S T G Raghukanth

This paper deals with the estimation of spectral acceleration for Manipur based on probabilistic seismic hazard analysis (PSHA). The 500km region surrounding Manipur is divided into seven tectonic zones and major faults located in these zones are used to estimate seismic hazard. The earthquake recurrence relations for the seven zones have been estimated from past seismicity data. Ground motion prediction equations proposed by Boore and Atkinson (2008 Earthq. Spectra 24 99-138) for shallow active regions and Atkinson and Boore (2003 Bull. Seismol. Soc. Am. 93 1703-29) for the Indo-Burma subduction zone are used for estimating ground motion. The uniform hazard response spectra for all the nine constituent districts of Manipur (Senapati, Tamenglong, Churachandpur, Chandel, Imphal east, Imphal west, Ukhrul, Thoubal and Bishnupur) at 100-, 500- and 2500-year return periods have been computed from PSHA. A contour map of peak ground acceleration over Manipur is also presented for 100-, 500-, and 2500-year return periods with variations of 0.075-0.225, 0.18-0.63 and 0.3-0.1.15g, respectively, throughout the state. These results may be of use to planners and engineers for site selection, designing earthquake resistant structures and, further, may help the state administration in seismic hazard mitigation. © 2012 Sinopec Geophysical Research Institute.

This article presents site-specific probable seismic hazard of the Himachal Pradesh province, situated in a seismically active region of northwest Himalaya, using the ground motion relations presented in a companion article. Seismic recurrence parameters for all the documented probable sources are established from an updated earthquake catalogue. The contour maps of probable spectral acceleration at 0, 0.2, and 1 s (5% damping) are presented for 475 and 2475 years return periods. Also, the hazard curves and uniform hazard response spectrums are presented for all the important cities in this province. Results indicate that the present codal provision underestimates the seismic hazard at cities of Bilaspur, Shimla, Hamirpur, Chamba, Mandi, and Solan. In addition, regions near Bilaspur and Chamba exhibit higher hazard levels than what is reported in literature.

The present study aims at developing a prediction model for ground motion intensity measures using the artificial neural network (ANN) technique for active shallow crustal earthquakes in India. The database for the study consists of 659 ground motion records collected from 138 earthquakes recorded by various seismic networks in the study region. Owing to the lack of near-field data, we have added 116 records from seven earthquakes over a distance < 30 km and M > 6 from the NGA database. The developed model predicts 21 ground motion parameters (GMPs) in both horizontal and vertical directions, with input predictor variables of magnitude (M), hypocentral distance (R), site condition (S), and flag for the region (f). A multi-layer perceptron (MLP), with a total of 276 unknowns, constitutes the architecture of the model. The residuals associated with the GMPs are analyzed in detail to aid in hazard calculations. In addition, a comparison of the developed model with global relations is performed. Further, the model is demonstrated by performing seismic hazard analysis for GMPs for 2% and 10% probability of exceedance in 50 years. The ANN model is a first version and has to be improved as more strong motion data becomes available for the region. The developed ground motion model must be combined along with other global models in seismic hazard analysis.

This article focuses on developing a ground motion prediction equation based on artificial neural network (ANN) technique for shallow crustal earthquakes. A hybrid technique combining genetic algorithm and Levenberg–Marquardt technique is used for training the model. The present model is developed to predict peak ground velocity, and 5% damped spectral acceleration. The input parameters for the prediction are moment magnitude (Mw), closest distance to rupture plane (Rrup), shear wave velocity in the region (Vs30) and focal mechanism (F). A total of 13,552 ground motion records from 288 earthquakes provided by the updated NGA-West2 database released by Pacific Engineering Research Center are utilized to develop the model. The ANN architecture considered for the model consists of 192 unknowns including weights and biases of all the interconnected nodes. The performance of the model is observed to be within the prescribed error limits. In addition, the results from the study are found to be comparable with the existing relations in the global database. The developed model is further demonstrated by estimating site-specific response spectra for Shimla city located in Himalayan region.

This article presents four regional site-specific ground motion relations developed for the state of Himachal Pradesh in northwest Himalaya, situated in a seismically active region. These relations are developed from synthetic free surface ground motion databases obtained from a calibrated stochastic seismological model considering the characteristic properties of this specific region. The adopted methodology incorporates the site effects characterised through active MASW tests conducted in 22 important cities. The estimated ground motion levels from the developed relations are found to be in reasonable agreement with the recorded data.

One of the most challenging problems in the estimation of seismic hazard is the ability to quantify seismic activity. Empirical models based on the available earthquake catalogue are often used to obtain activity of source regions. The major limitation with this approach is the lack of sufficient data near a specified source. The non-availability of data poses difficulties in obtaining distribution of earthquakes with large return periods. Such events recur over geological time scales during which tectonic processes, including mantle convection, formation of faults and new plate boundaries, are likely to take place. The availability of geometries of plate boundaries, plate driving forces, lithospheric stress field and GPS measurements has provided numerous insights on the mechanics of tectonic plates. In this article, a 2D finite element model of Indo-Australian plate is developed with the focus of representing seismic activity in India. The effect of large scale geological features including sedimentary basins, fold belts and cratons on the stress field in India is explored in this study. In order to address long term behaviour, the orientation of stress field and tectonic faults of the present Indo-Australian plate are compared with a reconstructed stress field from the early Miocene (20 Ma).

In this article, a study on development of ground motion prediction equations (GMPEs) is undertaken for seismically active regions in India. To derive the equations, the seismically active regions are divided into four units based on seismotectonic setting and geology. Due to lack of strong motion data, a stochastic finite-fault simulation method is used for generating a complete synthetic database with respect to magnitude and distance. The input parameters in the stochastic seismological model, such as site amplification and stress drop, are first derived from the past strong-motion data. A total of 236 three-component records from 62 earthquakes with magnitudes ranging from Mw 3.4 to 7.8 are used to calibrate the seismological model. The obtained stress drops of these 62 events lie in between 60 and 165 bars. With the help of a large synthetic database generated from the calibrated seismological model, ground motion relations for 5 % damped spectral acceleration are obtained by regression analysis. The developed ground motion relations are compared with the existing GMPEs of the other active regions in the world. Although the proposed equations have trends similar to those of the existing relations, there are some differences attributed to stress drop and the quality factor of active regions in India. These relations will be useful to prepare spectral acceleration hazard maps of India for a given annual probability of exceedance.

The geologic analysis of lunar tectonic and co-existing mass wasting features provides important insights into seismicity, seismic ground motion, and the seismic risk of the landed missions. Hence, we performed a detailed geologic mapping of tectonic features and co-seismic boulder avalanches present at the 930-km-diameter lunar Orientale basin. We traced 6869 boulder falls at 141 sites along the basin rings, impact crater walls, and volcanic features. The boulder fields also occur on the graben walls and wrinkle ridges. The boulder trail length and width, and slopes of trail and source region of fallen boulders provide insights into formation processes and transport dynamics. Tens of sites have anomalously larger number of boulder falls and trail density. The cumulative size-frequency distributions of superimposed impact craters present on the boulder trails provided their model formation ages varying between present and 7.5 Ma with at least eight formation episodes, suggesting the timings of seismic activities along the Cordillera and Outer Rook Rings. Many boulder falls are devoid of superimposed impact craters suggesting their recent origins, including some possibly triggered by the 1972 (MW 2.7) shallow moonquake that occurred near the Cordillera Ring. The formation rates of shallow moonquakes and impact craters along with the seismic ground motion simulations suggest that shallow moonquakes are more dominant sources of ground shaking for triggering the boulder falls in the last 30 million years. Therefore, the Orientale basin has been seismically active for long time and it may be seismically hazardous locally for the future landed missions.

A deep learning model is developed for the Next Generation Attenuation–Subduction database for predicting spectral accelerations and peak amplitude measures. The developed model satisfies the statistical criteria necessary for prediction. Standard deviations lie in 0.2864–0.3809, 0–0.2696, and 0.4514–0.7892, range for inter-event, -region, and intra-events, respectively. Transfer learning is applied to the New Zealand region. Probabilistic seismic hazard analysis is performed for the Andaman-Nicobar region and obtained a peak ground acceleration of 0.6–0.7 g and 0.4–0.5 g at the Andaman and the Nicobar Islands, respectively, for a 2475-year return period.