Talk Planning for Transportation and Ecosystem Adaptation to Sea Level Rise
  • Fraser M Shilling
    Bio statement : I am the co-director of the Road Ecology Center at the University of California, Davis. I driect research and education programs at the REC and within the Department of Environmental Science and Policy at UC Davis.
    Reviewing interests: roadkill, road effect zone, wildlife crossing structrues, camera traps, monitoring, connectivity, traffic noise, sea level rise, sustainability
    Country : US
    Contact : fmshilling@ucdavis.edu
    Website : http://roadecology.ucdavis.edu
Abstract

I describe a generalizable planning and assessment process for adaptive management and adaptation of transportation infrastructure to sea level rise (SLR). A single coastal California (CA) highway and surrounding tidal and terrestrial ecosystems were used as the laboratory. Sea level has risen in CA by >20 cm and by 2100 may be 1 to 1.7 m higher. During the winter of 2015-16, low and high tides were up to 25 cm higher than predicted (probably due to El Nino), providing a view into a world with 25 cm of SLR. Climate change is expected to result in accelerated rates of sea level rise and changing seasonal wave conditions, further exposing the shorelines to impacts. Infrastructural and living systems adaptations will need to occur to avoid a wholesale change in the marshes, estuarine systems, low-lying urban areas, and exposed highway infrastructure along global coastlines. A longitudinal survey of coastal managers in CA found SLR and related problems to be among their most challenging issues. Identifying and modifying infrastructure that is exposed and vulnerable to SLR and increased storminess is complicated and potentially expensive for governments. The physical structures themselves are vulnerable to SLR, which is likely to result in increased costs and eventual adaptation. in addition, the function of linked, regional transportation systems may be vulnerable to disruption if an SLR-vulnerable link fails.

State Route 37 (SR 37) is the California highway that may be most vulnerable to temporary flooding and permanent inundation due to SLR.  Like many other coastal highways in the US, SR 37 is adjacent to protected coastal ecosystems (e.g., beaches, tidal wetlands), meaning that any activity on the highway is subject to regulatory oversight. Due to a combination of congestion and threats from SLR, planning for a new highway adaptive and resilient to SLR impacts was conducted in the context of stakeholder participation and Eco-Logical, a planning process developed by the (US) Federal Highways Administration to better integrate transportation and environmental planning. In order to understand which stretches of approximately 30 km of SR 37 and adjacent landscape might be most vulnerable to SLR, and to what degree, a model of potential inundation was developed by a contractor (AECOM) using a recent, high-resolution elevation assessment conducted using LiDAR. Potential inundation was modeled based upon comparison of future daily and extreme tide levels with surrounding ground elevations. The risk to and vulnerability of each segment was scored and cost of adaptive structures estimated (US$0.8 to 4 billion) in order to inform infrastructural planning. The adaptive structures were also assessed for potential (dis)benefits.

The tidal ecosystems adjacent to SR 37 both buffer the highway from wave and tidal energy and are vulnerable to impacts from SLR. In order to monitor SLR impacts at a timescale relevant to transportation and conservation planning. I developed a combined time-lapse camera and image analysis technique to monitor changes in tidal inundation and shoreline resulting from SLR and storm events. The technique is very sensitive to small vertical changes in SLR (<10 cm) because of the large horizontal changes in shoreline resulting from small vertical changes. This technique is high-resolution and scaleable from local to national extents. Early results from this system will be presented.

Keywords
sea level rise, adaptation, adaptive management