Strong Motion Data Research Articles

Failures of structures during the January 24, 2020, Sivrice (Elazığ) Earthquake in Turkey

On January 24, 2020, a severe earthquake of magnitude Mw 6.8 hit the Sivrice district of Elazig province at 20:55 (17:55 GMT) local time. This earthquake caused significant damages, partial or total collapses in many buildings with 41 fatalities. A few days after the earthquake, our reconnaissance team visited city centers, districts and villages in the region and, then, carried out an investigation and assessments. The results and suggestions obtained after the earthquakes are very important in designing earthquake-resistant structures and reducing the casualties. This study aims to identify deficiencies and reveal the causes of damages by examining the failure mechanisms of structures. Firstly, the effect of the destructive seismic event is discussed and the historical earthquakes in the region are summarized. Then, strong ground motion data and the structural damages observed from different building types are evaluated. The damage patterns and failure mechanisms are analyzed and interpreted based on the Turkish Earthquake Codes.

The Selection and Scaling of Ground Motion Accelerograms for Use in Stable Continental Regions

ABSTRACT This paper presents an application of the Conditional Mean Spectrum (CMS) methodology for sourcing accelerogram records for use in dynamic analyses of structures in intraplate regions of lower seismicity. The main challenges with deriving CMS for selecting and scaling accelerograms in regions of lower seismicity stem from the paucity of representative strong motion data and event recurrence data. A step-by-step illustration of the methodology is presented using the south-eastern Australia (SEA) region as an example. The study involves making use of a diversity of Ground Motion Prediction Expressions (GMPEs) including a recently developed regionally adjustable Component Attenuation Model (CAM). Three different schemes using a weighted averaging of candidate GMPEs were adopted and a comparison of predictions demonstrated only minor differences confirming the robustness of the modelling. The CMS constructed in this study have been used to develop a proposed suite of scaled accelerograms for SEA.

Strong Ground Motion Sensor Network for Civil Protection Rapid Decision Support Systems.

Strong motion sensor networks deployed in metropolitan areas are able to provide valuable information for civil protection Decision Support Systems (DSSs) aiming to mitigate seismic risk and earthquake social-economic impact. To this direction, such a network is installed and real-time operated in Chania (Crete Island, Greece), city located in the vicinity of the seismically active south front of the Hellenic Subduction Zone. A blend of both traditional and advanced analysis techniques and interpretation methods of strong ground motion data are presented, studying indicative cases of Chania shaking due to earthquakes in the last couple years. The orientation independent spectral acceleration as well as the spatial distribution of the strong ground motion parameters such as the Peak Ground Acceleration (PGA), Peak Ground Velocity (PGV), Peak Ground Displacement (PGD) and Arias Ιntensity observed at the urban area of Chania are presented with the use of a Geographic Information System (GIS) environment. The results point to the importance of the strong ground motion networks as they can provide valuable information on earthquake hazards prior to and after detrimental seismic events to feed rapid systems supporting civil protection decisions for prevention and emergency response.

Confirmation and Characterization of the Rupture Model of the 2017 Ms 7.0 Jiuzhaigou, China, Earthquake

AbstractOn 8 August 2017, an Ms 7.0 earthquake struck the Jiuzhaigou town, Sichuan Province, China, rupturing an unmapped fault, which is adjacent to the Maqu seismic gap in the Min Shan uplift zone in the easternmost part of the Bayan Har block. Having summarized the previous studies on the source of this earthquake, we confirmed the rupture model by jointly inverting the teleseismic P-wave and SH-wave data, Interferometric Synthetic Aperture Radar line-of-sight displacement data, and the near-field seismic and strong-motion data, a most complete dataset until now. The confirmation showed that a scalar seismic moment of 6.6×1018 N·m was released (corresponding to a moment magnitude of Mw 6.5), and 95% of the release occurred in the first 10 s. The slip area was composed of two asperities, with a horizontal extension of ∼20 km and a depth range of ∼2–15 km. A bilateral extending occurred at shallow depths, but the rupturing upward from deep depth dominated in the early time. The rupture process was found generally featuring the slip-pulse mode, which was related to the weak prestress condition. The aftershocks almost took place in gaps of the mainshock slip because of the coulomb stress change. Combining the aftershock relocations, aftershock focal mechanism solutions, and our confirmed rupture model, we suggest that the seismogenic fault was a northward extension of the mapped Huya fault. The occurrence of this earthquake made the Maqu seismic gap at a higher level of seismic risk, in addition to the moderate to high strain accumulation on the easternmost tip of the Kunlun fault system and the weak lower crust below.

A Seismic Intensity Survey of the 16 April 2016 Mw 7.8 Pedernales, Ecuador, Earthquake: A Comparison with Strong-Motion Data and Teleseismic Backprojection

AbstractWe conducted a seismic intensity survey in Ecuador, following the 16 April 2016 Mw 7.8 Pedernales earthquake, to document the level of damage caused by the earthquake. Our modified Mercalli intensities (MMIs) reach a maximum value of VIII along the coast, where single, two, and multistory masonry and concrete designed buildings partially or completely collapsed. The contours of our MMI maps are similar in shape to the contour maps of peak ground acceleration (PGA) and peak ground velocity (PGV). A comparison of our seismic intensities with the recorded PGA and PGV values reveals that our MMI values are lower than predicted by ground-motion intensity conversion equations that are based on shallow crustal earthquakes. The image of the earthquake rupture obtained using teleseismic backprojection at 0.5–2.0 Hz is coincident with the region of maximum MMI, PGA, and PGV values, Thus, rapid calculation of backprojection may be a useful tool for guiding the deployment of emergency response teams following large earthquakes. The most severe damage observed was, primarily, due to a combination of poorly constructed buildings and site conditions.

Source Parameters of Moderate-To-Large Chinese Earthquakes From the Time Evolution of P-Wave Peak Displacement on Strong Motion Recordings

In this work we propose and apply a straightforward methodology for the automatic characterization of the extended earthquake source, based on the progressive measurement of the P-wave displacement amplitude at the available stations deployed around the source. Specifically, we averaged the P-wave peak displacement measurements among all the available stations and corrected the observed amplitude for distance attenuation effect to build the logarithm of amplitude vs. time function, named LPDT curve. The curves have an exponential growth shape, with an initial increase and a final plateau level. By analyzing and modelling the LPDT curves, the information about earthquake rupture process and earthquake magnitude can be obtained. We applied this method to the Chinese strong motion data from 2007 to 2015 with Ms ranging between 4 and 8. We used a refined model to reproduce the shape of the curves and different source models based on magnitude to infer the source-related parameters for the study dataset. Our study shows that the plateau level of LPDT curves has a clear scaling with magnitude, with no saturation effect for large events. By assuming a rupture velocity of 0.9 Vs, we found a consistent self-similar, constant stress drop scaling law for earthquakes in China with stress drop mainly distributed at a lower level (0.2 MPa) and a higher level (3.7 MPa). The derived relation between the magnitude and rupture length may be feasible for real-time applications of Earthquake Early Warning systems.

Slip distribution and rupture history of the August 11, 2012, double earthquakes in Ahar – Varzaghan, Iran, using joint inversion of teleseismic broadband and local strong motion data

We use combined teleseismic and strong motion data sets to investigate finite-fault slip models for a double of earthquakes that occurred on August 11, 2012, in northwestern Iran near the cities of Ahar and Varzaghan. The data include teleseismic P-waveforms retrieved from broadband seismic stations located between 30°–94° from the earthquakes and local strong motion data recorded by the Iran Strong Motion Network, installed and operated by the Building and Housing Research Centre. We first invert teleseismic P-waveforms and local strong motion data separately. For the first event (12:23 UTC), the teleseismic broadband inversion yields a somewhat deeper and simpler distribution of slip than the local strong motion inversion. The strong motion inversion results in a more complex distribution because of higher frequency content but can also be influenced by complexities in the propagation path. For the second event (12:34 UTC), the slip distribution from strong motion data is more similar to the teleseismic result and shows a simple slip area with a small relative movement to the west. To resolve the differences between the results of these two data sets and obtain a better constrained slip model, we perform a joint inversion of teleseismic broadband and local strong motion data.The joint inversion for the first event shows two asperities with a maximum slip of 3.9 m up- dip from the hypocenter and extending to the west between depths of 1 and 5 km. A second narrower high-slip area is seen just above the hypocenter from 6 to 10 km depth. The total moment for this earthquake is calculated to be Mo = 3.8 × 1025 dyn-cm (3.8 × 1018 N.m) (Mw 6.4). For the second event, the results of the joint inversion show a simple slip distribution that is mainly confined in a single patch around the hypocenter with a depth range from about 10 to 13 km and maximum slip of 1.9 m. We compute a total seismic moment of Mo = 1.6 × 1025 dyn-cm (1.6 × 1018 N.m) (Mw 6.1) for the second event. The largest stress drops for the first event occur above the hypocenter with an average stress drop over the rupture area of 120 bar (12 Mpa). For the second event, the maximum stress drop occurs at the reported focal depth with an average stress drop over the rupture area of 80 bar (8 Mpa).

A New Ground Motion Model (GMM) for Northeast India (NEI) and Its Adjacent Countries for Interface Earthquakes Considering Both Strong Motion Records and Simulated Data

A ground motion model (GMM) for interface subduction zone earthquakes of Northeast India (NEI) and its adjacent countries is developed for the first time. Countries adjacent to NEI are Bangladesh, Bhutan, China, Myanmar and Nepal. High-magnitude earthquakes occur frequently in these regions due to buildup of high-stress parameters in the subduction zone of the Indian tectonic plate. Strong motion data are too few and sparse to develop a robust GMM for this region. We used both finite-fault simulations and a stochastic point-source model in developing our GMM. In our GMM, we used 50,000 ground motion samples which were stochastically simulated for different moment magnitudes (Mw) of 5.0–9.0 and hypocentral distances of 30–300 km using a point-source seismological stochastic model and finite fault model. In this study, we calculated stress drop (∆σ), quality factor Q(f) and all other region-specific seismic input parameters from the past strong motion records of interface subduction zone earthquakes of NEI and its adjacent countries. We used these seismic input parameters in ground motion simulation. Sensitivity analyses of the input parameters were also performed to check the bias of the present model. Our GMM was validated by comparing it with the existing NEI interface strong motion records. We compared our GMM with other GMMs developed for interface subduction zone earthquakes for different regions in the world. We also compared our GMM with point-source and finite-fault simulation models. Ground motion parameters estimated using the point-source model are comparatively higher than the finite-fault simulation model. Horizontal components of peak ground acceleration (PGA) and spectral acceleration (Sa) can be estimated for NEI using our GMM.

Duration prediction of Chilean strong motion data using machine learning

Chile is rocked by inslab, interface as well as crustal events. Duration estimates based on Chilean strong motion flatfile is used to predict total duration as well as significant-duration. We use six different machine learning algorithms k-nearest neighbours, support vector machine, Random forest, Neural network, AdaBoost, decision tree and estimate the accuracies of prediction for each component (EW, NS, Z) of ground motion for different tectonic environments. The estimates of duration using machine learning are found to be quite accurate and the best performing machine learning algorithm in prediction of the total duration and the significant-duration are highlighted.

Implications of high-frequency decay parameter, “κ-kappa”, in the estimation of kinematic soil-structure interaction effects

In the present study, the difference between the peak seismic response measures recorded on building basements and those at nearby free-field conditions is studied by means of estimating the high-frequency spectral decay parameter, “κ” (known as “kappa”). Computation of “κ” is performed for selected accelerographic stations belonging to three strong motion networks, namely the Hellenic National Accelerographic Network (HNAN) in Greece, the Center for Engineering Strong Motion Data (CESMD) in California, USA and the Building Research Institute (BRI) in Japan. Parameter “κ” is computer according to Anderson and Hough (1984), while an automated signal energy-based procedure is developed to calculate the S-wave windows of each waveform, accounting for any errors. Site-specific restrictions on the upper frequency limit, f2, for the calculation of “κ” at the foundation level are imposed, based on the empirical transfer functions between foundation and free-field motions. Based on the above procedure, non-linear regression analyses are conducted to relate “κ”, as computed for free-field and foundation motions (κff, - κfnd), to magnitude Mw, source-to-site distance Repi and shear wave velocity VS30. Simulation of ground motions though the point-source stochastic method is accomplished, utilizing the regression expression to define “κ” and assess its effectiveness to predict the variation of intensity between free-field and foundation motions as a proxy for assessing soil-structure interaction effects. It is shown that the regression-based expressions, combined with stochastic simulations, consist a promising tool for correcting seismic motions recorded at a building foundation or basement levels and thus, for reliably predicting the corresponding intensity and characteristics of the actual “building-free” ground motions.

Seismic response of monopile supported offshore wind turbine in liquefiable soil

Offshore wind turbines (OWT) are now constructed in the seismically active regions due to rising energy demand. This study investigates the seismic response of the monopile supported OWT in liquefiable sand deposits under combined operational and seismic loads. A coupled soil-monopile-tower interaction model is developed in OpenSees. Monopile and tower are modelled as linear Euler – Bernoulli beam. Monopile-soil interaction is modelled using nonlinear p-y spring. Free-field motion at the outer spring nodes due to seismic motion is simulated by modelling a soil domain using a two-dimensional plane strain quadrilateral element considering a with a solid–fluid fully coupled model. Various historical strong motion records and spectrum consistent artificial strong motion data are scaled and applied on OWT structure and various operational loads on the structure. The effect of intensity, sustained maximum acceleration of earthquake, and depth of liquefaction on the dynamic response of the OWT structure is studied. A design implication is also suggested for the OWT structure in liquefiable soil.

Accessing European Strong-Motion Data: An Update on ORFEUS Coordinated Services

AbstractStrong ground motion records and free open access to strong-motion data repositories are fundamental inputs to seismology, engineering seismology, soil dynamics, and earthquake engineering science and practice. This article presents the current status and outlook of the Observatories and Research Facilities for European Seismology (ORFEUS) coordinated strong-motion seismology services, namely the rapid raw strong-motion (RRSM) and the engineering strong-motion (ESM) databases and associated web interfaces and webservices. We compare and discuss the role and use of these two systems using the Mw 6.5 Norcia (Central Italy) earthquake that occurred on 30 October 2016 as an example of a well-recorded earthquake that triggered major interest in the seismological and earthquake engineering communities. The RRSM is a fully automated system for rapid dissemination of earthquake shaking information, whereas the ESM provides quality-checked, manually processed waveforms and reviewed earthquake information. The RRSM uses only data from the European Integrated Waveform Data Archive, whereas the ESM also includes offline data from other sources, such as the ITalian ACcelerometric Archive (ITACA). Advanced software tools are also included in the ESM to allow users to process strong-motion data and to select ground-motion waveform sets for seismic structural analyses. The RRSM and ESM are complementary services designed for a variety of possible stakeholders, ranging from scientists to the educated general public. The RRSM and ESM are developed, organized, and reviewed by selected members of the seismological community in Europe, including strong-motion data providers and expert users. Global access and usage of the data is encouraged. The ESM is presently the reference database for harmonized seismic hazard and risk studies in Europe. ORFEUS strong-motion data are open, “Findable, Accessible, Interoperable, and Reusable,” and accompanied by licensing information. The users are encouraged to properly cite the data providers, using the digital object identifiers of the seismic networks.

Network analysis of earthquake ground motion spatial correlation: a case study with the San Jacinto seismic nodal array

SUMMARYThe spatial correlation of earthquake ground motion intensity can be measured from strong motion data; however, the data used in past studies is sparsely sampled in space, and only the interstation distance was considered as a correlation variable. These limitations mean that we have only weak constraints on the true correlation structure of ground motion and that potentially important aspects of spatial correlation are unconstrained. In this study, we combine a large-N seismic array and graph analytics to explore this issue at a local scale using small local and regional earthquakes. Our result suggests site conditions, and how they interact with the incident seismic wavefield, strongly condition the spatial correlation of ground motion. Future progress in characterizing ground motion spatial variability will require dense wavefield measurements, either through nodal deployments, or perhaps distributed acoustic sensing measurements, of seismic wavefields. Aftershock sequences of major earthquakes would provide particularly data-rich targets of opportunity.

The 18 March 2020 M 5.7 Magna, Utah, Earthquake: Strong-Motion Data and Implications for Seismic Hazard in the Salt Lake Valley

Abstract The 2020 oblique normal-faulting M 5.7 Magna mainshock has provided the best dataset of recorded strong ground motions for an earthquake within the Wasatch Front region, Utah, and the larger Basin and Range Province. We performed a preliminary evaluation of the strong motion and broadband data from this earthquake and compared the data with the Next Generation Attenuation - West2 Project (NGA-West2) ground-motion models (GMMs). The highest horizontal peak ground acceleration (PGA) recorded was 0.43g (geometric mean of the two horizontal components) at a station located above the rupture plane at a rupture distance of 8 km. Eleven stations recorded PGAs >0.20g. Most of these stations are located on the deep sedimentary deposits within the Salt Lake Valley, and all are at rupture distances <20 km. The data compare favorably with the NGA-West2 GMMs, although the expected variability was observed. PGAs exceed the GMM predictions at the closest distances for the source model that we used. The area of the strongest ground shaking encompassed the town of Magna, where some of the heaviest damage occurred. A significant implication of the 2020 Magna earthquake for seismic hazards in the Salt Lake Valley arises from the possibility that this earthquake occurred on the Salt Lake City segment of the Wasatch fault. If so, then the dip of this fault segment must decrease with depth to ≤30°–35°, as proposed by Pang et al. (2020)—at least along the northern part of the segment where the earthquake occurred. Because of the lack of information about the subsurface geometry of the Wasatch fault zone, modeling of this fault zone in seismic hazard analyses has assumed a moderate dip of 50°±15°. Assuming a more shallowly dipping fault results in higher estimates of ground shaking in future large earthquakes on this fault. Alternative interpretations of the Magna earthquake are that it occurred (1) on an auxiliary fault within the Wasatch fault zone or (2) on a listric section of the northern Salt Lake City segment that is not representative of the geometry of the whole fault segment.

Rupture Process of the Mainshock of the 2019 Ridgecrest Earthquake Sequence from Waveform Inversion with Empirical Green’s Functions

ABSTRACTThe 2019 Mw 7.1 mainshock of the Ridgecrest earthquake sequence, which was the first event exceeding Mw 7.0 in California since the 1999 Hector Mine earthquake, caused near-fault ground motions exceeding 0.5g and 70 cm/s. In this study, the rupture process and the generation mechanism of strong ground motions of the mainshock were investigated through waveform inversions of strong-motion data in the frequency range of 0.2–2.0 Hz using empirical Green’s functions (EGFs). The results suggest that the mainshock involved two large slip regions: the primary one with a maximum slip of approximately 4.4 m was centered ∼3 km northwest of the hypocenter, which was slightly shallower than the hypocenter, and the secondary one was centered ∼25 km southeast of the hypocenter. Outside these regions, the slip was rather small and restricted to deeper parts of the fault. A relatively small rupture velocity of 2.1 km/s was identified. The robustness of the slip model was examined by conducting additional inversion analyses with different combinations of EGF events and near-fault stations. In addition, using the preferred slip model, we synthesized strong motions at stations that were not used in the inversion analyses. The synthetic waveforms captured the timing of the main phases of observed waveforms, indicating the validity of the major spatiotemporal characteristics of the slip model. Our large slip regions are also generally visible in the models proposed by other researchers based on different datasets and focusing on lower frequency ranges (generally lower than 0.5 Hz). In particular, two large slip regions in our model are very consistent with two of the four subevents identified by Ross et al. (2019), which may indicate that part of the large slip regions that generated low-frequency ground motions also generated high-frequency ground motions up to 2.0 Hz during the Ridgecrest mainshock.

Similarities and Differences in the Rupture Processes of the 1952 and 2003 Tokachi‐Oki Earthquakes

AbstractWe investigated the similarities and differences between the rupture processes of the 1952 and 2003 Tokachi‐oki earthquakes (Mw ∼ 8) that occurred 51 years apart in the southernmost region of the Kuril subduction zone. This event pair is rare because seismic waveforms of both events were instrumentally recorded. We performed joint source inversion analyses of both earthquakes to better understand the rupture processes of this earthquake sequence. The dataset for the 1952 earthquake consists of teleseismic and strong motion data which were obtained by digitizing copies of analog seismograms. Two datasets were made for the 2003 earthquake to examine the effect of data limitation and to facilitate a comparison of the inversion results of the two earthquakes. One dataset consists of a large amount of teleseismic, strong motion, and geodetic data. The other dataset is similar to that of the 1952 earthquake. Our results show that the rupture propagation, slip areas, and maximum slip amounts were similar for the 1952 and 2003 earthquakes in the Tokachi‐oki region. However, there are two important differences: the 1952 earthquake was initiated by an Mw 6.1 subevent in the Tokachi‐oki region, and its rupture extended to the adjacent Akkeshi‐oki region. The similarity in the rupture pattern of the M8‐class earthquake pair suggests the persistence of asperities on the plate interface, while the differences imply a degree of variability in the initiation and termination of the cascading rupture process.

Re-digitization of Strong Motion Data Recorded by SMAC-M Accelerographs

Re-digitization of Strong Motion Data Recorded by SMAC-M Accelerographs

A Ground-Motion Prediction Model for Shallow Crustal Earthquakes in Greece

ABSTRACT Using a recently completed database of uniformly processed strong-motion data recorded in Greece, we derive a ground-motion prediction model (GMPM) for horizontal-component peak ground velocity, peak ground acceleration, and 5% damped pseudoacceleration response spectra, at 105 periods ranging from 0.01 to 10 s. The equations were developed by modifying a global GMPM, to account for more rapid attenuation and weaker magnitude scaling in the Greek ground motions than in the global GMPM. Our GMPM is calibrated using the Greek data for distances up to 300 km, magnitudes from 4.0 to 7.0, and time-averaged 30 m shear-wave velocities from 150 to 1200 m/s. The GMPM has important attributes for hazard applications including magnitude scaling that extends the range of applicability to M 8.0 and nonlinear site response. These features are possible because they are well constrained by data in the global GMPM from which our model is derived. An interesting feature of the Greek data, also observed previously in studies of mid-magnitude events (6.1–6.5) in Italy, is that they are substantially overpredicted by the global GMPM, which may be a repeatable regional feature, but may also be influenced by soil–structure interaction. This bias is an important source of epistemic uncertainty that should be considered in hazard analysis.

Ground-Motion Model for Deep Intraslab Subduction Zone Earthquakes of Northeastern India (NEI) and Adjacent Regions

ABSTRACTIn this study, a ground-motion model (GMM) for deep intraslab subduction zone earthquakes in northeastern India (NEI) and adjacent regions, including portions of Bangladesh, Bhutan, China, Myanmar, and Nepal, is developed. Strong-motion data for deep intraslab earthquakes in NEI are very sparse, so it is not possible to develop a robust empirical GMM; hence, we used the stochastic point-source model to develop a new GMM. The model is based on ground-motion simulations of 36,500 Mw 5–8 earthquakes and epicentral distances of 50–300 km. We used region-specific key seismic parameters, for example, stress parameter, quality factor, and path duration in ground-motion simulation. Sensitivity analyses were also performed to evaluate the bias of each key seismic input parameter. We compared our GMM with the existing strong-motion data and compared our model with those of Lin and Lee (2008), Abrahamson et al. (2016), and Idini et al. (2017), which were developed for intraslab earthquakes based on VS30 and hypocentral depth. Our model gives higher values compared with their GMMs. Both peak ground acceleration and spectral acceleration values are estimated for NEI and adjacent regions intraslab earthquakes.

Source and strong-motion characteristics of two M\u2009>\u20096 buried earthquakes in southwest Taiwan

We used near-field strong-motion data to investigate the complex combination of source effect and site response for two recent disastrous earthquakes in southwest Taiwan. We estimated strong-motion generation areas (SMGAs) of 2.8 km × 2.8 km and 6.0 km × 4.2 km in a frequency band of 0.4–10 Hz for the 2010 Jiashian and 2016 Meinong earthquakes, respectively. The high-stress drops of 26.2 and 17.0 MPa for these two buried events were potentially related to the small dimension and deep rupture. Our results revealed that both earthquakes exhibited westward rupture directivity, whereas the 2016 Meinong event exhibited a stronger directivity effect because of the consistency between the propagation and slip directions. The localized high peak ground velocity (PGV) patch and the nonlinear site response could be attributed to the soft sediment with high pore fluid pressure and low-velocity structure beneath this region. However, the greater seismic moment and closer faulting location to the thick-mudstone-layer region for the 2016 Meinong event reinforced the strong ground shaking and serious damage over the broad area. This implies that this thick-mudstone-layer region in southern Taiwan plays a crucial role in earthquake response, and an investigation of characteristic site effects should be conducted for seismic hazard mitigation.Graphic abstract