scholarly journals Uncertainties in the 2004 Sumatra–Andaman source through nonlinear stochastic inversion of tsunami waves

2017 ◽  
Vol 473 (2205) ◽  
pp. 20170353 ◽  
Author(s):  
D. Gopinathan ◽  
M. Venugopal ◽  
D. Roy ◽  
K. Rajendran ◽  
S. Guillas ◽  
...  
Keyword(s):  
Joint Inversion ◽  
A Priori ◽  
Source Parameters ◽  
Early Warning Systems ◽  
Physical Models ◽  
Parameter Distribution ◽  
Remarkable Feature ◽  
Tsunami Waves ◽  
Earthquake Source Parameters ◽  
Finite Fault

Numerical inversions for earthquake source parameters from tsunami wave data usually incorporate subjective elements to stabilize the search. In addition, noisy and possibly insufficient data result in instability and non-uniqueness in most deterministic inversions, which are barely acknowledged. Here, we employ the satellite altimetry data for the 2004 Sumatra–Andaman tsunami event to invert the source parameters. We also include kinematic parameters that improve the description of tsunami generation and propagation, especially near the source. Using a finite fault model that represents the extent of rupture and the geometry of the trench, we perform a new type of nonlinear joint inversion of the slips, rupture velocities and rise times with minimal a priori constraints. Despite persistently good waveform fits, large uncertainties in the joint parameter distribution constitute a remarkable feature of the inversion. These uncertainties suggest that objective inversion strategies should incorporate more sophisticated physical models of seabed deformation in order to significantly improve the performance of early warning systems.

Quick determination of earthquake source parameters from GPS measurements: a study of suitability for Taiwan

2019 ◽  
Vol 219 (2) ◽  
pp. 1148-1162
Author(s):  
Jiun-Ting Lin ◽  
Wu-Lung Chang ◽  
Diego Melgar ◽  
Amanda Thomas ◽  
Chi-Yu Chiu
Keyword(s):  
Rapid Determination ◽  
Moment Tensor ◽  
Near Field ◽  
Source Parameters ◽  
Early Warning Systems ◽  
Earthquake Magnitude ◽  
Observation System ◽  
Earthquake Source Parameters ◽  
Finite Fault

SUMMARY We test the feasibility of GPS-based rapid centroid moment tensor (GPS CMT) methods for Taiwan, one of the most earthquake prone areas in the world. In recent years, Taiwan has become a leading developer of seismometer-based earthquake early warning systems, which have successfully been applied to several large events. The rapid determination of earthquake magnitude and focal mechanism, important for a number of rapid response applications, including tsunami warning, is still challenging because of the limitations of near-field inertial recordings. This instrumental issue can be solved by an entirely different observation system: a GPS network. Taiwan is well posed to take advantage of GPS because in the last decade it has developed a very dense network. Thus, in this research, we explore the suitability of the GPS CMT inversion for Taiwan. We retrospectively investigate six moderate to large (Mw6.0 ∼ 7.0) earthquakes and propose a resolution test for our model, we find that the minimum resolvable earthquake magnitude of this system is ∼Mw5.5 (at 5 km depth). Our tests also suggest that the finite fault complexity, often challenging for the near-field methodology, can be ignored under such good station coverage and thus, can provide a fast and robust solution for large earthquake directly from the near field. Our findings help to understand and quantify how the proposed methodology could be implemented in real time and what its contributions could be to the overall earthquake monitoring system.

A user-friendly probabilistic earthquake source inversion framework for joint inversion of seismic, geodetic, and gravitational signals - The Grond toolkit

2020 ◽  
Author(s):  
Sebastian Heimann ◽  
Marius Isken ◽  
Daniela Kühn ◽  
Hannes Vasyura-Bathke ◽  
Henriette Sudhaus ◽  
...  
Keyword(s):  
Open Source ◽  
Joint Inversion ◽  
Moment Tensor ◽  
Source Parameters ◽  
Seismic Source ◽  
Magma Ascent ◽  
Caldera Collapse ◽  
Waveform Data ◽  
Trade Offs ◽  
Finite Fault

<p>Seismic source and moment tensor waveform inversion is often ill-posed or non-unique if station coverage is poor or signals are weak. Three key ingredients can help in these situations: (1) probabilistic inference and global search of the full model space, (2) joint optimisation with datasets yielding complementary information, and (3) robust source parameterisation or additional source constraints. These demands lead to vast technical challenges, on the performance of forward modelling, on the optimisation algorithms, as well as on visualisation, optimisation configuration, and management of the datasets. Implementing a high amount of automation is inevitable.</p><p>To tackle all these challenges, we are developing a sophisticated new seismic source optimisation framework, Grond. With its innovative Bayesian bootstrap optimiser, it is able to efficiently explore large model spaces, the trade-offs and the uncertainties of source parameters. The program is highly flexible with respect to the adaption to specific source problems, the design of objective functions, and the diversity of empirical datasets.</p><p>It uses an integrated, robust waveform data processing, and allows for interactive visual inspection of many aspects of the optimisation problem, including visualisation of the result uncertainties. Grond has been applied to CMT moment tensor and finite-fault optimisations at all scales, to nuclear explosions, to a meteorite atmospheric explosion, and to volcano-tectonic processes during caldera collapse and magma ascent. Hundreds of seismic events can be handled in parallel given a single optimisation setup.</p><p>Grond can be used to optimise simultaneously seismic waveforms, amplitude spectra, waveform features, phase picks, static displacements from InSAR and GNSS, and gravitational signals.</p><p>Grond is developed as an open-source package and community effort. It builds on and integrates with other established open-source packages, like Kite (for InSAR) and Pyrocko (for seismology).</p>

Structural joint inversion on irregular meshes

2019 ◽  
Vol 220 (3) ◽  
pp. 1995-2008 ◽  
Author(s):  
C Jordi ◽  
J Doetsch ◽  
T Günther ◽  
C Schmelzbach ◽  
H Maurer ◽  
...  
Keyword(s):  
Electrical Resistivity ◽  
Joint Inversion ◽  
A Priori ◽  
Structural Similarity ◽  
P Wave ◽  
Parameter Distribution ◽  
Data Sets ◽  
Inversion Algorithm ◽  
Structural Joint ◽  
Irregular Meshes

SUMMARY Structural joint inversion of several data sets on an irregular mesh requires appropriate coupling operators. To date, joint inversion algorithms are primarily designed for the use on regular rectilinear grids and impose structural similarity in the direct neighbourhood of a cell only. We introduce a novel scheme for calculating cross-gradient operators based on a correlation model that allows to define the operator size by imposing physical length scales. We demonstrate that the proposed cross-gradient operators are largely decoupled from the discretization of the modelling domain, which is particularly important for irregular meshes where cell sizes vary. Our structural joint inversion algorithm is applied to a synthetic electrical resistivity tomography and ground penetrating radar 3-D cross-well experiment aiming at imaging two anomalous bodies and extracting the parameter distribution of the geostatistical background models. For both tasks, joint inversion produced superior results compared with individual inversions of the two data sets. Finally, we applied structural joint inversion to two field data sets recorded over a karstified limestone area. By including geological a priori information via the correlation-based operators into the joint inversion, we find P-wave velocity and electrical resistivity tomograms that are in accordance with the expected subsurface geology.

scholarly journals Joint Inversion of GPS, Leveling, and InSAR Data for The 2013 Lushan (China) Earthquake and Its Seismic Hazard Implications

2020 ◽  
Vol 12 (4) ◽  
pp. 715 ◽  
Author(s):  
Zhicai Li ◽  
Yangmao Wen ◽  
Peng Zhang ◽  
Yang Liu ◽  
Yong Zhang
Keyword(s):  
Joint Inversion ◽  
Source Parameters ◽  
Estimation Method ◽  
Lushan Earthquake ◽  
Coseismic Deformation ◽  
Seismogenic Fault ◽  
Finite Fault ◽  
Stress Changes ◽  
Gps Leveling ◽  
2013 Lushan Earthquake

On 20 April 2013, a moment magnitude (Mw) 6.6 earthquake occurred in the Lushan region of southwestern China and caused more than 190 fatalities. In this study, we use geodetic data from nearly 30 continuously operating global positioning system (GPS) stations, two periods of leveling data, and interferometric synthetic aperture radar (InSAR) observations to image the coseismic deformation of the Lushan earthquake. By using the Helmert variance component estimation method, a joint inversion is performed to estimate source parameters by using these GPS, leveling, and InSAR data sets. The results indicate that the 2013 Lushan earthquake occurred on a blind thrust fault. The event was dominated by thrust faulting with a minor left-lateral strike–slip component. The dip angle of the seismogenic fault was approximately 45.0°, and the fault strike was 208°, which is similar to the strike of the southern Longmenshan fault. Our finite fault model reveals that the peak slip of 0.71 m occurred at a depth of ~12 km, with substantial slip at depths of 6–20 km. The estimated magnitude was approximately Mw 6.6, consistent with seismological results. Furthermore, the calculated static Coulomb stress changes indicate that the 2013 Lushan earthquake may have been statically triggered by the 2008 Wenchuan earthquake.

Optimization of the fault plane and coseismic slip from tide-gauge data for the 2nd May 2020 Ierapetra, Crete, Earthquake (Mw 6.6) and the associated tsunami

2021 ◽  
Author(s):  
Enrico Baglione ◽  
Alessandro Amato ◽  
Beatriz Brizuela ◽  
Hafize Basak Bayraktar ◽  
Stefano Lorito ◽  
...  
Keyword(s):  
Tide Gauge ◽  
Moment Tensor ◽  
A Priori ◽  
Source Parameters ◽  
Early Warning Systems ◽  
Tsunami Source ◽  
Coseismic Slip ◽  
Moment Tensors ◽  
Tsunami Early Warning ◽  
Oblique Convergence

<p>We present a tsunami source solution for the 2nd May 2020, Mw 6.6 earthquake that occurred about 80 km offshore south of Crete on the shallow portion of the Hellenic Arc Subduction Zone (HASZ). This earthquake generated a small local tsunami recorded by the Ierapetra tide gauge on Crete island's southern coast. We used these single-marigram data to constrain the main features of the causative rupture. We modelled synthetic tsunami waveforms and measured their misfits with the observed data for each set of source parameters, scanned systematically around the values constrained by some of the available moment tensors.</p><p>In the attempts to discriminate between the two auxiliary fault planes of the moment tensor solutions, our results identify a shallow highly-dipping back-thrust fault as the source of this earthquake with the lower misfit. However, a rupture on a lower angle fault, possibly a splay fault of the subduction interface, with a sinistral component due to the oblique convergence on this segment of the HASZ, cannot be ruled out.</p><p>These results are relevant in the framework of the tsunami hazard assessments and Tsunami Early Warning Systems. In these frameworks, in addition to the subduction interface and possible ruptures on splay faults, other rupture types, such as those on secondary structures of the considered subduction system, cannot be excluded a priori. This circumstance bears important consequences because, as well as splay faulting, back thrust faulting might enhance the tsunamigenic potential where the subduction itself is less tsunamigenic due to the oblique convergence.</p>

scholarly journals Imaging the subsurface using induced seismicity and ambient noise: 3-D tomographic Monte Carlo joint inversion of earthquake body wave traveltimes and surface wave dispersion

2020 ◽  
Vol 222 (3) ◽  
pp. 1639-1655
Author(s):  
Xin Zhang ◽  
Corinna Roy ◽  
Andrew Curtis ◽  
Andy Nowacki ◽  
Brian Baptie
Keyword(s):  
Surface Wave ◽  
Ambient Noise ◽  
Velocity Structure ◽  
Joint Inversion ◽  
Body Wave ◽  
Source Parameters ◽  
Wave Dispersion ◽  
Inversion Method ◽  
Surface Wave Dispersion ◽  
Wave Data

SUMMARY Seismic body wave traveltime tomography and surface wave dispersion tomography have been used widely to characterize earthquakes and to study the subsurface structure of the Earth. Since these types of problem are often significantly non-linear and have non-unique solutions, Markov chain Monte Carlo methods have been used to find probabilistic solutions. Body and surface wave data are usually inverted separately to produce independent velocity models. However, body wave tomography is generally sensitive to structure around the subvolume in which earthquakes occur and produces limited resolution in the shallower Earth, whereas surface wave tomography is often sensitive to shallower structure. To better estimate subsurface properties, we therefore jointly invert for the seismic velocity structure and earthquake locations using body and surface wave data simultaneously. We apply the new joint inversion method to a mining site in the United Kingdom at which induced seismicity occurred and was recorded on a small local network of stations, and where ambient noise recordings are available from the same stations. The ambient noise is processed to obtain inter-receiver surface wave dispersion measurements which are inverted jointly with body wave arrival times from local earthquakes. The results show that by using both types of data, the earthquake source parameters and the velocity structure can be better constrained than in independent inversions. To further understand and interpret the results, we conduct synthetic tests to compare the results from body wave inversion and joint inversion. The results show that trade-offs between source parameters and velocities appear to bias results if only body wave data are used, but this issue is largely resolved by using the joint inversion method. Thus the use of ambient seismic noise and our fully non-linear inversion provides a valuable, improved method to image the subsurface velocity and seismicity.

Present-day orogenic processes in the western Kalpin nappe explored by interseismic GNSS measurements and coseismic InSAR observations of the 2020 Mw 6.1 Kalpin event

2021 ◽  
Author(s):  
Ping He ◽  
Yangmao Wen ◽  
Shuiping Li ◽  
Kaihua Ding ◽  
Zhicai Li ◽  
...  
Keyword(s):  
Source Parameters ◽  
Satellite System ◽  
Tien Shan ◽  
Dislocation Model ◽  
Maximum Displacement ◽  
Finite Fault ◽  
Instantaneous Deformation ◽  
Gnss Measurements ◽  
Global Navigation Satellite ◽  
Finite Fault Model

Summary As the largest and most active intracontinental orogenic belt on Earth, the Tien Shan (TS) is a natural laboratory for understanding the Cenozoic orogenic processes driven by the India-Asia collision. On 19 January 2020, a Mw 6.1 event stuck the Kalpin region, where the southern frontal TS interacts with the Tarim basin. To probe the local ongoing orogenic processes and potential seismic hazard in the Kalpin region, both interseismic and instantaneous deformation derived from geodetic observations are employed in this study. With the constraint of interseismic global navigation satellite system (GNSS) velocities, we estimate the décollement plane parameters of the western Kalpin nappe based on a two-dimensional dislocation model, and the results suggest that the décollement plane is nearly subhorizontal with a dip of ∼3° at a depth of 24 km. Then, we collect both Sentinel-1 and ALOS-2 satellite images to capture the coseismic displacements caused by the 2020 Kalpin event, and the interferometric synthetic aperture radar (InSAR) images show a maximum displacement of 7 cm in the line of sight near the epicentral region. With these coseismic displacement measurements, we invert the source parameters of this event using a finite-fault model. We determine the optimal source mechanism in which the fault geometry is dominated by thrust faulting with an E–W strike of 275° and a northward dip of 11.2°, and the main rupture slip is concentrated within an area 28.0 km in length and${\rm{\,\,}}$10.3 km in width, with a maximum slip of 0.3 m at a depth of 6–8 km. The total released moment of our preferred distributed slip model yields a geodetic moment of 1.59 × 1018 N$\cdot $m, equivalent to Mw 6.1. The contrast of the décollement plane depth from interseismic GNSS and the rupture depth from coseismic InSAR suggests that a compression still exists in the Kalpin nappe forefront, which is prone to frequent moderate events and may be at risk of a much more dangerous earthquake.

scholarly journals The waveform inversion of mainshock and aftershock data of the 2006 M6.3 Yogyakarta earthquake

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Hijrah Saputra ◽  
Wahyudi Wahyudi ◽  
Iman Suardi ◽  
Ade Anggraini ◽  
Wiwit Suryanto
Keyword(s):  
Joint Inversion ◽  
Body Wave ◽  
Moment Tensor ◽  
Near Field ◽  
Source Parameters ◽  
Waveform Inversion ◽  
Moment Tensor Inversion ◽  
Slip Distribution ◽  
Aftershock Distribution ◽  
Velocity Models

AbstractThis study comprehensively investigates the source mechanisms associated with the mainshock and aftershocks of the Mw = 6.3 Yogyakarta earthquake which occurred on May 27, 2006. The process involved using moment tensor inversion to determine the fault plane parameters and joint inversion which were further applied to understand the spatial and temporal slip distributions during the earthquake. Moreover, coseismal slip distribution was overlaid with the relocated aftershock distribution to determine the stress field variations around the tectonic area. Meanwhile, the moment tensor inversion made use of near-field data and its Green’s function was calculated using the extended reflectivity method while the joint inversion used near-field and teleseismic body wave data which were computed using the Kikuchi and Kanamori methods. These data were filtered through a trial-and-error method using a bandpass filter with frequency pairs and velocity models from several previous studies. Furthermore, the Akaike Bayesian Information Criterion (ABIC) method was applied to obtain more stable inversion results and different fault types were discovered. Strike–slip and dip-normal were recorded for the mainshock and similar types were recorded for the 8th aftershock while the 9th and 16th June were strike slips. However, the fault slip distribution from the joint inversion showed two asperities. The maximum slip was 0.78 m with the first asperity observed at 10 km south/north of the mainshock hypocenter. The source parameters discovered include total seismic moment M0 = 0.4311E + 19 (Nm) or Mw = 6.4 with a depth of 12 km and a duration of 28 s. The slip distribution overlaid with the aftershock distribution showed the tendency of the aftershock to occur around the asperities zone while a normal oblique focus mechanism was found using the joint inversion.

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