Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Impulsive Source of the 2017 M_W=7.3 Ezgeleh, Iran, Earthquake.

ABSTRACT: On 12 November 2017, a M _W=7.3 earthquake struck near the Iranian town of Ezgeleh, at the Iran-Iraq border. This event was located within the Zagros fold and thrust belt which delimits the continental collision between the Arabian and Eurasian Plates. Despite a high seismic risk, the seismogenic behavior of the complex network of active faults is not well documented in this area due to the long recurrence interval of large earthquakes. In this study, we jointly invert interferometric synthetic aperture radar and near-field strong motions to infer a kinematic slip model of the rupture. The incorporation of these near-field observations enables a fine resolution of the kinematic rupture process. It reveals an impulsive seismic source with a strong southward rupture directivity, consistent with significant damage south of the epicenter. We also show that the slip direction does not match plate convergence, implying that some of the accumulated strain must be partitioned onto other faults.

SUBMITTER: Gombert B

PROVIDER: S-EPMC6774306 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Impulsive Source of the 2017 MW=7.3 Ezgeleh, Iran, Earthquake.

Gombert B B Duputel Z Z Shabani E E Rivera L L Jolivet R R Hollingsworth J J

Geophysical research letters 20190529 10

On 12 November 2017, a M W=7.3 earthquake struck near the Iranian town of Ezgeleh, at the Iran-Iraq border. This event was located within the Zagros fold and thrust belt which delimits the continental collision between the Arabian and Eurasian Plates. Despite a high seismic risk, the seismogenic behavior of the complex network of active faults is not well documented in this area due to the long recurrence interval of large earthquakes. In this study, we jointly invert interferometric ...[more]

PMID: 31598017

Similar Datasets

Earthquake in Western Iran: Renovation Kills.

Project description:Earthquake is the most important cause of death from natural disasters in Iran. This paper brings attention to the main causes of loss of life due to the Kermanshah province earthquake (Nov 12 2017), and provides a wakeup call about the unsafe nature of buildings there. This study is based on official reports review and a field assessment in the areas affected by the earthquake in western Iran. Although buildings in this area are mainly old structures, strangely, more than 70% of the destroyed buildings in this earthquake were under 5 years of age, newly built or renovated buildings according to mandated building codes. Mandated building codes and construction rules and regulations are not respected even for the newly constructed or reconstructed structures buildings.

| S-EPMC6117122 | biostudies-literature

GPS source solution of the 2004 Parkfield earthquake.

Project description:We compute a series of finite-source parameter inversions of the fault rupture of the 2004 Parkfield earthquake based on 1?Hz GPS records only. We confirm that some of the co-seismic slip at shallow depth (<5?km) constrained by InSAR data processing results from early post-seismic deformation. We also show 1) that if located very close to the rupture, a GPS receiver can saturate while it remains possible to estimate the ground velocity (~1.2?m/s) near the fault, 2) that GPS waveforms inversions constrain that the slip distribution at depth even when GPS monuments are not located directly above the ruptured areas and 3) the slip distribution at depth from our best models agree with that recovered from strong motion data. The 95(th) percentile of the slip amplitudes for rupture velocities ranging from 2 to 5?km/s is ~55 ± 6?cm.

| S-EPMC3894560 | biostudies-literature

Spatiotemporal Graph Convolutional Networks for Earthquake Source Characterization.

Project description:Accurate earthquake location and magnitude estimation play critical roles in seismology. Recent deep learning frameworks have produced encouraging results on various seismological tasks (e.g., earthquake detection, phase picking, seismic classification, and earthquake early warning). Many existing machine learning earthquake location methods utilize waveform information from a single station. However, multiple stations contain more complete information for earthquake source characterization. Inspired by recent successes in applying graph neural networks (GNNs) in graph-structured data, we develop a Spatiotemporal Graph Neural Network (STGNN) for estimating earthquake locations and magnitudes. Our graph neural network leverages geographical and waveform information from multiple stations to construct graphs automatically and dynamically by adaptive message passing based on graphs' edges. Using a recent graph neural network and a fully convolutional neural network as baselines, we apply STGNN to earthquakes recorded by the Southern California Seismic Network from 2000 to 2019 and earthquakes collected in Oklahoma from 2014 to 2015. STGNN yields more accurate earthquake locations than those obtained by the baseline models and performs comparably in terms of depth and magnitude prediction, though the ability to predict depth and magnitude remains weak for all tested models. Our work demonstrates the potential of using GNNs and multiple stations for better automatic estimation of earthquake epicenters.

| S-EPMC10078111 | biostudies-literature

Seismic and Aseismic Fault Slip During the Initiation Phase of the 2017 M W = 6.9 Valparaiso Earthquake.

Project description:Transient deformation associated with foreshocks activity has been observed before large earthquakes, suggesting the occurrence of a detectable preseismic slow slip during the initiation phase. A critical issue consists in discriminating the relative contributions from seismic and aseismic fault slip during the preparation phase of large earthquakes. We focus on the April-May 2017 Valparaíso earthquake sequence, which involved a M W = 6.9 earthquake preceded by intense foreshock activity. To assess the relative contribution of seismic and aseismic slip, we compare surface displacement predicted from foreshocks source models with transient motion measured prior to the mainshock. The comparison between observed and predicted displacements shows that only half of the total displacement can be explained by the contribution of foreshocks. This result suggests the presence of aseismic pre-slip during an initiation phase preceding the mainshock.

| S-EPMC8047919 | biostudies-literature

Flupirtine Analogues: Explorative Synthesis and Influence of Chemical Structure on KV7.2/KV7.3 Channel Opening Activity.

Project description:Neuronal voltage-gated potassium channels KV7.2/KV7.3 are sensitive to small-molecule drugs such as flupirtine, even though physiological response occurs in the absence of ligands. Clinically, prolonged use of flupirtine as a pain medication is associated with rare cases of drug-induced liver injury. Thus, safety concerns prevent a broader use of this non-opioid and non-steroidal analgesic in therapeutic areas with unmet medical needs such as hyperactive bladder or neonatal seizures. With the goal of studying influences of chemical structure on activity and toxicity of flupirtine, we explored modifications of the benzylamino bridge and the substitution pattern in both rings of flupirtine. Among twelve derivatives, four novel thioether derivatives showed the desired activity in cellular assays and may serve as leads for safer KV channel openers.

| S-EPMC6331712 | biostudies-literature

Pulmonary Nocardia ignorata Infection in Gardener, Iran, 2017.

Project description:Nocardia ignorata, which was first described in 2001, is a rare human pathogen. We report a case of pulmonary nocardiosis caused by this bacterium in a 55-year-old man from Iran. The patient, a gardener, had frequent exposure to soil and may have acquired the infection from that source.

| S-EPMC7045840 | biostudies-literature

Tomography of the source zone of the great 2011 Tohoku earthquake.

Project description:The mechanism and rupture process of the giant 2011 Tohoku-oki earthquake (Mw 9.0) are still poorly understood due to lack of permanent near-field observations. Using seismic arrival times recorded by dense seismograph networks on land and at ocean floor, we determine a detailed seismic tomography model of the megathrust zone beneath the Tohoku forearc. Our results show that the coseismic slip of the 2011 Tohoku-oki earthquake initiated at a boundary between a down-dip high-velocity anomaly and an up-dip low-velocity anomaly. The slow anomaly at shallow depths near the Japan trench may reflect low-rigidity materials that are close to the free surface, resulting in large slip and weak high-frequency radiation. Our new tomographic model can account for not only large slip near the trench but also weak high-frequency radiation from the shallow rupture areas.

| S-EPMC7054414 | biostudies-literature

Earthquake source characterization by machine learning algorithms applied to acoustic signals.

Project description:Underwater seismic events generate acoustic radiation (such as acoustic-gravity waves), that carries information about the source and can travel long distances before dissipating. Effective early warning, emergency response, and information dissemination for earthquakes and tsunamis require a rapid characterisation of the fault properties: geometry and dynamics. In this work, we analysed hydrophone recordings of 201 earthquakes, located in the Pacific and the Indian Ocean, by employing acoustic signal processing and classification methods. The analysis allows identifying the type of earthquake (i.e. slip type, magnitude) and provides near real-time estimation of the effective properties of the fault dynamics and geometry. The results were compared against values reported by the Harvard Global Centroid Moment Tensor catalog (gCMT), revealing statistical significance between the extracted acoustic properties used to feed machine learning algorithms and the predicted slip and magnitude values.

| S-EPMC8630080 | biostudies-literature