Estimation of Strong Ground Motion from a Great Earthquake Mw 8.5 in Central Seismic Gap Region, Himalaya (India) Using Empirical Green’s Function Technique

2013 ◽  
Vol 170 (12) ◽  
pp. 2127-2138 ◽  
Author(s):  
Babita Sharma ◽  
Sumer Chopra ◽  
Anup Kumar Sutar ◽  
B. K. Bansal
Keyword(s):  
Ground Motion ◽  
Green's Function ◽  
Strong Ground Motion ◽  
Function Technique ◽  
Great Earthquake ◽  
Seismic Gap ◽  
Empirical Green’S Function ◽  
Central Seismic Gap ◽  
Empirical Green's Function ◽  
Strong Ground

scholarly journals Estimation of strong ground motion in broad-frequency band based on a seismic source scaling model and an empirical Green's function technique

1994 ◽  
Vol 37 (6) ◽  
Author(s):  
K. Irikura ◽  
K. Kamae
Keyword(s):  
Green’S Function ◽  
Ground Motion ◽  
Green's Function ◽  
Strong Ground Motion ◽  
Function Technique ◽  
Similar Distribution ◽  
Empirical Green’S Function ◽  
Empirical Green's Function ◽  
Nankai Earthquake ◽  
Strong Ground

We introduce a generalized method for simulating strong ground motion from large earthquakes by summing subevent records to follow the ?2 law. The original idea of the method is based on a constant stress parameter between the target event and the subevent. It is applicable to a case where both events have a different stress drop after some manipulation. However, the simulation for a very large earthquake from a small event with this method has inevitably some deficiencies of spectral amplitudes in the intermediate frequency range deviating f`rom the ?2 model, although the high and low frequency motions match the scaling. We improve the simulation algorithm so as not to make spectral sags, introducing self-similar distribution of subfaults with different sizes in the fault plane, so-called fractal composite faulting model. We show successful simulations for intermediate-sized earthquakes (MJMA = 5.0, 6.0 and 6.1), the large aftershocks of the 1983 Akita-Oki earthquake. using the records of smaller aftershocks (MJMA = 3.9 and 5.0) as an empirical Green's function. Further, we attempted to estimate strong ground motion for the 1946 Nankai earthquake with Mw 8.2, using the records of a MJMA 5.1 earthquake occurring near the source region of the mainshock. We found that strong ground motions simulated for the fractal composite faulting model with two asperities radiating significantly high frequency motions matched well the observed data such as the near-field displacement record, the source spectrum estimated from the teleseismic record, and the seismic intensity distribution during the 1946 Nankai earthquake.

Estimation of Strong Ground Motion in Southern Peninsular India by Empirical Green's Function Method

2017 ◽  
Vol 112 (11) ◽  
pp. 2273
Author(s):  
K. Sivaram ◽  
Maheshreddy Gade ◽  
S. T. G. Raghukanth ◽  
Utpal Saikia ◽  
Nagaraju Kanna
Keyword(s):  
Green’S Function ◽  
Ground Motion ◽  
Green's Function ◽  
Function Method ◽  
Strong Ground Motion ◽  
Empirical Green’S Function ◽  
Green’S Function Method ◽  
Peninsular India ◽  
Empirical Green's Function ◽  
Strong Ground

Simulation of Strong Ground Motion in the National Capital Region, India, from a Future 8.5 Magnitude Earthquake Using Two-Step Empirical Green’s Function Method

2021 ◽  
Author(s):  
Krishnavajjhala Sivaram
Keyword(s):  
Green’S Function ◽  
Ground Motion ◽  
Green's Function ◽  
Seismic Gap ◽  
National Capital Region ◽  
Empirical Green’S Function ◽  
Ground Acceleration ◽  
Capital Region ◽  
National Capital ◽  
Empirical Green's Function

ABSTRACT In this study, I simulate high-frequency ground motions at five stations in the National Capital Region (NCR) of India for a large hypothetical Mw 8.5 earthquake in the Himalayan central seismic gap, at fault-distances of about 200–300 km. A smaller magnitude earthquake (22 July 2007 Mw 4.9 Kharsali) is used as the first-step empirical Green’s function (EGF) for the synthesis of an intermediate-sized earthquake of magnitude Mw 6.8 (1991 Uttarkashi earthquake). In the second step, the records of Mw 6.8 synthetics are further used as the EGF in the simulation of the postulated Mw 8.5 earthquake. Because the target region for the postulated earthquake is devoid of the necessary information on the geophysical constraints, I perform a suite of simulations for plausible scenarios of fault dimensions, stress-drop ratios, C, and scaling factor, N (between the EGF and target earthquake). This article uses heterogeneous slip distributions and variable stress drops on the rupture plane to simulate the target earthquake, based on the power spectral density of the von Karman correlation function. The estimated values of the ground-motion intensity measure (GMIM) such as peak ground acceleration, along with the engineering parameters such as the 5% damped, pseudospectral acceleration (Sa), Arias intensity (IA), and significant duration (TD), are compared for both the recorded and the simulated time histories. The estimated GMIMs of the Mw 6.8 synthetics are examined with those of the 1991 Mw 6.8 Uttarkashi earthquake, whereas the Mw 8.5 simulations are compared with those predicted by prevalent ground-motion prediction equations for rock sites. The Mw 8.5 earthquake scenarios indicate higher GMIMs and seismic hazard in the NCR, principally due to the area being underlain by sediment layers and fluvial deposits.

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