Thesis

Methods to assess the impact of geographic interdependencies induced by extreme rainfall on the resilience of public transport networks

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Awarding institution
  • University of Strathclyde
Date of award
  • 2025
Thesis identifier
  • T17285
Person Identifier (Local)
  • 201892382
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Department, School or Faculty
Abstract
  • Severe rainfall events can concurrently affect components of public transport modes operating on discrete infrastructure networks which are co-located within the spatial extent of these events, thereby revealing geographic interdependencies between them. These interdependencies may in turn disrupt the functionality of public transport services, consequently reducing the available travel options or, in more extreme cases, causing complete loss of connectivity between locations. Despite the growing risk of these events, existing research has largely overlooked the potential of concurrent disruptions across interdependent networks. This thesis presents a novel framework for the assessment of resilience and vulnerability of geographically interdependent public transport networks using the Scottish long-distance public transport networks as a case study. The framework initially evaluates the potential impacts of area-wide events of varying spatial scales on the accessibility provided by two discrete public transport networks. Indicators are developed which quantify the contributions of alternative travel options to the accessibility of locations while also considering the geographic interdependencies between them arising from their close spatial proximity. Building on this, an empirical method is proposed to estimate the geographic interdependencies between public transport networks for a given hazard (in this case, rainfall) and integrate them into the vulnerability assessment of public transport links. The estimation of geographic interdependencies is based on historical disruption records which are analysed to determine the proximity of past concurrent flooding incidents due to rainfall. The research is then further extended by modelling the rainfall-related geographic interdependencies in probabilistic terms and incorporating them into the resilience assessment of interdependent networks, therefore providing a more realistic estimation of concurrent failures compared to deterministic approaches. Results reveal that the potential losses in accessibility can be substantial even for localised hazards and that these are positively correlated with the spatial scale of event. This suggests that the contribution of alternative travel options to accessibility of locations may be significantly reduced due to the occurrence of area-wide events and that ignoring the potential for concurrent disruptions, significantly underestimates the true consequences. When analysing rainfall as the hazard of interest, the empirical analysis confirms the existence of geographic interdependencies between rail and bus networks and reveals that the vulnerability of public transport links is significantly affected when geographic interdependencies are considered, especially within and around urban centres where many public transport services operate in close spatial proximity. This observation is further validated through probabilistic modelling, reinforcing the need to incorporate interdependencies into impact assessments. Although the findings focus on Scotland’s long-distance public transport networks, they are applicable to other regions and countries exposed to heavy rainfall. This research provides infrastructure managers and public transport operators with practical and easily implementable methods for the evaluation of resilience of geographically interdependent networks that can be implemented using readily available data and tools to identify locations and parts of their networks that require further scrutiny. Keywords: Resilience, Vulnerability, Public transport, Geographic interdependency, Accessibility, Connectivity, Redundancy, Substitutability, Flooding, Rainfall.
Advisor / supervisor
  • Ferguson, Neil S.
Resource Type
DOI

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