After a disaster, cities experience profound social and environmental upheaval. Current research on disasters describes this social disruption along with collective community action to provide support. Pre-existing social capital is recognised as fundamental to this observed support. This research examines the relationship between sense of place for neighbourhood, social connectedness and resilience. Canterbury residents experienced considerable and continued disruption following a large and protracted sequence of earthquakes starting in September 2010. A major aftershock on 22 February 2011 caused significant loss of life, destruction of buildings and infrastructure. Following this earthquake some suburbs of Christchurch showed strong collective action. This research examines the features of the built environment that helped to form this cooperative support. Data were collected through semi-structured interviews with 20 key informants followed by 38 participants from four case study suburbs. The objectives were to describe the community response of suburbs, to identify the key features of the built environment and the role of social infrastructure in fostering social connectedness. The last objective was to contribute to future planning for community resilience. The findings from this research indicated that social capital and community competence are significant resources to be called upon after a disaster. Features of the local environment facilitated the formation of neighbourhood connections that enabled participants to cope, manage and to collectively solve problems. These features also strengthened a sense of belonging and attachment to the home territory. Propinquity was important; the bumping and gathering places such as schools, small local shops and parks provided the common ground for meaningful pre-existing local interaction. Well-defined geography, intimate street typology, access to quality natural space and social infrastructure helped to build the local social connections and develop a sense of place. Resourceful individuals and groups were also a factor, and many are drawn to live near the inner city or more natural places. The features are the same well understood attributes that contribute to health and wellbeing. The policy and planning framework needs to consider broader social outcomes, including resilience in new and existing urban developments. The socio-political structures that provide access to secure and stable housing and local education should also be recognised and incorporated into local planning for resilience and the everyday.
The Canterbury Earthquake Sequence (CES) of 2010-2011 caused widespread liquefaction in many parts of Christchurch. Observations from the CES highlight some sites were liquefaction was predicted by the simplified method but did not manifest. There are a number of reasons why the simplified method may over-predict liquefaction, one of these is the dynamic interaction between soil layers within a stratified deposit. Soil layer interaction occurs through two key mechanisms; modification of the ground motion due to seismic waves passing through deep liquefied layers, and the effect of pore water seepage from an area of high excess pore water pressure to the surrounding soil. In this way, soil layer interaction can significantly alter the liquefaction behaviour and surface manifestation of soils subject to seismic loading. This research aimed to develop an understanding of how soil layer interaction, in particular ground motion modification, affects the development of excess pore water pressures and liquefaction manifestation in a soil deposit subject to seismic loading. A 1-D soil column time history Effective Stress Analysis (ESA) was conducted to give an in depth assessment of the development of pore pressures in a number of soil deposits. For this analysis, ground motions, soil profiles and model parameters were required for the ESA. Deconvolution of ground motions recorded at the surface during the CES was used to develop some acceleration time histories to input at the base of the soil-column model. An analysis of 55 sites around Christchurch, where detailed site investigations have been carried out, was then conducted to identify some simplified soil profiles and soil characteristics. From this analysis, four soil profiles representative of different levels of liquefaction manifestation were developed. These were; two thick uniform and vertically continuous sandy deposits that were representative of sites were liquefaction manifested in both the Mw 7.1 September 2010 and the Mw 6.3 February 2011 earthquakes, and two vertically discontinuous profiles with interlayered liquefiable and non-liquefiable layers representative of sites that did not manifest liquefaction in either the September 2010 or the February 2011 events. Model parameters were then developed for these four representative soil profiles through calibration of the constitutive model in element test simulations. Simulations were run for each of the four profiles subject to three levels of loading intensity. The results were analysed for the effect of soil layer interaction. These were then compared to a simplified triggering analysis for the same four profiles to determine where the simplified method was accurate in predicting soil liquefaction (for the continuous sandy deposits) and were it was less accurate (the vertically discontinuous deposits where soil layer interaction was a factor).
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.
Critical infrastructure networks are highly relied on by society such that any disruption to service can have major social and economic implications. Furthermore, these networks are becoming increasingly dependent on each other for normal operation such that an outage or asset failure in one system can easily propagate and cascade across others resulting in widespread disruptions in terms of both magnitude and spatial reach. It is the vulnerability of these networks to disruptions and the corresponding complexities in recovery processes which provide direction to this research. This thesis comprises studies contributing to two areas (i) the modelling of national scale in-terdependent infrastructure systems undergoing major disruptions, and (ii) the tracking and quantification of infrastructure network recovery trajectories following major disruptions. Firstly, methods are presented for identifying nationally significant systemic vulnerabilities and incorporating expert knowledge into the quantification of infrastructure interdependency mod-elling and simulation. With application to the interdependent infrastructures networks across New Zealand, the magnitudes and spatial extents of disruption are investigated. Results high-light the importance in considering interdependencies when assessing disruptive risks and vul-nerabilities in disaster planning applications and prioritising investment decisions for enhancing resilience of national networks. Infrastructure dependencies are further studied in the context of recovery from major disruptions through the analysis of curves measuring network functionality over time. Continued studies into the properties of recovery curves across a database of global natural disasters produce statistical models for predicting the trajectory and expected recovery times. Finally, the use of connectivity based metrics for quantifying infrastructure system functionality during recovery are considered with a case study application to the Christchurch Earthquake (February 22, 2011) wastewater network response