Articles | Volume 20, issue 7
https://doi.org/10.5194/nhess-20-1903-2020
https://doi.org/10.5194/nhess-20-1903-2020
Research article
 | 
02 Jul 2020
Research article |  | 02 Jul 2020

Spatial seismic hazard variation and adaptive sampling of portfolio location uncertainty in probabilistic seismic risk analysis

Christoph Scheingraber and Martin Käser

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Cited articles

Atkinson, G. M. and Boore, D. M.: Empirical ground-motion relations for subduction-zone earthquakes and their application to Cascadia and other regions, Bull. Seismol. Soc. Am., 93, 1703–1729, https://doi.org/10.1785/0120080108, 2003. a
Bal, I. E., Bommer, J. J., Stafford, P. J., Crowley, H., and Pinho, R.: The influence of geographical resolution of urban exposure data in an earthquake loss model for Istanbul, Earthq. Spectra, 26, 619–634, https://doi.org/10.1193/1.3459127, 2010. a
Bender, B. and Perkins, D. M.: SEISRISK III: a computer program for seismic hazard estimation, Bulletin, United States Geological Survey, Reston, Virgina, USA, 1772–1820, https://doi.org/10.3133/b1772, 1987. a
Bier, V. M. and Lin, S. W.: On the treatment of uncertainty and variability in making decisions about risk, Risk Anal., 33, 1899–1907, https://doi.org/10.1111/risa.12071, 2013. a
Boore, D. M. and Atkinson, G. M.: Ground-motion prediction equations for the average horizontal component of PGA, PGV, and 5 %-damped PSA at spectral periods between 0.01 s and 10.0 s, Earthq. Spectra, 24, 99–138, https://doi.org/10.1193/1.2830434, 2008. a
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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.
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