Giovanna Calderoni, Luigi Improta, Rita Di Giovambattista
Abstract We investigate the variability of Brune stress drop (Δσ), apparent stress (τa), and Savage–Wood radiation efficiency (ηsw=τa/Δσ), in the 2013–2014 Mw 5.0 earthquake sequence that struck the Matese area in the southern Apennines range of Italy. The sequence is clustered in a relatively small crustal volume in the 13–22 km depth range, which is greater than that of background seismicity and normal-faulting sequences that occurred under the range axis, usually located in the first 15 km of the crust. We find high Savage–Wood radiation efficiency values for most of the analyzed earthquakes located in a narrow crustal volume, with values ranging from well above the self-similarity value to very high values as high as 0.55. In addition, a large variability in radiation efficiency (up to 90%) is observed for two similar magnitude events at different depths. Previous studies reported seismic evidence of fluid involvement in the nucleation process of the Matese earthquakes. By integrating our results with crustal geophysical data published recently, we propose that most of the earthquakes characterized by high values of ηsw are nucleated within high pore pressure zones located in the crystalline midcrust of Adria. We reckon that high pore pressure fluids of deep origin played a role in the rupture process and were responsible for the mixed shear-tensile sources inferred from the analysis of the S-wave/P-wave spectral amplitude ratio for most of 2013–2014 earthquakes.
{"title":"Investigating the Role of Fluids in the Source Parameters of the 2013–2014 Mw 5 Matese Seismic Sequence, Southern Italy","authors":"Giovanna Calderoni, Luigi Improta, Rita Di Giovambattista","doi":"10.1785/0220230046","DOIUrl":"https://doi.org/10.1785/0220230046","url":null,"abstract":"Abstract We investigate the variability of Brune stress drop (Δσ), apparent stress (τa), and Savage–Wood radiation efficiency (ηsw=τa/Δσ), in the 2013–2014 Mw 5.0 earthquake sequence that struck the Matese area in the southern Apennines range of Italy. The sequence is clustered in a relatively small crustal volume in the 13–22 km depth range, which is greater than that of background seismicity and normal-faulting sequences that occurred under the range axis, usually located in the first 15 km of the crust. We find high Savage–Wood radiation efficiency values for most of the analyzed earthquakes located in a narrow crustal volume, with values ranging from well above the self-similarity value to very high values as high as 0.55. In addition, a large variability in radiation efficiency (up to 90%) is observed for two similar magnitude events at different depths. Previous studies reported seismic evidence of fluid involvement in the nucleation process of the Matese earthquakes. By integrating our results with crustal geophysical data published recently, we propose that most of the earthquakes characterized by high values of ηsw are nucleated within high pore pressure zones located in the crystalline midcrust of Adria. We reckon that high pore pressure fluids of deep origin played a role in the rupture process and were responsible for the mixed shear-tensile sources inferred from the analysis of the S-wave/P-wave spectral amplitude ratio for most of 2013–2014 earthquakes.","PeriodicalId":21687,"journal":{"name":"Seismological Research Letters","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136352913","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}
Abstract The Anninghe fault (ANHF), located in southwest China, was a major block boundary that hosted M 7.5 earthquakes historically. For seismic hazard assessment, it is critical to investigate fault properties before future earthquakes. To investigate the fault structure, we deployed three linear dense arrays with an aperture of ∼8–9 km across different segments of the ANHF from October 2019 to March 2020. More importantly, we detonated a new methane source to generate seismic waves, which is environmentally friendly and can be used in different regions such as mountainous and urban areas. After data acquisition, we first removed the noise to accurately pick up the first arrivals of seismic waves. Then, we conducted the first-arrival seismic tomography, a method commonly used in the petroleum industry, to obtain the high-resolution P-wave velocity structure. The tomographic results showed distinct low-velocity zones (LVZs) of ∼1000–1500 m in width and ∼300–400 m in depth along the fault, well consistent with the lateral distribution of site amplification that was derived from regional earthquake waveforms. These LVZs may have formed as a combined result of the fault damage zone and ANHF-controlled sediments. As the Anning River Valley is densely populated, our newly identified LVZs shed lights on earthquake hazard in the region. In addition, we demonstrate that using a combination of methane detonation sources, linear dense arrays, and active source tomography can effectively determine the shallow P-wave velocity model in complex environments (i.e., mountains and urban areas).
{"title":"High-Resolution Shallow Structure along the Anninghe Fault Zone, Sichuan, China, Constrained by Active Source Tomography","authors":"Xinru Mu, Junhao Song, Hongfeng Yang, Jianping Huang, Huajian Yao, Baofeng Tian","doi":"10.1785/0220230137","DOIUrl":"https://doi.org/10.1785/0220230137","url":null,"abstract":"Abstract The Anninghe fault (ANHF), located in southwest China, was a major block boundary that hosted M 7.5 earthquakes historically. For seismic hazard assessment, it is critical to investigate fault properties before future earthquakes. To investigate the fault structure, we deployed three linear dense arrays with an aperture of ∼8–9 km across different segments of the ANHF from October 2019 to March 2020. More importantly, we detonated a new methane source to generate seismic waves, which is environmentally friendly and can be used in different regions such as mountainous and urban areas. After data acquisition, we first removed the noise to accurately pick up the first arrivals of seismic waves. Then, we conducted the first-arrival seismic tomography, a method commonly used in the petroleum industry, to obtain the high-resolution P-wave velocity structure. The tomographic results showed distinct low-velocity zones (LVZs) of ∼1000–1500 m in width and ∼300–400 m in depth along the fault, well consistent with the lateral distribution of site amplification that was derived from regional earthquake waveforms. These LVZs may have formed as a combined result of the fault damage zone and ANHF-controlled sediments. As the Anning River Valley is densely populated, our newly identified LVZs shed lights on earthquake hazard in the region. In addition, we demonstrate that using a combination of methane detonation sources, linear dense arrays, and active source tomography can effectively determine the shallow P-wave velocity model in complex environments (i.e., mountains and urban areas).","PeriodicalId":21687,"journal":{"name":"Seismological Research Letters","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136294647","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}
Abstract Predicting surface-wave travel-time shifts is valuable for analyzing potential effects caused by changes in medium properties, station clock errors, instrument response errors, and other factors. Many current neural networks used in seismology are single-station models trained using single-station (pair) data. However, most seismic methods require knowledge of the spatial positions between multiple stations. Multiple stations contain rich interrelationships and spatial information that cannot be exploited by single-station models. We proposed a multistation neural network structure Transformer Graph Convolutional Network (TGCN) that utilizes temporal attention and spatial attention to capture spatiotemporal information for predicting relative travel-time shifts. Before that, we introduced a method that treats station pairs as nodes and constructs a graph with multiple station pairs. We collected original ambient noise waveforms from 2017 to 2019 in the Alaska region and 2010 to 2014 in the southern California region to obtain relative travel-time shift sequences of station pairs for model training and testing. To showcase the improvement of spatial information to the model, we compared TGCN with two other baseline single-station models—temporal convolutional network and long short-term memory. Our proposed method predicted travel-time values more accurately than the two baseline models, and it also exhibited slower decay in performance when predicting over larger intervals. We also found that the number of station pairs has an impact on the model. When there are a sufficient number of station pairs, the model can effectively utilize the rich spatial information and achieve higher accuracy. Our approach, which incorporates spatiotemporal information, provides outputs that are more efficient and accurate compared with the traditional single-station (pair) method that only considers temporal information, suggesting that spatial information does enhance the performance of the model.
{"title":"Transformer Graph Convolutional Network for Relative Travel-Time Shift Prediction","authors":"Chunwei Jin, Fang Ye, Jinhui Cai, Yan Yao","doi":"10.1785/0220230158","DOIUrl":"https://doi.org/10.1785/0220230158","url":null,"abstract":"Abstract Predicting surface-wave travel-time shifts is valuable for analyzing potential effects caused by changes in medium properties, station clock errors, instrument response errors, and other factors. Many current neural networks used in seismology are single-station models trained using single-station (pair) data. However, most seismic methods require knowledge of the spatial positions between multiple stations. Multiple stations contain rich interrelationships and spatial information that cannot be exploited by single-station models. We proposed a multistation neural network structure Transformer Graph Convolutional Network (TGCN) that utilizes temporal attention and spatial attention to capture spatiotemporal information for predicting relative travel-time shifts. Before that, we introduced a method that treats station pairs as nodes and constructs a graph with multiple station pairs. We collected original ambient noise waveforms from 2017 to 2019 in the Alaska region and 2010 to 2014 in the southern California region to obtain relative travel-time shift sequences of station pairs for model training and testing. To showcase the improvement of spatial information to the model, we compared TGCN with two other baseline single-station models—temporal convolutional network and long short-term memory. Our proposed method predicted travel-time values more accurately than the two baseline models, and it also exhibited slower decay in performance when predicting over larger intervals. We also found that the number of station pairs has an impact on the model. When there are a sufficient number of station pairs, the model can effectively utilize the rich spatial information and achieve higher accuracy. Our approach, which incorporates spatiotemporal information, provides outputs that are more efficient and accurate compared with the traditional single-station (pair) method that only considers temporal information, suggesting that spatial information does enhance the performance of the model.","PeriodicalId":21687,"journal":{"name":"Seismological Research Letters","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135480714","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}
Wenhuan Kuang, Congcong Yuan, Zhihui Zou, Jie Zhang, Wei Zhang
Abstract Recent advances in artificial intelligence allow seismologists to upgrade the workflow for locating earthquakes. The standard workflow concatenates a sequence of data processing modules, including event detection, phase picking, association, and event location, with elaborately fine-tuned parameters, lacking automation and convenience. Here, we leverage deep reinforcement learning and develop a state-of-the-art earthquake robot (EQBot) to help advance automated earthquake location. The EQBot learns from tremendous trial-and-error explorations, which aims to best align the observed P and S waves, complying with the geophysical principle of gather alignments in source imaging. After training on earthquakes (M ≥ 2.0) for a decade in the Los Angeles region, it can locate earthquakes directly from waveforms with mean absolute errors of 1.32 km, 1.35 km, and 1.96 km in latitude, longitude, and depth, respectively, closely comparable to the cataloged locations. Moreover, it can automatically implement quality control by examining the alignments of P and S waves. Our study provides a new solution to advance the earthquake location process toward full automation.
{"title":"Autonomous Earthquake Location via Deep Reinforcement Learning","authors":"Wenhuan Kuang, Congcong Yuan, Zhihui Zou, Jie Zhang, Wei Zhang","doi":"10.1785/0220230118","DOIUrl":"https://doi.org/10.1785/0220230118","url":null,"abstract":"Abstract Recent advances in artificial intelligence allow seismologists to upgrade the workflow for locating earthquakes. The standard workflow concatenates a sequence of data processing modules, including event detection, phase picking, association, and event location, with elaborately fine-tuned parameters, lacking automation and convenience. Here, we leverage deep reinforcement learning and develop a state-of-the-art earthquake robot (EQBot) to help advance automated earthquake location. The EQBot learns from tremendous trial-and-error explorations, which aims to best align the observed P and S waves, complying with the geophysical principle of gather alignments in source imaging. After training on earthquakes (M ≥ 2.0) for a decade in the Los Angeles region, it can locate earthquakes directly from waveforms with mean absolute errors of 1.32 km, 1.35 km, and 1.96 km in latitude, longitude, and depth, respectively, closely comparable to the cataloged locations. Moreover, it can automatically implement quality control by examining the alignments of P and S waves. Our study provides a new solution to advance the earthquake location process toward full automation.","PeriodicalId":21687,"journal":{"name":"Seismological Research Letters","volume":"33 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135689216","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}
Abstract Monitoring the temporal variation in seismic velocity plays a critical role in understanding the dynamic processes of the subsurface at different scales. Many seismic velocity changes related to earthquakes and volcanic activities have been obtained using ambient noise correlation in recent years; however, their temporal resolution is limited, typically from a few to dozens of days, which makes it challenging to explore the valuable but short-duration changes in subsurface media. In this article, we develop a method based on the correlation of the coda of the ambient noise correlation (C3) with a multiple-component combination and introduced singular value decomposition-based Wiener filter denoising technique. Using permanent network data, we achieved subdaily ambient noise monitoring at Parkfield, California, using 4-hr cross-correlation stacking with 2-hr step. We identified that the maximum seismic velocity drop delayed the mainshock of the 2004 Mw 6.0 Parkfield earthquake by ∼41 hr, during which the temporal velocity process may have been affected by strong aftershocks, including an Mw 5.0 aftershock that occurred one day after the mainshock; however, no significant precursory change was detected. Our method provides an opportunity for monitoring the short-term change of underground structures based on the widely distributed seismic networks. In addition, the idea of obtaining reliable subsurface information within a short time through high-order noise correlation in this work has important enlightenment for ambient noise imaging and monitoring in broader fields.
{"title":"Subdaily Ambient Noise Monitoring at Parkfield, California, by Combining C1 and C3","authors":"Yi Meng, Zhikun Liu, Tiancheng Li, Rui Zhang","doi":"10.1785/0220230119","DOIUrl":"https://doi.org/10.1785/0220230119","url":null,"abstract":"Abstract Monitoring the temporal variation in seismic velocity plays a critical role in understanding the dynamic processes of the subsurface at different scales. Many seismic velocity changes related to earthquakes and volcanic activities have been obtained using ambient noise correlation in recent years; however, their temporal resolution is limited, typically from a few to dozens of days, which makes it challenging to explore the valuable but short-duration changes in subsurface media. In this article, we develop a method based on the correlation of the coda of the ambient noise correlation (C3) with a multiple-component combination and introduced singular value decomposition-based Wiener filter denoising technique. Using permanent network data, we achieved subdaily ambient noise monitoring at Parkfield, California, using 4-hr cross-correlation stacking with 2-hr step. We identified that the maximum seismic velocity drop delayed the mainshock of the 2004 Mw 6.0 Parkfield earthquake by ∼41 hr, during which the temporal velocity process may have been affected by strong aftershocks, including an Mw 5.0 aftershock that occurred one day after the mainshock; however, no significant precursory change was detected. Our method provides an opportunity for monitoring the short-term change of underground structures based on the widely distributed seismic networks. In addition, the idea of obtaining reliable subsurface information within a short time through high-order noise correlation in this work has important enlightenment for ambient noise imaging and monitoring in broader fields.","PeriodicalId":21687,"journal":{"name":"Seismological Research Letters","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135689215","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}
Abstract Receiver functions can be used to estimate the Moho depth (H) and ratio of P to S wavespeed (α/β or κ) in the crust. This is commonly done by grid search, forward modeling travel times to produce so-called “H-κ” stacks of receiver function amplitude. However, radial anisotropy in the crust, which can be significant, is almost never considered in this process. Here, we show that radial anisotropy changes the H-κ stack, biasing interpretations of crustal structure by introducing errors up to ∼3% in H and ∼1% in κ for commonly observed anisotropy magnitudes. We propose a simple method to correct H-κ stacks by incorporating radial anisotropy in the forward calculation. Synthetic tests show that this approach almost completely removes error caused by radial anisotropy. We show examples of this procedure with stations in the eastern United States. We provide readers with code to construct radially anisotropic H-κ stacks.
{"title":"Radial Anisotropy in Receiver Function H−κ Stacks","authors":"Brennan Brunsvik, Zachary Eilon","doi":"10.1785/0220230114","DOIUrl":"https://doi.org/10.1785/0220230114","url":null,"abstract":"Abstract Receiver functions can be used to estimate the Moho depth (H) and ratio of P to S wavespeed (α/β or κ) in the crust. This is commonly done by grid search, forward modeling travel times to produce so-called “H-κ” stacks of receiver function amplitude. However, radial anisotropy in the crust, which can be significant, is almost never considered in this process. Here, we show that radial anisotropy changes the H-κ stack, biasing interpretations of crustal structure by introducing errors up to ∼3% in H and ∼1% in κ for commonly observed anisotropy magnitudes. We propose a simple method to correct H-κ stacks by incorporating radial anisotropy in the forward calculation. Synthetic tests show that this approach almost completely removes error caused by radial anisotropy. We show examples of this procedure with stations in the eastern United States. We provide readers with code to construct radially anisotropic H-κ stacks.","PeriodicalId":21687,"journal":{"name":"Seismological Research Letters","volume":"382 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135689502","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}
Maxime Bès de Berc, Dimitri Zigone, Peter Danecek, Alain Steyer, Francesco Zanolin, Alessia Maggi, Jean-Yves Thoré, Armelle Bernard, Hervé Blumentritt, Sophie Lambotte, Jean-Jacques Lévêque, Luis Rivera, Olivier Alemany, Philippe Possenti, Martin Vallée, Eléonore Stutzmann, Adriano Cavaliere, Nathalie Cotte, Stefano Marino, Baptiste Gombert, Wenceslas Marie-Sainte, Nicolas Leroy, Constanza Pardo, Frédérick Pesqueira, Céleste Broucke
Abstract In the Southern Hemisphere, the prevalence of oceans and the difficulty of access to land result in reduced coverage of seismological stations, limiting our detailed knowledge of Earth’s structures and of large earthquakes sources. This situation is exacerbated inside the antarctic continent, where only two permanent seismic stations are currently available (IU.QSPA at South Pole and G.CCD). The CCD station, built in early 2000s with state-of-the-art surface instrumentation and located at the French–Italian Concordia base (75° S, 123° E), has been providing seismological data since 2008. However, it suffers from several problems: the vault is deformed by the hydrostatic pressure of the snow, the firn waveguide traps anthropogenic noise from the base causing strong noise below 1 s, and a coupling defect limits the performance above 30 s on the horizontal channels. To ensure the continuity of CCD and to improve its overall performance, we started in 2014 to plan the installation of a borehole seismometer at the site. In this article, we describe in detail this renovation of CCD and some examples of data analysis. The new borehole sensor shows that short-period disturbances are largely attenuated (−20 dB at 0.1 s) compared to the surface installation and that the horizontal channels have a lower noise level at long periods (−8 dB at 100 s). Data for all components are below the standard noise model between 0.1 and 0.2 s, which makes this sensor one of the quietest installations in the world for this bandwidth. For periods >600 s we observe atmospheric pressure-related perturbations on the vertical component. Despite this problem, the new CCD borehole station is a success with better-than-expected performances at all periods <600 s. The data produced are now distributed in the world’s data centers as G.CCD.20 and we encourage the scientific community to use the data for all studies requiring seismograms from Antarctica.
{"title":"A New Posthole Seismometer at Concordia Permanent Research Facility in the Heart of the Icy East Antarctic Plateau","authors":"Maxime Bès de Berc, Dimitri Zigone, Peter Danecek, Alain Steyer, Francesco Zanolin, Alessia Maggi, Jean-Yves Thoré, Armelle Bernard, Hervé Blumentritt, Sophie Lambotte, Jean-Jacques Lévêque, Luis Rivera, Olivier Alemany, Philippe Possenti, Martin Vallée, Eléonore Stutzmann, Adriano Cavaliere, Nathalie Cotte, Stefano Marino, Baptiste Gombert, Wenceslas Marie-Sainte, Nicolas Leroy, Constanza Pardo, Frédérick Pesqueira, Céleste Broucke","doi":"10.1785/0220230188","DOIUrl":"https://doi.org/10.1785/0220230188","url":null,"abstract":"Abstract In the Southern Hemisphere, the prevalence of oceans and the difficulty of access to land result in reduced coverage of seismological stations, limiting our detailed knowledge of Earth’s structures and of large earthquakes sources. This situation is exacerbated inside the antarctic continent, where only two permanent seismic stations are currently available (IU.QSPA at South Pole and G.CCD). The CCD station, built in early 2000s with state-of-the-art surface instrumentation and located at the French–Italian Concordia base (75° S, 123° E), has been providing seismological data since 2008. However, it suffers from several problems: the vault is deformed by the hydrostatic pressure of the snow, the firn waveguide traps anthropogenic noise from the base causing strong noise below 1 s, and a coupling defect limits the performance above 30 s on the horizontal channels. To ensure the continuity of CCD and to improve its overall performance, we started in 2014 to plan the installation of a borehole seismometer at the site. In this article, we describe in detail this renovation of CCD and some examples of data analysis. The new borehole sensor shows that short-period disturbances are largely attenuated (−20 dB at 0.1 s) compared to the surface installation and that the horizontal channels have a lower noise level at long periods (−8 dB at 100 s). Data for all components are below the standard noise model between 0.1 and 0.2 s, which makes this sensor one of the quietest installations in the world for this bandwidth. For periods &gt;600 s we observe atmospheric pressure-related perturbations on the vertical component. Despite this problem, the new CCD borehole station is a success with better-than-expected performances at all periods &lt;600 s. The data produced are now distributed in the world’s data centers as G.CCD.20 and we encourage the scientific community to use the data for all studies requiring seismograms from Antarctica.","PeriodicalId":21687,"journal":{"name":"Seismological Research Letters","volume":"222 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135244638","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}
Abstract The epidemic-type aftershock sequence (ETAS) model is the most effective mathematical description of the short-term space–time earthquake clustering. However, the use of such a model is sometimes hampered by the difficulty in estimating the high number of its unknown correlated parameters. Moreover, the most recent ETAS formulations introduce the space–time variability of some parameters that makes their estimation even more arduous. Here, we investigate the model in an opposite perspective, looking for the simplest ETAS parameterization that can satisfactorily describes the earthquake clustering in crustal tectonic regions; we named this model simplETAS. We show that simplETAS calibrated with the Italian seismicity of the last decades adequately describes the space–time occurrence of the out-of-sample largest earthquakes in the instrumental and historical catalog, confirming the validity of the assumptions made to build the model. Owing to its simplicity, simplETAS is easily applicable in most regions, and it has some important properties that are worth being remarked. First, simplETAS can be used as a benchmark model to assess the relative predictive skill of more complex earthquake forecasts. Second, it may be used for operational earthquake forecasting purposes in regions with limited earthquake catalogs. Third, it provides a straightforward, flexible, and effective approach to generate synthetic earthquake catalogs of variable length to be implemented in seismic hazard and risk analysis, overcoming all the declustering-related problems and the controversial Poisson assumption.
{"title":"SimplETAS: A Benchmark Earthquake Forecasting Model Suitable for Operational Purposes and Seismic Hazard Analysis","authors":"Simone Mancini, Warner Marzocchi","doi":"10.1785/0220230199","DOIUrl":"https://doi.org/10.1785/0220230199","url":null,"abstract":"Abstract The epidemic-type aftershock sequence (ETAS) model is the most effective mathematical description of the short-term space–time earthquake clustering. However, the use of such a model is sometimes hampered by the difficulty in estimating the high number of its unknown correlated parameters. Moreover, the most recent ETAS formulations introduce the space–time variability of some parameters that makes their estimation even more arduous. Here, we investigate the model in an opposite perspective, looking for the simplest ETAS parameterization that can satisfactorily describes the earthquake clustering in crustal tectonic regions; we named this model simplETAS. We show that simplETAS calibrated with the Italian seismicity of the last decades adequately describes the space–time occurrence of the out-of-sample largest earthquakes in the instrumental and historical catalog, confirming the validity of the assumptions made to build the model. Owing to its simplicity, simplETAS is easily applicable in most regions, and it has some important properties that are worth being remarked. First, simplETAS can be used as a benchmark model to assess the relative predictive skill of more complex earthquake forecasts. Second, it may be used for operational earthquake forecasting purposes in regions with limited earthquake catalogs. Third, it provides a straightforward, flexible, and effective approach to generate synthetic earthquake catalogs of variable length to be implemented in seismic hazard and risk analysis, overcoming all the declustering-related problems and the controversial Poisson assumption.","PeriodicalId":21687,"journal":{"name":"Seismological Research Letters","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135243243","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}
Gang Liu, Bin Zhao, Rui Xu, Xuejun Qiao, Chengli Liu, Yu Li, Mu Lin, Xinyu Zhao, Zhaosheng Nie, Wei Xiong, Rongxin Fang, Qi Wang
Abstract Impulse motion characterized by a large amplitude in the fault-normal direction can be observed at near-fault strong motion sites during strike-slip earthquakes. The large pulse, which always causes high intensity and stronger damage to structures close to faults, is usually attributed to the directivity effect of rupture propagating along strike and the proximity to the fault. We present an analysis of such a large directivity pulse captured by the near-fault high-rate Global Navigation Satellite System (GNSS) during the 2022 Mw 6.7 Luding, China, earthquake—the largest event ever observed by space geodesy on the seismically active Xianshuihe fault in the eastern Tibetan Plateau. We invert the displacement waveforms and offsets derived from the continuous and campaign GNSS for the rupture kinematics. The inferred slip model reveals a rupture zone of 30 km in length above 15 km depth along the Moxi segment, yielding a seismic moment of 1.1×1019 N·m and a source duration of 13 s. The high-rate GNSS (hrGNSS) waveforms suggest an asymmetric bilateral rupture: most slips with long rise time are concentrated on the southern part of the ruptured fault, whereas a short-duration pulse-like slip rate with low final slip propagates during the northward rupture. We found that the directivity pulse observed by the nearest hrGNSS site is controlled primarily by the sharp pulse-like slip rate and rapid rupture velocity approximating the local S-wave velocity. Along with additional local amplification, this large directivity pulse may be responsible for the heavy damage in Moxi town close to the northern ruptured fault.
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Avinash Nayak, Verónica Rodríguez Tribaldos, Jonathan Ajo-Franklin, Brianna Miranda, Chih-Chieh Chien, Robert Mellors, Michelle Robertson, Matthew Brandin, John Rekoske, Todd Wood, Patrick Dobson, Trenton Cladouhos, Nicholas Madera, Eitan Shmagin, Emily Duran, Suzie Duran
Abstract Distributed acoustic sensing (DAS) technology provides the capability to efficiently acquire dense and continuous seismic data on preexisting, unused fiber-optic cables buried in the ground (dark fiber) that were originally deployed for telecommunication. However, these fiber installations typically use existing “right-of-way corridors” along roadways and railway tracks, leading to piecewise linear or quasi-linear seismic receiver geometries, thereby reducing their utility in seismic studies over a broad areal extent. Short-term and dense arrays of seismometers can be deployed to complement dark fiber DAS arrays, leading to improved seismic receiver coverage over a broader area in the vicinity of the DAS array. This study describes the deployment strategies and procedures, data, and metadata of a contemporaneous and complementary network of three temporary broadband seismic stations and 69 nodal seismometers operated in the vicinity of a 27 km long segment of dark fiber DAS array in the Imperial Valley, Southern California. The study area is a sedimentary basin characterized by intense seismicity and faulting in a transtensional tectonic regime, and hosts multiple producing geothermal fields. The broadband stations used direct-burial sensors with a corner period of 120 s and operated continuously for a year from September 2021 to September 2022. The 5 Hz three-component nodal seismometers acquired continuous data for a month approximately from February to March 2022 over a ∼37 km × ∼24 km area, with an average interstation spacing of ∼3 km. Both the broadband and the nodal stations recorded a wealth of ambient seismic noise and high-quality local earthquake data that can be used in a variety of seismological analyses, including local earthquake detection and location, and body-wave and surface-wave tomography.
分布式声传感(DAS)技术提供了有效获取密集连续地震数据的能力，这些数据来自预先存在的、未使用的埋在地下的光缆(暗光纤)，这些光缆最初是为电信而部署的。然而，这些光纤装置通常沿着公路和铁路轨道使用现有的“路权走廊”，导致分段线性或准线性地震接收器几何形状，从而降低了它们在大范围地震研究中的效用。短期和密集的地震仪阵列可以用来补充暗光纤DAS阵列，从而提高DAS阵列附近更广泛区域的地震接收器覆盖范围。本研究描述了在南加州帝国谷27公里长的暗光纤DAS阵列附近运行的三个临时宽带地震站和69个节点地震仪的同步和互补网络的部署策略和程序、数据和元数据。研究区是一个地震活动性强、断陷性强的张拉构造沉积盆地，区内有多处产地热田。宽带站采用直埋式传感器，转角周期为120s，从2021年9月至2022年9月连续运行一年。从2022年2月到3月，5hz三分量节点地震仪在~ 37 km × ~ 24 km的区域内获得了大约一个月的连续数据，平均站间距为~ 3 km。宽带和节点站都记录了大量的环境地震噪声和高质量的当地地震数据，这些数据可用于各种地震学分析，包括当地地震探测和定位，以及体波和面波断层扫描。
{"title":"Nodal and Broadband Seismometer Complement to the Imperial Valley Dark Fiber DAS Array","authors":"Avinash Nayak, Verónica Rodríguez Tribaldos, Jonathan Ajo-Franklin, Brianna Miranda, Chih-Chieh Chien, Robert Mellors, Michelle Robertson, Matthew Brandin, John Rekoske, Todd Wood, Patrick Dobson, Trenton Cladouhos, Nicholas Madera, Eitan Shmagin, Emily Duran, Suzie Duran","doi":"10.1785/0220230081","DOIUrl":"https://doi.org/10.1785/0220230081","url":null,"abstract":"Abstract Distributed acoustic sensing (DAS) technology provides the capability to efficiently acquire dense and continuous seismic data on preexisting, unused fiber-optic cables buried in the ground (dark fiber) that were originally deployed for telecommunication. However, these fiber installations typically use existing “right-of-way corridors” along roadways and railway tracks, leading to piecewise linear or quasi-linear seismic receiver geometries, thereby reducing their utility in seismic studies over a broad areal extent. Short-term and dense arrays of seismometers can be deployed to complement dark fiber DAS arrays, leading to improved seismic receiver coverage over a broader area in the vicinity of the DAS array. This study describes the deployment strategies and procedures, data, and metadata of a contemporaneous and complementary network of three temporary broadband seismic stations and 69 nodal seismometers operated in the vicinity of a 27 km long segment of dark fiber DAS array in the Imperial Valley, Southern California. The study area is a sedimentary basin characterized by intense seismicity and faulting in a transtensional tectonic regime, and hosts multiple producing geothermal fields. The broadband stations used direct-burial sensors with a corner period of 120 s and operated continuously for a year from September 2021 to September 2022. The 5 Hz three-component nodal seismometers acquired continuous data for a month approximately from February to March 2022 over a ∼37 km × ∼24 km area, with an average interstation spacing of ∼3 km. Both the broadband and the nodal stations recorded a wealth of ambient seismic noise and high-quality local earthquake data that can be used in a variety of seismological analyses, including local earthquake detection and location, and body-wave and surface-wave tomography.","PeriodicalId":21687,"journal":{"name":"Seismological Research Letters","volume":"2016 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135387382","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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