Natural disasters are increasingly disruptive events that affect livelihoods, organisations, and economies worldwide. Research has identified the impacts and responses of organisations to different types of natural disasters, and have outlined factors, such as industry sector, that are important to organisational vulnerability and resilience. One of the most costly types of natural disasters in recent years has been earthquakes, and yet to date, the majority of studies have focussed on the effects of earthquakes in urban areas, while rural organisational impact studies have primarily focused on the effects of meteorological and climatic driven hazards. As a result, the likely impacts of an earthquake on rural organisations in a developed context is unconstrained in the literature. In countries like New Zealand, which have major earthquakes and agricultural sectors that are significant contributors to the economy, it is important to know what impacts an earthquake event would have on the rural industries, and how these impacts compare to that of a more commonly analysed, high-frequency event. In September of 2010, rural organisations in Canterbury experienced the 4 September 2010 Mw 7.1 `Darfield' earthquake and the associated aftershocks, which came to be known as the Canterbury earth- quake sequence. The earthquake sequence caused intense ground shaking, creating widespread critical service outages, structural and non-structural damage to built infrastructure, as well as ground surface damage from ooding, liquefaction and surface rupture. Concurrently on September 18 2010, rural organisations in Southland experienced an unseasonably late snowstorm and cold weather snap that brought prolonged sub-zero temperatures, high winds and freezing rain, damaging structures in the City of Invercargill and causing widespread livestock losses and production decreases across the region. This thesis documents the effects of the Canterbury earthquake sequence and Southland snowstorm on farming and rural non-farming organisations, utilizing comparable methodologies to analyse rural organisational impacts, responses and recovery strategies to natural disasters. From the results, a short- term impact assessment methodology is developed for multiple disasters. Additionally, a regional asset repair cost estimation model is proposed for farming organisations following a major earthquake event, and the use of social capital in rural organisational recovery strategies following natural disasters is analysed.
Researchers have begun to explore the opportunity presented by blue-green infrastructure(a subset of nature-based solutions that provide blue and green space in urban infrastructure)as a response to the pressures of climate change. The 2010/2011 Canterbury earthquake sequence created a unique landscape within which there is opportunity to experiment with and invest in new solutions to climate change adaptation in urban centres. Constructed wetlands are an example of blue-green infrastructure that can potentially support resilience in urban communities. This research explores interactions between communities and constructed wetlands to understand how this may influence perceptions of community resilience. The regeneration of the Ōtākaro Avon River Corridor (OARC) provides a space to investigate these relationships. Seven stakeholders from the community, industry, and academia, each with experience in blue-green infrastructure in the OARC, participated in a series of semi-structured interviews. Each participant was given the opportunity to reflect on their perspectives of community, community resilience, and constructed wetlands and their interconnections. Interview questions aligned with the overarching research objectives to (1) understand perceptions around the role of wetlands in urban communities, (2) develop a definition for community resilience in the context of the Ōtākaro Avon community, and (3) reflect on how wetlands can contribute to (or detract from) community resilience. This study found that constructed wetlands can facilitate learning about the challenges and solutions needed to adapt to climate change. From the perspective of the community representatives, community resilience is linked to social capital. Strong social networks and a relationship with nature were emphasised as core components of a community’s ability to adapt to disruption. Constructed wetlands are therefore recognised as potentially contributing to community resilience by providing spaces for people to engage with each other and nature. Investment in constructed wetlands can support a wider response to climate change impacts. This research was undertaken with the support of the Ōtākaro Living Laboratory Trust, who are invested in the future of the OARC. The outcomes of this study suggest that there is an opportunity to use wetland spaces to establish programmes that explore the perceptions of constructed wetlands from a broader community definition, at each stage of the wetland life cycle, and at wider scales(e.g., at a city scale or beyond).
Voluntary turnover has been the subject of scholarly inquiry for more than 100 years and much is understood about the drivers of turnover, and the decision-making processes involved. To date most models of voluntary turnover have assumed a rational and sequential decision process, initiated primarily by dissatisfaction with the job and the perceived availability of alternatives. Operating within a strong predictive research agenda, countless studies have sought to validate, extend and refine these traditional models through the addition of distal antecedents, mediators, moderators, and proximal antecedents of turnover. The net result of this research is a large body of empirical support for a somewhat modest relationship between job dissatisfaction, perceived alternatives, turnover intentions, job search behaviour and actual turnover. Far less scholarly attention has been directed at understanding shock-induced turnover that is not necessarily derived from dissatisfaction. Moreover, almost no consideration has been given to understanding how a significant and commonly experienced extra-organisational shock, such as natural disaster, might impact turnover decision making. Additionally, the dynamic and cumulative impacts of multiple shocks on turnover decision making have to date not been examined by turnover researchers. In addressing these gaps this thesis presents a leaver-centric theory of employee turnover decision making that is grounded in the post-disaster context. Data for the study were collected from in-depth interviews with 31 leavers in four large organisations in Christchurch, New Zealand; an area that experienced a major natural disaster in the form of the Canterbury earthquake sequence. This context provided a unique setting in which to study turnover as the primary shock was followed by a series of smaller shocks, resulting in a period of sustained disruption to the pre-shock status quo. Grounded theory methods are used to develop a typology of leaving which describes four distinct patterns of turnover decision making that follow a significant extra-organisational shock. The proposed typology not only addresses the heterogeneous and complex nature of turnover decision making, but also provides a more nuanced explanation of the turnover process explicating how the choice of decision path followed is influenced by four contextual factors which emerged from the data: (1) pre-shock motivational state; (2) decision difficulty; (3) experienced shock magnitude; and (4) the availability of resources. The research findings address several shortcomings in the extant literature on employee turnover, and offer practical recommendations for managers seeking to retain employees in a post-disaster setting.
The research is funded by Callaghan Innovation (grant number MAIN1901/PROP-69059-FELLOW-MAIN) and the Ministry of Transport New Zealand in partnership with Mainfreight Limited. Need – The freight industry is facing challenges related to climate change, including natural hazards and carbon emissions. These challenges impact the efficiency of freight networks, increase costs, and negatively affect delivery times. To address these challenges, freight logistics modelling should consider multiple variables, such as natural hazards, sustainability, and emission reduction strategies. Freight operations are complex, involving various factors that contribute to randomness, such as the volume of freight being transported, the location of customers, and truck routes. Conventional methods have limitations in simulating a large number of variables. Hence, there is a need to develop a method that can incorporate multiple variables and support freight sustainable development. Method - A minimal viable model (MVM) method was proposed to elicit tacit information from industrial clients for building a minimally sufficient simulation model at the early modelling stages. The discrete-event simulation (DES) method was applied using Arena® software to create simulation models for the Auckland and Christchurch corridor, including regional pick-up and delivery (PUD) models, Christchurch city delivery models, and linehaul models. Stochastic variables in freight operations such as consignment attributes, customer locations, and truck routes were incorporated in the simulation. The geographic information system (GIS) software ArcGIS Pro® was used to identify and analyse industrial data. The results obtained from the GIS software were applied to create DES models. Life cycle assessment (LCA) models were developed for both diesel and battery electric (BE) trucks to compare their life cycle greenhouse gas (GHG) emissions and total cost of ownership (TCO) and support GHG emissions reduction. The line-haul model also included natural hazards in several scenarios, and the simulation was used to forecast the stock level of Auckland and Christchurch depots in response to each corresponding scenario. Results – DES is a powerful technique that can be employed to simulate and evaluate freight operations that exhibit high levels of variability, such as regional pickup and delivery (PUD) and linehaul. Through DES, it becomes possible to analyse multiple factors within freight operations, including transportation modes, routes, scheduling, and processing times, thereby offering valuable insights into the performance, efficiency, and reliability of the system. In addition, GIS is a useful tool for analysing and visualizing spatial data in freight operations. This is exemplified by their ability to simulate the travelling salesman problem (TSP) and conduct cluster analysis. Consequently, the integration of GIS into DES modelling is essential for improving the accuracy and reliability of freight operations analysis. The outcomes of the simulation were utilised to evaluate the ecological impact of freight transport by performing emission calculations and generating low-carbon scenarios to identify approaches for reducing the carbon footprint. LCA models were developed based on simulation results. Results showed that battery-electric trucks (BE) produced more greenhouse gas (GHG) emissions in the cradle phase due to battery manufacturing but substantially less GHG emissions in the use phase because of New Zealand's mostly renewable energy sources. While the transition to BE could significantly reduce emissions, the financial aspect is not compelling, as the total cost of ownership (TCO) for the BE truck was about the same for ten years, despite a higher capital investment for the BE. Moreover, external incentives are necessary to justify a shift to BE trucks. By using simulation methods, the effectiveness of response plans for natural hazards can be evaluated, and the system's vulnerabilities can be identified and mitigated to minimize the risk of disruption. Simulation models can also be utilized to simulate adaptation plans to enhance the system's resilience to natural disasters. Novel contributions – The study employed a combination of DES and GIS methods to incorporate a large number of stochastic variables and driver’s decisions into freight logistics modelling. Various realistic operational scenarios were simulated, including customer clustering and PUD truck allocation. This showed that complex pickup and delivery routes with high daily variability can be represented using a model of roads and intersections. Geographic regions of high customer density, along with high daily variability could be represented by a two-tier architecture. The method could also identify delivery runs for a whole city, which has potential usefulness in market expansion to new territories. In addition, a model was developed to address carbon emissions and total cost of ownership of battery electric trucks. This showed that the transition was not straightforward because the economics were not compelling, and that policy interventions – a variety were suggested - could be necessary to encourage the transition to decarbonised freight transport. A model was developed to represent the effect of natural disasters – such as earthquake and climate change – on road travel and detour times in the line haul freight context for New Zealand. From this it was possible to predict the effects on stock levels for a variety of disruption scenarios (ferry interruption, road detours). Results indicated that some centres rather than others may face higher pressure and longer-term disturbance after the disaster subsided. Remedies including coastal shipping were modelled and shown to have the potential to limit the adverse effects. A philosophical contribution was the development of a methodology to adapt the agile method into the modelling process. This has the potential to improve the clarification of client objectives and the validity of the resulting model.
Tsunami have the potential to cause significant disruptions to society, including damage to infrastructure, critical to the every-day operation of society. Effective risk management is required to reduce the potential tsunami impacts to them. Christchurch city, situated on the eastern coast of New Zealand’s South Island, is exposed to a number of far-field tsunami hazards. Although the tsunami hazard has been well identified for Christchurch city infrastructure, the likely impacts have not been well constrained. To support effective risk management a credible and realistic infrastructure impact model is required to inform risk management planning. The objectives of this thesis are to assess the impacts on Christchurch city infrastructure from a credible, hypothetical far-field tsunami scenario. To achieve this an impact assessment process is adopted, using tsunami hazard and exposure measures to determine asset vulnerability and subsequent impacts. However, the thesis identified a number of knowledge gaps in infrastructure vulnerability to tsunami. The thesis addresses this by using two approaches: a tsunami damage matrix; and the development of tsunami fragility functions. The tsunami damage matrix pools together tsunami impacts on infrastructure literature, and post-event field observations. It represents the most comprehensive ‘look-up’ resource for tsunami impacts to infrastructure to date. This damage matrix can inform the assessment of tsunami impacts on Christchurch city infrastructure by providing a measure of damage likelihood at various hazard intensities. A more robust approach to tsunami vulnerability of infrastructure are fragility functions, which are also developed in this thesis. These were based on post-event tsunami surveys of the 2011 ‘Tohoku’ earthquake tsunami in Japan. The fragility functions are limited to road and bridge infrastructure, but represent the highest resolution measure of vulnerability for the given assets. As well as providing a measure of damage likelihood for a given tsunami hazard intensity, these also indicate a level of asset damage. The impact assessment process, and synthesized vulnerability measures, are used to run tsunami impact models for Christchurch infrastructure to determine the probability of asset damage occurring and to determine if impact will reach or exceed a given damage state. The models suggest that infrastructure damage is likely to occur in areas exposed to tsunami inundation in this scenario, with significant damage identified for low elevation roads and bridges. The results are presented and discussed in the context of the risk management framework, with emphasis on using risk assessment to inform risk treatment, monitoring and review. In summary, this thesis A) advances tsunami vulnerability and impact assessment methodologies for infrastructure and B) provides a tsunami impact assessment framework for Christchurch city infrastructure which will inform infrastructure tsunami risk management for planners, emergency managers and lifelines groups.
Access to clean and safe drinking water is a fundamental human requirement. However, in many areas of the world natural water sources have been impacted by a variety of biological and chemical contaminants. The ingestion of these contaminants may cause acute or chronic health problems. To prevent such illnesses, many technologies have been developed to treat, disinfect and supply safe drinking water quality. However, despite these advancements, water supply distribution systems can adversely affect the drinking water quality before it is delivered to consumers. The primary aim of this research was to investigate the effect that water distribution systems may have on household drinking water quality in Christchurch, New Zealand and Addis Ababa, Ethiopia. Water samples were collected from the source water and household taps in both cities. The samples were then tested for various physical, chemical and biological water quality parameters. The data collected was also used to determine if water samples complied with national drinking water quality standards in both countries. Independent samples t-test statistical analyses were also performed to determine if water quality measured in the samples collected from the source and household taps was significantly different. Water quality did not vary considerably between the source and tap water samples collected in Christchurch City. No bacteria were detected in any sample. However, the pH and total iron concentrations measured in source and tap water samples were found to be significantly different. The lower pH values measured in tap water samples suggests that corrosion may be taking place in the distribution system. No water samples transgressed the Drinking Water Standards for New Zealand (DWSNZ) MAVs. Monitoring data collected by the Christchurch City Council (CCC) was also used for comparison. A number of pH, turbidity and total iron concentration measurements collected by the CCC in 2011 were found to exceed the guideline values. This is likely due to structural damage to the source wells and pump-stations that occurred during the 2011 earthquake events. Overall, it was concluded that the distribution system does not adversely affect the quality of Christchurch City’s household drinking water. The water quality measured in samples collected from the source (LTP) and household taps in Addis Ababa was found to vary considerably. The water collected from the source complied with the Ethiopian (WHO) drinking water quality standards. However, tap water samples were often found to have degraded water quality for the physical and chemical parameters tested. This was especially the case after supply interruption and reinstatement events. Bacteria were also often detected in household tap water samples. The results from this study indicate that water supply disruptions may result in degraded water quality. This may be due to a drop in pipeline pressure and the intrusion of contaminants through the leaky and cross-connected pipes in the distribution network. This adversely affects the drinking water quality in Addis Ababa.
Recent surface-rupturing earthquakes in New Zealand have highlighted significant exposure and vulnerability of the road network to fault displacement. Understanding fault displacement hazard and its impact on roads is crucial for mitigating risks and enhancing resilience. There is a need for regional-scale assessments of fault displacement to identify vulnerable areas within the road network for the purposes of planning and prioritising site-specific investigations. This thesis employs updated analysis of data from three historical surface-rupturing earthquakes (Edgecumbe 1987, Darfield 2010, and Kaikoūra 2016) to develop an empirical model that addresses the gap in regional fault displacement hazard analysis. The findings contribute to understanding of • How to use seismic hazard model inputs for regional fault displacement hazard analysis • How faulting type and sediment cover affects the magnitude and spatial distribution of fault displacement • How the distribution of displacement and regional fault displacement hazard is impacted by secondary faulting • The inherent uncertainties and limitations associated with employing an empirical approach at a regional scale • Which sections of New Zealand’s roading network are most susceptible to fault displacement hazard and warrant site-specific investigations • Which regions should prioritise updating emergency management plans to account for post-event disruptions to roading. I used displacement data from the aforementioned historical ruptures to generate displacement versus distance-to-fault curves for various displacement components, fault types, and geological characteristics. Using those relationships and established relationships for along-strike displacement, displacement contours were generated surrounding active faults within the NZ Community Fault Model. Next, I calculated a new measure of 1D strain along roads as well as relative hazard, which integrated 1D strain and normalised slip rate data. Summing these values at the regional level identified areas of heightened relative hazard across New Zealand, and permits an assessment of the susceptibility of road networks using geomorphon land classes as proxies for vulnerability. The results reveal that fault-parallel displacements tend to localise near the fault plane, while vertical and fault-perpendicular displacements sustain over extended distances. Notably, no significant disparities were observed in off-fault displacement between the hanging wall and footwall sides of the fault, or among different surface geology types, potentially attributed to dataset biases. The presence of secondary faulting in the dataset contributes to increased levels of tectonic displacement farther from the fault, highlighting its significance in hazard assessments. Furthermore, fault displacement contours delineate broader zones around dip-slip faults compared to strike-slip faults, with correlations identified between fault length and displacement width. Road ‘strain’ values are higher around dip-slip faults, with notable examples observed in the Westland and Buller Districts. As expected, relative hazard analysis revealed elevated values along faults with high slip rates, notably along the Alpine Fault. A regional-scale analysis of hazard and exposure reveals heightened relative hazard in specific regions, including Wellington, Southern Hawke’s Bay, Central Bay of Plenty, Central West Coast, inland Canterbury, and the Wairau Valley of Marlborough. Notably, the Central West Coast exhibits the highest summed relative hazard value, attributed to the fast-slipping Alpine Fault. The South Island generally experiences greater relative hazard due to larger and faster-slipping faults compared to the North Island, despite having fewer roads. Central regions of New Zealand face heightened risk compared to Southern or Northern regions. Critical road links intersecting high-slipping faults, such as State Highways 6, 73, 1, and 2, necessitate prioritisation for site-specific assessments, emergency management planning and targeted mitigation strategies. Roads intersecting with the Alpine Fault are prone to large parallel displacements, requiring post-quake repair efforts. Mitigation strategies include future road avoidance of nearby faults, modification of road fill and surface material, and acknowledgement of inherent risk, leading to prioritised repair efforts of critical roads post-quake. Implementing these strategies enhances emergency response efforts by improving accessibility to isolated regions following a major surface-rupturing event, facilitating faster supply delivery and evacuation assistance. This thesis contributes to the advancement of understanding fault displacement hazard by introducing a novel regional, empirical approach. The methods and findings highlight the importance of further developing such analyses and extending them to other critical infrastructure types exposed to fault displacement hazard in New Zealand. Enhancing our comprehension of the risks associated with fault displacement hazard offers valuable insights into various mitigation strategies for roading infrastructure and informs emergency response planning, thereby enhancing both national and global infrastructure resilience against geological hazards.
Natural hazard disasters often have large area-wide impacts, which can cause adverse stress-related mental health outcomes in exposed populations. As a result, increased treatment-seeking may be observed, which puts a strain on the limited public health care resources particularly in the aftermath of a disaster. It is therefore important for public health care planners to know whom to target, but also where and when to initiate intervention programs that promote emotional wellbeing and prevent the development of mental disorders after catastrophic events. A large body of literature assesses factors that predict and mitigate disaster-related mental disorders at various time periods, but the spatial component has rarely been investigated in disaster mental health research. This thesis uses spatial and spatio-temporal analysis techniques to examine when and where higher and lower than expected mood and anxiety symptom treatments occurred in the severely affected Christchurch urban area (New Zealand) after the 2010/11 Canterbury earthquakes. High-risk groups are identified and a possible relationship between exposure to the earthquakes and their physical impacts and mood and anxiety symptom treatments is assessed. The main research aim is to test the hypothesis that more severely affected Christchurch residents were more likely to show mood and anxiety symptoms when seeking treatment than less affected ones, in essence, testing for a dose-response relationship. The data consisted of mood and anxiety symptom treatment information from the New Zealand Ministry of Health’s administrative databases and demographic information from the National Health Index (NHI) register, when combined built a unique and rich source for identifying publically funded stress-related treatments for mood and anxiety symptoms in almost the whole population of the study area. The Christchurch urban area within the Christchurch City Council (CCC) boundary was the area of interest in which spatial variations in these treatments were assessed. Spatial and spatio-temporal analyses were done by applying retrospective space-time and spatial variation in temporal trends analysis using SaTScan™ software, and Bayesian hierarchical modelling techniques for disease mapping using WinBUGS software. The thesis identified an overall earthquake-exposure effect on mood and anxiety symptom treatments among Christchurch residents in the context of the earthquakes as they experienced stronger increases in the risk of being treated especially shortly after the catastrophic 2011 Christchurch earthquake compared to the rest of New Zealand. High-risk groups included females, elderly, children and those with a pre-existing mental illness with elderly and children especially at-risk in the context of the earthquakes. Looking at the spatio-temporal distribution of mood and anxiety symptom treatments in the Christchurch urban area, a high rates cluster ranging from the severely affected central city to the southeast was found post-disaster. Analysing residential exposure to various earthquake impacts found that living in closer proximity to more affected areas was identified as a risk factor for mood and anxiety symptom treatments, which largely confirms a dose-response relationship between level of affectedness and mood and anxiety symptom treatments. However, little changes in the spatial distribution of mood and anxiety symptom treatments occurred in the Christchurch urban area over time indicating that these results may have been biased by pre-existing spatial disparities. Additionally, the post-disaster mobility activity from severely affected eastern to the generally less affected western and northern parts of the city seemed to have played an important role as the strongest increases in treatment rates occurred in less affected northern areas of the city, whereas the severely affected eastern areas tended to show the lowest increases. An investigation into the different effects of mobility confirmed that within-city movers and temporary relocatees were generally more likely to receive care or treatment for mood or anxiety symptoms, but moving within the city was identified as a protective factor over time. In contrast, moving out of the city from minor, moderately or severely damaged plain areas of the city, which are generally less affluent than Port Hills areas, was identified as a risk factor in the second year post-disaster. Moreover, residents from less damaged plain areas of the city showed a decrease in the likelihood of receiving care or treatment for mood or anxiety symptoms compared to those from undamaged plain areas over time, which also contradicts a possible dose-response relationship. Finally, the effects of the social and physical environment, as well as community resilience on mood and anxiety symptom treatments among long-term stayers from Christchurch communities indicate an exacerbation of pre-existing mood and anxiety symptom treatment disparities in the city, whereas exposure to ‘felt’ earthquake intensities did not show a statistically significant effect. The findings of this thesis highlight the complex relationship between different levels of exposure to a severe natural disaster and adverse mental health outcomes in a severely affected region. It is one of the few studies that have access to area-wide health and impact information, are able to do a pre-disaster / post-disaster comparison and track their sample population to apply spatial and spatio-temporal analysis techniques for exposure assessment. Thus, this thesis enhances knowledge about the spatio-temporal distribution of adverse mental health outcomes in the context of a severe natural disaster and informs public health care planners, not only about high-risk groups, but also where and when to target health interventions. The results indicate that such programs should broadly target residents living in more affected areas as they are likely to face daily hardship by living in a disrupted environment and may have already been the most vulnerable ones before the disaster. Special attention should be focussed on women, elderly, children and people with pre-existing mental illnesses as they are most likely to receive care or treatment for stress-related mental health symptoms. Moreover, permanent relocatees from affected areas and temporarily relocatees shortly after the disaster may need special attention as they face additional stressors due to the relocation that may lead to the development of adverse mental health outcomes needing treatment.
