Influence of shaking intensity attenuation peculiarities on reliability of earthquake loss estimation in emergency mode

Abstract

The methods and results of seismic hazard zoning are investigated for the Russian Federation territory and abroad. The input data used in the zoning procedure, aimed at revealing the boundaries of areas with stable seismic intensity attenuation parameters have been analyzed. The zoning procedure has been developed for determining the boundaries of territories, within which the macroseismic field parameters (i.e., the coefficients in N.V. Shebalin’s equation; the orientation of the elliptic isoseist axes, as well as the ratio of their semi-axes) show close values in each point. Examples are given in distinguishing zones characterized by quasi-stable parameters for separate regions, as well as in calibrating the computer model of the macroseismic field. The case studies are considered in the presence of a complete set of input data and under conditions of their insufficiency. The efficiency of the macroseismic field calibrated models application in the Extremum system in order to increase the reliability of near real time earthquake loss estimations is shown.

Impact database application for natural and technological risk management

“…that in the future, when obtaining additional data, the boundaries of zones with quasi-stable parameters and the values of the parameters can be refined. The work (Frolova et al, 2019) shows the results of joint research with employees of the Federal Geophysical Survey RAS (FGS RAS) on the identification of a zone with quasi-stable parameters of the macroseismic field (Fig. 6), which can be used later for rapid calculations of damage and losses in emergency mode.…”

Calibration Of Regional Vulnerability Functions By Applying Earthquake Events Database

“…1. Structure of EMERCOM Information System simulation model these parameters are: regional coefficients in the Shebalin macroseismic field equation (Shebalin 1977); the orientation of the elliptic isoseist axes; the ratio k of the major and minor axes of macroseismic field ellipse (Frolova et al 2019). The calibration of this kind satisfactory mimics learning processes for artificial intelligence systems.…”

“…The impact of the scenario earthquake for the test region was found by calculating the refined parameters of N.V. Shebalin's macroseismic field model I=1.5M-3.44lg(r)+3.13 that was previously reported in (Frolova et al 2019). The anisotropy of the macroseismic field was incorporated by using a compression ratio k equal to 1.5 and by arranging the greater axis of the isoseismal ellipse along the fault field.…”