Greater Christchurch has been through a lot over the past 25 years, and its public transport is no exception. This paper aims to understand the broader factors that have influenced public transport patronage growth from 1999-2025. This is split into two periods, 1999-2010 and 2015-2025, before and after the 2010-2011 Canterbury Earthquake Sequence which fundamentally changed Greater Christchurch. Patronage grew from 9.7 to 17.2 million per year in this first period, unprecedented growth for this network, during a time of significant investment into the network. In contrast, 2015-2025 saw stagnation in growth, or even decreases, only growing after the COVID-19 pandemic. Patronage could not keep up with population growth after the earthquakes with growth mostly occurring in the outer areas of Christchurch and its satellite towns. People are less likely to bus from these areas due to long travel times into much of Christchurch, significantly longer than by car. Additionally, many businesses and employees moved outside of Central Christchurch, the main employment area for Greater Christchurch, after the earthquakes, into areas with relatively low bus routes. Significantly less people were willing to bus to work in these areas, apart from Riccarton and Papanui. However, businesses have been returning to Central Christchurch, with more people willing to bus to work there. These past determinants of growth are important to understand so that their effects can be individually researched more in-depth in future, to provide greater clarity on what have been successful factors for public transport growth in Greater Christchurch, and find out if they can be reimplemented or expanded to reignite some of the growth experienced in the 2000’s.
Road networks are highly exposed to natural hazard events, which can lead to significant economic and social consequences. In New Zealand, events such as the 2011 Christchurch earthquake, the 2016 Kaikōura earthquake, and the Cyclone Gabrielle in 2023 have demonstrated the severe consequences of road network disruptions. Traditional post event economic assessments often focus solely on clean-up and repair costs, neglecting the broader and more enduring impacts these events can have. Furthermore, business cases for resilience investments usually fail when quantifying the economic benefits of mitigation strategies, due to the underestimation of road disruption consequences. Importantly, not all road link disruptions contribute equally to these consequences, making the identification of critical road links a key step in resilience focused investment prioritization. Furthermore, traditional transportation asset management typically evaluates the life cycle of roads under normal conditions, such as traffic loads and standard environmental factors, while neglecting the influence of natural hazards. However, these events can significantly alter road deterioration and increase maintenance costs, emphasizing the need for integrating risk and resilience into transportation asset management approaches. This thesis presents a methodology to evaluate road criticality by assessing the economic consequences of road disruptions in combination with a hazard model in a prioritization index. Initially, the consequences are quantified through increased travel time, higher vehicle operating costs, and increased gas emissions. Thereafter, a new consequence model is introduced to estimate the increase in maintenance costs on alternative routes that absorb diverted traffic following a disruption. These consequence models are initially applied in a 'full-scan' analysis approach, where each road link is removed in turn to quantify its potential impact and, therefore, its criticality. Subsequently, a hazard model is integrated to develop a road prioritization index that combines the expected impacts of road disruptions, the individual road link criticality, and the probability of occurrence of natural hazard events. This index is designed to help road agencies in prioritizing mitigation strategies. Furthermore, the proposed methodology can also be applied to quantify the indirect economic impacts of natural hazard events. The methodology is demonstrated using New Zealand’s South Island inter-urban network as a case study, incorporating an earthquake-induced landslide model, with Python based simulations, providing road agencies a valuable tool to quantify the economic benefits of resilience investments
