Seismic damage and loss estimation for central Indo-Gangetic Plains, India

M C, Raghucharan and Somala, S N (2018) Seismic damage and loss estimation for central Indo-Gangetic Plains, India. Natural Hazards. ISSN 0921-030X

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Abstract

The Indo-Gangetic Plains which lies between the Himalayan mountain ranges and peninsular India is considered to be the region of great concern due to its thick sediments and proximity to the seismically most active zone of India, the Himalayan collision zone. No earthquake loss estimation studies have been taken up previously in central Indo-Gangetic Plains (CIGP) so far. The goal of this paper is to compute the social and economic loss in CIGP region which will raise the awareness of the general public, policymakers and structural engineers about seismic risk in CIGP so that necessary mitigation measures will be taken up in advance. Further, the relative contribution of six input parameters to the overall uncertainty is ascertained from sensitivity analysis. Earthquake loss estimation reveals that Allahabad district, even though demarcated as zone II in IS 1893:2002, has expected economic losses around 9–13 billion dollars and the highest number of homeless and uninhabitable dwellings. Also, model building class (MBC) MMB (mud mortar bricks with temporary roof), comprising of 16.48% of total households in CIGP region, has high collapse rate when compared to other MBCs, due to the fact that those buildings have temporary roof made of wood, bamboo, polythene, plastic, thatch, mud and others. Further, for a scenario magnitude range of Mw 7.5–8.5, the expected human casualties vary between 0.14 and 1.7 lakhs, and the economic losses vary from 18 to 140 billion dollars, respectively. These results may not be unrealistic, as the region happens to be in the seismic bypass of 1905 Kangra and 1934 Bihar–Nepal earthquakes, with an anticipated catastrophic earthquake of Mw > 8.0. The poor quality and low seismic resilience of buildings in CIGP region are the principal reasons for the corresponding huge casualties and economic losses. Finally, from the sensitivity analysis, we found that the most sensitive parameter is magnitude followed by GMPE and source location, respectively.

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