The purpose of this research is to investigate men’s experiences of the 2016 7.8 magnitude Kaikōura earthquake and Tsunami. While, research into the impacts of the earthquake has been conducted, few studies have examined how gender shaped people’s experiences of this natural hazard event. Analysing disasters through a gender lens has significantly contributed to disaster scholarship in identifying the resilience and vulnerabilities of individuals and communities pre- and post-disaster (Fordham, 2012; Bradshaw, 2013). This research employs understandings of masculinities (Connell, 2005), to examine men’s strengths and challenges in responding, recovering, and coping following the earthquake. Qualitative inquiry was carried out in Northern Canterbury and Marlborough involving 18 face-to-face interviews with men who were impacted by the Kaikōura earthquake and its aftermath. Interview material is being analysed using thematic and narrative analysis. Some of the preliminary findings have shown that men took on voluntary roles in addition to their fulltime paid work resulting in long hours, poor sleep and little time spent with family. Some men assisted wives and children to high ground then drove into the tsunami zone to check on relatives or to help evacuate people. Although analysis of the findings is currently ongoing, preliminary findings have identified that the men who participated in the study have been negatively impacted by the 2016 Kaikōura earthquake. A theme identified amongst participants was an avoidance to seek support with the challenges they were experiencing due to the earthquake. The research findings align with key characteristics of masculinity, including demonstrating risky behaviours and neglecting self or professional care. This study suggests that these behaviours affect men’s overall resilience, and thus the resilience of the wider community.
Tsunami events including the 2004 Indian Ocean Tsunami and the 2011 Tohoku Earthquake and Tsunami confirmed the need for Pacific-wide comprehensive risk mitigation and effective tsunami evacuation planning. New Zealand is highly exposed to tsunamis and continues to invest in tsunami risk awareness, readiness and response across the emergency management and science sectors. Evacuation is a vital risk reduction strategy for preventing tsunami casualties. Understanding how people respond to warnings and natural cues is an important element to improving evacuation modelling techniques. The relative rarity of tsunami events locally in Canterbury and also globally, means there is limited knowledge on tsunami evacuation behaviour, and tsunami evacuation planning has been largely informed by hurricane evacuations. This research aims to address this gap by analysing evacuation behaviour and movements of Kaikōura and Southshore/New Brighton (coastal suburb of Christchurch) residents following the 2016 Kaikōura earthquake. Stage 1 of the research is engaging with both these communities and relevant hazard management agencies, using a survey and community workshops to understand real-event evacuation behaviour during the 2016 Kaikōura earthquake and subsequent tsunami evacuations. The second stage is using the findings from stage 1 to inform an agent-based tsunami evacuation model, which is an approach that simulates of the movement of people during an evacuation response. This method improves on other evacuation modelling approaches to estimate evacuation times due to better representation of local population characteristics. The information provided by the communities will inform rules and interactions such as traffic congestion, evacuation delay times and routes taken to develop realistic tsunami evacuation models. This will allow emergency managers to more effectively prepare communities for future tsunami events, and will highlight recommended actions to increase the safety and efficiency of future tsunami evacuations.
The purpose of this research is to investigate men’s experiences of the 2016 7.8 magnitude Kaikōura earthquake and Tsunami. While, research into the impacts of the earthquake has been conducted, few studies have examined how gender shaped people’s experiences of this natural hazard event. Analysing disasters through a gender lens has significantly contributed to disaster scholarship in identifying the resilience and vulnerabilities of individuals and communities pre- and post-disaster (Fordham, 2012; Bradshaw, 2013). This research employs understandings of masculinities (Connell, 2005), to examine men’s strengths and challenges in responding, recovering, and coping following the earthquake. Qualitative inquiry was carried out in Northern Canterbury and Marlborough involving 18 face-to-face interviews with men who were impacted by the Kaikōura earthquake and its aftermath. Interview material is being analysed using thematic and narrative analysis. Some of the preliminary findings have shown that men took on voluntary roles in addition to their fulltime paid work resulting in long hours, poor sleep and little time spent with family. Some men assisted wives and children to high ground then drove into the tsunami zone to check on relatives or to help evacuate people. Although analysis of the findings is currently ongoing, preliminary findings have identified that the men who participated in the study have been negatively impacted by the 2016 Kaikōura earthquake. A theme identified amongst participants was an avoidance to seek support with the challenges they were experiencing due to the earthquake. The research findings align with key characteristics of masculinity, including demonstrating risky behaviours and neglecting self or professional care. This study suggests that these behaviours affect men’s overall resilience, and thus the resilience of the wider community.
The development of Digital City technologies to manage and visualise spatial information has increasingly become a focus of the research community, and application by city authorities. Traditionally, the Geographic Information Systems (GIS) and Building Information Models (BIM) underlying Digital Cities have been used independently. However, integrating GIS and BIM into a single platform provides benefits for project and asset management, and is applicable to a range of issues. One of these benefits is the means to access and analyse large datasets describing the built environment, in order to characterise urban risk from and resilience to natural hazards. The aim of this thesis is to further explore methodologies of integration in two distinct areas. The first, integration through connectivity of heterogeneous datasets where GIS spatial infrastructure data is merged with 3D BIM building data to create a digital twin. Secondly, integration through analysis whereby data from the digital twin are extracted and integrated with computational models. To achieve this, a workflow was developed to identify the required datasets of a digital twin, and develop a process of integrating those datasets through a combination of; semi-autonomous conversion, translation and extension of data; and semantic web and services-based processes. Through use of a designed schema, the data were streamed in a homogenous format in a web-based platform. To demonstrate the value of this workflow with respect to urban risk and resilience, the process was applied to the Taiora: Queen Elizabeth II recreation and sports centre in eastern Christchurch, New Zealand. After integration of as-built GIS and BIM datasets, targeted data extraction was implemented, with outputs tailored for analysis in an infrastructure serviceability loss model, which assessed potable water network performance in the 22nd February 2011 Christchurch Earthquake. Using the same earthquake conditions as the serviceability loss model, performance of infrastructure assets in service at the time of the 22nd February 2011 Christchurch Earthquake was compared to new assets rebuilt at the site, post-earthquake. Due to improved potable water infrastructure resilience resulting from installation of ductile piles, a decrease of 35.5% in the probability of service loss was estimated in the serviceability loss model. To complete the workflow, the results from the external analysis were uploaded to the web-based platform. One of the more significant outcomes from the workflow was the identification of a lack of mandated metadata standards for fittings/valves connecting a building to private laterals. Whilst visually the GIS and BIM data show the building and pipes as connected, the semantic data does not include this connectivity relationship. This has no material impact on the current serviceability loss model as it is not one of the defined parameters. However, a proposed modification to the model would utilise the metadata to further assess the physical connection robustness, and increase the number of variables for estimating probability of service loss. This thesis has made a methodological contribution to urban resilience analysis by demonstrating how readily available up-to-date building and infrastructure data can be integrated, and with tailored extraction from a Digital City platform, be used for disaster impact analysis in an external computational engine, with results in turn imported and visualised in the Digital City platform. The workflow demonstrated that translation and integration of data would be more successful if a regional/national mandate was implemented for the submission of consent documentation in a specified standard BIM format. The results of this thesis have identified that the key to ensuring the success of an integrated tool lies in the initial workflow required to safeguard that all data can be either captured or translated in an interoperable format.
The development of Digital City technologies to manage and visualise spatial information has increasingly become a focus of the research community, and application by city authorities. Traditionally, the Geographic Information Systems (GIS) and Building Information Models (BIM) underlying Digital Cities have been used independently. However, integrating GIS and BIM into a single platform provides benefits for project and asset management, and is applicable to a range of issues. One of these benefits is the means to access and analyse large datasets describing the built environment, in order to characterise urban risk from and resilience to natural hazards. The aim of this thesis is to further explore methodologies of integration in two distinct areas. The first, integration through connectivity of heterogeneous datasets where GIS spatial infrastructure data is merged with 3D BIM building data to create a digital twin. Secondly, integration through analysis whereby data from the digital twin are extracted and integrated with computational models. To achieve this, a workflow was developed to identify the required datasets of a digital twin, and develop a process of integrating those datasets through a combination of; semi-autonomous conversion, translation and extension of data; and semantic web and services-based processes. Through use of a designed schema, the data were streamed in a homogenous format in a web-based platform. To demonstrate the value of this workflow with respect to urban risk and resilience, the process was applied to the Taiora: Queen Elizabeth II recreation and sports centre in eastern Christchurch, New Zealand. After integration of as-built GIS and BIM datasets, targeted data extraction was implemented, with outputs tailored for analysis in an infrastructure serviceability loss model, which assessed potable water network performance in the 22nd February 2011 Christchurch Earthquake. Using the same earthquake conditions as the serviceability loss model, performance of infrastructure assets in service at the time of the 22nd February 2011 Christchurch Earthquake was compared to new assets rebuilt at the site, post-earthquake. Due to improved potable water infrastructure resilience resulting from installation of ductile piles, a decrease of 35.5% in the probability of service loss was estimated in the serviceability loss model. To complete the workflow, the results from the external analysis were uploaded to the web-based platform. One of the more significant outcomes from the workflow was the identification of a lack of mandated metadata standards for fittings/valves connecting a building to private laterals. Whilst visually the GIS and BIM data show the building and pipes as connected, the semantic data does not include this connectivity relationship. This has no material impact on the current serviceability loss model as it is not one of the defined parameters. However, a proposed modification to the model would utilise the metadata to further assess the physical connection robustness, and increase the number of variables for estimating probability of service loss. This thesis has made a methodological contribution to urban resilience analysis by demonstrating how readily available up-to-date building and infrastructure data can be integrated, and with tailored extraction from a Digital City platform, be used for disaster impact analysis in an external computational engine, with results in turn imported and visualised in the Digital City platform. The workflow demonstrated that translation and integration of data would be more successful if a regional/national mandate was implemented for the submission of consent documentation in a specified standard BIM format. The results of this thesis have identified that the key to ensuring the success of an integrated tool lies in the initial workflow required to safeguard that all data can be either captured or translated in an interoperable format.
