SeisFinder is an open-source web service developed by QuakeCoRE and the University of Canterbury, focused on enabling the extraction of output data from computationally intensive earthquake resilience calculations. Currently, SeisFinder allows users to select historical or future events and retrieve ground motion simulation outputs for requested geographical locations. This data can be used as input for other resilience calculations, such as dynamic response history analysis. SeisFinder was developed using Django, a high-level python web framework, and uses a postgreSQL database. Because our large-scale computationally-intensive numerical ground motion simulations produce big data, the actual data is stored in file systems, while the metadata is stored in the database.
Overview of SeisFinder SeisFinder is an open-source web service developed by QuakeCoRE and the University of Canterbury, focused on enabling the extraction of output data from computationally intensive earthquake resilience calculations. Currently, SeisFinder allows users to select historical or future events and retrieve ground motion simulation outputs for requested geographical locations. This data can be used as input for other resilience calculations, such as dynamic response history analysis. SeisFinder was developed using Django, a high-level python web framework, and uses a postgreSQL database. Because our large-scale computationally-intensive numerical ground motion simulations produce big data, the actual data is stored in file systems, while the metadata is stored in the database. The basic SeisFinder architecture is shown in Figure 1.
While some scholarship on refugee youth has focussed on leaving a place that is typically considered ‘home,’ there has been little attention to what ‘home’ means to them and how this is negotiated in the country of (re)settlement. This is particularly the case for girls and women. New Zealand research on refugee settlement has largely focussed on the economic integration of refugees. Although this research is essential, it runs the risk of overlooking the socio-cultural aspects of the resettlement experiences and renders partial our understanding of how particular generations and ethnic groups develop a sense of belonging to their adopted homeland. In order to address these research gaps, this thesis explores the experiences of 12 Afghan women, aged 19-29 years, of refugee background who relocated to Christchurch, New Zealand, during their childhood and early teenage years. This study employed semi-structured, one-to-one, in-depth interviews and photo-elicitation to encourage talk about participants’ experiences of leaving Afghanistan, often living in countries of protracted displacement (Iran and/or Pakistan) and making- and being-at-home in New Zealand. In this thesis, I explore the ways in which they frame Afghanistan, and the ways in which their experiences in Iran and Pakistan disrupt the dichotomisation of belonging in terms of ‘here’ (ancestral land) and ‘there’ (country of residence). Furthermore, I use affect theorising to analyse the participants’ expressions of resettlement and home in New Zealand. Feeling at home is as much about negotiating cultural and gendered identities in Western secular societies as it is about belonging to a particular community. Through their experiences of ‘living in two worlds’, the participants are able to strategically challenge cultural expectations without undermining their reputations as Muslims and as Afghan women. The participants discussed their emotional responses to double-displacement: one as a result of war and the other as a result of 2011 Canterbury earthquakes. Therefore, I suggest that for young Afghan women, Afghanistan was among several markers of home in a long embodied journey of (re)settlement.
This dissertation addresses a diverse range of topics in the area of physics-based ground motion simulation with particular focus on the Canterbury, New Zealand region. The objectives achieved provide the means to perform hybrid broadband ground motion simulation and subsequently validates the simulation methodology employed. In particu- lar, the following topics are addressed: the development of a 3D seismic velocity model of the Canterbury region for broadband ground motion simulation; the development of a 3D geologic model of the interbedded Quaternary formations to provide insight on observed ground motions; and the investigation of systematic effects through ground motion sim- ulation of small-to-moderate magnitude earthquakes. The paragraphs below outline each contribution in more detail. As a means to perform hybrid broadband ground motion simulation, a 3D model of the geologic structure and associated seismic velocities in the Canterbury region is devel- oped utilising data from depth-converted seismic reflection lines, petroleum and water well logs, cone penetration tests, and implicitly guided by existing contour maps and geologic cross sections in data sparse subregions. The model explicitly characterises five significant and regionally recognisable geologic surfaces that mark the boundaries between geologic units with distinct lithology and age, including the Banks Peninsula volcanics, which are noted to strongly influence seismic wave propagation. The Basement surface represents the base of the Canterbury sedimentary basin, where a large impedance contrast exists re- sulting in basin-generated waves. Seismic velocities for the lithological units between the geologic surfaces are derived from well logs, seismic reflection surveys, root mean square stacking velocities, empirical correlations, and benchmarked against a regional crustal model, thus providing the necessary information for a Canterbury velocity model for use in broadband seismic wave propagation. A 3D high-resolution model of the Quaternary geologic stratigraphic sequence in the Canterbury region is also developed utilising datasets of 527 high-quality water well logs, and 377 near-surface cone penetration test records. The model, developed using geostatistical Kriging, represents the complex interbedded regional Quaternary geology by characterising the boundaries between significant interbedded geologic formations as 3D surfaces including explicit modelling of the formation unconformities resulting from the Banks Peninsula volcanics. The stratigraphic layering present can result in complex wave propagation. The most prevalent trend observed in the surfaces was the downward dip from inland to the eastern coastline as a result of the dominant fluvial depositional environment of the terrestrial gravel formations. The developed model provides a benefi- cial contribution towards developing a comprehensive understanding of recorded ground motions in the region and also providing the necessary information for future site char- acterisation and site response analyses. To highlight the practicality of the model, an example illustrating the role of the model in constraining surface wave analysis-based shear wave velocity profiling is illustrated along with the calculation of transfer functions to quantify the effect of the interbedded geology on wave propagation. Lastly, an investigation of systematic biases in the (Graves and Pitarka, 2010, 2015) ground motion simulation methodology and the specific inputs used for the Canterbury region is presented considering 144 small-to-moderate magnitude earthquakes. In the simulation of these earthquakes, the 3D Canterbury Velocity Model, developed as a part of this dissertation, is used for the low-frequency simulation, and a regional 1D velocity model for the high-frequency simulation. Representative results for individual earthquake sources are first presented to highlight the characteristics of the small-to-moderate mag- nitude earthquake simulations through waveforms, intensity measure scaling with source- to-site distance, and spectral bias of the individual events. Subsequently, a residual de- composition is performed to examine the between- and within-event residuals between observed data, and simulated and empirical predictions. By decomposing the residuals into between- and within-event residuals, the biases in source, path and site effects, and their causes, can be inferred. The residuals are comprehensively examined considering their aggregated characteristics, dependence on predictor variables, spatial distribution, and site-specific effects. The results of the simulation are also benchmarked against empir- ical ground motion models, where their similarities manifest from common components in their prediction. Ultimately, suggestions to improve the predictive capability of the simulations are presented as a result of the analysis.
Disasters, either man-made or natural, are characterised by a multiplicity of factors including loss of property, life, environmental degradation, and psychosocial malfunction of the affected community. Although much research has been undertaken on proactive disaster management to help reduce the impacts of natural and man-made disasters, many challenges still remain. In particular, the desire to re-house the affected as quickly as possible can affect long-term recovery if a considered approach is not adopted. Promoting recovery activities, coordination, and information sharing at national and international levels are crucial to avoid duplication. Mannakkara and Wilkinson’s (2014) modified “Build Back Better” (BBB) concept aims for better resilience by incorporating key resilience elements in post-disaster restoration. This research conducted an investigation into the effectiveness of BBB in the recovery process after the 2010–2011 earthquakes in greater Christchurch, New Zealand. The BBB’s impact was assessed in terms of its five key components: built environment, natural environment, social environment, economic environment, and implementation process. This research identified how the modified BBB propositions can assist in disaster risk reduction in the future, and used both qualitative and quantitative data from both the Christchurch and Waimakariri recovery processes. Semi-structured interviews were conducted with key officials from the Christchurch Earthquake Recovery Authority, and city councils, and supplemented by reviewing of the relevant literature. Collecting data from both qualitative and quantitative sources enabled triangulation of the data. The interviewees had directly participated in all phases of the recovery, which helped the researcher gain a clear understanding of the recovery process. The findings led to the identification of best practices from the Christchurch and Waimakariri recovery processes and underlined the effectiveness of the BBB approach for all recovery efforts. This study contributed an assessment tool to aid the measurement of resilience achieved through BBB indicators. This tool provides systematic and structured approach to measure the performance of ongoing recovery.
In September 2010 and February 2011, the Canterbury region experienced devastating earthquakes with an estimated economic cost of over NZ$40 billion (Parker and Steenkamp, 2012; Timar et al., 2014; Potter et al., 2015). The insurance market played an important role in rebuilding the Canterbury region after the earthquakes. Homeowners, insurance and reinsurance markets and New Zealand government agencies faced a difficult task to manage the rebuild process. From an empirical and theoretic research viewpoint, the Christchurch disaster calls for an assessment of how the insurance market deals with such disasters in the future. Previous studies have investigated market responses to losses in global catastrophes by focusing on the insurance supply-side. This study investigates both demand-side and supply-side insurance market responses to the Christchurch earthquakes. Despite the fact that New Zealand is prone to seismic activities, there are scant previous studies in the area of earthquake insurance. This study does offer a unique opportunity to examine and document the New Zealand insurance market response to catastrophe risk, providing results critical for understanding market responses after major loss events in general. A review of previous studies shows higher premiums suppress demand, but how higher premiums and a higher probability of risk affect demand is still largely unknown. According to previous studies, the supply of disaster coverage is curtailed unless the market is subsidised, however, there is still unsettled discussion on why demand decreases with time from the previous disaster even when the supply of coverage is subsidised by the government. Natural disaster risks pose a set of challenges for insurance market players because of substantial ambiguity associated with the probability of such events occurring and high spatial correlation of catastrophe losses. Private insurance market inefficiencies due to high premiums and spatially concentrated risks calls for government intervention in the provision of natural disaster insurance to avert situations of noninsurance and underinsurance. Political economy considerations make it more likely for government support to be called for if many people are uninsured than if few people are uninsured. However, emergency assistance for property owners after catastrophe events can encourage most property owners to not buy insurance against natural disaster and develop adverse selection behaviour, generating larger future risks for homeowners and governments. On the demand-side, this study has developed an intertemporal model to examine how demand for insurance changes post-catastrophe, and how to model it theoretically. In this intertemporal model, insurance can be sought in two sequential periods of time, and at the second period, it is known whether or not a loss event happened in period one. The results show that period one demand for insurance increases relative to the standard single period model when the second period is taken into consideration, period two insurance demand is higher post-loss, higher than both the period one demand and the period two demand without a period one loss. To investigate policyholders experience from the demand-side perspective, a total of 1600 survey questionnaires were administered, and responses from 254 participants received representing a 16 percent response rate. Survey data was gathered from four institutions in Canterbury and is probably not representative of the entire population. The results of the survey show that the change from full replacement value policy to nominated replacement value policy is a key determinant of the direction of change in the level of insurance coverage after the earthquakes. The earthquakes also highlighted the plight of those who were underinsured, prompting policyholders to update their insurance coverage to reflect the estimated cost of re-building their property. The survey has added further evidence to the existing literature, such as those who have had a recent experience with disaster loss report increased risk perception if a similar event happens in future with females reporting a higher risk perception than males. Of the demographic variables, only gender has a relationship with changes in household cover. On the supply-side, this study has built a risk-based pricing model suitable to generate a competitive premium rate for natural disaster insurance cover. Using illustrative data from the Christchurch Red-zone suburbs, the model generates competitive premium rates for catastrophe risk. When the proposed model incorporates the new RMS high-definition New Zealand Earthquake Model, for example, insurers can find the model useful to identify losses at a granular level so as to calculate the competitive premium. This study observes that the key to the success of the New Zealand dual insurance system despite the high prevalence of catastrophe losses are; firstly the EQC’s flat-rate pricing structure keeps private insurance premiums affordable and very high nationwide homeowner take-up rates of natural disaster insurance. Secondly, private insurers and the EQC have an elaborate reinsurance arrangement in place. By efficiently transferring risk to the reinsurer, the cost of writing primary insurance is considerably reduced ultimately expanding primary insurance capacity and supply of insurance coverage.
