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.
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.
Improving community resilience requires a way of thinking about the nature of a community. Two complementary aspects are proposed: the flows connecting the community with its surrounding environment and the resources the community needs for its ongoing life. The body of necessary resources is complex, with many interactions between its elements. A systems approach is required to understand the issues adequately. Community resilience is discussed in general terms together with strategies for improving it. The ideas are then illustrated and amplified by an extended case study addressing means of improving the resilience of a community on the West Coast of New Zealand to natural disasters. The case study is in two phases. The first relies on a mix of on-the-ground observations and constructed scenarios to provide recommendations for enhancing community resilience, while the second complements the first by developing a set of general lessons and issues to be addressed from observations of the Christchurch earthquakes of 2010 and 2011.
