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Measuring Seismic Risk in Turkey - Latest Modeling Techniques

This presentation explores cutting-edge seismic risk assessment methods in Turkey, focusing on historical context, notably the 1509 Istanbul earthquake. It addresses Turkey-specific factors influencing risk modeling, including seismicity, source zone characteristics, and the role of subsoil conditions. Panelists discuss three differing risk models and the implications of these variations, including hazard inputs, vulnerability curves, and statistical validation against loss experience. Conclusions emphasize the need for rigorous testing of models and highlight the challenges in achieving reliable seismic assessments.

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Measuring Seismic Risk in Turkey - Latest Modeling Techniques

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  1. Measuring Seismic Risk in Turkey - Latest Modeling Techniques Introduction and moderation: Anselm Smolka, Munich Re Panelists: Dennis Kuzak, EQECAT Oliver Peterken, Willis Fouad Bendimerad, RMS

  2. The Istanbul earthquake of 1509

  3. Turkey-specific factors General modelling related issues Three models and three answers –why the differences?

  4. Risk information Hazard input Value distribution Individualexposure EP curve Event Set loss experience vulnerab.curves Vulnerability function Statistics Risk models – general approach

  5. Seismicity: disagreement about Marmara region Source zones/ fault geometry Time dependence Collateral hazards which ones considered, and how ? Subsoil conditions data base assigning „average“ class Turkey-specific factors - Hazard

  6. Ground motion parameter Macroseismic MMI/EMS Spectral acceleration Displacement response spectrum Attenuation does not seem an issue for Turkey, but magnitude threshold for fault length General modelling issues

  7. Vulnerability: Difficult comparison for different g/m parameters threshold value for beginning damage=> great influence on AAL need for testing against actual loss experience(I don‘t believe in statistics but the ones falsified by myself...) General modelling issues

  8. Putting together „best components“ does not yet mean a good model Final results must be tested against actual recent and significant historic events In terms of statistical stability the number of simulations is important Wi(l)dely disagreeing results between models are not a good service to the market Conclusions

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