geological Survey jointly installed a circular array of nodal geophones surrounding the seismogenic zone. Over the next 4 months, this quick-response array (nicknamed “Peace River Induced Seismic Monitoring” array, for short PRISM) operated at temperatures as low as −30°C and substantially bolstered the seismic data coverage in this previously undersampled region. Our preliminary array data analysis has detected more than 2000 earthquakes with magnitudes ranging from −1.9 to 5.0 since the initial outbreak in late 2022. Investigations based on earthquake location, focal mechanism, and magnitude jointly reveal distinct earthquake clusters distributed along pre-existing faults from earlier tectonic events. The data recovered from this array offer unique and vital constraints on the tectonic histories and seismic risks of the Peace River region.","PeriodicalId":508466,"journal":{"name":"Seismological Research Letters","volume":"19 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141801855","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}
Kenny Graham, A. Christophersen, D. Rhoades, Matthew C. Gerstenberger, Katrina M. Jacobs, R. Huso, S. Canessa, Chris Zweck
Earthquake forecasts estimate the likelihood of seismic activity within a specific region over a given timeframe, utilizing historical data and patterns from past earthquakes. In New Zealand, the GeoNet program within GNS Science is the main source of geological hazard information and has publicly provided earthquake forecasts since the Darfield earthquake in September 2010. The generation and provision of initial forecasts and subsequent updates have relied on extensive time commitments of experts. The growing use and the desire to make forecast delivery less dependent on personnel capacity have motivated the development of a robust software solution through a hybrid forecast tool (HFT). The HFT is composed of forecast models that cover several different timescales: short term (ranging from a few hours to several years, based on empirical relations for aftershock decay), medium term (spanning years to decades, utilizing the increased seismic activity preceding major earthquakes), and long term (covering decades to centuries, combining information from the spatial distribution of cataloged earthquake locations and slip rates of mapped faults and strain rates estimated from geodetic data). Originally, these models were developed over many years by individual researchers using various programming languages such as Fortran, Java, and R, operating on separate operating systems, with their features documented and published. The HFT unites these models under one umbrella, utilizing a Docker container to navigate disparate software library compatibility issues. Furthermore, the HFT offers user-friendly navigation through a graphical user interface and a command-line feature, facilitating the configuration of automatic and periodic forecast runs. The stability and integration provided by the HFT greatly improve the capability of GNS Science to provide forecasts that inform responses to significant regional seismic events and bring New Zealand closer to automated and operational earthquake forecasting. Although HFT is specifically designed for New Zealand’s earthquake forecasting, the framework, implementation, and containerization approach could also benefit forecasting efforts in other regions.
{"title":"A Software Tool for Hybrid Earthquake Forecasting in New Zealand","authors":"Kenny Graham, A. Christophersen, D. Rhoades, Matthew C. Gerstenberger, Katrina M. Jacobs, R. Huso, S. Canessa, Chris Zweck","doi":"10.1785/0220240196","DOIUrl":"https://doi.org/10.1785/0220240196","url":null,"abstract":"\u0000 Earthquake forecasts estimate the likelihood of seismic activity within a specific region over a given timeframe, utilizing historical data and patterns from past earthquakes. In New Zealand, the GeoNet program within GNS Science is the main source of geological hazard information and has publicly provided earthquake forecasts since the Darfield earthquake in September 2010. The generation and provision of initial forecasts and subsequent updates have relied on extensive time commitments of experts. The growing use and the desire to make forecast delivery less dependent on personnel capacity have motivated the development of a robust software solution through a hybrid forecast tool (HFT). The HFT is composed of forecast models that cover several different timescales: short term (ranging from a few hours to several years, based on empirical relations for aftershock decay), medium term (spanning years to decades, utilizing the increased seismic activity preceding major earthquakes), and long term (covering decades to centuries, combining information from the spatial distribution of cataloged earthquake locations and slip rates of mapped faults and strain rates estimated from geodetic data). Originally, these models were developed over many years by individual researchers using various programming languages such as Fortran, Java, and R, operating on separate operating systems, with their features documented and published. The HFT unites these models under one umbrella, utilizing a Docker container to navigate disparate software library compatibility issues. Furthermore, the HFT offers user-friendly navigation through a graphical user interface and a command-line feature, facilitating the configuration of automatic and periodic forecast runs. The stability and integration provided by the HFT greatly improve the capability of GNS Science to provide forecasts that inform responses to significant regional seismic events and bring New Zealand closer to automated and operational earthquake forecasting. Although HFT is specifically designed for New Zealand’s earthquake forecasting, the framework, implementation, and containerization approach could also benefit forecasting efforts in other regions.","PeriodicalId":508466,"journal":{"name":"Seismological Research Letters","volume":"52 22","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141799602","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}
Induced seismicity magnitude models seek to forecast upcoming magnitudes of induced earthquakes during the operation of subsurface industries such as hydraulic fracturing, geothermal stimulation, wastewater disposal (WWD), and carbon capture and storage. Accurate forecasting models could guide operational decision making in real time; for example, operations could be reduced or paused if forecast models indicate that magnitudes may exceed acceptable levels. Robust and transparent testing of forecasting models is required if they are to be adopted by operators and regulators of such industries. We develop and test a suite of models based on extreme value estimators to forecast the magnitudes of upcoming induced seismic events based on observed seismicity. We apply these models to multiple induced seismicity cases from WWD in Oklahoma and in western Texas, as well as other cases of seismicity caused by subsurface fluid injection in North America, Europe, and China. In total, our testing dataset consists of >80 individual sequences of induced seismicity. We find that all the models produce strong correlation between observed and modeled magnitudes, indicating that the forecasting provides useful information about upcoming magnitudes. However, some models are found to systematically overpredict the observed magnitudes, whereas others tend to underpredict. As such, the combined suite of models can be used to define upper and lower estimators for the expected magnitudes of upcoming events, as well as empirically constrained statistical expectations for how these magnitudes will be distributed between the upper and lower values. We conclude by demonstrating how our empirically constrained distribution can be used to produce probabilistic forecasts of upcoming induced earthquake magnitudes, applying this approach to two recent cases of induced seismicity.
{"title":"An Empirically Constrained Forecasting Strategy for Induced Earthquake Magnitudes Using Extreme Value Theory","authors":"J. Verdon, Leo Eisner","doi":"10.1785/0220240061","DOIUrl":"https://doi.org/10.1785/0220240061","url":null,"abstract":"\u0000 Induced seismicity magnitude models seek to forecast upcoming magnitudes of induced earthquakes during the operation of subsurface industries such as hydraulic fracturing, geothermal stimulation, wastewater disposal (WWD), and carbon capture and storage. Accurate forecasting models could guide operational decision making in real time; for example, operations could be reduced or paused if forecast models indicate that magnitudes may exceed acceptable levels. Robust and transparent testing of forecasting models is required if they are to be adopted by operators and regulators of such industries. We develop and test a suite of models based on extreme value estimators to forecast the magnitudes of upcoming induced seismic events based on observed seismicity. We apply these models to multiple induced seismicity cases from WWD in Oklahoma and in western Texas, as well as other cases of seismicity caused by subsurface fluid injection in North America, Europe, and China. In total, our testing dataset consists of >80 individual sequences of induced seismicity. We find that all the models produce strong correlation between observed and modeled magnitudes, indicating that the forecasting provides useful information about upcoming magnitudes. However, some models are found to systematically overpredict the observed magnitudes, whereas others tend to underpredict. As such, the combined suite of models can be used to define upper and lower estimators for the expected magnitudes of upcoming events, as well as empirically constrained statistical expectations for how these magnitudes will be distributed between the upper and lower values. We conclude by demonstrating how our empirically constrained distribution can be used to produce probabilistic forecasts of upcoming induced earthquake magnitudes, applying this approach to two recent cases of induced seismicity.","PeriodicalId":508466,"journal":{"name":"Seismological Research Letters","volume":"60 13","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141798996","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}
The small medieval city of Ston in southern Dalmatia (Croatia) has been hit by several strong earthquakes since mid-nineteenth century. The two most important are the ones from the years of 1850 and 1996. Although various aspects of the 1996 event have been well studied so far, the earthquake of 1850 has only recently been macroseismically analyzed. It turned out that the macroseismic epicenters, focal depths, and the epicentral intensities of the two events are virtually the same. As the categories of damage to buildings in Ston caused by the 1996 event were available from previous studies, we here combine details on damage and property ownership from reports in 1850 with the cadastral records from 1837. This allowed us to geolocate most of the damaged houses and thus directly compare the spatial distribution of damage from the two earthquakes. Although the building identification was not straight-forward and unambiguous due to unknown history of each building during the 13 yr between the cadastral survey and the earthquake, the overall damage distributions of both events are found to be similar. They both show the largest damage confined to the plain terrain below the Bartolomija hill characterized by a sedimentary cover 10–30 m thick and expected ground-motion amplification by factors of 3–5. Minimal damage for both events is observed on the hillslopes of Bartolomija in the northern part of the city, where the bedrock is shallow or outcropping. To our knowledge, this observation of the shaking effects for two strong similar earthquakes in a city that has changed little in the 146 yr between them is the only one of its kind in Croatia. It confirms consistency of spatial distribution of earthquake ground-motion amplification for comparable input earthquake motion.
{"title":"A Comparative Study of Building Damage in Ston, Croatia, Caused by the Earthquakes of 1850 and 1996","authors":"M. Herak, D. Herak","doi":"10.1785/0220240248","DOIUrl":"https://doi.org/10.1785/0220240248","url":null,"abstract":"\u0000 The small medieval city of Ston in southern Dalmatia (Croatia) has been hit by several strong earthquakes since mid-nineteenth century. The two most important are the ones from the years of 1850 and 1996. Although various aspects of the 1996 event have been well studied so far, the earthquake of 1850 has only recently been macroseismically analyzed. It turned out that the macroseismic epicenters, focal depths, and the epicentral intensities of the two events are virtually the same. As the categories of damage to buildings in Ston caused by the 1996 event were available from previous studies, we here combine details on damage and property ownership from reports in 1850 with the cadastral records from 1837. This allowed us to geolocate most of the damaged houses and thus directly compare the spatial distribution of damage from the two earthquakes. Although the building identification was not straight-forward and unambiguous due to unknown history of each building during the 13 yr between the cadastral survey and the earthquake, the overall damage distributions of both events are found to be similar. They both show the largest damage confined to the plain terrain below the Bartolomija hill characterized by a sedimentary cover 10–30 m thick and expected ground-motion amplification by factors of 3–5. Minimal damage for both events is observed on the hillslopes of Bartolomija in the northern part of the city, where the bedrock is shallow or outcropping. To our knowledge, this observation of the shaking effects for two strong similar earthquakes in a city that has changed little in the 146 yr between them is the only one of its kind in Croatia. It confirms consistency of spatial distribution of earthquake ground-motion amplification for comparable input earthquake motion.","PeriodicalId":508466,"journal":{"name":"Seismological Research Letters","volume":"8 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141802130","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}
Resonance frequency and seismic-wave velocity monitoring are both important for structural health monitoring (SHM). However, the limited number of vibration sensors or seismometers in most buildings necessitates the study of the sensitivity of monitoring indicators to ensure effective monitoring while reducing data acquisition costs and processing time. This study compares the changes in resonance frequency and seismic-wave velocity under ambient noise and a regional seismic event. Resonance frequency is calculated by power spectral density, whereas seismic-wave velocity is estimated using impulse response function and moving-window cross-spectrum methods. The results indicate that relative resonance frequency changes are more suitable for overall SHM due to its higher sensitivity and lower instrument requirements. Moreover, the time–frequency analysis method provides higher resolution results in resonance frequency during seismic events, a precision that seismic velocity methods cannot achieve.
{"title":"Structural Health Monitoring of a High-Rise Building Using Ambient Noise Recordings and a Regional Earthquake Record","authors":"Linpeng Qin, Yun Wang, Zhen Guo, Yi Zhang, Chunqi Liao, Chang Chen, Baojian Zhang","doi":"10.1785/0220230368","DOIUrl":"https://doi.org/10.1785/0220230368","url":null,"abstract":"\u0000 Resonance frequency and seismic-wave velocity monitoring are both important for structural health monitoring (SHM). However, the limited number of vibration sensors or seismometers in most buildings necessitates the study of the sensitivity of monitoring indicators to ensure effective monitoring while reducing data acquisition costs and processing time. This study compares the changes in resonance frequency and seismic-wave velocity under ambient noise and a regional seismic event. Resonance frequency is calculated by power spectral density, whereas seismic-wave velocity is estimated using impulse response function and moving-window cross-spectrum methods. The results indicate that relative resonance frequency changes are more suitable for overall SHM due to its higher sensitivity and lower instrument requirements. Moreover, the time–frequency analysis method provides higher resolution results in resonance frequency during seismic events, a precision that seismic velocity methods cannot achieve.","PeriodicalId":508466,"journal":{"name":"Seismological Research Letters","volume":"56 20","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141809777","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}
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