Imaging the rupture process of recent earthquakes using backprojection of local high frequency records

2020 ◽  
Author(s):  
Ioannis Fountoulakis ◽  
Christos Evangelidis ◽  
Olga-Joan Ktenidou
Keyword(s):  
High Frequency ◽  
A Priori ◽  
Strong Motion ◽  
Seismic Hazard Assessment ◽  
Seismic Source ◽  
Site Effect ◽  
Source Inversion ◽  
Waveform Data ◽  
Novel Approach ◽  
Spatio Temporal

<p>The seismic source spatio-temporal rupture processes of events in Japan, Greece and Turkey are imaged by backprojection of strong-motion waveforms. Normalized high-frequency (> 2Hz) S-waveforms from recordings on dense strong-motion networks are used to scan a predefined 3D source volume over time. </p><p>Backprojection is an alternative novel approach to image the spatio-temporal earthquake rupture. The method was first applied for large earthquakes at teleseismic distances, but is nowadays also used at local distances and over higher frequencies. The greatest advantage of the method is that processing is done without any a-priori constraints on the geometry, or size of the source. Thus, the spatio-temporal imaging of the rupture is feasible at higher frequencies (> 1Hz) than conventional source inversion studies, even when the examined fault geometry is complex. This high-frequency energy emitted during an earthquake is of great importance in seismic hazard assessment for certain critical infrastructures. The actual challenge in using high-frequency local recordings is to distinguish the local site effects from the true earthquake source content - otherwise, mapping the former incorrectly onto the latter limits the resolvability of the method. It is not straightforward to remove the site effect component or even to distinguish good reference stations from amid hard-soil and rock sites. In this study, the advantages and limitations of the method are explored using waveform data from well-recorded events in Japan (Kumamoto Mw7.1, 2016), Turkey (Marmara Mw6.4, 2019) and Greece (Antikythera Mw6.1, 2019). For each event and seismic array the resolution limits of the applied method are explored by performing various synthetic tests.</p>

Rupture process of the Ms 6.6 Superstition Hills, California, earthquake determined from strong-motion recordings: Application of tomographic source inversion

1989 ◽  
Vol 79 (2) ◽  
pp. 515-541
Author(s):  
Arthur Frankel ◽  
Leif Wennerberg
Keyword(s):  
Wave Velocity ◽  
High Frequency ◽  
Slow Component ◽  
Surface Displacement ◽  
Strong Motion ◽  
Seismic Energy ◽  
P Wave ◽  
Source Inversion ◽  
Long Time ◽  
Northern Portion

Abstract We analyze strong-motion recordings of the Ms 6.6 Superstition Hills earthquake to determine the timing, location, spatial extent, and rupture velocity of the subevents that produced the bulk of the high-frequency (0.5 to 4 Hz) seismic energy radiated by this shock. The earthquake can be characterized by three principal subevents, the largest ones occurring about 3 and 10 sec after initiation of rupture. Timing relationships between pulses on the seismograms indicate that the three subevents are located within 8 km of each other along the northern portion of the Superstition Hills fault. The two largest subevents display different directivity effects. We apply a tomographic source inversion to the integrated accelerograms to determine the slip acceleration on the fault as a function of time and distance, based on a one-dimensional fault model. The azimuthal distribution of amplitudes for the second subevent can be largely explained by a rupture that propagated about 2 km to the southeast along the Superstition Hills fault at a velocity about equal to the P-wave velocity. An alternative model with rupture propagating to the northeast along a conjugate fault plane can also account for the observed directivity of this subevent, but it is not supported by the aftershock distribution. The third subevent ruptured to the southeast along an 8-km long portion of the Superstition Hills fault at about the shear-wave velocity. This rupture propagation caused the relatively large accelerations and velocities observed in strong-motion records for stations southeast of the hypocenter. The long time intervals between the subevents and their relative proximity to each other indicate a very slow component to the rupture development. The southern half of the Superstition Hills fault did not generate significant high-frequency strong ground motion, although it showed substantial co-seismic surface displacement. The subevents are situated along the same northern portion of the fault where most of the aftershocks are located. The locations of the subevents appear to be controlled by bends in the fault mapped at the surface and by changes in basement structure at depth.

Imaging the Samos 2020 Mw7.0 earthquake rupture by backprojecting local strong-motion recordings and relocating the aftershock sequence

2021 ◽  
Author(s):  
Ioannis Fountoulakis ◽  
Christos P. Evangelidis ◽  
Olga-Joan Ktenidou
Keyword(s):  
High Frequency ◽  
A Priori ◽  
Research Work ◽  
Strong Motion ◽  
Aftershock Sequence ◽  
Earthquake Rupture ◽  
Moment Tensors ◽  
Research And Innovation ◽  
Frequency Radiation ◽  
High Frequency Radiation

<p>On November 30, 2020 11:51 UTC, a major earthquake (Mw7.0) struck the northern area offshore Samos island, Greece, causing serious damage to the island and nearby Turkish coast. This seismic event is an ideal opportunity to explore extensional seismicity in the back-arc area of the Hellenic subduction zone. To that end, first and foremost we study the behavior and characteristics of the main event source. Then, we examine the evolution of the aftershock in space and time and relate it to the main event. We implement the technique of local backprojection on strong-motion recordings  (e.g. Kao & Shan, 2007; Evangelidis, 2013) to infer the spatiotemporal distribution of the earthquake source. This method is performed at relatively short periods, making it possible to map in detail the high-frequency radiation of the source, without imposing any a priori constraints on the geometry or shape of the ruptured fault. Furthermore, and which is not often the case, the strong-motion recordings were carefully assessed prior to being used in backprojection, in order to avoid any significant influence of local site effects and amplification, which could in impact the robustness of the backprojection solution. Synthetic tests were also used to resolve the accuracy. Our results show evidence of multiple distinct sources of high-frequency radiation during the earthquake rupture. In addition, the first month of the aftershock sequence was located, clustered and relocated, ultimately highlighting the faults activated in the area. The quality of the resulting high-resolution catalogue was further assessed, and the moment tensors of the strongest events were estimated. Combining the backprojection results with the detailed picture of the aftershock seismic sequence leads to an interpretation of the short- and long-term fault rupture process and their associated secondary effects (tsunami, landslides) in the area. </p><p>The research work was supported by the Hellenic Foundation for Research and Innovation (H.F.R.I.) under the “First Call for H.F.R.I. Research Projects to support Faculty members and Researchers and the procurement of high-cost research equipment grant” (SIREN, Project Number: 910).</p><p> </p>

Assessment of performance of an automatic procedure for a review of recent seismicity in Western Alps compiling an homogeneous and reliable catalog

2020 ◽  
Author(s):  
Fabrizio Bosco ◽  
Daniele Spallarossa ◽  
Anne Deschamps
Keyword(s):  
Travel Time ◽  
Strong Motion ◽  
Seismic Hazard Assessment ◽  
Western Alps ◽  
Quality Parameters ◽  
Raw Data ◽  
Cross Border ◽  
Seismic Catalogs ◽  
Motion Parameters ◽  
Spatio Temporal

<p>The Alpine chain marks the border between different nations, so it’s important in this area the cooperation, the data sharing and the coordination among institutions operating in contiguous regions and nations that are involved in the observation and the management of natural hazards such as earthquakes affecting large portions of the territory.</p><p>As part of the Interreg Alcotra cross-border program, one of the objectives of the RISVAL project concerns the improvement of the seismic hazard assessment and in general of the knowledge of seismicity in the Western Alps. In this area, Italian, French and Swiss stations operate in various national and regional networks, connected to each other, sharing data also with European services (e.g. EIDA). Streaming raw data are the basic type of data shared, since each institution produces its own analyses and computed data, resulting for instance in different seismic catalogs, with of course different characteristics, also in spatio-temporal boundaries.</p><p>Furthermore the monitoring and analysis systems have been interested over the years by technological developments, so that the available data grow exponentially and the catalogs derived from the surveillance activities in near-real time show several internal inhomogeneities in the various time intervals, also considering the different sensitivity and subjectivity of the operators who alternate in carrying out the manual review.</p><p>Therefore emerges the need to process increasingly large amounts of data available, that could be re-analyzed and updated in a homogeneous way according to new developments. To face this effort we wanted to test the performance of a complete automatic procedure (Scafidi et. al, 2019) to re-compile a portion (2012-2019) of the seismic catalog derived by RSNI network (Regional Seismic network of Northwestern Italy) operating routines, including travel-time and strong-motion parameters dataset.</p><p>The procedure, driven by customizable set of parameters suitable for network geometry and seismicity features, relies on a multistep algorithm, that in this work we tested skipping the initial steps concerning the event detection tool on continuous raw data. So we perform it on 21391 already available detected waveform traces for 1549 events: 1) automatic P- and S-phase picker, 2) hypocenter locator (using NonLinLoc package and 3D velocities model), 3) magnitude and strong-motion parameter calculator.</p><p>We firstly evaluate the results for the re-compiled catalog both in terms of distributions of errors and other quality parameters and in terms of time-residuals distributions on the basis of azimuth variation for each station, distinguishing shorter and longer epicentral distances, in order to evaluate anomalies in propagation velocities pattern.</p><p>Then we compare the new catalog results with manual catalogs available in the area, to point out differences in sources and stations calculated parameters: primarily the original RSNI, confirming the reliability of the method, then the Italian national CPTI by INGV, and, with a closer view in the cross-border Alps area, the French ones (RéNaSS, Sismoazur, SISmalp).</p><p>Scafidi D. et al. 2019. A Complete Automatic Procedure to Compile Reliable Seismic Catalogs and Travel-Time and Strong-Motion Parameters Datasets, in Seismological Research Letters, Volume XX, Number XX – 2019, DOI: 10.1785/02201802</p>

scholarly journals Construction of fault geometry by finite-fault inversion of teleseismic data

2020 ◽  
Vol 224 (2) ◽  
pp. 1003-1014
Author(s):  
Kousuke Shimizu ◽  
Yuji Yagi ◽  
Ryo Okuwaki ◽  
Yukitoshi Fukahata
Keyword(s):  
Fault Plane ◽  
Seismic Source ◽  
Rupture Process ◽  
Inversion Method ◽  
Source Inversion ◽  
Fault Geometry ◽  
Waveform Data ◽  
Finite Fault Inversion ◽  
Finite Fault ◽  
Double Couple

SUMMARY Conventional seismic source inversion estimates the earthquake rupture process on an assumed fault plane that is determined a priori. It has been a difficult challenge to obtain the fault geometry together with the rupture process by seismic source inversion because of the nonlinearity of the inversion technique. In this study, we propose an inversion method to estimate the fault geometry and the rupture process of an earthquake from teleseismic P waveform data, through an elaboration of our previously published finite-fault inversion analysis (Shimizu et al. 2020). That method differs from conventional methods by representing slip on a fault plane with five basis double-couple components, expressed by potency density tensors, instead of two double-couple components compatible with the fault direction. Because the slip direction obtained from the potency density tensors should be compatible with the fault direction, we can obtain the fault geometry consistent with the rupture process. In practice we rely on an iterative process, first assuming a flat fault plane and then updating the fault geometry by using the information included in the obtained potency density tensors. In constructing a non-planar model-fault surface, we assume for simplicity that the fault direction changes only in either the strike or the dip direction. After checking the validity of the proposed method through synthetic tests, we applied it to the MW 7.7 2013 Balochistan, Pakistan, and MW 7.9 2015 Gorkha, Nepal, earthquakes, which occurred along geometrically complex fault systems. The modelled fault for the Balochistan earthquake is a curved strike-slip fault convex to the south-east, which is consistent with the observed surface ruptures. The modelled fault for the Gorkha earthquake is a reverse fault with a ramp-flat-ramp structure, which is also consistent with the fault geometry derived from geodetic and geological data. These results exhibit that the proposed method works well for constraining fault geometry of an earthquake.

Rupture parameters of dynamic source models compatible with NGA-West2 GMPEs

2020 ◽  
Author(s):  
Frantisek Gallovic ◽  
Lubica Valentova
Keyword(s):  
Ground Motions ◽  
Source Parameters ◽  
Strong Motion ◽  
Seismic Hazard Assessment ◽  
Response Spectra ◽  
Maximum Magnitude ◽  
Source Inversion ◽  
Dynamic Rupture ◽  
Heterogeneous Distribution ◽  
Dynamic Source

<p>Dynamic source inversions of individual earthquakes provide constraints on stress and frictional parameters, which are inherent to the studied event. However, general characteristics of both kinematic and dynamic rupture parameters are not well known, especially in terms of their variability. Here we constrain them by creating and analyzing a synthetic event database of dynamic rupture models that generate waveforms compatible with strong ground motions in a statistical sense.</p><p>We employ a framework that is similar to the Bayesian dynamic source inversion by Gallovič et al. (2019). Instead of waveforms of a single event, the data are represented by Ground Motion Prediction Equations (GMPEs), namely NGA-West2  (Boore et al., 2014). The Markov chain Monte Carlo technique produces samples of the dynamic source parameters with heterogeneous distribution on a fault. For all simulations, we assume a vertical 36x20km strike-slip fault, which limits our maximum magnitude to Mw<7. For dynamic rupture calculations, we employ upgraded finite-difference code FD3D_TSN (Premus et al., 2020) with linear slip-weakening friction law. Seismograms are calculated on a regular grid of phantom stations assuming a 1D velocity model using precalculated full wavefield Green's functions. The procedure results in a database with those dynamic rupture models that generate ground motions compatible with the GMPEs (acceleration response spectra in period band 0.5-5s) in terms of both median and variability.</p><p>The events exhibit various magnitudes and degrees of complexity (e.g. one or more asperities). We inspect seismologically determinable parameters, such as duration, moment rate spectrum, stress drop, size of the ruptured area, and energy budget, including their variabilities.  Comparison with empirically derived values and scaling relations suggests that the events are compatible with real earthquakes (Brune, 1970, Kanamori and Brodsky, 2004). Moreover, we investigate the stress and frictional parameters in terms of their scaling, power spectral densities, and possible correlations. The inferred statistical properties of the dynamic source parameters can be used for physics-based strong-motion modeling in seismic hazard assessment.</p>

Waveform Data Collection for Source Inversion Studies

1988 ◽  
Author(s):  
William N. Alexander ◽  
Raymond H. Kimmel ◽  
Lauren Malaspina
Keyword(s):  
Data Collection ◽  
Source Inversion ◽  
Waveform Data

scholarly journals Novel approach to modeling high-frequency activity data to assess therapeutic effects of analgesics in chronic pain conditions

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Zekun Xu ◽  
Eric Laber ◽  
Ana-Maria Staicu ◽  
B. Duncan X. Lascelles
Keyword(s):  
High Frequency ◽  
Activity Patterns ◽  
Treatment Strategies ◽  
Therapeutic Effects ◽  
Activity Levels ◽  
Activity Data ◽  
Novel Approach ◽  
High Frequency Activity ◽  
Using Data ◽  
Chronic Pain Conditions

AbstractOsteoarthritis (OA) is a chronic condition often associated with pain, affecting approximately fourteen percent of the population, and increasing in prevalence. A globally aging population have made treating OA-associated pain as well as maintaining mobility and activity a public health priority. OA affects all mammals, and the use of spontaneous animal models is one promising approach for improving translational pain research and the development of effective treatment strategies. Accelerometers are a common tool for collecting high-frequency activity data on animals to study the effects of treatment on pain related activity patterns. There has recently been increasing interest in their use to understand treatment effects in human pain conditions. However, activity patterns vary widely across subjects; furthermore, the effects of treatment may manifest in higher or lower activity counts or in subtler ways like changes in the frequency of certain types of activities. We use a zero inflated Poisson hidden semi-Markov model to characterize activity patterns and subsequently derive estimators of the treatment effect in terms of changes in activity levels or frequency of activity type. We demonstrate the application of our model, and its advance over traditional analysis methods, using data from a naturally occurring feline OA-associated pain model.

A novel approach for quantifying high-frequency urban land cover changes at the block level with scarce clear-sky Landsat observations

2021 ◽  
Vol 255 ◽  
pp. 112293
Author(s):  
Chuanbao Jing ◽  
Weiqi Zhou ◽  
Yuguo Qian ◽  
Wenjuan Yu ◽  
Zhong Zheng
Keyword(s):  
Land Cover ◽  
High Frequency ◽  
Urban Land ◽  
Land Cover Changes ◽  
Clear Sky ◽  
Urban Land Cover ◽  
Novel Approach ◽  
Block Level

scholarly journals Extracting Stops from Spatio-Temporal Trajectories within Dynamic Contextual Features

2021 ◽  
Vol 13 (2) ◽  
pp. 690
Author(s):  
Tao Wu ◽  
Huiqing Shen ◽  
Jianxin Qin ◽  
Longgang Xiang
Keyword(s):  
Moving Objects ◽  
Major Effect ◽  
Location Based Services ◽  
Trajectory Data ◽  
The Road ◽  
Contextual Features ◽  
Novel Approach ◽  
Gps Trajectories ◽  
Time Distance ◽  
Spatio Temporal

Identifying stops from GPS trajectories is one of the main concerns in the study of moving objects and has a major effect on a wide variety of location-based services and applications. Although the spatial and non-spatial characteristics of trajectories have been widely investigated for the identification of stops, few studies have concentrated on the impacts of the contextual features, which are also connected to the road network and nearby Points of Interest (POIs). In order to obtain more precise stop information from moving objects, this paper proposes and implements a novel approach that represents a spatio-temproal dynamics relationship between stopping behaviors and geospatial elements to detect stops. The relationship between the candidate stops based on the standard time–distance threshold approach and the surrounding environmental elements are integrated in a complex way (the mobility context cube) to extract stop features and precisely derive stops using the classifier classification. The methodology presented is designed to reduce the error rate of detection of stops in the work of trajectory data mining. It turns out that 26 features can contribute to recognizing stop behaviors from trajectory data. Additionally, experiments on a real-world trajectory dataset further demonstrate the effectiveness of the proposed approach in improving the accuracy of identifying stops from trajectories.

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