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A New Ground Motion Model (GMM) for Northeast India (NEI) and Its Adjacent Countries for Interface Earthquakes Considering Both Strong Motion Records and Simulated Data
Pure and Applied Geophysics ( IF 1.9 ) Pub Date : 2021-03-08 , DOI: 10.1007/s00024-021-02677-3
Tauhidur Rahman , Ricky L. Chhangte

A ground motion model (GMM) for interface subduction zone earthquakes of Northeast India (NEI) and its adjacent countries is developed for the first time. Countries adjacent to NEI are Bangladesh, Bhutan, China, Myanmar and Nepal. High-magnitude earthquakes occur frequently in these regions due to buildup of high-stress parameters in the subduction zone of the Indian tectonic plate. Strong motion data are too few and sparse to develop a robust GMM for this region. We used both finite-fault simulations and a stochastic point-source model in developing our GMM. In our GMM, we used 50,000 ground motion samples which were stochastically simulated for different moment magnitudes (Mw) of 5.0–9.0 and hypocentral distances of 30–300 km using a point-source seismological stochastic model and finite fault model. In this study, we calculated stress drop (∆σ), quality factor Q(f) and all other region-specific seismic input parameters from the past strong motion records of interface subduction zone earthquakes of NEI and its adjacent countries. We used these seismic input parameters in ground motion simulation. Sensitivity analyses of the input parameters were also performed to check the bias of the present model. Our GMM was validated by comparing it with the existing NEI interface strong motion records. We compared our GMM with other GMMs developed for interface subduction zone earthquakes for different regions in the world. We also compared our GMM with point-source and finite-fault simulation models. Ground motion parameters estimated using the point-source model are comparatively higher than the finite-fault simulation model. Horizontal components of peak ground acceleration (PGA) and spectral acceleration (Sa) can be estimated for NEI using our GMM.

更新日期:2021-03-08
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