Seismic isolation is an effective technology for significantly reducing damage to buildings and building contents. However, its application to light-frame wood buildings has so far been unable to overcome cost and technical barriers such as susceptibility to movement during high-wind loading. The precursor to research in the field of isolation of residential buildings was the 1994 Northridge Earthquake (6.7 MW) in the United States and the 1995 Kobe Earthquake (6.9 MW) in Japan. While only a small number of lives were lost in residential buildings in these events, the economic impact was significant with over half of earthquake recovery costs given to repair and reconstruction of residential building damage. A value case has been explored to highlight the benefits of seismically isolated residential buildings compared to a standard fixed-base dwellings for the Wellington region. Loss data generated by insurance claim information from the 2011 Christchurch Earthquake has been used by researchers to determine vulnerability functions for the current light-frame wood building stock. By further considering the loss attributed to drift and acceleration sensitive components, and a simplified single degree of freedom (SDOF) building model, a method for determining vulnerability functions for seismic isolated buildings was developed. Vulnerability functions were then applied directly in a loss assessment using the GNS developed software, RiskScape. Vulnerability was shown to dramatically reduce for isolated buildings compared to an equivalent fixed-base building and as a result, the monetary savings in a given earthquake scenario were significant. This work is expected to drive further interest for development of solutions for the seismic isolation of residential dwellings, of which one option is further considered and presented herein.
Natural hazards continue to have adverse effects on communities and households worldwide, accelerating research on proactively identifying and enhancing characteristics associated with resilience. Although resilience is often characterized as a return to normal, recent studies of postdisaster recovery have highlighted the ways in which new opportunities can emerge following disruption, challenging the status quo. Conversely, recovery and reconstruction may serve to reinforce preexisting social, institutional, and development pathways. Our understanding of these dynamics is limited however by the small number of practice examples, particularly for rural communities in developed nations. This study uses a social–ecological inventory to document the drivers, pathways, and mechanisms of resilience following a large-magnitude earthquake in Kaikōura, a coastal community in Aotearoa New Zealand. As part of the planning and implementation phase of a multiyear project, we used the tool as the basis for indepth and contextually sensitive analysis of rural resilience. Moreover, the deliberate application of social–ecological inventory was the first step in the research team reengaging with the community following the event. The inventory process provided an opportunity for research partners to share their stories and experiences and develop a shared understanding of changes that had taken place in the community. Results provide empirical insight into reactions to disruptive change associated with disasters. The inventory also informed the design of targeted research collaborations, established a platform for longer-term community engagement, and provides a baseline for assessing longitudinal changes in key resilience-related characteristics and community capacities. Findings suggest the utility of social–ecological inventory goes beyond natural resource management, and that it may be appropriate in a range of contexts where institutional, social, and economic restructuring have developed out of necessity in response to felt or anticipated external stressors.
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.
