Characteristic ground motions of the 25th April 2015 Nepal earthquake (Mw 7.9) and its implications for the structural design codes for the border areas of India to Nepal

Sharma, Babita; Chingtham, Prasanta; Sharma, Varun; Kumar, Vikas; Mandal, H. S.; Mishra, O. P.

doi:10.1016/j.jseaes.2016.07.021

Cited by 17 publications

(9 citation statements)

References 35 publications

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“…and observed PGA values of the 2015 Nepal aftershock of M w 6.9 show an excellent correlation as seen from Fig. 4c (Sharma et al, 2017). We have also plotted the modelled ground-motion attenuation curve for an M w 6.6 earthquake, which shows a good correlation with the observed PGA values of the 1999 M w 6.6 Chamoli earthquake, the 1967 Koyna mainshock and the 2015 M w 6.6 Nepal aftershock between attenuation curve for M w 5.9 from our ML model (Fig.…”

Section: Resultssupporting

confidence: 74%

Peak Ground Acceleration Prediction using supervised Machine Learning algorithm for earthquakes of Mw5.6-7.9 occurring in India and Nepal

Mandal

2022

Preprint

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The absence of key input parameters and use of least squares technique have resulted in most of the available empirical ground motion prediction models (GMPEs) in India, as a function of epicentral distances and magnitudes, resulting in large uncertainty in the predictive model. Here we apply a supervised Machine Learning technique (XGBoost) to design a robust improved GMPE of peak ground acceleration (PGA) for the Indian sub-continent and Nepal, utilizing independent input parameters viz., moment magnitudes, hypocentral distances, focal depths and site proxy (in terms of average seismic shear-wave velocity from the surface to a depth of 30m (Vs30)). This has been achieved using PGA dataset of nine earthquakes of Mw5.6-7.9 from Nepal Himalaya, Uttarakhand Himalaya, Kachchh (Gujarat), and Koyna (Maharashtra). Our dataset also includes 225 strong-motion records of 30 significant Bhuj aftershocks of Mw3.3-5.0 (during 2002–2008) with epicentral distances ranging from 1.0 to 288 km. We also test the ground motion predictability of our supervised ML model using the whole dataset and randomized test dataset (30% of total data points). The correlation coefficient of observed and predicted PGA values for the whole dataset is found to be ±0.994 while our predictability on the randomized test dataset suggests a correlation coefficient of 0.944. Also, the model predictability of our supervised ML model suggests a good prediction of the observed PGA dataset for twelve Indian and Nepal earthquakes of Mw5.6-7.9 (viz., the 2001 Bhuj (Gujarat) earthquake sequence, the 2015 Nepal earthquake sequence, the 1999 Chamoli earthquake, the 1967 Koyna earthquake, the 2009 Mw6.2 Bhutan event and two Mw5.9 Myanmar-India border earthquakes of September 2009 and January 2013), suggesting that our ML GMPE model would work for earthquakes occurring in India and Nepal, within the range of Mw [3.3–7.9], focal depths [3–94 km], epicentral distances [1-565 km] and Vs30 [177–760 m/s].

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Section: Resultssupporting

confidence: 74%

Peak Ground Acceleration Prediction using supervised Machine Learning algorithm for earthquakes of Mw5.6-7.9 occurring in India and Nepal

Mandal

2022

Preprint

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“…LEKHA show decreasing pattern upwardly to the NE direction of the mainshock while the estimated values of PGA exhibit increasing trend in the rupture direction of the mainshock, i.e., upwardly to the NW direction of the mainshock (ITAN, SHL). Similarly increasing trend of estimated PGA values for stations located in the rupture direction and decreasing PGA patterns for stations other than the rupture propagation is also observed during the investigation of ground motion characteristics of 2015 Nepal earthquake (Mw 7.9) and 2009 Bhutan (Mw 6.1) earthquakes(Sharma et al 2017; Sharma and Mishra 2020). In other words, the decay radiation pattern in both NW and NE directions is almost same but the relatively higher PGA values in the NW direction can be explained by the rupture directivity of the earthquakes (both element and simulated) towards the NW of the earthquake.…”

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confidence: 66%

Simulation of a plausible great earthquake (Mw 8.0) sourced on down-going Indian slab beneath Indo-Burmese wedge and its implications for North East (NE) Indian region

Chingtham¹,

Sharma

Mohan

2022

Preprint

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The 4th January 2016 Manipur earthquake (Mw 6.7) occurred along the Indo-Burmese wedge and ruptured towards NW direction causing severe damage to buildings/structures in North-East (NE) Indian region. A plausible earthquake (Mw 8.0) is simulated to estimate the ground motions and associated seismic hazard by means of the waveforms of 2016 Manipur earthquake (Mw 6.7) as an element earthquake considering the source in the subduction boundary of the Indo-Burmese wedge at an intermediate depth. The empirical greens function mechanism (EGFM) is adopted to accomplish the better utilization of the observed ground motions of the recorded earthquake as an element earthquake and to achieve the probable ground motions in order to acquire the appropriate path/site effects in the simulated ground motions. The obtained results demonstrate the impact of the comparable rupture directivity pattern in both element as well as the simulated earthquakes. The Peak Ground Acceleration (PGA) in NE India from element and simulated earthquakes vary from 3 cm/sec2 and 11 cm/sec2 to 103 cm/sec2 and 342 cm/sec2 at epicentral distances of 624 km and 53 km respectively. The high amplitude surface waves due to the interference of seismic waves along with the combined effects of rupture directivity and site amplification showcased the highest PGA value at Shillong (SHL). This site is located on Pre-Cambrian rock and situated at an epicentral distance of 214 km from the source zone, which is lying at an intermediate depth that might have propelled the direct seismic waves of higher intensity at a longer distance compared to other sites. The outcome of the present study highlights the significance of varied ground motion parameters among the observed sites to the extent of bearing the damage potential of strong ground motions. The related analysis also advocates for the simulated PGA variations and associated duration of the earthquake waveforms exposed on different geological formations that have strong bearings on the seismic risk involved with future probable great earthquake in the study region. Moreover, simulated ground motions of expected plausible disastrous earthquakes on numerous geological formations beneath the various sites have significant impacts on designing critical structures/buildings such as schools, hospitals, bridges, dams and nuclear power plants for NE India. Thus, the detailed investigations on ground motion parameters, simulation of ground motion and the influence of different geological/geomorphological conditions on duration, shape and maximum amplitude of ground motion may be supportive for implementing earthquake risk and mitigation plans in order to assess the seismic hazard of the study region.

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“…The GPS measurements showed that the Nepal region had been accommodating the convergence at a rate of approximately 20 or even 40-50 mm yr −1 , due to the ongoing northward movement of the Indian plate relative to the stable Eurasian plate (e.g. Bilham et al 1997;Larson et al 1999;Wang et al 2001), leading to the occurrence of multiple large earthquakes with magnitudes larger than 7.5, such as the 1100 Nepal M w 8.5 earthquake, 1934 Bihar M w 8.1 earthquake and 2015 Gorkha M w 7.8 earthquake (Cattin & Avouac 2000;Sapkota et al 2013;Srivastava et al 2013;Sharma et al 2017). Many geophysical and geological investigations (e.g.…”

Section: Introductionmentioning

confidence: 99%

Lateral Moho variations and the geometry of the Main Himalayan Thrust beneath the Nepal Himalayan orogen revealed by teleseismic receiver functions

Lei

Yuan

et al. 2018

Geophysical Journal International

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The lateral Moho variations and the geometry of the Main Himalayan Thrust under the Nepal Himalayan orogen are investigated to determine a new crustal model using a large number of high-quality receiver functions recorded by the HIMNT and HiCLIMB portable seismic networks. Our new model shows an evident and complicated lateral Moho depth variation of 8-16 km in the east-west direction, which is related to the surface tectonic features. These results suggest a non-uniformed crustal deformation, resulted from the splitting and/or tearing of the Indian plate during the northward subduction. Our migrated receiver function images illustrate a discernible ramp structure of the Main Himalayan Thrust with an abrupt downward bending close to the hypocentre of the 2015 Gorkha M w 7.8 earthquake. The distribution of the aftershocks coincides with the present decollement structure. Integrated with previous magnetotelluric soundings and tomographic results, our results suggest that the ramp-shaped structure within the Main Himalayan Thrust could enhance stress concentration leading to the nucleation of the large earthquake. Our new crustal model provides new clues to the formation of the Himalayan orogen.

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Characteristic ground motions of the 25th April 2015 Nepal earthquake (Mw 7.9) and its implications for the structural design codes for the border areas of India to Nepal

Cited by 17 publications

References 35 publications

Peak Ground Acceleration Prediction using supervised Machine Learning algorithm for earthquakes of Mw5.6-7.9 occurring in India and Nepal

Peak Ground Acceleration Prediction using supervised Machine Learning algorithm for earthquakes of Mw5.6-7.9 occurring in India and Nepal

Simulation of a plausible great earthquake (Mw 8.0) sourced on down-going Indian slab beneath Indo-Burmese wedge and its implications for North East (NE) Indian region

Lateral Moho variations and the geometry of the Main Himalayan Thrust beneath the Nepal Himalayan orogen revealed by teleseismic receiver functions

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