Seismic hazard and risk assessment based on Unified Scaling Law for Earthquakes: thirteen principal urban agglomerations of India

Imtiyaz A. Parvez (), Anastasia Nekrasova and Vladimir Kossobokov
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Imtiyaz A. Parvez: CSIR Fourth Paradigm Institute (Formerly CSIR C-MMACS)
Anastasia Nekrasova: Institute of Earthquake Prediction Theory and Mathematical Geophysics, RAS
Vladimir Kossobokov: Institute of Earthquake Prediction Theory and Mathematical Geophysics, RAS

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2018, vol. 92, issue 3, No 12, 1509-1522

Abstract: Abstract The deterministic seismic hazard map of India with spatially distributed peak ground acceleration was used to estimate seismic risk using two data sets of the Indian population—the model population data set and the data set based on India’s Census 2011. Four series of the earthquake risk maps of the region based on these two population density sets were cross-compared. The discrepancy of the population data and seismic risks estimation were illuminated for the thirteen principal urban agglomerations of India. The confirmed fractal nature of earthquakes and their distribution in space implies that traditional probabilistic estimations of seismic hazard and risks of cities and urban agglomerations are usually underestimated. The evident patterns of distributed seismic activity follow the Unified Scaling Law for Earthquakes, USLE, which generalizes Gutenberg–Richter recurrence relation. The results of the systematic global analysis imply that the occurrence of earthquakes in a region is characterized with USLE: log10N (M, L) = A + B × (5 − M) + C × log10L, where N(M, L)—expected annual number of earthquakes of magnitude M within an area of liner size L, A determines seismic static rate, B—balance between magnitude ranges, and C—fractal dimension of seismic loci. We apply the seismic hazard and risk assessment methodology developed recently based on USLE, pattern recognition of earthquake-prone geomorphic nodes, and neo-deterministic scenarios of destructive ground shaking. Objects of risk are individuals (1) as reported in the 2011 National Census data and (2) as predicted for 2010 by Gridded Population of the World (model GPWv3); vulnerability depends nonlinearly on population density. The resulting maps of seismic hazard and different risk estimates based on population density are cross-compared. To avoid misleading interpretations, we emphasize that risk estimates presented here for academic purposes only. In the matter of fact, they confirm that estimations addressing more realistic and practical kinds of seismic risks should involve experts in distribution of objects of risk of different vulnerability, i.e., specialists in earthquake engineering, social sciences, and economics.

Keywords: Neo-deterministic seismic hazard assessment (NDSHA); Unified Scaling Law for Earthquakes (USLE); Earthquake risk; Population density; PGA and vulnerability (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1007/s11069-018-3261-8

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