Webinar 10
Coastal Adaptation to Sea Level Rise Tool (COAST)

May 23, 2011

Summary of the Federal Highway Administration’s Quarterly Webinar: Applications of Geospatial Technologies in Transportation

These notes provide a summary of the PowerPoint presentation discussed during the webinar and detail the question and answer session that followed the presentation.

The presentation is available upon request from the webinar speaker, Dr. Sam Merrill (smerrill@usm.maine.edu).


Samuel B. Merrill, Ph. D.
New England Environmental Finance Center
Muskie School of Public Service, University of Southern Maine


Approximately 50 participants attended the webinar.

Introduction to Presentation

Mark Sarmiento of the Federal Highway Administration (FHWA) thanked participants for joining the webinar. This webinar was the tenth in a quarterly series of FHWA-sponsored webinars. The series deals with the application of geospatial information systems (GIS) and other geospatial technologies to transportation. This webinar focused on the application of the Coastal Adaptation to Sea Level Rise Tool (COAST) in determining and addressing the financial implications of sea level rise.


Global sea levels are rising, although the exact rate and extent of this change is unclear. Recently revised estimates suggest average sea levels could rise by up to five feet by 2100, resulting in massive inundation of coastal areas. Large coastal cities are expected to experience significant loss of land due to sea level rise. For example, given subsidence, New Orleans is expected to lose 50 acres per day over the next century, even without considering the effects of hurricanes. Similarly, Boston and New York are expected to lose 30 percent of their landmasses over the same period. Portland, Maine, recently lost roads, residential and commercial real estate, and other public assets due to a severe storm while Connecticut has experienced three 500-year floods in the past twelve years. Dr. Merrill emphasized the fact that the combination of sea level rise and storm surge has a particularly high potential to cause damage.

COAST Overview
To enable local governments to address the rising threat of sea level rise and storm surge, Dr. Merrill worked with Charles Colgan at the University of Southern Maine's Muskie School of Public Service to develop the technique that forms the basis of COAST.

The technique projects polygons representing hypothesized extreme weather events on top of vulnerable economic assets. The value of the assets is tallied based on whether or not certain adaptation actions have been taken in the present. For instance, in working with York County, Maine (ME), Dr. Merrill combined State economic output data with hurricane projections from the National Oceanic and Atmospheric Administration's Sea, Lake and Overland Surges from Hurricanes (SLOSH) model to determine the extent to which economic assets would be affected by hurricanes of varying magnitudes with and without a beach berm to protect waterfront hotels.

While the SLOSH model does not account for sea level rise, COAST can integrate varying degrees of sea level rise to evaluate the combined economic impact. Dr. Merrill is also working to integrate wave action into the COAST analysis, so that assets closest to the shoreline accurately experience more damage than those farther inland.

Using economic data, climate projections, and depth-damage functions developed by the U.S. Army Corps of Engineers, COAST can present the total economic loss for specific severe weather event scenarios by economic sector. However, Dr. Merrill recognized that these data on their own do not motivate action at the local level and even overhead maps can be too abstract. COAST addresses this issue by modeling the economic impacts of climate change using a “bird's eye” view, portraying both lost structural value and lost content value in a three-dimensional perspective. This modeling helps demonstrate how sea level rise could affect the value of existing infrastructure, motivating local response.

Dr. Merrill believes the COAST model is an effective tool for encouraging civic engagement around climate change. COAST does not advocate for one adaptation action over another. In some cases no action may be the best solution. The tool serves as an effective mechanism to spur conversations that might not otherwise occur and enable a public process to help decide whether and how to fortify infrastructure or conduct some form of assets relocation.

Some of the features of COAST are described below:

  • COAST can model only one scenario at a time but it can be used to pool the residual damage cost of several likely scenarios for sea level rise and compare that to the cost of available adaptation options. This approach can help communities identify strategies that are cost-effective regardless of the actual level of sea level rise. For example, COAST predicts that spending $52 million to nourish a beach up to the 50-year flood level could result in net savings of about $625 million between 2010 and 2050, even if sea levels did not rise. The same action would save almost $900 million in damage under a high sea level rise scenario.
  • COAST is capable of evaluating economic benefits of a variety of adaptation solutions, including revetments, geotextile tubes, scouring aprons, grimes, sea walls, and jetties.
  • COAST can evaluate economic impacts based on a full build-out scenario or a scenario in which restrictions to development are implemented.
  • Using inputs on sea level rise, storm surge, adaptation actions, and zoning, COAST can measure economic impact in terms of lost real estate value, lost economic output, displaced persons, and value of lost natural or cultural resources.
  • COAST can analyze the cost of lost infrastructure, a function the Maine Department of Transportation (DOT) is using to develop cost-effective storm surge-sensitive design standards for large coastal bridges.

COAST Applications
Dr. Merrill described several examples of COAST's application to local sea level rise and storm surge planning. The International Council for Local Environmental Initiatives employed COAST during a six-month series of public meetings on sea level rise adaptation planning in Groton, Connecticut (CT). The workshops used COAST to model the economic impact of a 10-year flood combined with low sea-level rise in 2070 under several adaptation scenarios. With no adaptation action taken, COAST estimated about $40 million in real estate loss. Under a scenario in which a tide gate was built and flood walls extended, many of the same parcels experienced little to no loss given the same sea level rise and 10-year storm. This comparison sparked several conversations among workshop participants about funding and how to implement strategies equitably and efficiently.

Dr. Merrill presented a second COAST example from Mystic, CT. In this example, COAST estimated that elevating certain roads, flood-proofing businesses, and installing a hurricane barrier would prevent nearly all damage caused by a 10-year storm under a low sea-level rise scenario in 2070. Damages were estimated to cost about $8.7 million without any adaptation action. In this example, COAST was also used to evaluate the cost of staged adaptation to a range of sea level rise and storm event scenarios.

Next Steps for COAST
The University of Southern Maine currently has a contract with a software development firm to develop COAST into a standalone ArcGIS extension that would include user-specified costs for pre-specified engineering actions. However, developing a downloadable tool that includes a range of input data, vulnerable asset types, and adaptation engineering options is a multi-year effort. Until this effort occurs, Dr. Merrill's team will need to be involved in any application of COAST, since it currently consists of multiple algorithms and software programs managed by different organizations.

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Question and Answer Session

In determining scenarios for bridge design standards, what did you use for long-term precipitation projections?
For freshwater storm surge modeling, we are using data sets from Maine DOT. Maine DOT has reasonable databases of volume runoff from streams entering the watershed over given periods of time. We are incorporating this information into our probability modeling. In using historic data, we try to use as much locally sourced data as possible.

I am concerned about the water table in coastal zones, where the general rule of thumb is that the water table is at mean sea level but rises and falls with the tides. Is anyone looking at how the water table will produce flooding and new wetlands inland?
I am not aware of anyone doing that kind of modeling and would be surprised if they were doing it in conjunction with cost/benefit analysis of adaptation actions. I agree it is something that is changing constantly. In Portland, ME, for example, there are areas that flood during most high tides. It is happening more and more often and people are not paying attention. That would be a good way to start looking at the issue. One could model regular recurrence intervals, perhaps over a 12-hour time period. We plot frequencies of projected storm surge based on literature and client group expectations but there is no reason we could not introduce modest and regular flooding events at high tide. That would cause accelerated degradation of roadways, which can be modeled.

Do your cost/benefit analyses include damage to, moving, or replacing drinking water and wastewater infrastructure?
They have not yet. We have done some modeling of single point files for water utilities, like a pumping station or generator, but they were small items and relatively low cost. In considering all drinking or waste water infrastructure, the impacts are larger and, although we look forward to getting more involved with them, it would be a much more expensive effort. It could cost $20,000 to $30,000 for a project of similar size to what we did in Groton, CT. If it is a city conducting an entire master planning process for a new sewer system in the next 70 years and performing cost/benefit analyses for various layouts, that could cost several hundred thousand dollars. A range of costs might apply but it can be done, since COAST is a scale-neutral tool.

Can you talk about how the uncertainty inherent in the projections affects COAST's ability to develop meaningful results?
Regarding the Maine DOT work, we are creating joint probability curves, which is a step-by-step procedure. It comes down to assumptions you want to make on the front end, so if the assumptions are poor, the outputs are poor. The first important question is: what are the data and what are you using for storm surge probabilities? For Maine DOT, we are incorporating existing data with what we have from a century's worth of tide gauge data. Once we create a probability curve based on those data, we will expand it to other areas between the tide gauges. We also provide a set of local hydrologic variables that need to be collected at the specific sites. We then combine the freshwater historic data, extrapolated tide data, local hydrologic data, and depth damage functions using a method we plan to publish in a report for the Maine DOT later this year.

The great unknown in redeveloping the Mississippi Gulf Coast is the cost and availability of insurance. Is there interest in using the cost/benefit ratio of adaptation as an incentive to the insurance industry to provide coverage in high-risk areas?
There is interest from the insurance industry for this kind of work. For example, a recent report from an analytic firm provided similar maps to what we just provided for Groton, CT, and Old Orchard Beach, ME. The report showed how much financial value is at risk for major metropolitan areas under a range of sea level rise scenarios but did not provide details about how the calculations were made. The insurance industry generally does not address adaptation options that community groups might take in response to sea level rise and storm surge or to the associated benefits. Insurance companies typically pay a lot of attention to climate change risks but not to the benefits of taking different types of actions.

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