Pre- and post-seismic deformation related to the 2015, <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si7.gif" overflow="scroll"><mml:msub><mml:mi mathvariant="script">M</mml:mi><mml:mi mathvariant="bold-italic">w</mml:mi></mml:msub><mml:mn>7.8</mml:mn></mml:math> Gorkha earthquake, Nepal

Gualandi, Adriano; Avouac, J. P.; Galetzka, J.; Genrich, J. F.; Blewitt, G.; Adhikari, Lok Bijaya; Koirala, Bharat Prasad; Gupta, R.M.; Upreti, B. N.; Pratt-Sitaula, Beth; Liu‐Zeng, Jing

doi:10.1016/j.tecto.2016.06.014

Cited by 89 publications

(116 citation statements)

References 53 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The inferred afterslip distribution is similar to the results of previous studies that used GPS observations spanning shorter epochs (e.g., Gualandi et al, 2016;Mencin et al, 2016;Zhao et al, 2017). The inferred afterslip distribution is similar to the results of previous studies that used GPS observations spanning shorter epochs (e.g., Gualandi et al, 2016;Mencin et al, 2016;Zhao et al, 2017).…”

Section: Discussionsupporting

confidence: 87%

“…Depending on the dominant mechanism(s) involved in postseismic relaxation, could vary spatially (e.g., Hetland & Hager, 2006;Rousset et al, 2012). (Wang & Fialko, 2015) and early postseismic (Gualandi et al, 2016;Mencin et al, 2016) motion, most of the sites continued to move southward ∼2 years after the earthquake (Figure 5a). We therefore assumed that the decay rate is uniform throughout the GPS network and estimated it using the north component of the displacement time series at site CHLM, which has the largest SNR and almost continuous recordings during the entire observation period following the main shock.…”

Section: Gps Datamentioning

confidence: 99%

See 1 more Smart Citation

Observations and Modeling of Coseismic and Postseismic Deformation Due To the 2015 M_w 7.8 Gorkha (Nepal) Earthquake

2018

View full text Add to dashboard Cite

We use space geodetic data to investigate coseismic and postseismic deformation due to the 2015 Mw 7.8 Gorkha earthquake that occurred along the central Himalayan arc. Because the earthquake area is characterized by strong variations in surface relief and material properties, we developed finite element models that explicitly account for topography and 3‐D elastic structure. We computed the line‐of‐sight displacement histories from three tracks of the Sentinel‐1A/B Interferometric Synthetic Aperture Radar (InSAR) satellites, using persistent scatter method. InSAR observations reveal an uplift of up to ∼70 mm over ∼20 months after the main shock, concentrated primarily at the downdip edge of the ruptured asperity. GPS observations also show uplift, as well as southward movement in the epicentral area, qualitatively similar to the coseismic deformation pattern. Kinematic inversions of GPS and InSAR data and forward models of stress‐driven creep suggest that the observed postseismic transient is dominated by afterslip on a downdip extension of the seismic rupture. A poroelastic rebound may have contributed to the observed uplift and southward motion, but the predicted surface displacements are small. We also tested a wide range of viscoelastic relaxation models, including 1‐D and 3‐D variations in the viscosity structure. Models of a low‐viscosity channel previously invoked to explain the long‐term uplift and variations in topography at the plateau margins predict opposite signs of horizontal and vertical displacements compared to those observed. Our results do not preclude a possibility of deep‐seated viscoelastic response beneath southern Tibet with a characteristic relaxation time greater than the observation period (2 years).

show abstract

Section: Discussionsupporting

confidence: 87%

Section: Gps Datamentioning

confidence: 99%

Observations and Modeling of Coseismic and Postseismic Deformation Due To the 2015 M_w 7.8 Gorkha (Nepal) Earthquake

2018

View full text Add to dashboard Cite

show abstract

“…This method, applied to geodetic time series, performs a spatiotemporal separation of the geodetic data into a limited number of signals, subsequently interpreted as the actual physical sources that generated the observed displacements. This method has been successfully used to extract tectonic and nontectonic (e.g., mainly related with hydrology) deformation signals in the GPS time series in different settings [26][27][28][29]. In particular, each source has a specific spatial distribution (U) and follows a specific temporal evolution (V).…”

Section: Gps Datamentioning

confidence: 99%

Poroelasticity and Fluid Flow Modeling for the 2012 Emilia-Romagna Earthquakes: Hints from GPS and InSAR Data

et al. 2018

Self Cite

View full text Add to dashboard Cite

The Emilia-Romagna seismic sequence in May 2012 was characterized by two mainshocks which were close in time and space. Several authors already modeled the geodetic data in terms of the mechanical interaction of the events in the seismic sequence. Liquefaction has been extensively observed, suggesting an important role of fluids in the sequence. In this work, we focus on the poroelastic effects induced by the two mainshocks. In particular, the target of this work is to model the influence of fluids and pore-pressure changes on surface displacements and on the Coulomb failure function (CFF). The fluid flow and poroelastic modeling was performed in a 3D half-space whose elastic and hydraulic parameters are depth dependent, in accordance with the geology of the Emilia-Romagna subsoil. The model provides both the poroelastic displacements and the pore-pressure changes induced coseismically by the two mainshocks at subsequent periods and their evolution over time. Modeling results are then compared with postseismic InSAR and GPS displacement time series: the InSAR data consist of two SBAS series presented in previous works, while the GPS signal was detected adopting a variational Bayesian independent component analysis (vbICA) method. Thanks to the vbICA, we are able to separate the contribution of afterslip and poroelasticity on the horizontal surface displacements recorded by the GPS stations. The poroelastic GPS component is then compared to the modeled displacements and shown to be mainly due to drainage of the shallowest layers. Our results offer an estimation of the poroelastic effect magnitude that is small but not negligible and mostly confined in the near field of the two mainshocks. We also show that accounting for a 3D fault representation with a nonuniform slip distribution and the elastic-hydraulic layering of the half-space has an important role in the simulation results.

show abstract

“…This led to the release of the majority of the stresses built-up on this segment of the MHT due to the splitting of the last stage main-shock rupture and its subsequent arrest on a transverse fault. Alternatively the main-shock rupture could have ran into a patch of aseismic creep as proposed by Gualandi et al (2016) through study of post-seismic slip using GPS geodetic data. From the distribution (Fig.…”

Section: Discussionmentioning

confidence: 99%

The 2015 April 25 Gorkha (Nepal) earthquake and its aftershocks: implications for lateral heterogeneity on the Main Himalayan Thrust

Kumar¹,

Singh²,

Mitra³

et al. 2016

Geophys. J. Int.

View full text Add to dashboard Cite

S U M M A R YThe 2015 Gorkha earthquake (M w 7.8) occurred by thrust faulting on a ∼150 km long and ∼70 km wide, locked downdip segment of the Main Himalayan Thrust (MHT), causing the Himalaya to slip SSW over the Indian Plate, and was followed by major-to-moderate aftershocks. Back projection of teleseismic P-wave and inversion of teleseismic body waves provide constraints on the geometry and kinematics of the main-shock rupture and source mechanism of aftershocks. The main-shock initiated ∼80 km west of Katmandu, close to the locking line on the MHT and propagated eastwards along ∼117 • azimuth for a duration of ∼70 s, with varying rupture velocity on a heterogeneous fault surface. The main-shock has been modelled using four subevents, propagating from west-to-east. The first subevent (0-20 s) ruptured at a velocity of ∼3.5 km s −1 on a ∼6 • N dipping flat segment of the MHT with thrust motion. The second subevent (20-35 s) ruptured a ∼18 • W dipping lateral ramp on the MHT in oblique thrust motion. The rupture velocity dropped from 3.5 km s −1 to 2.5 km s −1 , as a result of updip propagation of the rupture. The third subevent (35-50 s) ruptured a ∼7 • N dipping, eastward flat segment of the MHT with thrust motion and resulted in the largest amplitude arrivals at teleseismic distances. The fourth subevent (50-70 s) occurred by left-lateral strikeslip motion on a steeply dipping transverse fault, at high angle to the MHT and arrested the eastward propagation of the main-shock rupture. Eastward stress build-up following the mainshock resulted in the largest aftershock (M w 7.3), which occurred on the MHT, immediately east of the main-shock rupture. Source mechanisms of moderate aftershocks reveal stress adjustment at the edges of the main-shock fault, flexural faulting on top of the downgoing Indian Plate and extensional faulting in the hanging wall of the MHT.

show abstract

Pre- and post-seismic deformation related to the 2015, Mw7.8 Gorkha earthquake, Nepal

Cited by 89 publications

References 53 publications

Observations and Modeling of Coseismic and Postseismic Deformation Due To the 2015 M_w 7.8 Gorkha (Nepal) Earthquake

Observations and Modeling of Coseismic and Postseismic Deformation Due To the 2015 M_w 7.8 Gorkha (Nepal) Earthquake

Poroelasticity and Fluid Flow Modeling for the 2012 Emilia-Romagna Earthquakes: Hints from GPS and InSAR Data

The 2015 April 25 Gorkha (Nepal) earthquake and its aftershocks: implications for lateral heterogeneity on the Main Himalayan Thrust

Contact Info

Product

Resources

About

Pre- and post-seismic deformation related to the 2015, Mw7.8 Gorkha earthquake, Nepal

Cited by 89 publications

References 53 publications

Observations and Modeling of Coseismic and Postseismic Deformation Due To the 2015 Mw 7.8 Gorkha (Nepal) Earthquake

Observations and Modeling of Coseismic and Postseismic Deformation Due To the 2015 Mw 7.8 Gorkha (Nepal) Earthquake

Poroelasticity and Fluid Flow Modeling for the 2012 Emilia-Romagna Earthquakes: Hints from GPS and InSAR Data

The 2015 April 25 Gorkha (Nepal) earthquake and its aftershocks: implications for lateral heterogeneity on the Main Himalayan Thrust

Contact Info

Product

Resources

About

Observations and Modeling of Coseismic and Postseismic Deformation Due To the 2015 M_w 7.8 Gorkha (Nepal) Earthquake

Observations and Modeling of Coseismic and Postseismic Deformation Due To the 2015 M_w 7.8 Gorkha (Nepal) Earthquake