Identifying Surface Transportation Vulnerabilities and Risk Assessment Opportunities Under Climate Change: Case Study in Portland, Oregon

Researchers at Portland State University (PSU) and the Oregon Transportation Research and Education Consortium developed a framework for assessing climate change vulnerabilities to multi-modal transportation systems using a geographic information system (GIS). They used Portland as a case study for testing the GIS model and provided recommendations for how the GIS could be used to develop adaptive responses in the transportation sector. In the study, the researchers focused on two climate impacts that could affect surface transportation networks in Portland – flooding and landslides - and used GIS to model hazard locations in Portland. The study provides a framework for using GIS to (1) identify climate change vulnerabilities and potential impacts to transportation assets; (2) prioritize adaptive projects and resources; and (3) incorporate adaptation into a transportation asset management (TAM) system.

To create the model, the researchers included shapefiles (a data format with both geometric and attribute data that can be displayed as points, lines or areas) of surface transportation networks (major arterials, bus routes, light rail, bike routes, etc), major waterways, the 100-year floodplain, landslide hazard areas, the city boundary, and land-use maps.  Any segments of the transportation network that intersected with areas that had historically experienced flooding or landslides were considered potentially vulnerable to more frequent or intense impacts as a result of climate change.  However, the GIS did not include specific climate change scenarios or incorporate elevation data.  So even a raised asset, such as a bridge, would be characterized as vulnerable by the model because approaches to the bridge may flood even though the bridge is unlikely to flood.

The study revealed that forty miles (approximately seven percent) of Portland’s major roadways are vulnerable to flooding, and seventy miles (thirteen percent) are vulnerable to landslide.  For railways, seventy miles (approximately eighteen percent) are vulnerable to flooding, while fifty miles (thirteen percent) are vulnerable to landslide.  The mileage of vulnerable bus, streetcar, and light rail routes and facilities was not calculated due to inadequate data relating to the length of affected route segments and a large portion of route segments extending outside the hazard areas.  Although it appeared that flood-vulnerable segments for certain routes are primarily in the downtown and waterfront areas, many routes for each transportation mode would be adaptable in the event of a flood.  For example, bus routes and bike paths could be detoured, and bus and light rail routes could be truncated.  Most landslide-vulnerable facilities were found to be located in the hilly western portion of the city, which has fewer major arterials, bicycle facilities, and railways, but also fewer alternate routes, meaning that the existing vulnerable routes carry greater risk.

The researchers validated the model by comparing the GIS output to reports of previous flooding and landslide incidents. The model successfully identified transportation vulnerabilities to historical hazards, but could not project expanded hazard areas without incorporating additional climate change data. The researchers recommended strengthening the model in the future by developing and incorporating climate data, and updating the model as new climate change data becomes available. For adaptation planning, the researchers suggested estimating the impacts of potential disruptions and considering the costs of feasible adaptation alternatives. To estimate disruption impacts, transportation agencies can look at traffic volume along affected segments and the availability of detour routes, and use traffic modeling to estimate different types and causes of delay. 

The study concluded with descriptions of the general methods for adapting transportation assets, including avoidance, protection, abandonment, and operational responses. Avoidance involves planning and rerouting outside of hazard areas, while protection involves making improvements to facilities to increase resilience, such as increasing seawall height or fencing landslide areas.  Abandonment involves closure or disuse of facilities when other adaptation responses are not feasible or cost-effective. Operational responses include ongoing maintenance and incident response, such as planned detours for areas with periodic flooding. The researchers identified operational response as being optimal for vulnerabilities with minimal impact or low probability, or for assets with a short life span. The study noted that costs of these different adaptation responses can be considered when selecting capital improvements and maintenance projects to undertake. Planners could also use GIS models to strengthen land-use planning and zoning to minimize investments in hazard areas or require that assets be built to withstand impacts.

Data gaps that were identified include variability in the currency of GIS data, limitations in the functionality of GIS data that was initially gathered for other specific purposes, lack of spatial data for future climate scenario impacts, uncertainty regarding magnitude and probability of impacts, and reluctance of private operators and organizations to share data relating to vulnerability.

Portland was selected for the study for a variety of reasons, including access to GIS data and city staff, familiarity with the transportation system, and the small size of the study area.  Portland also has a multimodal transportation network with a wide variety of options for passengers and freight trips, which allowed the researchers to develop the model for multimodal systems.  The researchers obtained most of the GIS data for the study through the Regional Land Information System, a database managed by the regional governing body in the Portland area, and the more specialized data, including landslide hazard areas and planned transit improvements, through city and agency staff.  

 

This Adaptation Clearinghouse entry was prepared with support from the Federal Highway Administration. This entry was last updated on January 30, 2015.

 

Publication Date: 2011

Authors or Affiliated Users:

  • Lindsay Walker
  • Miguel A. Figliozzi
  • Ashley R. Haire
  • John MacArthur

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Resource Types:

  • Academic research paper
  • Case study
  • Modeling tool

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