Estimation Of Ground Motion Research Articles

0–5 Hz deterministic 3-D ground motion simulations for the 2014 La Habra, California, Earthquake

SUMMARYWe have simulated 0–5 Hz deterministic wave propagation for a suite of 17 models of the 2014 Mw 5.1 La Habra, CA, earthquake with the Southern California Earthquake Center Community Velocity Model Version S4.26-M01 using a finite-fault source. Strong motion data at 259 sites within a 148 km × 140 km area are used to validate our simulations. Our simulations quantify the effects of statistical distributions of small-scale crustal heterogeneities (SSHs), frequency-dependent attenuation Q(f), surface topography and near-surface low-velocity material (via a 1-D approximation) on the resulting ground motion synthetics. The shear wave quality factor QS(f) is parametrized as QS, 0 and QS, 0fγ for frequencies less than and higher than 1 Hz, respectively. We find the most favourable fit to data for models using ratios of QS, 0 to shear wave velocity VS of 0.075–1.0 and γ values less than 0.6, with the best-fitting amplitude drop-off for the higher frequencies obtained for γ values of 0.2–0.4. Models including topography and a realistic near-surface weathering layer tend to increase peak velocities at mountain peaks and ridges, with a corresponding decrease behind the peaks and ridges in the direction of wave propagation. We find a clear negative correlation between the effects on peak ground velocity amplification and duration lengthening, suggesting that topography redistributes seismic energy from the large-amplitude first arrivals to the adjacent coda waves. A weathering layer with realistic near-surface low velocities is found to enhance the amplification at mountain peaks and ridges, and may partly explain the underprediction of the effects of topography on ground motions found in models. Our models including topography tend to improve the fit to data, as compared to models with a flat free surface, while our distributions of SSHs with constraints from borehole data fail to significantly improve the fit. Accuracy of the velocity model, particularly the near-surface low velocities, as well as the source description, controls the resolution with which the anelastic attenuation can be determined. Our results demonstrate that it is feasible to use fully deterministic physics-based simulations to estimate ground motions for seismic hazard analysis up to 5 Hz. Here, the effects of, and trade-offs with, near-surface low-velocity material, topography, SSHs and Q(f) become increasingly important as frequencies increase towards 5 Hz, and should be included in the calculations. Future improvement in community velocity models, wider access to computational resources, more efficient numerical codes and guidance from this study are bound to further constrain the ground motion models, leading to more accurate seismic hazard analysis.

Data-Driven Synthesis of Broadband Earthquake Ground Motions Using Artificial Intelligence

ABSTRACTRobust estimation of ground motions generated by scenario earthquakes is critical for many engineering applications. We leverage recent advances in generative adversarial networks (GANs) to develop a new framework for synthesizing earthquake acceleration time histories. Our approach extends the Wasserstein GAN formulation to allow for the generation of ground motions conditioned on a set of continuous physical variables. Our model is trained to approximate the intrinsic probability distribution of a massive set of strong-motion recordings from Japan. We show that the trained generator model can synthesize realistic three-component accelerograms conditioned on magnitude, distance, and VS30. Our model captures most of the relevant statistical features of the acceleration spectra and waveform envelopes. The output seismograms display clear P- and S-wave arrivals with the appropriate energy content and relative onset timing. The synthesized peak ground acceleration estimates are also consistent with observations. We develop a set of metrics that allow us to assess the training process’s stability and to tune model hyperparameters. We further show that the trained generator network can interpolate to conditions in which no earthquake ground-motion recordings exist. Our approach allows for the on-demand synthesis of accelerograms for engineering purposes.

Geomorphology, Three-Dimensional Geology, and Seismologic Hazards of the New Madrid Seismic Zone in Dyer County, Tennessee

ABSTRACTGeomorphic and three-dimensional geologic mapping reveals two major fault systems of the seismically active Reelfoot rift pass beneath Dyer County in northwestern Tennessee, the Reelfoot South fault, and the east-bounding faults of the Reelfoot rift. The Dyer County mapping also indicates that the two principal Reelfoot South fault hanging wall structures, the Lake County uplift and Tiptonville dome, pass beneath the county. Quaternary displacement was identified on southeastern Reelfoot rift margin faults in Dyer County, thus indicating that this rift margin has been active during the Quaternary from adjacent Obion County through Dyer County to Lauderdale County, Tennessee, for a distance of at least 60 km. The three-dimensional geologic mapping also provides stratigraphic thicknesses of surface sediment and underlying Paleogene and Cretaceous strata that significantly contribute to the estimation of ground motion in the event of a future large New Madrid seismic zone earthquake. The new ground motion maps using the three-dimensional geology of Dyer County are compared to the current U.S. Geological Survey earthquake hazard maps. This comparison reveals generally lower acceleration for buildings less than four stories high and greater acceleration for buildings greater than 10 stories high in the event of a large New Madrid seismic zone earthquake.

Inclusion of site-effects: An approach coherent with contemporary event-based PSHA practices

Contemporary probabilistic seismic hazard analysis (PSHA) is performed using an event-based approach, and that has motivated the review of the methods to consider site-effects within that analysis framework. Shortly after the classic proposal of PSHA, that only aimed at estimating ground motion levels for rock conditions, different ways to estimate the modifications of the amplitude at surface level because of soft soils were developed. To date, different approaches have been proposed, although they seem to be better suited for convolution-based PSHA, where the numerical integration of analytical functions is performed. This paper presents a proposal to consider site-effects within an event-based PSHA framework, and compares the obtained results with those of two commonly used methods. Different sensitivity tests related to variations of assumptions of the model are shown, in order to facilitate understanding the results.

Imaging an Underwater Basin and Its Resonance Modes Using Optical Fiber Distributed Acoustic Sensing

Abstract Distributed acoustic sensing (DAS) is an ideal tool for ambient noise tomography owing to the dense spatial measurements and the ability to continuously record in harsh environments, such as underwater. Although the fine spatial sampling of DAS facilitates the imaging of small-scale lateral velocity heterogeneities, efforts relying on dispersion-based ambient noise tomography are hampered by the underlying premise of negligible lateral variations across the segment used for dispersion curve extraction. To image small-scale structures, this method should be augmented with objective and independent approaches that are not scale limited. Here, we show that power spectral densities (PSDs) and autocorrelations (ACs) of DAS data reveal extremely detailed frequency-dependent resonance and wave propagation characteristics. These observations contain crucial information on lateral and vertical wave propagation. We use these methods to demonstrate the ability to image a complex underwater basin using ambient noise recorded on a fiber deployed offshore Greece. A 2D shear-wave velocity model was derived by analyzing Scholte-wave dispersion. The PSD and AC reveal significant lateral variations across the short 2.5 km long fiber segment, including basin edge effects and scattered waves. These were used to further constrain and modify the velocity model. The modified model is supported by waveform simulations that qualitatively reproduce the PSD and AC observations. Our results demonstrate the advantages of incorporating PSD and AC observations into ambient noise-based imaging. The spatially continuous observation of resonance modes across the basin highlights the benefit of DAS acquisitions for ground-motion estimation.

Application of Focal Plane Directions for Estimating Ground Motion Models with General Regression Neural Networks

Application of Focal Plane Directions for Estimating Ground Motion Models with General Regression Neural Networks

Records of Local Earthquakes as a Basis for the Correct Estimation of Strong Ground Motion (the Area of the Second Severomuisk Tunnel)

Abstract ––To obtain realistic and correct estimates of strong ground motion in the area of construction of the second Severomuisk tunnel, the records of local earthquakes obtained by the Severomuisk seismic station (SVKR) in 2005–2010 are studied (magnitudes Mb of ~4.2–5.5, hypocentral distances r of ~15–220 km). Stochastic-simulation methods are used to estimate the regional parameters of radiation and propagation of seismic waves in northeastern Buryatia: the stress parameter Δσ, shapes of source spectra, wave attenuation at high frequencies (k), parameters defining the shape and duration of the acceleration time history, etc. Beforehand, the duration of strong motion as a function of the hypocentral distance was evaluated from the records; the local site amplification A(f) was estimated based on the velocity structure of the region; and the envelope method was applied to estimate the quality function Q(f). The following data were obtained: Δσ ≈ 100 bars; k ≈ 0.012 s; Q(f) as ~60 f1.05 for r of ~15–30 km, ~80 f1.0 for r of ~40–60 km, ~90 f0.9 for r of ~100–110 km, and ~150 f0.7 for r of ~160–220 km; geometris spreading as 1/r for r <50 km, 1/50 for 50 < r <150 km, and 1/r0.5 for r >150 km; and duration as 0 for 0 < r < 5 km, 0.222r for 5 < r < 50 km, and 10 + 0.015r for r > 50 km. These estimates can be used to predict ground motion parameters during future strong earthquakes in the region.

Empirical model for frequency content estimation of strong ground motion records of Iran

This paper presents a new empirical model to predict the mean period (Tm) as a frequency-content parameter of earthquake record using the strong ground motions recorded in Iran during 1975–2019. An updated earthquake databank containing 2281 horizontal acceleration records was employed to develop the empirical model through a systematic fitting procedure. A simple functional form for the model was found as a function of epicentral distance (R), moment magnitude (Mw), and the shear wave velocity averaged at the top 30 m of the recording sites (Vs30). The proposed model is compared with three existing predictive models and the results are discussed in terms of magnitude, source-to-site, and site dependencies.

Analysis of Seismogram of the 1923 Kanto Earthquake at Tokyo by Ewing Strong-Motion Seismograph Part 2 Examination of Characteristics of Seismograph and Estimation of Ground Motion

Analysis of Seismogram of the 1923 Kanto Earthquake at Tokyo by Ewing Strong-Motion Seismograph Part 2 Examination of Characteristics of Seismograph and Estimation of Ground Motion

Broadband ground motion simulations for Northeast India

This study presents broadband (BB) ground motions for two historical earthquakes (Mw ≥ 8) in Northeast (NE) India. We apply a recently developed geology-based 3D velocity model of the Northeastern region (NER) to simulate low frequency (LF) ground motions (f < 1Hz). These synthetics are further combined with high frequency (HF) scattering wave-fields (f > 1Hz) using a hybrid approach, thus yielding BB ground motions (0.1–10Hz). First, we calibrate the 3D model and scattering parameters by comparing the simulated ground motions against recorded data available for four events (Mw 5.2, Mw 5.5, Mw 6.3, and Mw 7.2) in NE India. Our results indicate that the variability of the bias for spectral acceleration (SA) lies within limits [-1,1] for all four events. From the statistical analysis of the ground motion, we also observe that the hybrid approach gives a realistic estimation of site-specific BB ground motion and consistently reproduces the prominent features of the observed motions up to 10Hz at most of the stations. Next, we simulate a suite of BB ground motions to estimate ground motion intensities for two historical earthquakes (viz., 1897 Assam event, 1950 Assam event) in NE India. Our results indicate that the variations in the ground motion intensities at hard rock and soft soil sites are manifestations of the local geology and surface topography incorporated in the 3D regional velocity model. We also observe that the peak ground acceleration (PGA) for both events exceed 1 g in the epicentral region. The BB ground motions obtained from this approach will be useful to engineers in seismic design and site-specific hazard estimation.

Earthquake ground motion estimation for buildings using absolute floor acceleration response data

AbstractEarthquake ground motion information is useful for structural vibration control during earthquakes and post‐earthquake inspections of structural damage. However, in practice, the ground input data on a specific location may not be available because of instrumentation limitations or technical issues. Numerous studies have been devoted to identifying the unknown excitation. Most of these studies required responses in relative coordinates or from systems with direct feedthrough. On the other hand, acceleration monitoring systems in applications measure global responses of buildings, which corresponds to the absolute acceleration of a point on a structure, that is, the measured floor acceleration is the sum of the unknown earthquake‐induced ground motion and acceleration relative to the ground when an earthquake happens. In this study, a ground motion estimation approach was developed based on an extended Kalman filter (EKF) with an embedded Bayesian noise parameter updating technique, which requires a relatively small number of sensors for absolute acceleration measurements. Numerical simulations, a shaking table test, and a real‐world application were performed to demonstrate the applicability and accuracy of the proposed method.

Three-Dimensional Seismic-Wave Propagation Simulations in the Southern Korean Peninsula Using Pseudodynamic Rupture Models

ABSTRACTAccurate and practical ground-motion predictions for potential large earthquakes are crucial for seismic hazard analysis of areas with insufficient instrumental data. Studies on historical earthquake records of the Korean Peninsula suggest that damaging earthquakes are possible in the southeastern region. Yet classical ground-motion prediction methods are limited in considering the physical rupture process and its effects on ground motion in complex velocity structures. In this study, we performed ground-motion simulations based on rigorous physics through pseudodynamic source modeling and wave propagation simulations in a 3D seismic velocity model. Ensembles of earthquake scenarios were generated by emulating the one- and two-point statistics of earthquake source parameters derived from a series of dynamic rupture models. The synthetic seismograms and the distributions of simulated peak ground velocities (PGVs) were compared with the observations of the 2016 Mw 5.4 Gyeongju earthquake in the Korean Peninsula. The effects of surface-wave radiation, rupture directivity, and both local and regional amplifications from the 3D wave propagation were reproduced accurately in the spatial distribution of simulated PGVs, in agreement with the observations from dense seismic networks by mean log residuals of −0.28 and standard deviations of 0.78. Amplifications in ground motions were found in regions having low crustal velocities and in regions of constructive interference from the crustal shear-wave phases associated with postcritical reflections from the Moho discontinuity. We extended the established approach to earthquake scenarios of Mw 6.0, 6.5, and 7.0, at the same location, to provide the distribution of ground motions from potential large earthquakes in the area. Although we demonstrate the value of these simulations, improvements in the accuracy of the 3D seismic velocity model and the scaling relationship of the source models would be necessary for a more accurate estimation of near-source ground motions.

Influence of the Seismic Wave Velocity of the Damage Zone on Near-Field Ground Motions

In burst-prone deep underground engineering, seismic waves generated from a near-field ground motion event may play a critical role in causing localized rockburst damage. Accurate estimation of near-field ground motions around excavations is important for seismic hazard risk assessment and dynamic rock support design in underground engineering. During the excavation of an underground cavern, stress redistribution in the surrounding rock leads to the formation of damage zones, including the excavation damage zone (EDZ) and excavation fracture zone (EFZ). The poor properties of the rock in the damage zones cause the wave velocities of the rock mass to decrease and the dynamic wave interaction to change, thereby affecting the ground motions around the excavation. This paper studies the near-field ground motion behavior and reveals the control effect of the seismic wave velocity in the damage zones on the near-field ground motions by the aid of the finite fracturing source model (FFSSM). The research results provide a new knowledge of the influence of excavation disturbance on the ground motion distribution around the excavation, and provide new ideas for the seismic hazard risk assessment and prevention in underground engineering.

The Impact of 3D Finite-Fault Information on Ground-Motion Forecasting for Earthquake Early Warning

ABSTRACTWe identify aspects of finite-source parameterization that strongly affect the accuracy of estimated ground motion for earthquake early warning (EEW). EEW systems aim to alert users to impending shaking before it reaches them. The U.S. West Coast EEW system, ShakeAlert, currently uses two algorithms based on seismic data to characterize the earthquake’s location, magnitude, and origin time, treating it as a point or line source. From this information, ShakeAlert calculates shaking intensity and alerts locations where shaking estimates exceed a threshold. Several geodetic EEW algorithms under development would provide 3D finite-fault information. We investigate conditions under which this information produces sufficiently better intensity estimates to potentially improve alerting. Using scenario crustal and subduction interface sources, we (1) identify the most influential source geometry parameters for an EEW algorithm’s shaking forecast, and (2) assess the intensity alert thresholds and magnitude ranges for which more detailed source characterization affects alert accuracy. We find that alert regions determined using 3D-source representations of correct magnitude and faulting mechanism are generally more accurate than those obtained using line sources. If a line-source representation is used and magnitude is calculated from the estimated length, then incorrect length estimates significantly degrade alert region accuracy. In detail, the value of 3D-source characterization depends on the user’s chosen alert threshold, tectonic regime, and faulting style. For the suite of source models we tested, the error in shaking intensity introduced by incorrect geometry could reach levels comparable to the intrinsic uncertainty in ground-motion calculations (e.g., 0.5–1.3 modified Mercalli intensity [MMI] units for MMI 4.5) but, especially for crustal sources, was often less. For subduction interface sources, 3D representations substantially improved alert area accuracy compared to line sources, and incorrect geometry parameters were more likely to cause error in calculated shaking intensity that exceeded uncertainties.

Explainable Machine learning on New Zealand strong motion for PGV and PGA

Estimating ground motion characteristics at various locations as a function of fault characteristics is useful for the proper damage assessment and risk mitigation strategies. This paper explores the application of machine learning approaches to predict peak ground acceleration (PGA) and peak ground velocity (PGV) using New Zealand’s strong motion data. Five machine learning algorithms, namely linear regression, kNN, SVM, Random Forest, and XGBoost, are used in this study. Using the New Zealand flat-file database, the geometric mean of the peak ground motion parameters is used as predictor variables in training the machine learning algorithms. The performance of the chosen algorithms and how they work on PGV and PGA are discussed. The best prediction for PGA is obtained using random forest but for PGV XGboost worked best. The relative importance of various features in the flat file is also presented for the best-performing machine learning algorithm. Although the magnitude of an earthquake is found to be most influential for PGV, rupture distance showed the highest impact for PGA. Finally, the predictions are also explained using SHApley Additive exPlanations (SHAP) for the overall dataset as well as on a sample by sample basis, for a few samples. Pairwise dependency of some features with the highest feature importance is also presented using SHAP.

Applicability of Accurate Ground Motion Estimation Using Initial P Wave for Earthquake Early Warning

The earthquake early warning (EEW) system is capable of mitigating seismic hazards and reducing deaths, injuries, and economic losses. Although EEW approaches have already been developed worldwide, improving the accuracy and applicability is still controversial. Aiming at the ground motion estimation using the initial P wave, we investigated eight representative characteristic parameters, i.e., the peak measurements and integral quantities, using the database of the 2008 Wenchuan earthquake, where the aftershocks with the criteria that 4.0 ≤ Ms ≤ 6.5 and epicentral distance less than 150 km are analyzed. We established the relationships between the eight characteristic parameters and four ground motion parameters, respectively, based on which the estimation accuracy and reliability and the extent to which the increasingly expanding time windows could affect the estimates are analyzed accordingly. We found that the integral quantities could also be a robust estimator for peak ground acceleration (PGA), peak ground velocity (PGV), and spectral intensity (SI), while the peak measurement is more useful in estimating peak ground displacement (PGD). In addition, for estimating the ground motion of events with magnitudes less than 6.5, a 2-s window could effectively improve the estimation accuracy by approximately 11.5–18.5% compared with using a 1-s window, as the window increases to 3 s, the accuracy would further improve while the growth rate will be reduced to around 3.0–8.0%.

Ground motion intensity measures for New Zealand

Peak ground motions and spectral accelerations estimated from the prediction equations are highly significant in earthquake hazard studies. Recently, these predictive relationships developed for higher-order parameters obtained paramount importance as they describe different ground motion characteristics. The northeastern region of India experiences extreme seismicity due to the Indian plate subduction under the South Asian plate. However, only a few ground motion prediction equations (GMPEs) are available for such tectonic environments due to insufficient ground motion data. In this regard, it is noticed that the tectonic environment experienced by New Zealand is similar to that of northeast India. So, in this paper, two GMPE models for New Zealand are developed with the help of the artificial neural network (ANN) technique using the GeoNet database. Model-1 corresponds to various higher-order parameters, whereas model-2 developed for spectral accelerations (Sa) between 0.01 and 5s. Further, these models are compared against global and region-specific GMPEs. The developed models shows good agreement with other GMPEs and the data but slightly over predicts at distances greater than 300 km. Additional consideration of site-to-site variability in the current models reduced the total standard deviations of model-1 by 19–22 % and model-2 by 20%–23 %. Further, the estimates of these developed models are compared with some of the significant earthquakes in northeast India, and from these results, it is concluded that the current models can be adapted in such regions to estimate ground motion.

An assessment of the 3 February 2002 Cay (Turkey) earthquake (Mw=6.6): Modeling of ground motions and felt intensity distribution

Estimation of earthquake ground motions is important for several purposes including seismic design, analysis, risk mitigation and disaster management. For regions with insufficient data, simulations become critical, particularly for earthquake engineering applications requiring full ground motion data. In this study, stochastic finite-fault simulation of the 3 February 2002 Cay event is presented at three available stations within epicentral distances less than 200 km. The simulations are initially validated at these stations. Next, simulations of the earthquake at dummy nodes are performed in Afyon region. The simulated ground motion records for the Cay event are evaluated by comparing them against selected ground motion prediction equations. Then, the distributions of the observed intensity and damage are compared against the distribution of simulated intensities. The results reveal that the earthquake is simulated effectively.

Testing performance of pore pressure models implemented in one-dimensional site response analysis program against centrifuge test data measured in mildly sloping ground

A reliable prediction of the excess pore pressure build-up is essential in performing an effective site response analysis. In this study, centrifuge test measurements on mildly sloping ground subjected to ramped sinewaves are utilized to test the performances of three pore pressure models implemented in a one-dimensional (1D) site response analysis program conditioned on accumulated strain, energy, and stress, respectively. Three shear wave velocity (Vs) and relative density (Dr) profiles are utilized to account for the uncertainties in the soil properties. The pore pressure outputs calculated with the strain-based model is shown to be highly sensitive to Vs. Agreeable predictions are obtained near the surface, whereas the pore pressures at depths of 3 and 4 m are underestimated. The energy-based model significantly underestimates the pore pressure for all cases. The stress-based model is revealed to be less sensitive to Vs, whereas it is considerably dependent on Dr. Exceptional fit is achieved with a cone penetration test based Dr profile, whereas pore pressure is overestimated using the empirical liquefaction triggering chart to determine the cyclic strength. Further comparisons of the acceleration time histories illustrate the use of both the strain and energy-based models provide slightly higher and better estimates of the surface ground motion compared with that calculated with the stress-based model. Considering the sensitivity of the outputs, it is recommended to account for the uncertainties of soil properties and also to use both strain and stress-based models in performing 1D effective stress site response analyses.

Comparing the Performance of Regional Earthquake Early Warning Algorithms in Europe

Several earthquake early warning (EEW) algorithms have been developed worldwide for rapidly estimating real-time information (i.e., location, magnitude, ground shaking, and/or potential consequences) about ongoing seismic events. This study quantitatively compares the operational performance of two popular regional EEW algorithms for European conditions of seismicity and network configurations. We specifically test PRobabilistic and Evolutionary early warning SysTem (PRESTo) and the implementation of the Virtual Seismologist magnitude component within SeisComP, VS(SC), which we use jointly with the SeisComPscanlocmodule for locating events. We first evaluate the timeliness and accuracy of the location and magnitude estimates computed by both algorithms in real-time simulation mode, accounting for the continuous streaming of data and effective processing times. Then, we focus on the alert-triggering (decision-making) phase of EEW and investigate both algorithms’ ability to yield accurate ground-motion predictions at the various temporal instances that provide a range of warning times at target sites. We find that the two algorithms show comparable performances in terms of source parameters. In addition, PRESTo produces better rapid estimates of ground motion (i.e., those that facilitate the largest lead times); therefore, we conclude that PRESTo may have a greater risk-mitigation potential than VS(SC) in general. However, VS(SC) is the optimal choice of EEW algorithm if shorter warning times are permissible. The findings of this study can be used to inform current and future implementations of EEW systems in Europe.