Climate change in asset management of infrastructure: A riskbased methodology applied to disruption of traffic on road networks due to the flooding of tunnels
DOI:
https://doi.org/10.18757/ejtir.2016.16.1.3116Abstract
This paper presents a risk-based method to quantify climate change effects on road infrastructure, as a support for decision-making on interventions. This can be implemented in climate adaptation plans as an element of asset management. The method is illustrated by a specific case in which traffic on a road network is disrupted by the flooding of a tunnel due to extreme rainfall. Novel techniques to describe both probability of occurrence and consequences of an event are integrated into the proposed risk-based approach. To model a typical climate-change related phenomenon, i.e. rainfall intensity-duration, a model using copulas is proposed as well as a method to account for uncertainty using structured expert judgement. To quantify the consequences, an existing quick scan tool is adopted. The method calculates the risk of flooding of a tunnel, expressed in both probability of occurrence and subsequent additional travel duration on the road network. By comparison of this evolving risk to a societally acceptable threshold, the remaining resilience of the tunnel is evaluated. Furthermore, the method assesses the development of the resilience over time as a result of projected climate change. The maximum time-to-intervention is defined as the period up until the moment when the resilience is depleted. By application of the method to a tunnel in two different contexts, i.e. in a regional road network and a highway network, it is shown that the consequences of tunnel flooding may differ by an order of magnitude (25-fold for the example). Using a risk-based decision-making perspective leads to significant differences in the maximum time-to-intervention. In the example case the year of intervention is determined at 2020 for a tunnel in a highway network, while interventions can be postponed until 2140 in a regional road network.