Taiwan Earthquake Research Articles

Influence of velocity pulse directivity on seismic response of cross-fault bridges

Pulse-type ground motions have special destructive effects on structures, and directivity is one of the fundamental characteristics of velocity pulses. In this paper, the impact of the velocity pulse directivity of seismic motions on both sides of the fault on the seismic response of fault-crossing bridges was quantified using the original records from the Chi-Chi earthquake in Taiwan. First, an automatic baseline correction method was applied to restore the permanent ground displacement, and the direction corresponding to the strongest pulse energy on both sides of the fault was identified based on continuous wavelet transformation. On this basis, the variability of the peak intensity of ground motions on the hanging wall and footwall in different directions, as well as the differences in pulse characteristics between the strongest pulse component and the two initial horizontal components, were analysed. Finally, a typical 5 × 30 m continuous girder bridge was considered as the research object to reveal the influence of the velocity pulse directivity on the seismic response of key parts on both sides of the fault. The results showed that the variability in the peak ground-motion intensity on the hanging wall of the fault was higher than that on the footwall. The displacement variability was up to 863 %, velocity was 262 %, and acceleration was 124 %. The pulse characteristics of the strongest pulse component were stronger than those of the parallel and vertical fault components, and its acceleration, velocity, and displacement response spectra were larger. The amplification effects of the velocity pulse directivity on the transverse bending moment, longitudinal bending moment, and torque of the pier bottom reached 1.3, 1.1, and 1.6, respectively. However, the amplification effect of the velocity pulse directivity on the relative displacement of the pier top, displacement of the main beam, and displacement of the bearing was more than 1.6 times, which was more significant than the internal force of the pier bottom.

Integration of multiple observations for validation of mechanisms of earthquake-triggered groundwater level Anomalies: 2016 Taiwan Meinong earthquake

This study analyzes multi-depth groundwater level data and integrated observation data to validate the previously proposed mechanisms of hydrological anomalies triggered by the 2016 M6.4 Meinong earthquake in Taiwan. The main influence area was northwest of the epicenter, which may be due to the blind fault rupture, intensity distribution, and hydrogeological properties. The step changes in groundwater level do not fit the concept of epicentral distance, static stress–strain theory, or the focal mechanism. The distribution of step changes in groundwater level have a pattern similar to that of horizontal peak ground velocity. The results imply that these changes may be driven by dynamic stress–strain, instead of static stress–strain. The minimum horizontal peak ground velocity and acceleration of the Meinong earthquake, which induced obvious step changes in groundwater level and soil liquefaction, are provided. The pressure dissipation ability of an aquifer (e.g., transmissivity) may affect the persistence of groundwater responses. Four wells located near the surface rupture area, which has cemented or partial cemented geological material, showed an obvious step decrease in the groundwater level at a deep depth and all wells showed an increase in the groundwater level at a shallow depth. These decreases and increases of the groundwater level at different depths have different mechanisms, which are discussed in this study. The integrated observations made during the Meinong earthquake show that ground motion and the hydraulic properties might be important factors in hydrological anomalies. The results of this study are an important reference for further studies on earthquake hydrology.

Very‐Near‐Field Coseismic Fault Pressure Drop and Delayed Postseismic Cross‐Fault Flow Induced by Fault Damage From the 2018 M6.3 Hualien, Taiwan Earthquake

AbstractEarthquakes can produce rock damage, poroelastic deformation, and ground shaking that modify fault zone hydrogeologic properties. Coseismic and postseismic hydrologic response to the ruptured fault can serve as constraints on hydrogeologic property changes. Here, we document fluid pressure responses to the 2018 M6.3 Hualien, Taiwan earthquake and model the postseismic fault zone hydrology inferred from very‐near‐fault data. Two groundwater wells located ∼180–250 m from the fault damage zone experienced 10–15 m of groundwater level decline followed by a prolonged (>6 months) recovery. Poroelastic models indicate that strain dilation in the fault's hanging wall can produce water level reductions of several meters. However, the model cannot explain groundwater level change in the footwall nor the delayed postseismic recovery, suggesting fault zone damage played a primary role in both the coseismic and postseismic water level reductions. Fluid flow models incorporating the effects of coseismic fault damage on the temporal evolution of hydrologic fault properties show enhanced hydraulic anisotropy after the earthquake. The best‐fit models show that while both vertical hydraulic conductivity and specific storage likely increased within the fault zone, the horizontal hydraulic conductivity is low, suggesting the fault zone behaves as a hydraulic barrier to cross‐fault flow with modeled diffusivities as low as ∼10−3 m2/s. High‐fidelity hydrologic measurements in the very‐near‐field of fault zones (e.g., within a few hundred meters) may be a useful tool to constrain the spatial and temporal evolution of fault zone properties before, during, and after rupture.

Spatial–temporal variations of b-values prior to medium-to-large earthquakes in Taiwan and the feasibility of real-time precursor monitoring

This study explores the b-value variations prior to M ≥ 6.0 earthquakes in Taiwan, examining their potential as earthquake precursors. Focusing on the 2018 Hualien earthquake and others between 1999 and 2021, we found that many large earthquakes occurred in areas with low b-values a year prior, although there were no significant temporal changes near the epicenters. However, for more accurate earthquake precursors, incorporating additional factors is recommended to minimize uncertainty.Graphical

Increase in short-term and long-term stress-associated mental illness after Jiji earthquake in Taiwan: A twenty-year longitudinal population-based cohort study (1999–2019)

BackgroundEarthquakes have caused profound physical and mental health impacts in human history. The Jiji earthquake, which had a magnitude of 7.6 on the Richter scale, occurred on 21 September 1999 in Taiwan. A close follow-up on the mental health status of affected adults after major natural disasters to construct the short-term and long-term risk and prevalence of stress-associated mental illnesses has not been performed by using the nationwide health databases. MethodsThis population-based cohort study included 468,804 adults affected by Jiji earthquake spanning from 2000 to 2019 who were matched at a 1:4 ratio with unaffected individuals based on age and sex (n = 1,875,216). Employing a subdistribution hazard regression analysis, we assessed the incidence of sleep, anxiety, and depressive disorders after Jiji earthquake. Corrections for multiple comparisons were carried out using the Benjamini–Hochberg procedure. ResultsAffected adults experienced an increased incidence of short-term (approximately twice) stress-associated psychiatric disorders. The risk of the post-traumatic stress disorder (PTSD) is significantly higher in the affected adults (40–64 years: aSHR: 92.0; ≥65 years: aSHR: 96.7, p < 0.0001). Middle-aged (aged 40–64 years) male adults presented with significantly more short-term (< one year) and long-term (up to 20 years) stress-related mental illnesses, i.e., insomnia, anxiety, and depressive disorders, than individuals in the control group. ConclusionsAn earthquake has significant short and long-term effects on sleep quality, anxiety, and depressive disorders in affected adults. Optimal short and long-term close monitoring is needed to deploy medical resources and socioeconomic support to relieve mental stress burdens.

Using RSQSim to Determine Seismic Sequence in Eastern Taiwan Fault System

Abstract Understanding the spatial and temporal patterns of seismic activity, along with fault interactions in Taiwan, is essential for earthquake hazard assessment and advancing knowledge of regional tectonics. This study employs the Rate and State Earthquake Simulator (RSQSim) to simulate the eastern Taiwan fault system, integrating fault geometry from the multidisciplinary Taiwan Earthquake Model. We applied long-term simulations spanning 400,000 yr to conduct earthquake sequences and recurrence intervals on five distinct faults in eastern Taiwan: Milun fault, Longitudinal Valley fault, Central Range structure, Luyeh fault, and Taimali Coastline structure. The simulated earthquake catalogs are compared against the historical record in terms of seismicity, frequency–magnitude statistics, and recurrence patterns. The model reasonably reproduces key observational constraints, including spatial patterns, magnitude probabilities fitting a gamma distribution, and periods of quiescence resulting from fault interactions. Overall, the results demonstrate RSQSim’s potential for physics-based seismic hazard modeling and provide insights into regional seismotectonic processes in eastern Taiwan for constructing sustainable cities and communities.

The rupture process of the Hualien M7.3 sequence on April 3, 2024

The Hualien M7.3 earthquake on April 3, 2024, was a significant and strong earthquake in Taiwan, China in the past two decades. The rupture process of the main shock and strong aftershocks is of great significance to the subsequent seismic activity and seismogenic tectonic research. Based on local strong-motion data, we used the IDS (Iterative Deconvolution and Stacking) method to obtain the rupture process of the mainshock and two strong aftershocks on the 23rd. The rupture of the mainshock was mainly unilateral, lasting 31 s, with a maximum slip of 2 m, and the depth of the large slip zone is about 41-49 km. There is a clear difference between the rupture depth of the main shock and the two strong aftershocks. The depths of the large slip zones of the latter two are 3-9 km and 8-10 km, respectively. There is also a significant difference in the seismogenic fault between the mainshock and the aftershocks, and we believe that there are two seismogenic fault zones in the study area, the deep and the shallow fault zone. The slip of the deep faults activates the shallow faults.

Deciphering the cause of massive disaster during sept. 2022 Chihshang Taiwan earthquake of magnitude 6.8 using strong motion seismology

Deciphering the cause of massive disaster during sept. 2022 Chihshang Taiwan earthquake of magnitude 6.8 using strong motion seismology

Cyclic behavior and pushover analysis of large scale two-bay, two-story reinforced concrete frames infilled with walls with openings

This study presents experimental results on the seismic behavior of a large-scale two-bay, two-story RC frame with RC infill walls, including openings typical of low-rise RC row buildings in Taiwan. The test findings indicated that the specimen failed due to the failure of the vertical members of the first story. Specifically, the critical wall segments located between openings and between an opening and a boundary column and short columns resulting from the presence of these openings were shown to be the main contributors to the failure. Based on the observed phenomenon during the test, an analytical model was verified and proposed for the tested specimen’s pushover analysis. The selection of plastic hinges in the analytical model was determined according to the Taiwan Earthquake Assessment for Structures by Pushover Analysis (TEASPA). Pushover analysis performed by commercially available software indicated that the analytical model could well capture the specimen's behavior regarding peak base shear, initial stiffness, displacement of each story, and development of plastic hinges.

Integration of Machine learning and equal differential time method for enhanced hypocenter localization in earthquake early warning systems: application to dense seismic arrays in Taiwan

The Earthquake Early Warning System (EEWS) acts as a vital instrument for reducing seismic risks in regions with high seismic vulnerability. A rapid and accurate hypocenter estimation is pivotal for the EEWS, providing the groundwork for more reliable magnitude and intensity assessments necessary for effective earthquake warnings. This study presents an algorithm that integrates machine-learning-based (near) real-time phase picking with an Equal Differential Time (EDT) rapid hypocenter location algorithm, applying it to a 3D velocity model. The phase-picking model, refined through data augmentation, enhances the precision of phase detection in continuous recordings and simultaneous multiple events while ensuring the swift detection of the P-phase, which is critical for early earthquake warnings. Our rapid earthquake location method calculates theoretical P arrivals from potential hypocenters, which are grid points in a 3D velocity model, to stations that are close to their grid points, with the arrivals being stored by the station. As P arrivals are detected, the differences in arrival times across stations are utilized in EDT for estimating hypocenters. Furthermore, our earthquake location algorithm is adept at localizing multiple seismic events, a capability that can diminish the risk of unreported cases in scenarios where events occur in close temporal and spatial succession in high seismicity regions. We applied the algorithm to real waveform recordings of recent earthquakes in Taiwan that satisfied the early warning criteria. The results suggest that our algorithm consistently yields more reliable hypocenter estimates compared to those from the currently operational EEWS in Taiwan. Moreover, our algorithm succeeded in locating an earthquake that the current EEWS overlooked due to its failure to recognize P arrivals. These results showcase the potential of our algorithm to provide more accurate hypocenter estimates and to locate earthquake events with complex seismic recordings.Graphical

Anomaly Detection Using Machine Learning in Hydrochemical Data From Hot Springs: Implications for Earthquake Prediction

AbstractThis study explores the potential of machine learning algorithms for earthquake prediction, utilizing fluid chemical anomaly data from hot springs. Six hot springs, located within an active fault zone along the southeastern coast of China, were carefully chosen as hydrochemical monitoring sites for an extended period of two and a half years. Using this data, a prediction model integrating six algorithms was developed to forecast M ≥ 5 earthquakes in Taiwan. The model's performance was validated against recorded earthquake events, and the factors influencing its predictive capability were analyzed. Our comprehensive analysis conclusively demonstrates the superiority of machine learning algorithms over traditional statistical methods for earthquake prediction. Additionally, including sampling time in the data sets significantly improves the model's predictive performance. However, it is important to note that the model's predictive performance varies across different hot spring and indicators type, highlighting the importance of identifying optimal indicators for specific scenarios. The model parameters, including the anomaly detection rate (P) and earthquake response time threshold (M), significantly impact the model's predictive capabilities. Therefore, adjustments are needed to optimize the model's performance for practical use. Despite limitations such as the inability to differentiate pre‐earthquake anomalies from post‐earthquake anomalies and pinpoint the precise location of earthquakes, this study successfully showcases the potential of machine learning algorithms in earthquake prediction, paving the way for further research and improved prediction methods.

Analysis of Vibration Characteristics of Bridge Structures under Seismic Excitation.

Bridges may undergo structural vibration responses when exposed to seismic waves. An analysis of structural vibration characteristics is essential for evaluating the safety and stability of a bridge. In this paper, a signal time-frequency feature extraction method (NTFT-ESVD) integrating standard time-frequency transformation, singular value decomposition, and information entropy is proposed to analyze the vibration characteristics of structures under seismic excitation. First, the experiment simulates the response signal of the structure when exposed to seismic waves. The results of the time-frequency analysis indicate a maximum relative error of only 1% in frequency detection, and the maximum relative errors in amplitude and time parameters are 5.9% and 6%, respectively. These simulation results demonstrate the reliability of the NTFT-ESVD method in extracting the time-frequency characteristics of the signal and its suitability for analyzing the seismic response of the structure. Then, a real seismic wave event of the Su-Tong Yangtze River Bridge during the Hengchun earthquake in Taiwan (2006) is analyzed. The results show that the seismic waves only have a short-term impact on the bridge, with the maximum amplitude of the vibration response no greater than 1 cm, and the maximum vibration frequency no greater than 0.2 Hz in the three-dimensional direction, indicating that the earthquake in Hengchun will not have any serious impact on the stability and security of the Su-Tong Yangtze River Bridge. Additionally, the reliability of determining the arrival time of seismic waves by extracting the time-frequency information from structural vibration response signals is validated by comparing it with results from seismic stations (SSE/WHN/QZN) at similar epicenter distances published by the USGS. The results of the case study show that the combination of dynamic GNSS monitoring technology and time-frequency analysis can be used to analyze the impact of seismic waves on the bridge, which is of great help to the manager in assessing structural seismic damage.

Directionality characteristics of horizontal response spectra from the 2022 Mw 6.9 Chihshang, Taiwan earthquake

Horizontal earthquake ground motion intensity, and specifically response spectral ordinates, vary with orientation. This phenomenon is usually referred to as ground motion directionality and can be separated into two aspects: the orientation where the maximum spectral response occurs and the variation of response spectral ordinates as the orientation moves away from the orientation of maximum spectral response. This work studies both aspects using the recent 2022 Mw 6.9 Chihshang, Taiwan earthquake, which was recorded by a dense network of strong motion stations with various geological and topographical settings. The mean variation of response spectral ordinates with orientation is found to be slightly more significant than that of previous shallow crustal earthquakes in active tectonic regimes. Moreover, the orientation of maximum spectral response is found to be close to the transverse orientation, which is perpendicular to the orientation at a given site that points to the earthquake epicenter, confirming prior observations made for strike-slip earthquakes. These results suggest that the location of a site relative to the seismic source could be used to modify the outputs of ground motion models to estimate spectral responses at specific horizontal orientations.

Rapid Crisis Response in Resilient Cities: Emergency Response to and Reconnaissance of Earthquake Disasters in Taiwan

The devastating Chichi earthquake in Taiwan in 1999 highlighted the importance of disaster prevention and relief operations. In response to the challenge of extreme events and compound disasters, the National Science and Technology Center for Disaster Reduction (NCDR) contributes to operations at the Central Emergency Operation Center (CEOC) of Taiwan by providing integrated information and timely suggestions, and it delivers a common operational picture to central and local governments through a decision support system. This study was undertaken to explore the emergency response towards the reconnaissance of earthquake disasters in Taiwan to illustrate how resilient cities ensure rapid crisis response with a focus on the NCDR disaster response decision support system. This study examines the decision support system used following the 2016 ML 6.6 Meinong earthquake. The results demonstrate that the first line of relief for the emergency response commander is data-driven decision-making.

Some characteristics of foreshocks and aftershocks of the 2022 ML6.8 Chihshang, Taiwan, earthquake sequence

Foreshocks and aftershocks occurred before and after the ML6.8 (Mw7.0) earthquake in eastern Taiwan on 18 September 2022. We explore the epicentral distribution and temporal variations for the mainshock, foreshocks, and aftershocks. Most of the events were located in the area around the Longitudinal Valley. Most foreshocks occurred around the mainshock, while the aftershocks happened outwards from the foreshock area. The temporal variations in seismic-wave energy show that the largest foreshock and the mainshock were responsible for releasing most of the energy during the earthquake sequence. In addition, the b values of the Gutenberg-Richter frequency-magnitude law were 0.62 for foreshocks, 0.87 for aftershocks, and 0.71 for the whole seismic activity by using the least squares method and 0.52 for foreshocks, 0.84 for aftershocks, and 0.65 for the whole seismic activity by using the maximum likelihood method. The b values increase from foreshocks to aftershocks, suggesting the possibility that the fluid pressure of faults during foreshocks is higher than that of the faults during aftershocks due to the outward migration of water. The p-value of the Omori-Utsu law for the aftershock sequence was estimated to be 0.92 for all aftershocks in the study, 1.39 for the aftershocks occurred in the first 6 days, and 1.30 for the aftershocks occurred in the first 12 days. The foreshock sequence could not be described by the inverse Omori law.

Can the Thermal Infrared Radiation Anomalies Reported Before Earthquakes be a Precursor?

Twenty-seven earthquakes in Taiwan with local magnitudes [Formula: see text] and focal depths d = 8.0−215.8[Formula: see text]km were preceded by thermal infrared radiation (TIR) anomalies. The data are taken as an example to investigate the mechanisms of generating the TIR and to examine whether the TIR anomalies can be considered as a precursor or not. Let [Formula: see text] and [Formula: see text] be the largest number of days before forthcoming earthquakes when the anomalies are observed in the day-time and the night-time, respectively. The precursor time, T, for an event, is the larger value of [Formula: see text] and [Formula: see text]. The plots of both T vs. [Formula: see text] and [Formula: see text] vs. [Formula: see text] are scattered. Regardless of two data points with abnormally large [Formula: see text] values, it seems able to recognize a positive correlation between [Formula: see text] and [Formula: see text]. Among the 27 earthquakes, 8 events were proceeded by Rn concentration changes whose precursor times are [Formula: see text] days. For most of the eight events, [Formula: see text] is much longer than either [Formula: see text] or [Formula: see text]. Hence, the model of outflow of gases from the depths to the ground surface for describing the Rn concentration changes cannot interpret the TIR anomalies. Based on rock mechanics, the temperature rise, [Formula: see text], is generated by frictional heating due to preseismic slip. That the TIR anomalies discontinuously appeared before earthquakes and the occurrence times vary for different events is inconsistent with the processes of generation of frictional heating caused by preseismic slip on a few shallow faults in the source areas before forthcoming earthquakes. Since theoretical results and observations are not consistent, the answer to the title of this study is negative.

The first 30 min hidden aftershocks of the 2022 September 17, ML 6.4, Guanshan, Taiwan earthquake and its seismological implications

The first 30 min of the aftershock sequence following the 2022 September 17, ML 6.4, Guanshan, Taiwan earthquake is investigated by the back-projection (BP) method. Based on the Automatic Gain Control (AGC) to process individual earthquake record and sort waveforms by epicentral distance, 80 events are identified near the Guanshan earthquake epicenter to verify its temporal variation. However, most of these events cannot clearly image by the BP method to determine its spatial locations for its small amplitude and short time separation. In total, 29 aftershocks are imaged by this study to identify its spatial locations during this time period. The relocated events are compared with the Central Weather Bureau (CWB) rapid report catalogue. Only 5 events have been reported by the CWB rapid report catalogue. These unreported hidden aftershocks are identified to distribute surrounding the epicenter and extended to the east. This extracted information of hidden aftershocks is crucial for assessing the potential for future large aftershocks and estimating the associated seismic hazards in a given region, and provide extra message to evaluate the source physics in general.

The Assessment of Structural Damages by Potential M&lt;sub&gt;L&lt;/sub&gt; 7.0 Changhua Earthquake in Taiwan Using Hybrid Simulation Method, Modal Analysis and Story Drift Ratio

The Assessment of Structural Damages by Potential M&lt;sub&gt;L&lt;/sub&gt; 7.0 Changhua Earthquake in Taiwan Using Hybrid Simulation Method, Modal Analysis and Story Drift Ratio

Characteristics of Potential Ionospheric Anomalies Prior to the M7.4 April 2, 2024 Taiwan Earthquake Identified With Multiple Observations

Characteristics of Potential Ionospheric Anomalies Prior to the M7.4 April 2, 2024 Taiwan Earthquake Identified With Multiple Observations

Schumann resonance anomalies associated with two (M~7) Tohoku offshore earthquakes in the spring of 2021

ABSTRACT. We describe the Schumann resonance (SR) anomalies associated with two earthquakes (EQs) observed in Japan in the spring of 2021. SR is the global electromagnetic phenomenon observed in the ELF (extremely low frequency) band, and its resonance peaks are observed in the power spectra on natural radio noise at frequencies of 8, 14, 20, Hz, etc. The natural source of ELF radiation is the global lightning activity occurring in the Earth-ionosphere cavity. The anomalies were observed for the first time in Japan for the EQs in Taiwan when the distance between the observatory and the EQ epicenter was a few Mm (1 Mm = 1000 km). Recently, a new SR anomaly was addressed, related to nearby (a few hundred km) EQs (Hayakawa et al., 2019, 2020a,b). This paper presents the SR anomalies observed in the vicinity of Nagoya-city for two relatively close (~500 km) successive EQs with magnitude around 7 that occurred offshore the Tohoku area in Japan. The anomaly is characterized by the noticeable simultaneous increase or decrease in the amplitudes of three SR modes. This SR unusual behavior was observed prior to and after each of the two EQs that occurred in February and March, 2021. Observational data were interpreted in the model of seismogenic perturbations of the lower ionospheric conductivity profile. Model computations imply the full-wave solution of the ELF electromagnetic problem in the form of the Riccati equation and the 2D (two dimensional) telegraph equations. We show that observed disturbances in the SR power spectra might be attributed to two types of seismogenic modifications in the lower ionospheric profile: the compression or the expansion of the vertical profiles of mesospheric conductivity over the EQ epicenter.