Table 1 Input mean value and standard deviations for normalization Input parameter Mean Standard Deviation Mw 6.8988 1.0780 RJB (km) 244.1745 197.4410 log(RJB) 5.1741 1.0621 ZTOR (km) 42.1177 34.3836 log(Vs30) 6.0386 0.4643 Subduction region (R) 4.0263 1.2646 Table 2 Target mean value and standard deviations for normalization Period Mean Std. Period Mean Std. Period Mean Std.
Summary
The present study focuses on developing a 3D computational model of the Indo Gangetic basin (IG basin) using the spectral element method (SEM). The region includes the subcontinent's most densely populated areas. The basin is unique as it consists of geologically younger sedimentary layers along with several ridges and depressions in its domain. However, the proximity of great Himalayan earthquakes and the presence of thick sedimentary layers of the basin results in higher seismic hazards. The limited instrumentation of the domain poses challenges in understanding the response of the basin due to a seismic event. This motivated us to develop a computational model of the IG basin by incorporating the best-known geometry, material properties, and fine resolution topography. In the lateral direction, the modelled part of IG basin spans over ∼60 ×40 (between longitude 80.50-86.50E and latitude 250-290N). The validation of the developed basin model is performed by simulating the ground motions for the 2015 Mw 7.9 Nepal mainshock and five of its aftershocks. Both qualitative and quantitative comparison of the simulated time histories suggests that the developed model could accurately simulate ground motions over a frequency range of 0.02-0.5Hz. The developed basin model is then used to understand the seismic wavefield characteristics during the 2015 Mw 7.9 Nepal mainshock. The spatial variation of PGV, as well as amplification, are investigated at a 0.20×0.20 grid and selected cities in the basin. The contours of PGV amplification indicate a higher value of ∼8-10 in the horizontal direction and ∼2.5-3.5 in the vertical direction for sediment depth >4km. A comprehensive comparison of the simulated PGVs and the ground motion prediction equations (GMPEs) shows that, while the simulations agree with the prediction, they also show heterogeneity of ground-motion distribution that cannot be fully described by empirical prediction relations. Hence the results from the present study are more reliable and find applications in seismic hazard assessment of the cities in the basin. Besides, the results can be used to guide the installation of future seismic stations in the region.
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