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Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/nhess-2019-264
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-2019-264
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 20 Aug 2019

Submitted as: research article | 20 Aug 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Natural Hazards and Earth System Sciences (NHESS).

Impact data bases application for natural and technological risk management

Nina I. Frolova1, Valery I. Larionov1, Jean Bonnin2, Sergey P. Suchshev3, Alexander Ugarov3, and Nataliya Malaeva3 Nina I. Frolova et al.
  • 1Seismological Center of IGE, Russian Academy of Sciences, Moscow 101000, Russia
  • 2Institut de Physique du Globe, University of Strasbourg, Strasbourg F-67084, France
  • 3Extreme Situations Research Center, Moscow 127015, Russia

Abstract. Impact databases development and application for risk analysis and management promotes the usage of self-learning computer systems with elements of artificial intelligence. Such systems learning could be successful when the databases store the complete information about each event, parameters of the simulation models, the range of its application and residual errors. Each new description included in the database could increase the reliability of the results obtained with application of simulation models. The calibration of mathematical models is the first step to self-learning of automated systems. The article describes the events' database structure, and examples of calibrated computer models as applied to the impact of expected emergencies and risk indicators assessment. Examples of database statistics usage in order to rank the subjects of the Russian Federation by the frequency of emergencies of different character, as well as risk indicators are given.

Nina I. Frolova et al.
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Nina I. Frolova et al.
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Short summary
The paper is devoted to the structure and content of impact data bases due to natural disasters and technological accidents. The application of the database for disaster risk assessment and management is highlighted. The special attention is paid to usage of impact data for calibration of earthquake loss models in order to increase the reliability of near real time estimates.
The paper is devoted to the structure and content of impact data bases due to natural disasters...
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