The Impact of Portfolio Location Uncertainty on Probabilistic Seismic Risk Analysis

Risk Analysis ◽  
2018 ◽  
Vol 39 (3) ◽  
pp. 695-712 ◽  
Author(s):  
Christoph Scheingraber ◽  
Martin A. Käser
Keyword(s):  
Risk Analysis ◽  
Seismic Risk ◽  
Seismic Risk Analysis ◽  
Location Uncertainty ◽  
The Impact

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

2019 ◽  
Author(s):  
Christoph Scheingraber ◽  
Martin Käser
Keyword(s):  
Risk Analysis ◽  
Seismic Hazard ◽  
Seismic Risk ◽  
Adaptive Sampling ◽  
Variance Reduction ◽  
Loss Rate ◽  
Insurance Industry ◽  
Rate Variation ◽  
Seismic Risk Analysis ◽  
Location Uncertainty

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.

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

2020 ◽  
Vol 20 (7) ◽  
pp. 1903-1918
Author(s):  
Christoph Scheingraber ◽  
Martin Käser
Keyword(s):  
Risk Analysis ◽  
Seismic Hazard ◽  
Ground Motion ◽  
Seismic Risk ◽  
Adaptive Sampling ◽  
Variance Reduction ◽  
Loss Rate ◽  
Rate Variation ◽  
Seismic Risk Analysis ◽  
Location Uncertainty

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. 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. 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. 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.

Seismic Risk Analysis of Infrastructural Systems

1982 ◽  
Vol 108 (1) ◽  
pp. 10-23 ◽  
Author(s):  
Héctor Monzón-Despang ◽  
Haresh C. Shah
Keyword(s):  
Risk Analysis ◽  
Seismic Risk ◽  
Seismic Risk Analysis

GIS Based Seismic Risk Analysis of Ahmedabad City, India

2018 ◽  
pp. 108-116
Author(s):  
Tejas P. Thaker ◽  
Pankaj K. Savaliya ◽  
Mehul K. Patel ◽  
Kundan A. Patel
Keyword(s):  
Risk Analysis ◽  
Seismic Risk ◽  
Seismic Risk Analysis

Financial Seismic Risk Analysis of Building Portfolios

2014 ◽  
Vol 15 (2) ◽  
pp. 112-120 ◽  
Author(s):  
Hiromichi Yoshikawa ◽  
Katsuichiro Goda
Keyword(s):  
Risk Analysis ◽  
Seismic Risk ◽  
Seismic Risk Analysis

Collaborative project planning: A case study of seismic risk analysis using an e-engineering hub

2006 ◽  
Vol 57 (3) ◽  
pp. 218-230 ◽  
Author(s):  
Z. Ren ◽  
C.J. Anumba ◽  
T.M. Hassan ◽  
G. Augenbroe ◽  
M. Mangini
Keyword(s):  
Risk Analysis ◽  
Seismic Risk ◽  
Project Planning ◽  
Seismic Risk Analysis ◽  
Collaborative Project
Sign in / Sign up

Export Citation Format

Share Document