Social and natural capital are fundamental to people’s wellbeing, often within the context of local community. Developing communities and linking people together provide benefits in terms of mental well-being, physical activity and other associated health outcomes. The research presented here was carried out in Christchurch - Ōtautahi, New Zealand, a city currently re-building, after a series of devastating earthquakes in 2010 and 2011. Poor mental health has been shown to be a significant post-earthquake problem, and social connection has been postulated as part of a solution. By curating a disparate set of community services, activities and facilities, organised into a Geographic Information Systems (GIS) database, we created i) an accessibility analysis of 11 health and well-being services, ii) a mobility scenario analysis focusing on 4 general well-being services and iii) a location-allocation model focusing on 3 primary health care and welfare location optimisation. Our results demonstrate that overall, the majority of neighbourhoods in Christchurch benefit from a high level of accessibility to almost all the services; but with an urban-rural gradient (the further away from the centre, the less services are available, as is expected). The noticeable exception to this trend, is that the more deprived eastern suburbs have poorer accessibility, suggesting social inequity in accessibility. The findings presented here show the potential of optimisation modelling and database curation for urban and community facility planning purposes.
Recent tsunami events have highlighted the importance of effective tsunami risk management strategies (including land-use planning, structural and natural mitigation, warning systems, education and evacuation planning). However, the rarity of tsunami means that empirical data concerning reactions to tsunami warnings and evacuation behaviour is rare when compared to findings for evacuations from other hazards. More knowledge is required to document the full evacuation process, including responses to warnings, pre-evacuation actions, evacuation dynamics, and the return home. 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 the timings of evacuations, rather than behaviours of those evacuating. In this research, survey data was gathered from coastal communities in Banks Peninsula and Christchurch, New Zealand, relating to behaviours and actions during the November 14th 2016 Kaikōura earthquake tsunami. Survey questions asked about immediate actions following the earthquake shaking, reactions to tsunami warnings, pre-evacuation actions, evacuation dynamics and details on congestion. This data was analysed to characterise trends and identify factors that influenced evacuation actions and behaviour, and was further used to develop a realistic evacuation model prototype to evaluate the capacity of the roading network in Banks Peninsula during a tsunami evacuation. The evacuation model incorporated tsunami risk management strategies that have been implemented by local authorities, and exposure and vulnerability data, alongside the empirical data collected from the survey. This research enhances knowledge of tsunami evacuation behaviour and reactions to tsunami warnings, and can be used to refine evacuation planning to ensure that people can evacuate efficiently, thereby reducing their tsunami exposure and personal risk.
Rising disaster losses, growth in global migration, migrant labour trends, and increasingly diverse populations have serious implications for disaster resilience around the world. These issues are of particular concern in New Zealand, which is highly exposed to disaster risk and has the highest proportion of migrant workers to national population in the OECD. Since there has been no research conducted into this issue in New Zealand to date, greater understanding of the social capital used by migrant workers in specific New Zealand contexts is needed to inform more targeted and inclusive disaster risk management approaches. A New Zealand case study is used to investigate the extent and types of social capital and levels of disaster risk awareness reported by members of three Filipino migrant workers organisations catering to dairy farm, construction and aged care workers in different urban and rural Canterbury districts. Findings from (3) semi-structured interviews and (3) focus groups include consistently high reliance on bonding capital and low levels of bridging capital across all three organisations and industry sectors, and in both urban and rural contexts. The transitory, precarious residential status conveyed by temporary work visas, and the difficulty of building bridging capital with host communities has contributed to this heavy reliance on bonding capital. Social media was essential to connect workers with family and friends in other countries, while Filipino migrant workers organisations provided members with valuable access to industry and district-specific networks of other Filipino migrant workers. Linking capital varied between the three organisations, with members of the organisation set up to advocate for dairy farm workers reporting the highest levels of linking capital. Factors influencing the capacity of workers organisations to develop linking capital appeared to include motivation (establishment objectives), length of time since establishment, support from government and industry groups, urban-rural context, income levels and gender. Although aware of publicity around earthquake and tsunami risk in the Canterbury region, participants were less aware of flood risk, and expressed fatalistic attitudes to disaster risk. Workers organisations offer a valuable potential interface between CDEM Group activities and migrant worker communities, since organisation leaders were interested in accessing government support to participate (with and on behalf of members) in disaster risk planning at district and regional level. With the potential to increase disaster resilience among these vulnerable, hard to reach communities, such participation could also help to build capacity across workers organisations (within Canterbury and across the country) to develop linking capital at national, as well as regional level. However, these links will also depend on greater government and industry commitment to providing more targeted and appropriate support for migrant workers, including consideration of the cultural qualifications of staff tasked with liaising with this community.
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.
