The success of seismometer installations on the ocean floor, polar regions, remote continental areas, and even other planets’ surfaces has sparked renewed interest in determining the location via the azimuthal direction of a seismic event recorded by a single station, also known as the back azimuth (BAZ). However, classical algorithms for the BAZ estimate, like principal component and polarization analyses based on P-wave particle motions, are prone to ambiguities of 180°. Motivated by the sensor orientation correction techniques used for ocean-bottom seismometers and land stations for known event locations, we explore a receiver function rotation (RFR) method to determine the BAZ for events recorded by a single station. It is a parameter search over a range of horizontal component rotation angles from 0° to 360°. The fundamental feature of the method is that the direct P wave in the radial receiver function (RF) will have the maximum amplitude when the rotation from the ZNE system (vertical, north–south, and east–west) to ZRT (vertical, radial, and tangential) is aligned with the BAZ of the incoming P wave. Hence, the largest amplitude at zero time of the ensemble of RFs computed for different horizontal component rotations shows the optimal BAZ, which is consequently free of the 180° ambiguities. The technique’s performance is validated using the well-documented location of the 2017 Democratic People’s Republic of Korea nuclear explosion and over 1200 cataloged earthquakes on the two permanent stations in Australia. We further benchmark the RFR algorithm by the locations of two ground-truth Martian impact events documented by the orbital camera and recorded by InSight’s seismometer. Our method helps enhance the reliability of BAZ estimation as a complementary scheme to other methods. It can be used in remote areas on Earth and on the future missions to the Moon and other planets.
{"title":"Single-Station Back-Azimuth Determination with the Receiver Function Rotation Technique Validated by the Locations of Earthquakes, Impacts, and Explosions","authors":"Weijia Sun, H. Tkalčić, Qingya Tang","doi":"10.1785/0220240117","DOIUrl":"https://doi.org/10.1785/0220240117","url":null,"abstract":"\u0000 The success of seismometer installations on the ocean floor, polar regions, remote continental areas, and even other planets’ surfaces has sparked renewed interest in determining the location via the azimuthal direction of a seismic event recorded by a single station, also known as the back azimuth (BAZ). However, classical algorithms for the BAZ estimate, like principal component and polarization analyses based on P-wave particle motions, are prone to ambiguities of 180°. Motivated by the sensor orientation correction techniques used for ocean-bottom seismometers and land stations for known event locations, we explore a receiver function rotation (RFR) method to determine the BAZ for events recorded by a single station. It is a parameter search over a range of horizontal component rotation angles from 0° to 360°. The fundamental feature of the method is that the direct P wave in the radial receiver function (RF) will have the maximum amplitude when the rotation from the ZNE system (vertical, north–south, and east–west) to ZRT (vertical, radial, and tangential) is aligned with the BAZ of the incoming P wave. Hence, the largest amplitude at zero time of the ensemble of RFs computed for different horizontal component rotations shows the optimal BAZ, which is consequently free of the 180° ambiguities. The technique’s performance is validated using the well-documented location of the 2017 Democratic People’s Republic of Korea nuclear explosion and over 1200 cataloged earthquakes on the two permanent stations in Australia. We further benchmark the RFR algorithm by the locations of two ground-truth Martian impact events documented by the orbital camera and recorded by InSight’s seismometer. Our method helps enhance the reliability of BAZ estimation as a complementary scheme to other methods. It can be used in remote areas on Earth and on the future missions to the Moon and other planets.","PeriodicalId":21687,"journal":{"name":"Seismological Research Letters","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141366106","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}
A. Ardid, D. Dempsey, Josh Corry, Owen Garrett, Oliver D. Lamb, S. Cronin
Volcanic eruptions pose significant risks, demanding precise monitoring for timely hazard mitigation. However, interpreting noisy seismic data for eruptive precursors remains challenging. This study introduces a novel methodology that extends an earlier time-series feature engineering approach to include template matching against prior eruptions. We aim to identify subtle signals within seismic data to enhance our understanding of volcanic activity and future hazards. To do this, we analyze the continuous seismic record at a volcano and identify the time-series elements that regularly precede eruptions and the timescales over which these are observable. We conduct tests across various time lengths, ranging from 1 to 60 days. For Copahue (Chile/Argentina), Pavlof (Alaska), Bezymianny (Russia), and Whakaari (New Zealand) volcanoes, we confirm statistically significant eruption precursors. In particular, a feature named change quantiles (0.2–0.8), which is related to the conditional dynamics of surface acceleration at the volcano, emerges as a key indicator of future eruptions over 14-day timescales. This research offers new methods for real-time seismovolcanic monitoring, minimizing the effects of unknown, spurious noise, and discerning recurrent patterns through template matching. By providing deeper insights into pre-eruptive behavior, it may lead to more effective hazard reduction strategies, enhancing public safety around active volcanoes.
{"title":"Multitimescale Template Matching: Discovering Eruption Precursors across Diverse Volcanic Settings","authors":"A. Ardid, D. Dempsey, Josh Corry, Owen Garrett, Oliver D. Lamb, S. Cronin","doi":"10.1785/0220240012","DOIUrl":"https://doi.org/10.1785/0220240012","url":null,"abstract":"\u0000 Volcanic eruptions pose significant risks, demanding precise monitoring for timely hazard mitigation. However, interpreting noisy seismic data for eruptive precursors remains challenging. This study introduces a novel methodology that extends an earlier time-series feature engineering approach to include template matching against prior eruptions. We aim to identify subtle signals within seismic data to enhance our understanding of volcanic activity and future hazards. To do this, we analyze the continuous seismic record at a volcano and identify the time-series elements that regularly precede eruptions and the timescales over which these are observable. We conduct tests across various time lengths, ranging from 1 to 60 days. For Copahue (Chile/Argentina), Pavlof (Alaska), Bezymianny (Russia), and Whakaari (New Zealand) volcanoes, we confirm statistically significant eruption precursors. In particular, a feature named change quantiles (0.2–0.8), which is related to the conditional dynamics of surface acceleration at the volcano, emerges as a key indicator of future eruptions over 14-day timescales. This research offers new methods for real-time seismovolcanic monitoring, minimizing the effects of unknown, spurious noise, and discerning recurrent patterns through template matching. By providing deeper insights into pre-eruptive behavior, it may lead to more effective hazard reduction strategies, enhancing public safety around active volcanoes.","PeriodicalId":21687,"journal":{"name":"Seismological Research Letters","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141364890","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}
{"title":"The Magnificent Partnership of Yan Kagan and Dave Jackson","authors":"Frederic Schoenberg","doi":"10.1785/0220240188","DOIUrl":"https://doi.org/10.1785/0220240188","url":null,"abstract":"","PeriodicalId":21687,"journal":{"name":"Seismological Research Letters","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141379647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In Summer–Fall 2022, 80 three-component SmartSolo IGU-BD3C-5 nodal seismometers were deployed surrounding the Pāhala seismic swarm on the Island of Hawai‘i, with the goal of improving seismicity catalogs and seismic velocity images of the crust and upper mantle in this region. The Pāhala swarm, located south of Mauna Loa and Kīlauea, has been the site of a multiyear sustained swarm of seismicity at the depths of ∼25–40 km, with order of magnitude increases in rate in 2015, and then again in 2019. This seismicity is possibly related to the input of magma from the mantle plume below, which may then be subsequently transported to volcanic edifices. However, these processes remain enigmatic, in part due to a lack of precise earthquake locations and seismic velocity models in this region. Here, we provide an overview of the deployment, an assessment of the quality of the collected data, and discuss the viability of the data set for local earthquake relocation, tomography, and teleseismic receiver functions. Through comparisons with proximal permanent broadband and short-period instruments, we find that the nodes produce high-quality data, particularly at periods shorter than 5 s, although we find, document, and correct discrepancies with the gain and polarities of the instruments. We successfully record signals from teleseismic earthquakes, even at periods longer than 5 s (the corner of the flat response of the nodes). We also record local earthquakes, including details related to source characteristics. This indicates that the data are likely to prove useful for investigations using both local and teleseismic earthquake signals to better understand the connections between the deep and shallow magmatic systems of Hawai‘i. Although this deployment provides a snapshot in time, its success may provide a useful benchmark for future studies as the volcanic systems of Hawai‘i continue to evolve in the future.
{"title":"A Seismic Nodal Deployment to Understand Magmatic Structure in the Vicinity of the Pāhala Earthquake Swarm","authors":"Helen Janiszewski, N. Bennington, Jade Wight","doi":"10.1785/0220240060","DOIUrl":"https://doi.org/10.1785/0220240060","url":null,"abstract":"\u0000 In Summer–Fall 2022, 80 three-component SmartSolo IGU-BD3C-5 nodal seismometers were deployed surrounding the Pāhala seismic swarm on the Island of Hawai‘i, with the goal of improving seismicity catalogs and seismic velocity images of the crust and upper mantle in this region. The Pāhala swarm, located south of Mauna Loa and Kīlauea, has been the site of a multiyear sustained swarm of seismicity at the depths of ∼25–40 km, with order of magnitude increases in rate in 2015, and then again in 2019. This seismicity is possibly related to the input of magma from the mantle plume below, which may then be subsequently transported to volcanic edifices. However, these processes remain enigmatic, in part due to a lack of precise earthquake locations and seismic velocity models in this region. Here, we provide an overview of the deployment, an assessment of the quality of the collected data, and discuss the viability of the data set for local earthquake relocation, tomography, and teleseismic receiver functions. Through comparisons with proximal permanent broadband and short-period instruments, we find that the nodes produce high-quality data, particularly at periods shorter than 5 s, although we find, document, and correct discrepancies with the gain and polarities of the instruments. We successfully record signals from teleseismic earthquakes, even at periods longer than 5 s (the corner of the flat response of the nodes). We also record local earthquakes, including details related to source characteristics. This indicates that the data are likely to prove useful for investigations using both local and teleseismic earthquake signals to better understand the connections between the deep and shallow magmatic systems of Hawai‘i. Although this deployment provides a snapshot in time, its success may provide a useful benchmark for future studies as the volcanic systems of Hawai‘i continue to evolve in the future.","PeriodicalId":21687,"journal":{"name":"Seismological Research Letters","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141270141","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}
Deciphering a comprehensive 3D fault model for the regions with moderate-to-strong earthquakes is crucial for understanding earthquake triggering mechanisms and assessing future seismic hazards. On 21 May 2021, a massive Ms 6.4 earthquake occurred in Yangbi, Dali City, China, near the northern Red River fault zone. Despite numerous studies conducted over the past two years, the seismogenic fault of this earthquake remains a topic of controversy. In this article, we refine the workflow for 3D construction of fault surfaces from Riesner et al. (2017) and used it for the Yangbi earthquake. We constructed a seismogenic fault model for the Yangbi earthquake and Caoping fault from the collected multisource data. One utilizes a combination of focal mechanisms and relocated hypocenters, whereas the other combines geological and geophysical data from the study area. Upon analyzing these two fault models and the relocated hypocenter data, we propose that the seismogenic fault in the Yangbi earthquake is an undiscovered blind fault or a secondary blind fault of the Weixi–Qiaohou fault, rather than the surface-emerging Caoping fault.
{"title":"Seismogenic Fault Model for the 2021 Ms 6.4 Yangbi, China, Earthquake, Constraints from Multisource Data","authors":"Lianwen Wu, Zhigang Li, Chuang Sun, Xiangming Dai, Xiancan Wu, Fanchang Zeng, Liangwei Lv, Weiwang Long, Zhiyi Su","doi":"10.1785/0220230412","DOIUrl":"https://doi.org/10.1785/0220230412","url":null,"abstract":"\u0000 Deciphering a comprehensive 3D fault model for the regions with moderate-to-strong earthquakes is crucial for understanding earthquake triggering mechanisms and assessing future seismic hazards. On 21 May 2021, a massive Ms 6.4 earthquake occurred in Yangbi, Dali City, China, near the northern Red River fault zone. Despite numerous studies conducted over the past two years, the seismogenic fault of this earthquake remains a topic of controversy. In this article, we refine the workflow for 3D construction of fault surfaces from Riesner et al. (2017) and used it for the Yangbi earthquake. We constructed a seismogenic fault model for the Yangbi earthquake and Caoping fault from the collected multisource data. One utilizes a combination of focal mechanisms and relocated hypocenters, whereas the other combines geological and geophysical data from the study area. Upon analyzing these two fault models and the relocated hypocenter data, we propose that the seismogenic fault in the Yangbi earthquake is an undiscovered blind fault or a secondary blind fault of the Weixi–Qiaohou fault, rather than the surface-emerging Caoping fault.","PeriodicalId":21687,"journal":{"name":"Seismological Research Letters","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141270326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In response to the gaps in understanding the causal relationship between seismic waveform features and the types of seismic events, this research is focused on seismic events of low magnitude (ML≤3.0) in the North China region. Using the Bayesian network theory, we conduct an analysis to infer event types for natural earthquakes, artificial explosions, and mining collapses, and the outcomes achieved notable efficacy for the discrimination of seismic events. Through the analysis of seismic waveforms from 1818 events, we systematically extracted and quantified 55 features in temporal, spectral, and energy domains, which were then recoded as node variables for subsequent analysis. The new data set was subject to select nodes with strong associations to the node type. Subsequently, Bayesian network topologies were constructed using three different algorithms to reconstruct the custom network, calculating posterior probabilities and marginal probabilities. Simultaneously, an extensive evaluation with precision–recall curves of the network structure was carried out, encompassing accuracy, precision, recall, and F1-score. Ultimately, sensitivity analysis was performed on each node to reveal the extent of the influence of node variations on the inference of the node type. The findings showed that the sensitivity of discrimination of seismic events was notably high for several features, including high-frequency P/S spectral ratio values (11 to ∼20 Hz), central frequency, dominant frequency, average frequency, rise and decay average frequency, the real part of the complex cepstral coefficients, peak ground acceleration, and zero crossing. In the classification of natural earthquakes, artificial explosions, and mining collapses, it was observed that the probability of mining collapses was maximized when peak ground acceleration was less than 1526.08, and concurrently, the P/S spectral ratio (11 to ∼20 Hz) fell within the range of −0.25 to −0.02.
{"title":"Bayesian Network Inference for Low-Magnitude Nonnatural Seismic Event Discrimination","authors":"Xueyan Li, Xiaolin Hou, Yinju Bian, Tingting Wang, Mengyi Ren, Yixiao Zhang, Wenjing Wang","doi":"10.1785/0220230403","DOIUrl":"https://doi.org/10.1785/0220230403","url":null,"abstract":"\u0000 In response to the gaps in understanding the causal relationship between seismic waveform features and the types of seismic events, this research is focused on seismic events of low magnitude (ML≤3.0) in the North China region. Using the Bayesian network theory, we conduct an analysis to infer event types for natural earthquakes, artificial explosions, and mining collapses, and the outcomes achieved notable efficacy for the discrimination of seismic events. Through the analysis of seismic waveforms from 1818 events, we systematically extracted and quantified 55 features in temporal, spectral, and energy domains, which were then recoded as node variables for subsequent analysis. The new data set was subject to select nodes with strong associations to the node type. Subsequently, Bayesian network topologies were constructed using three different algorithms to reconstruct the custom network, calculating posterior probabilities and marginal probabilities. Simultaneously, an extensive evaluation with precision–recall curves of the network structure was carried out, encompassing accuracy, precision, recall, and F1-score. Ultimately, sensitivity analysis was performed on each node to reveal the extent of the influence of node variations on the inference of the node type. The findings showed that the sensitivity of discrimination of seismic events was notably high for several features, including high-frequency P/S spectral ratio values (11 to ∼20 Hz), central frequency, dominant frequency, average frequency, rise and decay average frequency, the real part of the complex cepstral coefficients, peak ground acceleration, and zero crossing. In the classification of natural earthquakes, artificial explosions, and mining collapses, it was observed that the probability of mining collapses was maximized when peak ground acceleration was less than 1526.08, and concurrently, the P/S spectral ratio (11 to ∼20 Hz) fell within the range of −0.25 to −0.02.","PeriodicalId":21687,"journal":{"name":"Seismological Research Letters","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141268965","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}
Maren Böse, S. Ceylan, Jen Andrews, F. Massin, John Clinton, J. Saunders, Orhan Tatar, Meltem Türkoğlu
In the immediate aftermath of devastating earthquakes such as in the 6 February 2023 Kahramanmaraş sequence in southcentral Türkiye, key stakeholders and the public demand timely and accurate earthquake information. Especially for large events, finite-fault models provide important insights into the rupture process and enable interpretation of the observed ground shaking, which can improve situational awareness and facilitate rapid assessment of future hazards. Using strong-motion waveforms recorded during the Kahramanmaraş sequence, we simulate a real-time playback and calculate how a finite-source model computed with the Finite-fault rupture Detector (FinDer) algorithm would evolve for the Mw 7.8 Pazarcık, Mw 7.6 Elbistan, and Mw 6.4 Yayladağı earthquakes. Using template matching FinDer compares observed and predicted ground-motion acceleration amplitudes to determine the orientation and spatial extent of fault rupture. We test both generic crustal and fault-specific templates from ground-motion models and rupture geometries of the east Anatolian and Çardak–Sürgü faults. In the second step, we estimate the seismic slip along the source models from the backprojection of the seismic displacement amplitudes. The algorithms achieve excellent performance for all three earthquakes, and the final source models and slip profiles available within tens of seconds of the rupture nucleation match well with models computed days to weeks after the events occurred. The temporal evolution of the source models for the Pazarcık and Elbistan earthquakes suggests that FinDer can provide insight into the rupture kinematics of large earthquakes. Cascading instrument failures as well as power and data telemetry interruptions during the Pazarcık earthquake led to an early termination of signals at a significant number of near-source stations. We show that FinDer is robust enough to cope with this type of degradation in network performance that can occur in large earthquakes, in general.
{"title":"Rapid Finite-Fault Models for the 2023 Mw 7.8 Kahramanmaraş, Türkiye, Earthquake Sequence","authors":"Maren Böse, S. Ceylan, Jen Andrews, F. Massin, John Clinton, J. Saunders, Orhan Tatar, Meltem Türkoğlu","doi":"10.1785/0220230426","DOIUrl":"https://doi.org/10.1785/0220230426","url":null,"abstract":"\u0000 In the immediate aftermath of devastating earthquakes such as in the 6 February 2023 Kahramanmaraş sequence in southcentral Türkiye, key stakeholders and the public demand timely and accurate earthquake information. Especially for large events, finite-fault models provide important insights into the rupture process and enable interpretation of the observed ground shaking, which can improve situational awareness and facilitate rapid assessment of future hazards. Using strong-motion waveforms recorded during the Kahramanmaraş sequence, we simulate a real-time playback and calculate how a finite-source model computed with the Finite-fault rupture Detector (FinDer) algorithm would evolve for the Mw 7.8 Pazarcık, Mw 7.6 Elbistan, and Mw 6.4 Yayladağı earthquakes. Using template matching FinDer compares observed and predicted ground-motion acceleration amplitudes to determine the orientation and spatial extent of fault rupture. We test both generic crustal and fault-specific templates from ground-motion models and rupture geometries of the east Anatolian and Çardak–Sürgü faults. In the second step, we estimate the seismic slip along the source models from the backprojection of the seismic displacement amplitudes. The algorithms achieve excellent performance for all three earthquakes, and the final source models and slip profiles available within tens of seconds of the rupture nucleation match well with models computed days to weeks after the events occurred. The temporal evolution of the source models for the Pazarcık and Elbistan earthquakes suggests that FinDer can provide insight into the rupture kinematics of large earthquakes. Cascading instrument failures as well as power and data telemetry interruptions during the Pazarcık earthquake led to an early termination of signals at a significant number of near-source stations. We show that FinDer is robust enough to cope with this type of degradation in network performance that can occur in large earthquakes, in general.","PeriodicalId":21687,"journal":{"name":"Seismological Research Letters","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141112296","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}
Ling Zhang, An Li, Xiaoping Yang, Weiliang Huang, Shengqiang Li, Haibo Yang
Bending-moment faults (BMFs), as a fundamental type of secondary faulting, are intrinsically linked to the primary causative faults within active thrust-fold belts. When these faults thrust through the ground surface, the resulting geomorphic scarps offer the characteristics of local earthquake recurrence. This information helps to fill a gap left by main faults, which often lack coseismic surface ruptures. The Qiulitage anticline where the 1949 M 7¼ Kuqa earthquake occurred is an active thrust-and-fold belt predominantly governed by blind faults. In addition, several typical BMFs extensively crop out as surface scarps in the front of the mountain. Our research concentrates on the well-developed BMF scarps in this region and seeks to explore the recurrence characteristics of paleoearthquakes, which remain inadequately comprehended. Our study reveals that (1) secondary BMF with high enough magnitude can directly generate coseismic ground ruptures, and (2) the seismic behavior of BMFs exhibits a degree of repeatability, potentially linked to the concurrent movement of various BMFs or the solitary action of a single fault. However, the case study presented in this article also highlights the limitation of fold earthquake research because of the swift attenuation of coseismic fault slip as it approaches the ground surface.
{"title":"Multiple Fold Earthquakes Recorded by the Paleoseismic Surface Ruptures of Bending-Moment Faults in the Qiulitage Anticline, South Tianshan, China","authors":"Ling Zhang, An Li, Xiaoping Yang, Weiliang Huang, Shengqiang Li, Haibo Yang","doi":"10.1785/0220230388","DOIUrl":"https://doi.org/10.1785/0220230388","url":null,"abstract":"\u0000 Bending-moment faults (BMFs), as a fundamental type of secondary faulting, are intrinsically linked to the primary causative faults within active thrust-fold belts. When these faults thrust through the ground surface, the resulting geomorphic scarps offer the characteristics of local earthquake recurrence. This information helps to fill a gap left by main faults, which often lack coseismic surface ruptures. The Qiulitage anticline where the 1949 M 7¼ Kuqa earthquake occurred is an active thrust-and-fold belt predominantly governed by blind faults. In addition, several typical BMFs extensively crop out as surface scarps in the front of the mountain. Our research concentrates on the well-developed BMF scarps in this region and seeks to explore the recurrence characteristics of paleoearthquakes, which remain inadequately comprehended. Our study reveals that (1) secondary BMF with high enough magnitude can directly generate coseismic ground ruptures, and (2) the seismic behavior of BMFs exhibits a degree of repeatability, potentially linked to the concurrent movement of various BMFs or the solitary action of a single fault. However, the case study presented in this article also highlights the limitation of fold earthquake research because of the swift attenuation of coseismic fault slip as it approaches the ground surface.","PeriodicalId":21687,"journal":{"name":"Seismological Research Letters","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141109841","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}
Xuelin Qiu, Sanyu Ye, Zizheng Li, Haoyu Zhang, Enyuan He, Sun Wang
Accurate positions of ocean-bottom seismometers (OBSs) on the seafloor are critical parameters and can only be obtained by inversion modeling of first-arrival travel times of overhead cross-line airgun shootings. With an increased sampling interval of ≤20 ms for long-term earthquake studies, apparent artifacts affect the phase alignment of first arrivals on the seismic sections of trace-cut airgun shots. Our analysis shows that these apparent misalignments are caused by timing inconsistencies and inaccuracies during the trace-cut, which are so-called rounding errors. To eliminate these rounding errors, a simple interpolation is used to resample traces. Further analysis shows the simple interpolation satisfactorily retains the original waveform. The improved timing accuracy significantly reduces the uncertainty of seafloor locations as shown by Hadal OBS data.
{"title":"Accurate Trace-Cut and Phase Alignment of Active Ocean-Bottom Seismometer Data","authors":"Xuelin Qiu, Sanyu Ye, Zizheng Li, Haoyu Zhang, Enyuan He, Sun Wang","doi":"10.1785/0220240059","DOIUrl":"https://doi.org/10.1785/0220240059","url":null,"abstract":"\u0000 Accurate positions of ocean-bottom seismometers (OBSs) on the seafloor are critical parameters and can only be obtained by inversion modeling of first-arrival travel times of overhead cross-line airgun shootings. With an increased sampling interval of ≤20 ms for long-term earthquake studies, apparent artifacts affect the phase alignment of first arrivals on the seismic sections of trace-cut airgun shots. Our analysis shows that these apparent misalignments are caused by timing inconsistencies and inaccuracies during the trace-cut, which are so-called rounding errors. To eliminate these rounding errors, a simple interpolation is used to resample traces. Further analysis shows the simple interpolation satisfactorily retains the original waveform. The improved timing accuracy significantly reduces the uncertainty of seafloor locations as shown by Hadal OBS data.","PeriodicalId":21687,"journal":{"name":"Seismological Research Letters","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141110140","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}
Conventional earthquake early warning systems (EEWS) rely on mathematical functions that utilize P-wave parameters extracted over a 3 s window to estimate peak ground acceleration (PGA). Advancements in the capabilities of deep neural networks to approximate universal functions, coupled with the availability of strong seismic event data, offer an unprecedented opportunity to evaluate the relationship between variable snapshots of P-wave data and the PGA of strong-motion earthquakes. This convergence of technology and data opens new avenues for research into utilizing smaller snapshots of P-wave in EEWS. Our study centers on the utilization of a long short-term memory (LSTM) neural network to model long dependencies within the P-wave of 1839 earthquakes recorded by the Kiyonshin Network (K-NET) for the prediction of PGA of S waves. Our methodology involves experiments that ultimately evaluate the network’s performance on 4, 3, and 2 s of P-wave snapshots. Our findings indicate that there is sufficient information in 2 s of temporal accelerometer readings after the onset of P waves to predict PGA accurately with an LSTM network.
传统的地震预警系统（EEWS）依赖于数学函数，这些函数利用在 3 秒窗口内提取的 P 波参数来估算峰值地面加速度（PGA）。深度神经网络近似通用函数的能力不断进步，加上强震事件数据的可用性，为评估 P 波数据的可变快照与强震的峰值地面加速度之间的关系提供了前所未有的机会。这种技术和数据的融合为研究在 EEWS 中利用较小的 P 波快照开辟了新的途径。我们的研究重点是利用长短期记忆（LSTM）神经网络对 Kiyonshin 网络（K-NET）记录的 1839 次地震的 P 波内的长依赖关系进行建模，以预测 S 波的 PGA。我们的方法包括通过实验最终评估网络在 4 秒、3 秒和 2 秒 P 波快照上的性能。我们的研究结果表明，在 P 波发生后 2 秒钟的时间加速度计读数中有足够的信息，可以通过 LSTM 网络准确预测 PGA。
{"title":"Predicting Peak Ground Acceleration of Strong-Motion Earthquakes Using Variable Snapshots of P-Wave Data with Long Short-Term Memory Neural Network","authors":"John Owusu Duah, Ofosu Osei, Stephen Osafo-Gyamfi","doi":"10.1785/0220230427","DOIUrl":"https://doi.org/10.1785/0220230427","url":null,"abstract":"\u0000 Conventional earthquake early warning systems (EEWS) rely on mathematical functions that utilize P-wave parameters extracted over a 3 s window to estimate peak ground acceleration (PGA). Advancements in the capabilities of deep neural networks to approximate universal functions, coupled with the availability of strong seismic event data, offer an unprecedented opportunity to evaluate the relationship between variable snapshots of P-wave data and the PGA of strong-motion earthquakes. This convergence of technology and data opens new avenues for research into utilizing smaller snapshots of P-wave in EEWS. Our study centers on the utilization of a long short-term memory (LSTM) neural network to model long dependencies within the P-wave of 1839 earthquakes recorded by the Kiyonshin Network (K-NET) for the prediction of PGA of S waves. Our methodology involves experiments that ultimately evaluate the network’s performance on 4, 3, and 2 s of P-wave snapshots. Our findings indicate that there is sufficient information in 2 s of temporal accelerometer readings after the onset of P waves to predict PGA accurately with an LSTM network.","PeriodicalId":21687,"journal":{"name":"Seismological Research Letters","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141119419","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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