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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-2019-110
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-2019-110
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 10 Jul 2019

Research article | 10 Jul 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).

Spatial Seismic Hazard Variation and Adaptive Sampling of Portfolio Location Uncertainty in Probabilistic Seismic Risk Analysis

Christoph Scheingraber1,2 and Martin Käser2,1 Christoph Scheingraber and Martin Käser
  • 1Ludwig-Maximilians-Universität, Munich, Germany
  • 2Munich Reinsurance, Munich, Germany

Abstract. Probabilistic Seismic Risk Analysis is widely used in the insurance industry to model the likelihood and severity of losses to insured portfolios by earthquake events. Due to geocoding issues of address information, risk items are often only known to be located within an administrative geographical zone, but precise coordinates remain unknown to the modeler.

In the first part of this paper, we analyze spatial seismic hazard and loss rate variation inside administrative geographical zones in western Indonesia. We find that the variation of hazard can vary strongly not only between different zones, but also between different return periods for a fixed zone. However, the spatial variation of loss rate displays a similar pattern as the variation of hazard, without depending on the return period.

We build upon these results in the second part of this paper. In a recent work, we introduced a framework for stochastic treatment of portfolio location uncertainty. This results in the necessity to simulate ground motion on a high number of sampled geographical coordinates, which typically dominates the computational effort in Probabilistic Seismic Risk Analysis. We therefore propose a novel sampling scheme to improve the efficiency of stochastic portfolio location uncertainty treatment. Depending on risk item properties and measures of spatial loss rate variation, the scheme dynamically adapts the location sample size individually for insured risk items. We analyze the convergence and variance reduction of the scheme empirically. The results show that the scheme can improve the efficiency of the estimation of loss frequency curves.

Christoph Scheingraber and Martin Käser
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Christoph Scheingraber and Martin Käser
Christoph Scheingraber and Martin Käser
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Short summary
Probabilistic Seismic Risk Analysis is widely used in the insurance industry to model losses to insured portfolios by earthquake events. Risk items are often only known to be located within an administrative geographical zone, but precise coordinates remain unknown to the modeler. We analyze spatial seismic hazard and loss rate variation inside administrative zones in western Indonesia. Building upon this, we present a novel framework for efficient treatment of portfolio location uncertainty.
Probabilistic Seismic Risk Analysis is widely used in the insurance industry to model losses to...
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