M. Mesimeri, L. Scarabello, Eric Zimmermann, Thomas Haag, Emil Zylis, L. Villiger, P. Kaestli, Men-Andrin Meier, A. P. Rinaldi, A. Obermann, M. Hertrich, John Clinton, D. Giardini, Stefan Wiemer
The Bedretto Underground Laboratory for Geoenergies and Geosciences (BULGG) is located in south-central Switzerland in the middle of a 5.2-km-long tunnel, which connects the Bedretto valley to the Furka railway tunnel. BULGG is a multidisciplinary laboratory that facilitates experiments and research across various fields. From a seismological perspective, a dense seismic network is deployed that allows real-time monitoring of both natural and induced seismicity occurring in the tunnel and the surroundings. In addition, a multilevel monitoring approach during experiments leads to the generation of real-time high-resolution earthquake catalogs issuing event-based alerts and is the input for a simple traffic light system (magnitude and/or ground-motion based), which provides essential information for the advanced traffic-light system (probabilistic approach). We have set up two separate real-time monitoring systems that monitor the background seismicity, as well as injection experiments, with both systems built on the SeisComP framework. The background monitoring, serving as the backbone network, includes broadband sensors at the surface and along the tunnel, as well as strong-motion sensors and high-frequency geophones along the tunnel and in boreholes. The sampling rate is divergent and depends on sensor type and proximity to faults (200–2000 Hz). Acoustic emission sensors and high-frequency accelerometers sampled at 200 kHz constitute the experimental setup that locates in multiple experimental volumes, which include fluid injections, extractions, and tunneling activities. All sensors transmit real-time data to a common server (SeedLink), which serves multiple clients for processing, real-time visualization, archiving via SeisComP, and risk control via dedicated software. A standardized workflow is applied to both background and experimental monitoring, encompassing automatic picking, automatic phase association and location, and magnitude estimation. Advanced methods are implemented in real time that include double-difference relocation and earthquake detection based on waveform cross correlation. BULGG provides a unique environment to implement novel methods in observational and network seismology across scales.
{"title":"Multiscale Seismic Monitoring in the Bedretto Underground Laboratory for Geosciences and Geoenergies (BULGG)","authors":"M. Mesimeri, L. Scarabello, Eric Zimmermann, Thomas Haag, Emil Zylis, L. Villiger, P. Kaestli, Men-Andrin Meier, A. P. Rinaldi, A. Obermann, M. Hertrich, John Clinton, D. Giardini, Stefan Wiemer","doi":"10.1785/0220240128","DOIUrl":"https://doi.org/10.1785/0220240128","url":null,"abstract":"\u0000 The Bedretto Underground Laboratory for Geoenergies and Geosciences (BULGG) is located in south-central Switzerland in the middle of a 5.2-km-long tunnel, which connects the Bedretto valley to the Furka railway tunnel. BULGG is a multidisciplinary laboratory that facilitates experiments and research across various fields. From a seismological perspective, a dense seismic network is deployed that allows real-time monitoring of both natural and induced seismicity occurring in the tunnel and the surroundings. In addition, a multilevel monitoring approach during experiments leads to the generation of real-time high-resolution earthquake catalogs issuing event-based alerts and is the input for a simple traffic light system (magnitude and/or ground-motion based), which provides essential information for the advanced traffic-light system (probabilistic approach). We have set up two separate real-time monitoring systems that monitor the background seismicity, as well as injection experiments, with both systems built on the SeisComP framework. The background monitoring, serving as the backbone network, includes broadband sensors at the surface and along the tunnel, as well as strong-motion sensors and high-frequency geophones along the tunnel and in boreholes. The sampling rate is divergent and depends on sensor type and proximity to faults (200–2000 Hz). Acoustic emission sensors and high-frequency accelerometers sampled at 200 kHz constitute the experimental setup that locates in multiple experimental volumes, which include fluid injections, extractions, and tunneling activities. All sensors transmit real-time data to a common server (SeedLink), which serves multiple clients for processing, real-time visualization, archiving via SeisComP, and risk control via dedicated software. A standardized workflow is applied to both background and experimental monitoring, encompassing automatic picking, automatic phase association and location, and magnitude estimation. Advanced methods are implemented in real time that include double-difference relocation and earthquake detection based on waveform cross correlation. BULGG provides a unique environment to implement novel methods in observational and network seismology across scales.","PeriodicalId":508466,"journal":{"name":"Seismological Research Letters","volume":"34 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141808563","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}
R. Kramer, W. Thelen, A. Iezzi, Seth C. Moran, B. Pauk
The U.S. Geological Survey Cascades Volcano Observatory (CVO) recently expanded its continuous geophysical monitoring at Mount Rainier, an active stratovolcano in Washington state. CVO monitors volcanoes in Oregon, Washington, and Idaho to characterize volcanic systems and detect unrest. Mount Rainier has a history of large lahar occurrences in the Holocene, including at least one that may not have been associated with volcanic activity. Pierce County, Washington, is one of the areas most at risk from large lahars. In the 1990s, CVO collaborated with Pierce County to install the Rainier lahar detection system (RLDS), an automated system designed to detect large lahars in high-risk drainages and mitigate hazards to heavily populated areas. The system was designed to detect lahars within 5–10 min of their occurrence and alert authorities of the need to evacuate populated low-lying areas before lahar arrival. In addition, CVO and the Pacific Northwest Seismic Network (PNSN) maintained and expanded a network of seismic and geodetic monitoring stations on and near the edifice to provide adequate volcano monitoring capabilities. Since 2016, CVO has worked to upgrade the existing RLDS and to expand its capabilities into other drainages around Mount Rainier. This expansion includes installation of 25 new broadband seismic stations with many including infrasound along high-risk drainages, as well as support for equipment upgrades at existing PNSN and CVO volcano monitoring sites. All stations transmit continuous, near-real-time data with dramatically improved spatial coverage for volcano monitoring and lahar hazard mitigation compared to the previous system.
{"title":"Recent Expansion of the Cascades Volcano Observatory Geophysical Network at Mount Rainier for Improved Volcano and Lahar Monitoring","authors":"R. Kramer, W. Thelen, A. Iezzi, Seth C. Moran, B. Pauk","doi":"10.1785/0220240112","DOIUrl":"https://doi.org/10.1785/0220240112","url":null,"abstract":"\u0000 The U.S. Geological Survey Cascades Volcano Observatory (CVO) recently expanded its continuous geophysical monitoring at Mount Rainier, an active stratovolcano in Washington state. CVO monitors volcanoes in Oregon, Washington, and Idaho to characterize volcanic systems and detect unrest. Mount Rainier has a history of large lahar occurrences in the Holocene, including at least one that may not have been associated with volcanic activity. Pierce County, Washington, is one of the areas most at risk from large lahars. In the 1990s, CVO collaborated with Pierce County to install the Rainier lahar detection system (RLDS), an automated system designed to detect large lahars in high-risk drainages and mitigate hazards to heavily populated areas. The system was designed to detect lahars within 5–10 min of their occurrence and alert authorities of the need to evacuate populated low-lying areas before lahar arrival. In addition, CVO and the Pacific Northwest Seismic Network (PNSN) maintained and expanded a network of seismic and geodetic monitoring stations on and near the edifice to provide adequate volcano monitoring capabilities. Since 2016, CVO has worked to upgrade the existing RLDS and to expand its capabilities into other drainages around Mount Rainier. This expansion includes installation of 25 new broadband seismic stations with many including infrasound along high-risk drainages, as well as support for equipment upgrades at existing PNSN and CVO volcano monitoring sites. All stations transmit continuous, near-real-time data with dramatically improved spatial coverage for volcano monitoring and lahar hazard mitigation compared to the previous system.","PeriodicalId":508466,"journal":{"name":"Seismological Research Letters","volume":"34 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141816624","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}
Claire Doody, Arthur J. Rodgers, Andrea Chiang, M. Afanasiev, C. Boehm, L. Krischer, Nathan Simmons
Seismic tomography harnesses earthquake data to explore the inaccessible structure of the Earth. Adjoint waveform tomography (AWT), a method of seismic tomography, updates the tomographic model by optimizing the fit between observed earthquake data and synthetic waveforms. The synthetic data are calculated by solving the wave equation through a given 3D model. An important requirement to calculating synthetics is the source information (location, centroid time, depth, and moment tensor). Errors in source information affect the quality of the synthetics produced, which in turn can limit how structure can be inferred in the AWT workflow. To test the effect of updating source information, we used MTTime (Chiang, 2020), a time-domain full-waveform moment tensor inversion code, to calculate the moment tensors and depths of 118 earthquakes that occurred in California and Nevada over a 20-yr period. We calculated 3D Green’s functions using a 3D seismic wavespeed model of California and Nevada (Doody et al., 2023b). We show that the inverted solutions provide better waveform fits than the Global Centroid Moment Tensor catalog and increase usable, well-correlated data by up to 7%. Therefore, we argue that recalculating source parameters should be considered in AWT workflows, particularly for smaller magnitude events (Mw<5.0).
{"title":"Improved Earthquake Source Parameters with 3D Wavespeed Models in California and Nevada","authors":"Claire Doody, Arthur J. Rodgers, Andrea Chiang, M. Afanasiev, C. Boehm, L. Krischer, Nathan Simmons","doi":"10.1785/0220240011","DOIUrl":"https://doi.org/10.1785/0220240011","url":null,"abstract":"\u0000 Seismic tomography harnesses earthquake data to explore the inaccessible structure of the Earth. Adjoint waveform tomography (AWT), a method of seismic tomography, updates the tomographic model by optimizing the fit between observed earthquake data and synthetic waveforms. The synthetic data are calculated by solving the wave equation through a given 3D model. An important requirement to calculating synthetics is the source information (location, centroid time, depth, and moment tensor). Errors in source information affect the quality of the synthetics produced, which in turn can limit how structure can be inferred in the AWT workflow. To test the effect of updating source information, we used MTTime (Chiang, 2020), a time-domain full-waveform moment tensor inversion code, to calculate the moment tensors and depths of 118 earthquakes that occurred in California and Nevada over a 20-yr period. We calculated 3D Green’s functions using a 3D seismic wavespeed model of California and Nevada (Doody et al., 2023b). We show that the inverted solutions provide better waveform fits than the Global Centroid Moment Tensor catalog and increase usable, well-correlated data by up to 7%. Therefore, we argue that recalculating source parameters should be considered in AWT workflows, particularly for smaller magnitude events (Mw<5.0).","PeriodicalId":508466,"journal":{"name":"Seismological Research Letters","volume":"16 23","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141814580","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}
František Čejka, Ľubica Valentová Krišková, S. Sgobba, F. Pacor, F. Gallovič
The region of Central Italy is well known for its moderate to large earthquakes. Events such as the 2016 Mw 6.2 Amatrice earthquake generated in the shallow extensional tectonic regime motivate numerical simulations to gain insights into source-related ground-motion complexities in the near-source region. We utilize a hybrid integral-composite kinematic rupture model by Gallovič and Brokešová (2007) to simulate the Amatrice earthquake in a broadband frequency range (up to 10 Hz). In the first step, we optimize the input source parameters using a grid-search method by minimizing the spectral acceleration bias between synthetic and recorded strong-motion data at reference rock stations within 50 km of the source. To verify the robustness of the optimal model, we simulate the ground motions at 400 virtual stations and compare their spectral accelerations with the predictions of an empirical nonergodic ground-motion model (GMM) for rock sites in Central Italy (Sgobba et al., 2021). The synthetics show a good agreement with the empirical model regarding both median and variability. Finally, we account for local site effects at nonreference stations by combining the simulations on rock with empirical site terms derived by the nonergodic GMM. The site-corrected spectral responses generally improve the match with the observations, demonstrating a successful fusion of numerical simulations with empirical estimates toward reproducing near-source ground motions.
{"title":"Ground-Motion Modeling of the 2016 Mw 6.2 Amatrice, Italy, Earthquake, by a Broadband Hybrid Kinematic Approach, Including Empirical Site Effects","authors":"František Čejka, Ľubica Valentová Krišková, S. Sgobba, F. Pacor, F. Gallovič","doi":"10.1785/0220230409","DOIUrl":"https://doi.org/10.1785/0220230409","url":null,"abstract":"\u0000 The region of Central Italy is well known for its moderate to large earthquakes. Events such as the 2016 Mw 6.2 Amatrice earthquake generated in the shallow extensional tectonic regime motivate numerical simulations to gain insights into source-related ground-motion complexities in the near-source region. We utilize a hybrid integral-composite kinematic rupture model by Gallovič and Brokešová (2007) to simulate the Amatrice earthquake in a broadband frequency range (up to 10 Hz). In the first step, we optimize the input source parameters using a grid-search method by minimizing the spectral acceleration bias between synthetic and recorded strong-motion data at reference rock stations within 50 km of the source. To verify the robustness of the optimal model, we simulate the ground motions at 400 virtual stations and compare their spectral accelerations with the predictions of an empirical nonergodic ground-motion model (GMM) for rock sites in Central Italy (Sgobba et al., 2021). The synthetics show a good agreement with the empirical model regarding both median and variability. Finally, we account for local site effects at nonreference stations by combining the simulations on rock with empirical site terms derived by the nonergodic GMM. The site-corrected spectral responses generally improve the match with the observations, demonstrating a successful fusion of numerical simulations with empirical estimates toward reproducing near-source ground motions.","PeriodicalId":508466,"journal":{"name":"Seismological Research Letters","volume":" 1029","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141823265","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}
Different frequency contents of seismic waveforms may reveal different earthquake rupture features, which could shed light on understanding the seismic rupture and its association with seismogenic fault structures. Here, we applied finite-fault inversions and compressive-sensing backprojection analyses to study the rupture process of the 2021 Mw 7.4 Maduo, China earthquake, using seismic data in different frequency ranges. Our results unveil an asymmetric west-to-east bilateral rupture of this earthquake, that is, the westward rupture hosted less coseismic slip and less energy radiations than the eastward one. The westward rupture may encounter a structural complexity, suppressing the propagation of the seismic rupture and radiating higher-frequency energy. Instead, the eastward rupture passed across a relatively continuous fault geometry and possibly reached super-shear velocities locally. The fault bifurcation at the eastern end may arrest the seismic rupture and facilitate its termination. We infer that asymmetric rupture features of the 2021 Maduo earthquake are associated with complex fault structures resulting from deformations caused by the northeastward growth of the Tibetan plateau.
{"title":"Asymmetric Bilateral Rupture of the 2021 Mw 7.4 Maduo Earthquake in China and Association with Seismogenic Fault Structures","authors":"Wei Liu, Lingci Zeng, Huajian Yao, Zhenjiang Yu, Xiaofei Chen","doi":"10.1785/0220240031","DOIUrl":"https://doi.org/10.1785/0220240031","url":null,"abstract":"\u0000 Different frequency contents of seismic waveforms may reveal different earthquake rupture features, which could shed light on understanding the seismic rupture and its association with seismogenic fault structures. Here, we applied finite-fault inversions and compressive-sensing backprojection analyses to study the rupture process of the 2021 Mw 7.4 Maduo, China earthquake, using seismic data in different frequency ranges. Our results unveil an asymmetric west-to-east bilateral rupture of this earthquake, that is, the westward rupture hosted less coseismic slip and less energy radiations than the eastward one. The westward rupture may encounter a structural complexity, suppressing the propagation of the seismic rupture and radiating higher-frequency energy. Instead, the eastward rupture passed across a relatively continuous fault geometry and possibly reached super-shear velocities locally. The fault bifurcation at the eastern end may arrest the seismic rupture and facilitate its termination. We infer that asymmetric rupture features of the 2021 Maduo earthquake are associated with complex fault structures resulting from deformations caused by the northeastward growth of the Tibetan plateau.","PeriodicalId":508466,"journal":{"name":"Seismological Research Letters","volume":" 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141822510","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 Ms 6.0 Luxian earthquake, which occurred in a shallow sedimentary cover on the southern margin of the Sichuan basin in China, stands as the most powerful earthquake ever recorded in this region. This study aims to integrate multiple seismological methods to comprehensively investigate the seismic nucleation environment. Using data from 91 densely distributed seismic stations within the Luxian earthquake zone, we constructed models for velocity, anisotropy, and interfaces. Our results suggest the presence of a detachment interface at depths of ∼4.0–5.0 km, which appears to function as a stress-decoupling layer. This is evidenced by a noticeable shift in the intensity and orientation of azimuthal anisotropy, transitioning from weak to strong, and altering its alignment from a northwest–southeast to a northeast–southwest orientation. The mainshock and aftershocks are predominantly clustered along the boundaries characterized by high- and low-velocity zones, as well as the boundary of VP/VS ratios beneath the detached layer. This suggests the likely existence of a pre-existing northwest–southeast-striking fault with a southwest dip, extending from the underlying basement to the overlying sedimentary cover. The radial anisotropy analysis reveals a predominance of negative values beneath the Huaying Mountain fault, whereas positive values are prominent in the Yujisi sedimentary syncline. This distinctive pattern implies tectonic movements related to fault activities within the fault zone. Based on our findings and previous research, we speculate that the Ms 6.0 Luxian earthquake may have been influenced by local stress fields and triggered by industrial activities.
泸县 6.0 级地震发生在中国四川盆地南缘浅层沉积覆盖区，是该地区有记录以来最强烈的地震。本研究旨在整合多种地震学方法，全面研究地震成核环境。利用泸县地震带内 91 个密集分布的地震台站的数据，我们构建了速度、各向异性和界面模型。我们的研究结果表明，在 4.0-5.0 千米深处存在一个剥离界面，它似乎起着应力解耦层的作用。这表现在方位各向异性的强度和方向发生了明显的变化，由弱变强，其走向也由西北-东南走向变为东北-西南走向。主震和余震主要集中在高速区和低速区的边界，以及脱离层下的VP/VS比率边界。这表明很可能存在一个预先存在的西北-东南走向的断层，其倾角为西南向，从底层基底延伸到上覆沉积覆盖层。径向各向异性分析表明，在华清山断层下，负值居多，而在于吉思沉积突岩中，正值则很突出。这种独特的模式暗示了断层带内与断层活动有关的构造运动。根据我们的发现和以往的研究，我们推测 Ms 6.0 泸县地震可能受到当地应力场的影响，并由工业活动引发。
{"title":"High-Resolution Velocity and Seismic Anisotropy Structures of the 2021 Ms 6.0 Luxian Earthquake Zone in Sichuan Basin","authors":"Pingping Wu, Huili Guo, Wei Xu, Tongwei Qin, Dahu Li, Laiyu Lu, Zhifeng Ding","doi":"10.1785/0220240046","DOIUrl":"https://doi.org/10.1785/0220240046","url":null,"abstract":"\u0000 The Ms 6.0 Luxian earthquake, which occurred in a shallow sedimentary cover on the southern margin of the Sichuan basin in China, stands as the most powerful earthquake ever recorded in this region. This study aims to integrate multiple seismological methods to comprehensively investigate the seismic nucleation environment. Using data from 91 densely distributed seismic stations within the Luxian earthquake zone, we constructed models for velocity, anisotropy, and interfaces. Our results suggest the presence of a detachment interface at depths of ∼4.0–5.0 km, which appears to function as a stress-decoupling layer. This is evidenced by a noticeable shift in the intensity and orientation of azimuthal anisotropy, transitioning from weak to strong, and altering its alignment from a northwest–southeast to a northeast–southwest orientation. The mainshock and aftershocks are predominantly clustered along the boundaries characterized by high- and low-velocity zones, as well as the boundary of VP/VS ratios beneath the detached layer. This suggests the likely existence of a pre-existing northwest–southeast-striking fault with a southwest dip, extending from the underlying basement to the overlying sedimentary cover. The radial anisotropy analysis reveals a predominance of negative values beneath the Huaying Mountain fault, whereas positive values are prominent in the Yujisi sedimentary syncline. This distinctive pattern implies tectonic movements related to fault activities within the fault zone. Based on our findings and previous research, we speculate that the Ms 6.0 Luxian earthquake may have been influenced by local stress fields and triggered by industrial activities.","PeriodicalId":508466,"journal":{"name":"Seismological Research Letters","volume":" 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141828978","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}
Peter Makus, M. Denolle, C. Sens‐Schönfelder, Manuela Kopfli, Frederik Tilmann
We estimate changes in the seismic velocity (dv/v) from 25 years of ambient seismic noise recorded at Mount St. Helens (MSH). At MSH, the availability of seismic stations changes frequently due to station failure and the installation of new stations. Therefore, it is difficult to combine relative measurements that do not span the same time and space. We tackle this challenge by developing a spatial imaging algorithm to normalize all ∼1400 dv/v time series onto one spatial grid. Thereby, we obtain time-dependent velocity change maps of the MSH region, which we analyze with the help of auxiliary observations, such as ground position (i.e., Global Navigation Satellite System [GNSS]), weather data, environmental observations, and regional seismicity. In the dv/v time series, we find a variety of dynamics caused by volcanic, tectonic, and environmental forcing. With the initiation of MSH’s 2004–2008 volcanic crisis, dv/v exhibits a significant increase, which we link to the deflation of the volcanic plumbing system, also observed on GNSS data. Between 2013 and 2018, when seismicity levels are elevated, we find lower velocities at depth. This phase is followed by an episode of relative quiescence, accompanied by significant dv/v increases close to the St. Helens seismic zone. We suggest a reinflation of the magmatic plumbing system after MSH’s 2004–2008 eruption lasting until about 2017. Afterward, the magmatic activity in the subsurface reduces, thereby decreasing pressure and increasing the seismic velocity. Fluctuating groundwater levels may dominate the seasonal cycles in the dv/v time series. A contrasting seasonal response between the high-elevation edifice and foothill valleys may indicate that surface freezing inhibits subsurface groundwater infiltration at higher altitudes.
{"title":"Analyzing Volcanic, Tectonic, and Environmental Influences on the Seismic Velocity from 25 Years of Data at Mount St. Helens","authors":"Peter Makus, M. Denolle, C. Sens‐Schönfelder, Manuela Kopfli, Frederik Tilmann","doi":"10.1785/0220240088","DOIUrl":"https://doi.org/10.1785/0220240088","url":null,"abstract":"\u0000 We estimate changes in the seismic velocity (dv/v) from 25 years of ambient seismic noise recorded at Mount St. Helens (MSH). At MSH, the availability of seismic stations changes frequently due to station failure and the installation of new stations. Therefore, it is difficult to combine relative measurements that do not span the same time and space. We tackle this challenge by developing a spatial imaging algorithm to normalize all ∼1400 dv/v time series onto one spatial grid. Thereby, we obtain time-dependent velocity change maps of the MSH region, which we analyze with the help of auxiliary observations, such as ground position (i.e., Global Navigation Satellite System [GNSS]), weather data, environmental observations, and regional seismicity. In the dv/v time series, we find a variety of dynamics caused by volcanic, tectonic, and environmental forcing. With the initiation of MSH’s 2004–2008 volcanic crisis, dv/v exhibits a significant increase, which we link to the deflation of the volcanic plumbing system, also observed on GNSS data. Between 2013 and 2018, when seismicity levels are elevated, we find lower velocities at depth. This phase is followed by an episode of relative quiescence, accompanied by significant dv/v increases close to the St. Helens seismic zone. We suggest a reinflation of the magmatic plumbing system after MSH’s 2004–2008 eruption lasting until about 2017. Afterward, the magmatic activity in the subsurface reduces, thereby decreasing pressure and increasing the seismic velocity. Fluctuating groundwater levels may dominate the seasonal cycles in the dv/v time series. A contrasting seasonal response between the high-elevation edifice and foothill valleys may indicate that surface freezing inhibits subsurface groundwater infiltration at higher altitudes.","PeriodicalId":508466,"journal":{"name":"Seismological Research Letters","volume":" 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141830335","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 temporary strong-motion observation in Yunnan Province, southwestern China, has obtained a valuable batch of near-source recordings from many small earthquakes from 2008 to 2018. Based on the 546 well-processed strong-motion recordings with R = 4–35 km, which were obtained at 56 temporary strong-motion stations in 198 small earthquakes with ML=2.0–4.3 in Yunnan Province, we established ground-motion attenuation models for peak ground acceleration and peak spectral accelerations (PSAs) at periods of 0.1–2.0 s and investigated the attenuation characteristics of the near-source ground motions of small events. Our model includes the source term represented by the quadratic functional form of M, the magnitude-dependent geometrical spreading term, and the local site effects on the horizontal ground motions. The predicted medians by our model can well describe the distance attenuation of the near-source ground motion observed in the small events. The attenuation model in this study well represents the dependence of geometrical spreading on both the magnitude and the oscillator period that is the larger the magnitude and the longer the period, the weaker the geometrical spreading. Our model was compared with the Sun19 model for small aftershocks in the Jinggu, Yunnan Province earthquake sequence and the Zhang22 model for moderate-to-large earthquakes in western China. Our model shows the weaker attenuation rate with distance and the weaker source effects, compared with the Sun19 model. Similarly, there is the weaker geometrical spreading for PSAs at periods greater than 0.5 s in our model than in the Zhang22 model.
{"title":"Attenuation Characteristics of Near-Source Ground Motions from Temporary Observations of Small Earthquakes in Yunnan Province, China","authors":"Hongrui Li, Hongwei Wang, R. Wen, Yefei Ren, Guoliang Lin, Jianwen Cui, Ying Zhou","doi":"10.1785/0220230373","DOIUrl":"https://doi.org/10.1785/0220230373","url":null,"abstract":"\u0000 The temporary strong-motion observation in Yunnan Province, southwestern China, has obtained a valuable batch of near-source recordings from many small earthquakes from 2008 to 2018. Based on the 546 well-processed strong-motion recordings with R = 4–35 km, which were obtained at 56 temporary strong-motion stations in 198 small earthquakes with ML=2.0–4.3 in Yunnan Province, we established ground-motion attenuation models for peak ground acceleration and peak spectral accelerations (PSAs) at periods of 0.1–2.0 s and investigated the attenuation characteristics of the near-source ground motions of small events. Our model includes the source term represented by the quadratic functional form of M, the magnitude-dependent geometrical spreading term, and the local site effects on the horizontal ground motions. The predicted medians by our model can well describe the distance attenuation of the near-source ground motion observed in the small events. The attenuation model in this study well represents the dependence of geometrical spreading on both the magnitude and the oscillator period that is the larger the magnitude and the longer the period, the weaker the geometrical spreading. Our model was compared with the Sun19 model for small aftershocks in the Jinggu, Yunnan Province earthquake sequence and the Zhang22 model for moderate-to-large earthquakes in western China. Our model shows the weaker attenuation rate with distance and the weaker source effects, compared with the Sun19 model. Similarly, there is the weaker geometrical spreading for PSAs at periods greater than 0.5 s in our model than in the Zhang22 model.","PeriodicalId":508466,"journal":{"name":"Seismological Research Letters","volume":"77 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141658072","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}
Kaiwen Wang, F. Waldhauser, D. Schaff, M. Tolstoy, William S. D. Wilcock, Yen Joe Tan
Axial Seamount, an extensively instrumented submarine volcano, lies at the intersection of the Cobb–Eickelberg hot spot and the Juan de Fuca ridge. Since late 2014, the Ocean Observatories Initiative (OOI) has operated a seven-station cabled ocean bottom seismometer (OBS) array that captured Axial’s last eruption in April 2015. This network streams data in real-time, facilitating seismic monitoring and analysis for volcanic unrest detection and eruption forecasting. In this study, we introduce a machine learning (ML)-based real-time seismic monitoring framework for Axial Seamount. Combining both supervised and unsupervised ML and double-difference techniques, we constructed a comprehensive, high-resolution earthquake catalog while effectively discriminating between various seismic and acoustic events. These events include earthquakes generated by different physical processes, acoustic signals of lava–water interaction, and oceanic sources such as whale calls. We first built a labeled ML-based earthquake catalog that extends from November 2014 to the end of 2021 and then implemented real-time monitoring and seismic analysis starting in 2022. With the rapid determination of high-resolution earthquake locations and the capability to track potential precursory signals and coeruption indicators of magma outflow, this system may improve eruption forecasting by providing short-term constraints on Axial’s next eruption. Furthermore, our work demonstrates an effective application that integrates unsupervised learning for signal discrimination in real-time operation, which could be adapted to other regions for volcanic unrest detection and enhanced eruption forecasting.
轴心海山（Axial Seamount）位于科布-艾克尔伯格（Cobb-Eickelberg）热点和胡安-德富卡海脊（Juan de Fuca ridge）的交汇处，是一座拥有大量仪器的海底火山。自2014年底以来，海洋观测站计划（OOI）运行了一个七站电缆海底地震仪（OBS）阵列，该阵列捕捉到了2015年4月轴心的最后一次喷发。该网络实时传输数据流，为火山动荡探测和喷发预报的地震监测和分析提供了便利。在本研究中，我们为轴心海隆引入了基于机器学习（ML）的实时地震监测框架。结合监督和非监督 ML 以及双差分技术，我们构建了一个全面、高分辨率的地震目录，同时有效区分了各种地震和声学事件。这些事件包括由不同物理过程产生的地震、熔岩与水相互作用的声学信号以及鲸鱼叫声等海洋信号源。我们首先建立了从 2014 年 11 月到 2021 年底的基于 ML 的标注地震目录，然后从 2022 年开始实施实时监测和地震分析。该系统能够快速确定高分辨率地震位置，并跟踪岩浆流出的潜在前兆信号和裹挟指标，从而为轴心火山的下一次喷发提供短期约束，从而改进喷发预测。此外，我们的工作还展示了一种有效的应用，它在实时操作中整合了信号辨别的无监督学习，可适用于其他地区的火山动乱探测和增强型喷发预报。
{"title":"Real-Time Detection of Volcanic Unrest and Eruption at Axial Seamount Using Machine Learning","authors":"Kaiwen Wang, F. Waldhauser, D. Schaff, M. Tolstoy, William S. D. Wilcock, Yen Joe Tan","doi":"10.1785/0220240086","DOIUrl":"https://doi.org/10.1785/0220240086","url":null,"abstract":"\u0000 Axial Seamount, an extensively instrumented submarine volcano, lies at the intersection of the Cobb–Eickelberg hot spot and the Juan de Fuca ridge. Since late 2014, the Ocean Observatories Initiative (OOI) has operated a seven-station cabled ocean bottom seismometer (OBS) array that captured Axial’s last eruption in April 2015. This network streams data in real-time, facilitating seismic monitoring and analysis for volcanic unrest detection and eruption forecasting. In this study, we introduce a machine learning (ML)-based real-time seismic monitoring framework for Axial Seamount. Combining both supervised and unsupervised ML and double-difference techniques, we constructed a comprehensive, high-resolution earthquake catalog while effectively discriminating between various seismic and acoustic events. These events include earthquakes generated by different physical processes, acoustic signals of lava–water interaction, and oceanic sources such as whale calls. We first built a labeled ML-based earthquake catalog that extends from November 2014 to the end of 2021 and then implemented real-time monitoring and seismic analysis starting in 2022. With the rapid determination of high-resolution earthquake locations and the capability to track potential precursory signals and coeruption indicators of magma outflow, this system may improve eruption forecasting by providing short-term constraints on Axial’s next eruption. Furthermore, our work demonstrates an effective application that integrates unsupervised learning for signal discrimination in real-time operation, which could be adapted to other regions for volcanic unrest detection and enhanced eruption forecasting.","PeriodicalId":508466,"journal":{"name":"Seismological Research Letters","volume":"102 S404","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141835117","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}
Viscoelastic postseismic deformation following the 2004 Mw 9.2 Sumatra and 2005 Mw 8.6 Nias earthquakes extend thousands and hundreds of kilometers from the rupture area, respectively, providing an opportunity to better understand the rheology of the northern Sumatra subduction zone. We have developed a 3D viscoelastic finite-element model to study the postseismic deformation of the 2004 and 2005 events. The time-dependent and stress-driven afterslip is simulated by a 2-km-thick shear zone. Model results indicate that the viscosity of the shear zone of the two events is different, and their boundary is the southern edge of the 2004 rupture area, which is also consistent with the southern edge of the Andaman microplate. The viscosity of the shear zone is determined to be 2×1017 Pa·s in the northern segment, 1016 Pa·s at shallow depths (≤20 km) and 2×1018 Pa·s at greater depths (>20 km) in the southern segment. Afterslip of the 2004 event takes place mostly surrounding the rupture area and is up to 3.2 m within 10 yr after the earthquake. Afterslip of the 2005 event takes place mostly up-dip of the rupture and is up to 4.3 m. The viscosity of the weakened areas in the Andaman spreading center and Toba volcano is determined to be 1018 Pa·s and 3×1018 Pa·s, respectively. A test model with the oceanic asthenosphere extending to depths up to 110 km better explains the vertical motion in the near field.
{"title":"Mantle Wedge Heterogeneities and Afterslip Distribution Following the 2004 Mw 9.2 and 2005 Mw 8.6 Sumatra Earthquakes","authors":"Siyuan Yang, Yan Hu, Jian Zhang","doi":"10.1785/0220230382","DOIUrl":"https://doi.org/10.1785/0220230382","url":null,"abstract":"\u0000 Viscoelastic postseismic deformation following the 2004 Mw 9.2 Sumatra and 2005 Mw 8.6 Nias earthquakes extend thousands and hundreds of kilometers from the rupture area, respectively, providing an opportunity to better understand the rheology of the northern Sumatra subduction zone. We have developed a 3D viscoelastic finite-element model to study the postseismic deformation of the 2004 and 2005 events. The time-dependent and stress-driven afterslip is simulated by a 2-km-thick shear zone. Model results indicate that the viscosity of the shear zone of the two events is different, and their boundary is the southern edge of the 2004 rupture area, which is also consistent with the southern edge of the Andaman microplate. The viscosity of the shear zone is determined to be 2×1017 Pa·s in the northern segment, 1016 Pa·s at shallow depths (≤20 km) and 2×1018 Pa·s at greater depths (>20 km) in the southern segment. Afterslip of the 2004 event takes place mostly surrounding the rupture area and is up to 3.2 m within 10 yr after the earthquake. Afterslip of the 2005 event takes place mostly up-dip of the rupture and is up to 4.3 m. The viscosity of the weakened areas in the Andaman spreading center and Toba volcano is determined to be 1018 Pa·s and 3×1018 Pa·s, respectively. A test model with the oceanic asthenosphere extending to depths up to 110 km better explains the vertical motion in the near field.","PeriodicalId":508466,"journal":{"name":"Seismological Research Letters","volume":"106 18","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141657341","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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