Next Generation Ground-Motion Prediction Equations for Indo-Gangetic Plains, India

India's Indo-Gangetic Plains (IGP) and its proximity to the Himalayas are seismically the most vulnerable zone. For seismic hazard analysis, it requires a reliable Ground Motion Prediction Equations (GMPEs) for this region. The strong motion accelerometer data are used for the present study from 2005 to 2015. PSA of 5% damped linear pseudo-absolute acceleration response spectra at 27 periods ranging from 0.01 s to 10 s used for regression. Two-stage nonlinear regression is used to train the functional form of a nonlinear magnitude scaling, distance scaling, and site conditions. The model includes a regionally independent geometric attenuation finite fault distance metric, style of faulting, shallow site response, basin response, hanging wall effect, hypocentre depth, regionally dependent anelastic attenuation, site conditions, and magnitude-dependent aleatory variability. We consider our new GMPE is valid for earthquakes from active tectonic shallow crustal continental earthquakes for estimating horizontal ground motion for rupture distances ranging from 1 km to 1500 km and magnitudes ranging from 3.3 to 7.9, and focal depth 1-70 km. The proposed GMPEs developed in this study for predicting PGA and PSA are compared with the Campbell and Bozorgnia 2008, 13 and 14, and North Indian GMPEs for IGP, which is agreed upon consistently. Calibration with observed data gives us the confidence to predict the ground motion from the seismic gaps of Himalaya ranges for the Indo-Gangetic plains. The predicted coefficients of the nonlinear model are anticipated to be valuable for probabilistic seismic hazard analysis over the IGP.

Propagation of epistemic uncertainty in magnitude–frequency relations through PSHA using predictive distributions

The current practice of Probabilistic Seismic Hazard Analysis (PSHA) considers the inclusion of epistemic uncertainties involved in different parts of the analysis via the logic-tree approach. Given the complexity of modern PSHA models, numerous branches are needed, which in some cases leads to concerns regarding performance issues. We introduce the use of a magnitude exceedance rate which, following Bayesian conventions, we call predictive exceedance rate. This rate is the original Gutenberg–Richter relation after having included the effect of the epistemic uncertainty in parameter β. The predictive exceedance rate was first proposed by Campbell but to our best knowledge is seldom used in current PSHA. We show that the predictive exceedance rate is as accurate as the typical logic-tree approach but allows for much faster computations, a very useful property given the complexity of some modern PSHA models.

Probabilistic Seismic Hazard Analysis Based on Arias Intensity in the North–South Seismic Belt of China

ABSTRACT Arias intensity (IA), as an important seismic parameter, which contains the information of amplitude, frequencies, and duration of ground motion, plays a crucial role in characterizing seismic hazard such as earthquake-induced landslides. In this article, we conducted probabilistic seismic hazard analysis (PSHA) based on IA in China’s north–south seismic belt. We adopted the seismic sources and seismicity parameters used in the fifth generation of the Seismic Ground Motion Parameter Zoning Map of China, and two ground-motion model of IA. The results show that the values of IA are greater than 0.11 m/s in most regions of the north–south seismic belt. The provincial capital cities and most prefecture-level cities in the seismic zone are located in the region with IA-values greater than 0.32 m/s. The values of IA are above 0.54 m/s in the region around the main fault zone. This means that the north–south seismic belt is prone to extremely high-seismic hazard, particularly earthquake-induced landslides. Therefore, it is important to strengthen the evaluation and prevention of earthquake-induced landslides in this area. As we have found significant differences in the values of IA calculated from different ground-motion model, it is necessary to study the ground-motion model of IA for the western geological environment of China. In addition, the PSHA based on IA gives more consideration to the influence of large earthquakes than that based on peak ground acceleration. Therefore, IA plays an important role in seismic design of major engineering projects. The results of this article are of great scientific significance for understanding the seismic hazard of the north–south seismic belt.