Abstract
Large Himalayan earthquakes expose rapidly growing populations of millions of people to high levels of seismic hazards, in particular in northeast India and Nepal. Calibrating vulnerability models specific to this region of the world is therefore crucial to the development of reliable mitigation measures. Here, we reevaluate the >15,700 casualties (8500 in Nepal and 7200 in India) from the M w ~8.2, 1934, Bihar–Nepal earthquake and calculate the fatality rates for this earthquake using an estimation of the population derived from two census held in 1921 and 1942. Values reach 0.7–1 % in the epicentral region, located in eastern Nepal, and 2–5 % in the urban areas of the Kathmandu valley. Assuming a constant vulnerability, we obtain, if the same earthquake would have repeated in 2011, fatalities of 33,000 in Nepal and 50,000 in India. Fast-growing population in India indeed must unavoidably lead to increased levels of casualty compared with Nepal, where the population growth is smaller. Aside from that probably robust fact, extrapolations have to be taken with great caution. Among other effects, building and life vulnerability could depend on population concentration and evolution of construction methods. Indeed, fatalities of the April 25, 2015, M w 7.8 Gorkha earthquake indicated on average a reduction in building vulnerability in urban areas, while rural areas remained highly vulnerable. While effective scaling laws, function of the building stock, seem to describe these differences adequately, vulnerability in the case of an M w >8.2 earthquake remains largely unknown. Further research should be carried out urgently so that better prevention strategies can be implemented and building codes reevaluated on, adequately combining detailed ancient and modern data.
Highlights
In a context of fast-growing population, more and more people are exposed to large devastating earthquakes (Bilham 2004; Jackson 2006)
These regions were impacted by the 1897 Shillong (Oldham 1899), 1905 Kangra (Middlemiss 1910) and 1934 Bihar (Rana 1935; Dunn et al 1939) and will be impacted by future earthquakes that will rupture inevitably the Main Himalayan Thrust along the foothills of the mountain range (Fig. 1), with a major seismic gap located between Dehli and Patna and focusing much of the current attention and debates (e.g., Rajendran et al 2015; Pulla 2015)
When presented as a function of the distance to epicenter (Fig. 3), the earthquake fatality rate decreases in a similar way as the macroseismic intensity, not taking into account the most densely populated areas of the Kathmandu valley
Summary
In a context of fast-growing population, more and more people are exposed to large devastating earthquakes (Bilham 2004; Jackson 2006). The collection of questionnaires prepared by the Geological Survey of India and sent through the government of Bihar and Orissa were a major source of information in terms of macroseismic effects (e.g., Dunn et al 1939) These macroseismic surveys resulted in a vast accumulation of data, including death toll and damages, consigned in Rana (1935) and Dunn et al (1939), compiled and further analyzed in review studies In order to avoid biases induced (1) by the variable quality of the sparse macroseismic data available in Nepal and (2) by the spatially unresolved accounting of the observations within a district associated with (3) an unresolved high variability of the geological and topographical site effects, we will further compare the destructions and fatalities to “estimated MSK intensities” deduced from Ambraseys and Douglas (2004) and associated with each district centroid. While more recent relations in EMS-98 intensities are presented in the literature for Himalayan
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