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Research papers, Victoria University of Wellington

The Canterbury earthquake sequence (2010-2011) was the most devastating catastrophe in New Zealand‘s modern history. Fortunately, in 2011 New Zealand had a high insurance penetration ratio, with more than 95% of residences being insured for these earthquakes. This dissertation sheds light on the functions of disaster insurance schemes and their role in economic recovery post-earthquakes.  The first chapter describes the demand and supply for earthquake insurance and provides insights about different public-private partnership earthquake insurance schemes around the world.  In the second chapter, we concentrate on three public earthquake insurance schemes in California, Japan, and New Zealand. The chapter examines what would have been the outcome had the system of insurance in Christchurch been different in the aftermath of the Canterbury earthquake sequence (CES). We focus on the California Earthquake Authority insurance program, and the Japanese Earthquake Reinsurance scheme. Overall, the aggregate cost of the earthquake to the New Zealand public insurer (the Earthquake Commission) was USD 6.2 billion. If a similar-sized disaster event had occurred in Japan and California, homeowners would have received only around USD 1.6 billion and USD 0.7 billion from the Japanese and Californian schemes, respectively. We further describe the spatial and distributive aspects of these scenarios and discuss some of the policy questions that emerge from this comparison.  The third chapter measures the longer-term effect of the CES on the local economy, using night-time light intensity measured from space, and focus on the role of insurance payments for damaged residential property during the local recovery process. Uniquely for this event, more than 95% of residential housing units were covered by insurance and almost all incurred some damage. However, insurance payments were staggered over 5 years, enabling us to identify their local impact. We find that night-time luminosity can capture the process of recovery; and that insurance payments contributed significantly to the process of local economic recovery after the earthquake. Yet, delayed payments were less affective in assisting recovery and cash settlement of claims were more effective than insurance-managed repairs.  After the Christchurch earthquakes, the government declared about 8000 houses as Red Zoned, prohibiting further developments in these properties, and offering the owners to buy them out. The government provided two options for owners: the first was full payment for both land and dwelling at the 2007 property evaluation, the second was payment for land, and the rest to be paid by the owner‘s insurance. Most people chose the second option. Using data from LINZ combined with data from Stats NZ, the fourth chapter empirically investigates what led people to choose this second option, and how peer effect influenced the homeowners‘ choices.  Due to climate change, public disclosure of coastal hazard information through maps and property reports have been used more frequently by local government. This is expected to raise awareness about disaster risks in local community and help potential property owners to make informed locational decision. However, media outlets and business sector argue that public hazard disclosure will cause a negative effect on property value. Despite this opposition, some district councils in New Zealand have attempted to implement improved disclosure. Kapiti Coast district in the Wellington region serves as a case study for this research. In the fifth chapter, we utilize the residential property sale data and coastal hazard maps from the local district council. This study employs a difference-in-difference hedonic property price approach to examine the effect of hazard disclosure on coastal property values. We also apply spatial hedonic regression methods, controlling for coastal amenities, as our robustness check. Our findings suggest that hazard designation has a statistically and economically insignificant impact on property values. Overall, the risk perception about coastal hazards should be more emphasized in communities.

Research papers, University of Canterbury Library

The overarching goal of this dissertation is to improve predictive capabilities of geotechnical seismic site response analyses by incorporating additional salient physical phenomena that influence site effects. Specifically, multidimensional wave-propagation effects that are neglected in conventional 1D site response analyses are incorporated by: (1) combining results of 3D regional-scale simulations with 1D nonlinear wave-propagation site response analysis, and (2) modelling soil heterogeneity in 2D site response analyses using spatially-correlated random fields to perturb soil properties. A method to combine results from 3D hybrid physics-based ground motion simulations with site-specific nonlinear site response analyses was developed. The 3D simulations capture 3D ground motion phenomena on a regional scale, while the 1D nonlinear site response, which is informed by detailed site-specific soil characterization data, can capture site effects more rigorously. Simulations of 11 moderate-to-large earthquakes from the 2010-2011 Canterbury Earthquake Sequence (CES) at 20 strong motion stations (SMS) were used to validate simulations with observed ground motions. The predictions were compared to those from an empirically-based ground motion model (GMM), and from 3D simulations with simplified VS30- based site effects modelling. By comparing all predictions to observations at seismic recording stations, it was found that the 3D physics-based simulations can predict ground motions with comparable bias and uncertainty as the GMM, albeit, with significantly lower bias at long periods. Additionally, the explicit modelling of nonlinear site-response improves predictions significantly compared to the simplified VS30-based approach for soft-soil or atypical sites that exhibit exceptionally strong site effects. A method to account for the spatial variability of soils and wave scattering in 2D site response analyses was developed and validated against a database of vertical array sites in California. The inputs required to run the 2D analyses are nominally the same as those required for 1D analyses (except for spatial correlation parameters), enabling easier adoption in practice. The first step was to create the platform and workflow, and to perform a sensitivity study involving 5,400 2D model realizations to investigate the influence of random field input parameters on wave scattering and site response. Boundary conditions were carefully assessed to understand their effect on the modelled response and select appropriate assumptions for use on a 2D model with lateral heterogeneities. Multiple ground-motion intensity measures (IMs) were analyzed to quantify the influence from random field input parameters and boundary conditions. It was found that this method is capable of scattering seismic waves and creating spatially-varying ground motions at the ground surface. The redistribution of ground-motion energy across wider frequency bands, and the scattering attenuation of high-frequency waves in 2D analyses, resemble features observed in empirical transfer functions (ETFs) computed in other studies. The developed 2D method was subsequently extended to more complicated multi-layer soil profiles and applied to a database of 21 vertical array sites in California to test its appropriate- ness for future predictions. Again, different boundary condition and input motion assumptions were explored to extend the method to the in-situ conditions of a vertical array (with a sensor embedded in the soil). ETFs were compared to theoretical transfer functions (TTFs) from conventional 1D analyses and 2D analyses with heterogeneity. Residuals of transfer-function- based IMs, and IMs of surface ground motions, were also used as validation metrics. The spatial variability of transfer-function-based IMs was estimated from 2D models and compared to the event-to-event variability from ETFs. This method was found capable of significantly improving predictions of median ETF amplification factors, especially for sites that display higher event-to-event variability. For sites that are well represented by 1D methods, the 2D approach can underpredict amplification factors at higher modes, suggesting that the level of heterogeneity may be over-represented by the 2D random field models used in this study.