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Developing a Hybrid Ground-Motion Modeling Framework for the Himalayan Region of India

In addressing the challenge of ground-motion modeling in the Indian context, where unavailability of recorded ground-motion data for the scenarios that dominate hazards across the major urban centers within the Indo-Gangetic plains is scarce, it poses a significant challenge. To overcome this limitation, conventional practice involves the utilization of ground-motion models (GMMs) calibrated on data from regions like California and Japan. To mitigate this issue, we develop a hybrid ground-motion modeling framework in which adjustments in global GMMs are performed to account for the differences in seismological characteristics such as anelastic attenuation and stress drop. Initially, we employ a strong-motion dataset from small-to-moderate magnitude events to derive seismological parameters aligned with the tectonic conditions of the study area (northern part of India). This involves a generalized inversion of Fourier spectral ordinates for the study region. In the next step, these parameters are adjusted with the magnitude and distance scaling of the global GMMs in the Fourier spectral domain. The adjusted Fourier spectra are then converted to response spectral ordinates using random vibration theory. Our analysis is based on a recently compiled and uniformly processed strong-motion dataset for the Himalayan region, comprising approximately 190 earthquake events with 798 records, where moment magnitudes (Mw) exceed 3 and recorded distances (REpi) less than 500 km. To illustrate the effectiveness of our proposed framework, we demonstrate its application using a host GMM (calibrated on the NGA-West2 database) for Fourier spectral ordinates (Bora et al., 2019). For comparative purposes, we also incorporate a response spectral GMM (Chiou and Youngs, 2014) into our study.

Session: From Earthquake Recordings to Empirical Ground-Motion Modelling [Poster Session]

Type: Poster

Room: Exhibit Hall

Date: 5/2/2024

Presentation Time: 08:00 AM (local time)

Presenting Author: Shikha Sharma

Student Presenter: Yes

Additional Authors