The 2010 and 2011 earthquakes in the region of Canterbury, New Zealand caused widespread damage and the deaths of 185 people. Suburbs on the eastern side of Christchurch and in the satellite town of Kaiapoi, 20 kilometres north of Christchurch, were badly damaged by liquefaction. The Canterbury Earthquake Recovery Authority (CERA), a government organisation set up in the wake of the earthquakes, began to systematically zone all residential land in 2011. Based on the possibility for land remediation, 7860 houses in Christchurch and Kaiapoi were zoned red. Those who were in this zone were compensated and had to buy or build elsewhere. The other zone examined within this research – that of TC3 – lies within the green zone. Residents, in this zone, were able to stay in their houses but land was moderately damaged and required site-specific geotechnical investigations. This research sought to understand how residents’ senses of home were impacted by a disaster and the response efforts. Focusing on the TC3 and red zone of the eastern suburbs and the satellite town of Kaiapoi, this study interviewed 29 residents within these zones. The concept of home was explored with the respondents at three scales: home as a household; home as a community; and home as a city. There was a large amount of resistance to the zoning process and the handling of claims by insurance companies and the Earthquake Commission (EQC) after the earthquakes. Lack of transparency and communication, as well as extremely slow timelines were all documented as failings of these agencies. This research seeks to understand how participant’s sense of home changed on an individual level and how it was impacted by outside agencies. Homemaking techniques were also focused on showing that a changed sense of home will impact on how a person interacts with a space.
The supply of water following disasters has always been of significant concern to communities. Failure of water systems not only causes difficulties for residents and critical users but may also affect other hard and soft infrastructure and services. The dependency of communities and other infrastructure on the availability of safe and reliable water places even more emphasis on the resilience of water supply systems. This thesis makes two major contributions. First, it proposes a framework for measuring the multifaceted resilience of water systems, focusing on the significance of the characteristics of different communities for the resilience of water supply systems. The proposed framework, known as the CARE framework, consists of eight principal activities: (1) developing a conceptual framework; (2) selecting appropriate indicators; (3) refining the indicators based on data availability; (4) correlation analysis; (5) scaling the indicators; (6) weighting the variables; (7) measuring the indicators; and (8) aggregating the indicators. This framework allows researchers to develop appropriate indicators in each dimension of resilience (i.e., technical, organisational, social, and economic), and enables decision makers to more easily participate in the process and follow the procedure for composite indicator development. Second, it identifies the significant technical, social, organisational and economic factors, and the relevant indicators for measuring these factors. The factors and indicators were gathered through a comprehensive literature review. They were then verified and ranked through a series of interviews with water supply and resilience specialists, social scientists and economists. Vulnerability, redundancy and criticality were identified as the most significant technical factors affecting water supply system robustness, and consequently resilience. These factors were tested for a scenario earthquake of Mw 7.6 in Pukerua Bay in New Zealand. Four social factors and seven indicators were identified in this study. The social factors are individual demands and capacities, individual involvement in the community, violence level in the community, and trust. The indicators are the Giving Index, homicide rate, assault rate, inverse trust in army, inverse trust in police, mean years of school, and perception of crime. These indicators were tested in Chile and New Zealand, which experienced earthquakes in 2010 and 2011 respectively. The social factors were also tested in Vanuatu following TC Pam, which hit the country in March 2015. Interestingly, the organisational dimension contributed the largest number of factors and indicators for measuring water supply resilience to disasters. The study identified six organisational factors and 17 indicators that can affect water supply resilience to disasters. The factors are: disaster precaution; predisaster planning; data availability, data accessibility and information sharing; staff, parts, and equipment availability; pre-disaster maintenance; and governance. The identified factors and their indicators were tested for the case of Christchurch, New Zealand, to understand how organisational capacity affected water supply resilience following the earthquake in February 2011. Governance and availability of critical staff following the earthquake were the strongest organisational factors for the Christchurch City Council, while the lack of early warning systems and emergency response planning were identified as areas that needed to be addressed. Economic capacity and quick access to finance were found to be the main economic factors influencing the resilience of water systems. Quick access to finance is most important in the early stages following a disaster for response and restoration, but its importance declines over time. In contrast, the economic capacity of the disaster struck area and the water sector play a vital role in the subsequent reconstruction phase rather than in the response and restoration period. Indicators for these factors were tested for the case of the February 2011 earthquake in Christchurch, New Zealand. Finally, a new approach to measuring water supply resilience is proposed. This approach measures the resilience of the water supply system based on actual water demand following an earthquake. The demand-based method calculates resilience based on the difference between water demand and system capacity by measuring actual water shortage (i.e., the difference between water availability and demand) following an earthquake.
