Influence of a private-public risk pool and an opt-out framing on earthquake protection demand for Canadian homeowners in Quebec and British Columbia.

This article describes the design and analysis of web-based choice experiments that examine how the demand for earthquake protection in Quebec and British Columbia (BC), Canada, is influenced by the default option and the structure of the insurance plan. Homeowners in both provinces were given the opportunity to purchase protection against earthquake losses when presented with one of the following options: the current private insurance plan and proposed public-private Risk Pools with different levels of the public layer. The default frame was changed so the homeowner could either opt-in by purchasing this coverage or opt-out of being given this protection and receiving a premium discount. Assigning participants to the public-private Risk Pools rather than the current private insurance plan increases the likelihood of purchasing earthquake insurance protection by an odds ratio of 2.7 or greater in BC and Quebec. Furthermore, opt-out enrollment design substantially increases take-up of earthquake protection relative to opt-in enrollment. The policy implications of these findings are discussed.

Portfolio Seismic Loss Estimation and Risk-based Critical Scenarios for Residential Wooden Houses in Victoria, British Columbia, and Canada.

This study presents a city-wide seismic risk assessment of single-family wooden houses in Victoria, British Columbia, and Canada. The novelty and uniqueness of this study include considerations of detailed building-by-building exposure model for residential houses, current national seismic hazard model for Canada, and rigorous seismic fragility modeling of wooden houses based on nonlinear dynamic analysis of structures subjected to mainshock-aftershock sequences. A full consideration of stochastic event scenarios in probabilistic seismic risk analysis allows the identification of critical scenarios from overall regional seismic risk perspectives and provides valuable insights in informing earthquake disaster risk management actions. Outputs from the developed catastrophe model for Victoria are compared with the empirical model that was developed based on insurance claim data from the 1994 Northridge earthquake. Results of the seismic loss calculations highlight the importance of seismic resistance of the existing houses and of aftershock effects. The integrated use of the outputs from the advanced catastrophe model facilitates risk-based identification of critical earthquake scenarios, which are useful for different stakeholders for earthquake risk management purposes.

Time-dependent probabilistic tsunami risk assessment: application to Tofino, British Columbia, Canada, subjected to Cascadia subduction earthquakes.

A new time-dependent probabilistic tsunami risk model is developed to facilitate the long-term risk management strategies for coastal communities. The model incorporates the time-dependency of earthquake occurrence and considers numerous heterogeneous slip distributions via a stochastic source modeling approach. Tidal level effects are examined by considering different baseline sea levels. The model is applied to Tofino, British Columbia, Canada within the Cascadia subduction zone. High-resolution topography and high-quality exposure data are utilized to accurately evaluate tsunami damage and economic loss to buildings. The results are tsunami loss curves accounting for different elapsed times since the last major event. The evolutionary aspects of Tofino's time-dependent tsunami risk profiles show that the current tsunami risk is lower than the tsunami risk based on the conventional time-independent Poisson occurrence model. In contrast, the future tsunami risk in 2100 will exceed the time-independent tsunami risk estimate.

Assessment of seismic loss dependence using copula.

The catastrophic nature of seismic risk is attributed to spatiotemporal correlation of seismic losses of buildings and infrastructure. For seismic risk management, such correlated seismic effects must be adequately taken into account, since they affect the probability distribution of aggregate seismic losses of spatially distributed structures significantly, and its upper tail behavior can be of particular importance. To investigate seismic loss dependence for two closely located portfolios of buildings, simulated seismic loss samples, which are obtained from a seismic risk model of spatially distributed buildings by taking spatiotemporally correlated ground motions into account, are employed. The characterization considers a loss frequency model that incorporates one dependent random component acting as a common shock to all buildings, and a copula-based loss severity model, which facilitates the separate construction of marginal loss distribution functions and nonlinear copula function with upper tail dependence. The proposed method is applied to groups of wood-frame buildings located in southwestern British Columbia. Analysis results indicate that the dependence structure of aggregate seismic losses can be adequately modeled by the right heavy tail copula or Gumbel copula, and that for the considered example, overall accuracy of the proposed method is satisfactory at probability levels of practical interest (at most 10% estimation error of fractiles of aggregate seismic loss). The developed statistical seismic loss model may be adopted in dynamic financial analysis for achieving faster evaluation with reasonable accuracy.

Stochastic coupled simulation of strong motion and tsunami for the 2011 Tohoku, Japan earthquake.

This study conducts coupled simulation of strong motion and tsunami using stochastically generated earthquake source models. It is focused upon the 2011 Tohoku, Japan earthquake. The ground motion time-histories are simulated using the multiple-event stochastic finite-fault method, which takes into account multiple local rupture processes in strong motion generation areas. For tsunami simulation, multiple realizations of wave profiles are generated by evaluating nonlinear shallow water equations with run-up. Key objectives of this research are: (i) to investigate the sensitivity of strong motion and tsunami hazard parameters to asperities and strong motion generation areas, and (ii) to quantify the spatial variability and dependency of strong motion and tsunami predictions due to common earthquake sources. The investigations provide valuable insights in understanding the temporal and spatial impact of cascading earthquake hazards. Importantly, the study also develops an integrated strong motion and tsunami simulator, which is capable of capturing earthquake source uncertainty. Such an advanced numerical tool is necessary for assessing the performance of buildings and infrastructure that are subjected to cascading earthquake-tsunami hazards.

Bayesian tsunami fragility modeling considering input data uncertainty.

Empirical tsunami fragility curves are developed based on a Bayesian framework by accounting for uncertainty of input tsunami hazard data in a systematic and comprehensive manner. Three fragility modeling approaches, i.e. lognormal method, binomial logistic method, and multinomial logistic method, are considered, and are applied to extensive tsunami damage data for the 2011 Tohoku earthquake. A unique aspect of this study is that uncertainty of tsunami inundation data (i.e. input hazard data in fragility modeling) is quantified by comparing two tsunami inundation/run-up datasets (one by the Ministry of Land, Infrastructure, and Transportation of the Japanese Government and the other by the Tohoku Tsunami Joint Survey group) and is then propagated through Bayesian statistical methods to assess the effects on the tsunami fragility models. The systematic implementation of the data and methods facilitates the quantitative comparison of tsunami fragility models under different assumptions. Such comparison shows that the binomial logistic method with un-binned data is preferred among the considered models; nevertheless, further investigations related to multinomial logistic regression with un-binned data are required. Finally, the developed tsunami fragility functions are integrated with building damage-loss models to investigate the influences of different tsunami fragility curves on tsunami loss estimation. Numerical results indicate that the uncertainty of input tsunami data is not negligible (coefficient of variation of 0.25) and that neglecting the input data uncertainty leads to overestimation of the model uncertainty.