Whole document is available to authenticated members of The University of Auckland until Feb. 2014 The increasing scale of losses from earthquake disasters has reinforced the need for property owners to become proactive in seismic risk reduction programs. However, despite advancement in seismic design methods and legislative frameworks, building owners are often reluctant to adopt mitigation measures required to reduce earthquake losses. The magnitude of building collapses from the recent Christchurch earthquakes in New Zealand shows that owners of earthquake prone buildings (EPBs) are not adopting appropriate risk mitigation measures in their buildings. Owners of EPBs are found unwilling or lack motivation to adopt adequate mitigation measures that will reduce their vulnerability to seismic risks. This research investigates how to increase the likelihood of building owners undertaking appropriate mitigation actions that will reduce their vulnerability to earthquake disaster. A sequential two-phase mixed methods approach was adopted for the research investigation. Multiple case studies approach was adopted in the first qualitative phase, followed by the second quantitative research phase that includes the development and testing of a framework. The research findings reveal four categories of critical obstacles to building owners‘ decision to adopt earthquake loss prevention measures. These obstacles include perception, sociological, economic and institutional impediments. Intrinsic and extrinsic interventions are proposed as incentives for overcoming these barriers. The intrinsic motivators include using information communication networks such as mass media, policy entrepreneurs and community engagement in risk mitigation. Extrinsic motivators comprise the use of four groups of incentives namely; financial, regulatory, technological and property market incentives. These intrinsic and extrinsic interventions are essential for enhancing property owners‘ decisions to voluntarily adopt appropriate earthquake mitigation measures. The study concludes by providing specific recommendations that earthquake risk mitigation managers, city councils and stakeholders involved in risk mitigation in New Zealand and other seismic risk vulnerable countries could consider in earthquake risk management. Local authorities could adopt the framework developed in this study to demonstrate a combination of incentives and motivators that yield best-valued outcomes. Consequently, actions can be more specific and outcomes more effective. The implementation of these recommendations could offer greater reasons for the stakeholders and public to invest in building New Zealand‘s built environment resilience to earthquake disasters
Recent global tsunami events have highlighted the importance of effective tsunami risk management strategies (including land-use planning, structural and natural defences, warning systems, education and evacuation measures). However, the rarity of tsunami means that empirical data concerning reactions to tsunami warnings and tsunami evacuation behaviour is rare when compared to findings about evacuations to avoid other sources of hazard. To date empirical research into tsunami evacuations has focused on evacuation rates, rather than other aspects of the evacuation process. More knowledge is required about responses to warnings, pre-evacuation actions, evacuation dynamics and the return home after evacuations. Tsunami evacuation modelling has the potential to inform evidence-based tsunami risk planning and response. However to date tsunami evacuation models have largely focused on timings of evacuations, rather than evacuation behaviours. This Masters research uses a New Zealand case study to reduce both of these knowledge gaps. Qualitative survey data was gathered from populations across coastal communities in Banks Peninsula and Christchurch, New Zealand, required to evacuate due to the tsunami generated by the November 14th 2016 Kaikōura Earthquake. Survey questions asked about reactions to tsunami warnings, actions taken prior to evacuating and movements during the 2016 tsunami evacuation. This data was analysed to characterise trends and identify factors that influenced evacuation actions and behaviour. Finally, it was used to develop an evacuation model for Banks Peninsula. Where appropriate, the modelling inputs were informed by the survey data. Three key findings were identified from the results of the evacuation behaviour survey. Although 38% of the total survey respondents identified the earthquake shaking as a natural cue for the tsunami, most relied on receiving official warnings, including sirens, to prompt evacuations. Respondents sought further official information to inform their evacuation decisions, with 39% of respondents delaying their evacuation in order to do so. Finally, 96% of total respondents evacuated by car. This led to congestion, particularly in more densely populated Christchurch city suburbs. Prior to this research, evacuation modelling had not been completed for Banks Peninsula. The results of the modelling showed that if evacuees know how to respond to tsunami warnings and where and how to evacuate, there are no issues. However, if there are poor conditions, including if people do not evacuate immediately, if there are issues with the roading network, or if people do not know where or how to evacuate, evacuation times increase with there being more bottlenecks leading out of the evacuation zones. The results of this thesis highlight the importance of effective tsunami education and evacuation planning. Reducing exposure to tsunami risk through prompt evacuation relies on knowledge of how to interpret tsunami warnings, and when, where and how to evacuate. Recommendations from this research outline the need for public education and engagement, and the incorporation of evacuation signage, information boards and evacuation drills. Overall these findings provide more comprehensive picture of tsunami evacuation behaviour and decision making based on empirical data from a recent evacuation, which can be used to improve tsunami risk management strategies. This empirical data can also be used to inform evacuation modelling to improve the accuracy and realism of the evacuation models.
