Modelling Network Resiliency to Prepare for Climate Change

Climate change has the potential to transcend our way of life, and a key element of that is how we get around. Increasingly severe weather events such as snowstorms, hurricanes, or flash floods, or slower processes such as rising water levels, may leave our highways underwater, our transportation hubs isolated, and our rail lines blocked. Under these conditions, the ability of the overall transportation network to continue to allow emergency responders to act and people to evacuate will be placed under a severe strain. At this point, a transportation network unable to cope with the conditions may result in mobility chaos at best and disaster at worst, making it critical to incorporate resilience testing into future network planning. The Greater Golden Horseshoe Transportation Plan, currently under development by the Ontario Ministry of Transportation (MTO), will test network and service elements in the region under pressure to ensure proofing of transportation infrastructure in Southern Ontario against future conditions. One way in which this could be tested is by assessing the resilience of the existing network to major and recurring events using long range modelling and macroscopic forecasting tools. Using such tools we can stress-test the busiest and most critical network elements and mimic the impact of inclement weather events, or emergency situations, such as the closure of a major rail terminal or highway corridor, or the blockage of interchanges along the busiest freeways, and evaluate for each scenario how resilient the overall network is in reacting to and accommodating demand. A different application of a similar approach could be considered when planning for future road and rail infrastructure in an attempt to act pre-emptively and offset the impact of climate change. Certain locations, such as floodplains, areas susceptible to blowing snow, and urban heat islands, inherently place more stress on infrastructure, and pose higher risks to people and goods travelling through them. Using macroscopic forecasting models and GIS tools we can identify the demand that a potential corridor would generate and compare the extent of infrastructure or the demand in terms of people, vehicles, and value of goods that would use the risk-prone corridors. This approach could help us identify “safer” routes, corridors and infrastructure elements in order to build resilient transportation networks.


  • English

Media Info

  • Media Type: Web
  • Pagination: 1 PDF file, 873 KB, 11p.
  • Monograph Title: Edmonton 2018 - CITE Annual Meeting and Conference - Technical Compendium

Subject/Index Terms

Filing Info

  • Accession Number: 01685377
  • Record Type: Publication
  • Source Agency: Transportation Association of Canada (TAC)
  • Files: ITRD, TAC
  • Created Date: Nov 16 2018 3:32PM