Near-Field Ground Motions and Shaking from the 2019 Mw 7.1 Ridgecrest, California, Mainshock: Insights from Instrumental, Macroseismic Intensity, and Remote-Sensing Data

2020 ◽  
Vol 110 (4) ◽  
pp. 1506-1516 ◽  
Author(s):  
Susan E. Hough ◽  
Sang-Ho Yun ◽  
Jungkyo Jung ◽  
Eric Thompson ◽  
Grace A. Parker ◽  
...  
Keyword(s):  
Ground Motion ◽  
Structural Damage ◽  
Ground Motions ◽  
Near Field ◽  
Remote Sensing Data ◽  
Prediction Equation ◽  
Intensity Data ◽  
Radar Images ◽  
Conversion Equation ◽  
The Town

ABSTRACT Shaking from the 6 July 2019 Mw 7.1 Ridgecrest, California, mainshock was strongly felt through southern California, but generated relatively minimal structural damage in Ridgecrest. We consider the extent to which a damage proxy map (DPM) generated from satellite-based Synthetic Aperture Radar images can detect minor damage throughout the town of Ridgecrest. The DPM does not, as expected, detect all minor structural damage to individual structures, nor can it distinguish between structural damage and earthquake-related movement that is not consequential. However, the DPM does confirm many instances of minor structural damage to larger structures and groups of smaller structures and in some instances suggests minor structural damage that is not apparent upon visual inspection. Although ambiguous identification of minor damage may not be useful to guide earthquake response, the identification of minor, possibly hidden damage is potentially useful for other purposes. Overall, the DPM confirms that structural damage was commensurate with modified Mercalli intensity no higher than 7 throughout Ridgecrest. We consider both instrumental and intensity data to explore further the distribution of near-field ground motions over the frequency range of engineering concern. Peak ground accelerations and peak ground velocities estimated from “Did You Feel It?” intensity data using the Worden et al. (2012) ground-motion intensity conversion equation (GMICE) are consistent with recorded instrumental data. Both instrumental and estimated mainshock peak accelerations are further consistent with predictions from both the Boore et al. (2014) ground-motion prediction equation (GMPE), but lower than predicted by the Atkinson and Wald (2007) and Atkinson et al. (2014) intensity prediction equations (IPEs). A GMPE such as Boore et al. (2014), which is constrained by a large global dataset, together with a well-constrained GMICE, may thus characterize expected shaking intensities for large earthquakes better than an IPE based on more limited intensity data.

scholarly journals The 30 October 2020 Samos (Eastern Aegean Sea) Earthquake: effects of source rupture, path and local-site conditions on the observed and simulated ground motions

2021 ◽  
Author(s):  
Aybige Akinci ◽  
Daniele Cheloni ◽  
AHMET ANIL DINDAR
Keyword(s):  
Ground Motion ◽  
Structural Damage ◽  
Ground Motions ◽  
Aegean Sea ◽  
Peak Ground Velocity ◽  
Ground Shaking ◽  
Local Site ◽  
Eastern Aegean ◽  
Motion Characteristics ◽  
Eastern Aegean Sea

Abstract On 30 October 2020 a MW 7.0 earthquake occurred in the eastern Aegean Sea, between the Greek island of Samos and Turkey’s Aegean coast, causing considerable seismic damage and deaths, especially in the Turkish city of Izmir, approximately 70 km from the epicenter. In this study, we provide a detailed description of the Samos earthquake, starting from the fault rupture to the ground motion characteristics. We first use Interferometric Synthetic Aperture Radar (InSAR) and Global Positioning System (GPS) data to constrain the source mechanisms. Then, we utilize this information to analyze the ground motion characteristics of the mainshock in terms of peak ground acceleration (PGA), peak ground velocity (PGV), and spectral pseudo-accelerations. Modelling of geodetic data shows that the Samos earthquake ruptured a NNE-dipping normal fault located offshore north of Samos, with up to 2.5-3 m of slip and an estimated geodetic moment of 3.3 ⨯ 1019 Nm (MW 7.0). Although low PGA were induced by the earthquake, the ground shaking was strongly amplified in Izmir throughout the alluvial sediments. Structural damage observed in Izmir reveals the potential of seismic risk due to the local site effects. To better understand the earthquake characteristics, we generated and compared stochastic strong ground motions with the observed ground motion parameters as well as the ground motion prediction equations (GMPEs), exploring also the efficacy of the region-specific parameters which may be improved to better predict the expected ground shaking from future large earthquakes in the region.

Optimizing Earthquake Early Warning Alert Distance Strategies Using the July 2019 Mw 6.4 and Mw 7.1 Ridgecrest, California, Earthquakes

2020 ◽  
Vol 110 (4) ◽  
pp. 1872-1886 ◽  
Author(s):  
Jessie K. Saunders ◽  
Brad T. Aagaard ◽  
Annemarie S. Baltay ◽  
Sarah E. Minson
Keyword(s):  
Ground Motion ◽  
Early Warning ◽  
Ground Motions ◽  
Protective Action ◽  
Warning System ◽  
Prediction Equation ◽  
Earthquake Early Warning ◽  
Source Characterization ◽  
Earthquake Early Warning System ◽  
Alert Distance

ABSTRACT The ShakeAlert earthquake early warning system aims to alert people who experience modified Mercalli intensity (MMI) IV+ shaking during an earthquake using source estimates (magnitude and location) to estimate median-expected peak ground motions with distance, then using these ground motions to determine median-expected MMI and thus the extent of MMI IV shaking. Because median ground motions are used, even if magnitude and location are correct, there will be people outside the alert region who experience MMI IV shaking but do not receive an alert (missed alerts). We use 91,000 “Did You Feel It?” survey responses to the July 2019 Mw 6.4 and Mw 7.1 Ridgecrest, California, earthquakes to determine which ground-motion to intensity conversion equation (GMICE) best fits median MMI with distance. We then explore how incorporating uncertainty from the ground-motion prediction equation and the GMICE in the alert distance calculation can produce more accurate MMI IV alert regions for a desired alerting strategy (e.g., aiming to alert 95% of people who experience MMI IV+ shaking), assuming accurate source characterization. Without incorporating ground-motion uncertainties, we find MMI IV alert regions using median-expected ground motions alert fewer than 20% of the population that experiences MMI IV+ shaking. In contrast, we find >94% of the people who experience MMI IV+ shaking can be included in the MMI IV alert region when two standard deviations of ground-motion uncertainty are included in the alert distance computation. The optimal alerting strategy depends on the false alert tolerance of the community due to the trade-off between minimizing missed and false alerts. This is especially the case for situations like the Mw 6.4 earthquake when alerting 95% of the 5 million people who experience MMI IV+ also results in alerting 14 million people who experience shaking below this level and do not need to take protective action.

Spectral Matching of Real Ground Motions: Applications to Horizontally Irregular Systems in Elastic Range

2014 ◽  
Vol 17 (11) ◽  
pp. 1623-1638 ◽  
Author(s):  
R. Roy ◽  
P. Thakur ◽  
S. Chakroborty
Keyword(s):  
Ground Motion ◽  
Hazard Analysis ◽  
Ground Motions ◽  
Near Field ◽  
Spectral Matching ◽  
Uniform Hazard Spectrum ◽  
Elastic Range ◽  
Conditional Mean Spectrum ◽  
Performance Based Seismic Design ◽  
Irregular Systems

In the context of performance-based seismic design (PBSD), ground motions are often scaled to certain convenient target spectra derived from probabilistic seismic hazard analysis (PSHA). While Uniform Hazard Spectrum (UHS) is more widely used, Conditional Mean Spectrum (CMS) is recently proposed to be more desirable for scaling of real accelerograms. In this backdrop, a set of near-field and far-field ground motions are spectrally scaled, using wavelets, to both UHS and CMS. Seismic demand of horizontally irregular structures under bi-directional ground motion is assessed under both scaled and seed records in the elastic range. Spectral matching, within limits, of both the horizontal components of real records to a single hazard spectrum is observed to adequately predict the amplification in response due to asymmetry (at least for the records and target spectra relevant to soil class D). Further, such scaling effectively reduces the variability in predicted magnification from one ground motion to other. Dynamic amplification factors recommended in international codes to apply in equivalent static design of asymmetric systems are shown to be deficient.

Event Detection Performance of the PLUM Earthquake Early Warning Algorithm in Southern California

2019 ◽  
Vol 109 (4) ◽  
pp. 1524-1541 ◽  
Author(s):  
Elizabeth S. Cochran ◽  
Julian Bunn ◽  
Sarah E. Minson ◽  
Annemarie S. Baltay ◽  
Deborah L. Kilb ◽  
...  
Keyword(s):  
Los Angeles ◽  
Ground Motion ◽  
Early Warning ◽  
Southern California ◽  
Ground Motions ◽  
Tohoku Earthquake ◽  
Prediction Equation ◽  
Earthquake Early Warning ◽  
Japan Meteorological Agency ◽  
Origin Time

Abstract We test the Japanese ground‐motion‐based earthquake early warning (EEW) algorithm, propagation of local undamped motion (PLUM), in southern California with application to the U.S. ShakeAlert system. In late 2018, ShakeAlert began limited public alerting in Los Angeles to areas of expected modified Mercalli intensity (IMMI) 4.0+ for magnitude 5.0+ earthquakes. Most EEW systems, including ShakeAlert, use source‐based methods: they estimate the location, magnitude, and origin time of an earthquake from P waves and use a ground‐motion prediction equation to identify regions of expected strong shaking. The PLUM algorithm uses observed ground motions directly to define alert areas and was developed to address deficiencies in the Japan Meteorological Agency source‐based EEW system during the 2011 Mw 9.0 Tohoku earthquake sequence. We assess PLUM using (a) a dataset of 193 magnitude 3.5+ earthquakes that occurred in southern California between 2012 and 2017 and (b) the ShakeAlert testing and certification suite of 49 earthquakes and other seismic signals. The latter suite includes events that challenge the current ShakeAlert algorithms. We provide a first‐order performance assessment using event‐based metrics similar to those used by ShakeAlert. We find that PLUM can be configured to successfully issue alerts using IMMI trigger thresholds that are lower than those implemented in Japan. Using two stations, a trigger threshold of IMMI 4.0 for the first station and a threshold of IMMI 2.5 for the second station PLUM successfully detect 12 of 13 magnitude 5.0+ earthquakes and issue no false alerts. PLUM alert latencies were similar to and in some cases faster than source‐based algorithms, reducing area that receives no warning near the source that generally have the highest ground motions. PLUM is a simple, independent seismic method that may complement existing source‐based algorithms in EEW systems, including the ShakeAlert system, even when alerting to light (IMMI 4.0) or higher ground‐motion levels.

On the Seismic Response of the Faculty of Architecture and Engineering Building at Tohoku University

2016 ◽  
Vol 32 (1) ◽  
pp. 523-545 ◽  
Author(s):  
Ying Wang ◽  
Enrique Villalobos ◽  
Santiago Pujol ◽  
Hamood Al-Washali ◽  
Kazuki Suzuki ◽  
...  
Keyword(s):  
Seismic Response ◽  
Ground Motion ◽  
Structural Damage ◽  
Ground Motions ◽  
Strong Ground Motions ◽  
First Motion ◽  
Strong Ground

The Faculty of Architecture and Engineering Building at Tohoku University survived two strong ground motions. This is not surprising because the structure was stiff and strong. What is surprising is that the first ground motion did not cause severe structural damage but the second one caused so much structural damage that the building had to be evacuated and demolished. The damage occurred despite two key facts: (1) the intensities of the mentioned ground motions are understood to have been similar and (2) the building was strengthened after the first motion (and before the second) following stringent standards.

The 30 November 2018 Mw 7.1 Anchorage Earthquake

2019 ◽  
Vol 91 (1) ◽  
pp. 66-84 ◽  
Author(s):  
Michael E. West ◽  
Adrian Bender ◽  
Matthew Gardine ◽  
Lea Gardine ◽  
Kara Gately ◽  
...  
Keyword(s):  
Ground Motion ◽  
Structural Damage ◽  
Ground Motions ◽  
Hazard Evaluation ◽  
Soil Conditions ◽  
Aftershock Activity ◽  
Deep Earthquake ◽  
Near Surface ◽  
Lower Amplitude ◽  
Rupture Mechanism

Abstract The Mw 7.1 47 km deep earthquake that occurred on 30 November 2018 had deep societal impacts across southcentral Alaska and exhibited phenomena of broad scientific interest. We document observations that point to future directions of research and hazard mitigation. The rupture mechanism, aftershocks, and deformation of the mainshock are consistent with extension inside the Pacific plate near the down‐dip limit of flat‐slab subduction. Peak ground motions >25%g were observed across more than 8000  km2, though the most violent near‐fault shaking was avoided because the hypocenter was nearly 50 km below the surface. The ground motions show substantial variation, highlighting the influence of regional geology and near‐surface soil conditions. Aftershock activity was vigorous with roughly 300 felt events in the first six months, including two dozen aftershocks exceeding M 4.5. Broad subsidence of up to 5 cm across the region is consistent with the rupture mechanism. The passage of seismic waves and possibly the coseismic subsidence mobilized ground waters, resulting in temporary increases in stream flow. Although there were many failures of natural slopes and soils, the shaking was insufficient to reactivate many of the failures observed during the 1964 M 9.2 earthquake. This is explained by the much shorter duration of shaking as well as the lower amplitude long‐period motions in 2018. The majority of observed soil failures were in anthropogenically placed fill soils. Structural damage is attributed to both the failure of these emplaced soils as well as to the ground motion, which shows some spatial correlation to damage. However, the paucity of instrumental ground‐motion recordings outside of downtown Anchorage makes these comparisons challenging. The earthquake demonstrated the challenge of issuing tsunami warnings in complex coastal geographies and highlights the need for a targeted tsunami hazard evaluation of the region. The event also demonstrates the challenge of estimating the probabilistic hazard posed by intraslab earthquakes.

Simplified Method of Isolated Structure Collapse Capacity Part, (I): Ground Motion Intensity Measure

2013 ◽  
Vol 275-277 ◽  
pp. 1466-1470
Author(s):  
Yang Liu ◽  
Wen Guang Liu ◽  
Wen Fu He ◽  
Qiao Rong Yang
Keyword(s):  
Correlation Coefficient ◽  
Ground Motion ◽  
Ground Motions ◽  
Near Field ◽  
Far Field ◽  
Intensity Measure ◽  
Maximum Deformation ◽  
Average Value ◽  
Short Period ◽  
Ground Motion Intensity Measure

The equivalent velocity spectrum as a new ground motion intensity measure (IM) characterization parameter is proposed in this paper. 44 far field ground motions and 20 near-field high-speed pulse seismic waves were used for single-degree-freedom (SDOF) nonlinear time history analysis, respectively. The correlations between five IMs and maximum deformation for SDOF at various periods and different yield coefficients were analyzed. The results show that for the structures with medium-to-long period, the correlation coefficient average value of the proposed equivalent speed and maximum deformation is more than 0.6, and maximum of those is more than 0.9. The correlation coefficient average value by using the proposed equivalent speed under far field ground motions is more than those under near field ground motions. The P-delta effect on the correlation coefficients between proposed IM for the structures with medium-to-short period is significant

Empirical Terrain-Based Topographic Modification Factors for Use in Ground Motion Prediction

2017 ◽  
Vol 33 (1) ◽  
pp. 157-177 ◽  
Author(s):  
Manisha Rai ◽  
Adrian Rodriguez-Marek ◽  
Brian S. Chiou
Keyword(s):  
Ground Motion ◽  
Ground Motions ◽  
Prediction Equation ◽  
Motion Prediction ◽  
Topographic Effects ◽  
Ground Motion Prediction ◽  
Modeling Error ◽  
Data Set ◽  
A Site ◽  
The Relationship

We develop a model to predict topographic effects on ground motions using the NGA-West2 data set. Topography at a site is quantified using three parameters: smoothed curvature, smoothed slope, and relative elevation. We examine the relationship between the site residuals, which represent the average modeling error of the reference ground motion prediction equation at a station, and the three topographic parameters. Our analysis shows that there are statistically significant trends in site residuals with respect to relative elevation and smoothed curvature. We propose modification factors to the Chiou and Youngs (2014) model that account for topographic effects on both the median and the standard deviation. These factors are period dependent and are a function of the relative elevation at the site. The factors result in amplification on median by a factor as high as 1.13 at T = 0.5 s for higher values of relative elevation, and deamplification as low as 0.75 between T = 2 s to 3 s for lower values of relative elevations.

scholarly journals Application of wavelet for seismic wave analysis in Kathmandu Valley after the 2015 Gorkha earthquake, Nepal

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Binod Adhikari ◽  
Subodh Dahal ◽  
Monika Karki ◽  
Roshan Kumar Mishra ◽  
Ranjan Kumar Dahal ◽  
...  
Keyword(s):  
Wavelet Transform ◽  
Random Process ◽  
Ground Motion ◽  
Structural Damage ◽  
Ground Motions ◽  
Vertical Motion ◽  
Earthquake Ground Motion ◽  
Kathmandu Valley ◽  
Time Frequency ◽  
Long Period

AbstractIn this paper, we estimate the seismogenic energy during the Nepal Earthquake (25 April 2015) and studied the ground motion time-frequency characteristics in Kathmandu valley. The idea to analyze time-frequency characteristic of seismogenic energy signal is based on wavelet transform which we employed here. Wavelet transform has been used as a powerful signal analysis tools in various fields like compression, time-frequency analysis, earthquake parameter determination, climate studies, etc. This technique is particularly suitable for non-stationary signal. It is well recognized that the earthquake ground motion is a non-stationary random process. In order to characterize a non-stationary random process, it is required immeasurable samples in the mathematical sense. The wavelet transformation procedures that we follow here helps in random analyses of linear and non-linear structural systems, which are subjected to earthquake ground motion. The manners of seismic ground motion are characterized through wavelet coefficients associated to these signals. Both continuous wavelet transform (CWT) and discrete wavelet transform (DWT) techniques are applied to study ground motion in Kathmandu Valley in horizontal and vertical directions. These techniques help to point out the long-period ground motion with site response. We found that the long-period ground motions have enough power for structural damage. Comparing both the horizontal and the vertical motion, we observed that the most of the high amplitude signals are associated with the vertical motion: the high energy is released in that direction. It is found that the seismic energy is damped soon after the main event; however the period of damping is different. This can be seen on DWT curve where square wavelet coefficient is high at the time of aftershock and the value decrease with time. In other words, it is mostly associated with the arrival of Rayleigh waves. We concluded that long-period ground motions should be studied by earthquake engineers in order to avoid structural damage during the earthquake. Hence, by using wavelet technique we can specify the vulnerability of seismically active region and local topological features out there.

Sign in / Sign up

Export Citation Format

Share Document