Spatial seismic hazard variation and adaptive sampling of portfolio location uncertainty in probabilistic seismic risk analysis
<p>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. The available ground motion data – especially for strong and infrequent earthquakes – are often limited to a few decades, r...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2020-07-01
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| Series: | Natural Hazards and Earth System Sciences |
| Online Access: | https://www.nat-hazards-earth-syst-sci.net/20/1903/2020/nhess-20-1903-2020.pdf |
| Summary: | <p>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. The available ground motion data – especially for strong and infrequent earthquakes – are often limited to a few decades, resulting in incomplete earthquake catalogues and related uncertainties and assumptions. The situation is further aggravated by the sometimes poor data quality with regard to insured portfolios. For example, 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.</p>
<p>We analyze spatial seismic hazard and loss rate variation inside administrative geographical zones in western Indonesia. We find that the variation in hazard can vary strongly between different zones. The spatial variation in loss rate displays a similar pattern as the variation in hazard, without depending on the return period.</p>
<p>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 and may thereby help to spread the treatment and communication of uncertainty in probabilistic seismic risk analysis.</p> |
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| ISSN: | 1561-8633 1684-9981 |