About 59% of the land area of the Indian subcontinent has high chances of moderate to severe earthquakes, of which the Himalayas are the most seismically active. Regardless of the high seismic activity, the seismic network in the region is largely insufficient. Macro-level seismic zonation of the Himalayan region using new ground motion prediction equations has been attempted. For seismic zonation, estimation of Peak Ground Acceleration (PGA) at bedrock level is important to understand the seismic hazard in the region. For this, region-specific Ground Motion Prediction Equations (GMPEs) are generated using multiple-regression analyses, separately for North and Central Himalayas (NCH) as well as North East Himalayas (NEH), considering the difference in their tectonic setting, purely based on recorded strong motion data. An updated large dataset is used in the study, making the new equations applicable to a large magnitude and distance range, thus overcoming a major limitation of the currently available region-specific GMPEs. After validation, the new GMPEs could be used for Seismic Hazard Analysis (SHA) considering various source models. Based on the regional seismic source zoning using the Gutenberg-Richter (GR) parameters, the NCH was delineated into 5 zones and the NEH into 4. The whole study area was divided into grids of size 0.05° × 0.05° and the PGA at the center of each grid point is estimated using deterministic (DSHA) and probabilistic (PSHA) approaches, using the region-specific GMPEs. Seismic Hazard maps are then generated using a GIS platform which showed that the PGA estimated in the regions is comparatively higher than what is reported in the codal provisions for design horizontal acceleration.
New GMPEs developed for the NCH and NEH were observed to predict ground acceleration better than the existing GMPEs adopted for these regions. Quantitative assessments showed that the new GMPEs are more accurate and residuals generated in predicting the PGA were much lesser than other widely adopted region-specific GMPEs. The new GMPEs also had a standard error term, which enabled them to be used in probabilistic hazard assessments. After thorough checking and validation, the newly developed region-specific GMPEs were used for a comprehensive SHA of the Himalayas.
DSHA yielded bedrock level PGA values up to the range of 0.4 to 0.7 g in the North and Central Himalayan region, and 0.6 to 0.8 g in the North-East Himalayan region, with the peaks observed towards the plate boundaries with a decreasing trend towards the peninsular region. PSHA was carried out for 10% and 2% probability of exceedance (POE) with return periods of 475 and 2475 years respectively. For the North and Central Himalayas, for PSHA considering 2% POE, PGA values ranged from 0.16 to 0.22 g in the Northern region with a decreasing trend towards the peninsular region, and for 10% POE, PGA values in the range of 0.10 to 0.20 g, following a similar trend from north to south. For the North-East Himalayan region, for 2% POE, the highest PGA values were ranging between 0.20 to 0.45 g and for 10% POE, between 0.20 to 0.40 g around the plate boundary regions. The existing seismic zonation map and zone factors delineated by the Indian standards in IS1893-Part 1, 2016 seems underestimated, looking at the hazard values predicted in the present study, as a higher hazard is reported in most of the Himalayan region. Based on the new results, a revision of the existing zoning and zonation-based design parameters is recommended, along with the strict implementation of safer design and construction practices in the light of high seismicity and seismic gap in the region. Further, the hazard maps developed now can be used as a base layer for seismic risk and vulnerability assessment, by combining it with results of further analyses like site geology, subsurface stratification, land use patterns, Rapid Visual Screening (RVS) of existing structures at the site, liquefaction potential, individual and community earthquake preparedness levels, etc.