Lisa Rygel, Penn State University Penn State Logo

Link to poster presented at The 2003 Open Meeting, Human Dimensions of Global Environmental Change, Montreal Canada.

Lisa RygelMy master's degree research (in the Geography department at Penn State) used Hampton Roads, Virginia as a case study to understand how sea-level rise might increase the vulnerability of people and infrastructure to hurricane storm-surge flooding over the next century. Here is a link to my thesis: Modeling the Vulnerability of Coastal Communities to Hurricane Storm Surge With Sea-Level Rise: A Case Study of Hampton Roads, Virginia.

See case study, Defining the Elements of a Decision Landscape Diagram + Additional Hampton Roads Discussion

The best estimate given by the United States Global Change Research Program for global sea-level rise by the year 2100 is 48 cm (18.7 in) (NAST, 2000). However, relative local sea-level rise for the Mid-Atlantic Region will be greater than global averages, as the region is experiencing subsidence at a rate of about 2 mm (.08in)/year (Najjar et al., 2000). Thus, I chose a baseline sea-level rise scenario of 60 cm (23.4 in) for Hampton Roads by the year 2100. I also chose a low-end sea-level rise scenario of 30 cm (11.7 in) and a high-end scenario of 90 cm (35.1 in).

I used output from the SLOSH (Sea, Lake, and Overland Surges from Hurricanes) model to evaluate the possible exposure of Hampton Roads to storm-surge flooding. The SLOSH model, run by the National Hurricane Center, is a computerized model used to estimate hurricane storm surge heights. The SLOSH model was originally meant to make real-time forecasts for surge heights of approaching hurricanes (Jelesnianski et al., 1992). When the model is used to estimate surge from an actual hurricane, results are generally accurate within plus or minus twenty percent (NHC, 2004).

In recent years, in addition to estimating surge heights for predicted storms, the SLOSH model has been used to ascertain which coastal areas are at risk of storm-surge flooding (Jelesnianski et al., 1992; see Wu et al., 2002). SLOSH model output has become important to the development of coastal hurricane evacuation plans (NHC, 2004).

The National Hurricane Center has divided the coasts of the United States into a series of 38 SLOSH basins, and each basin is divided into hundreds of grid cells. For each basin, the NHC runs hundreds of hypothetical hurricanes of various intensities, forward speeds, and landfall locations. After all model runs are completed, the NHC reports the maximum surge height obtained by each cell for hurricanes of a particular Saffir-Simpson category (NWS, 2004). Surge heights can then be compared to elevation values.

For this study, I used output for the Pamlico Sound SLOSH basin, which covers the entire study area. The model output contains five gridded layers that correspond to storm surge heights at high tide for hurricanes of intensities 1 through 5 on the on the Saffir-Simpson scale. Results are given in feet above mean sea level.

I compared the SLOSH model output to a digital elevation model (DEM) obtained from the United States Geological Survey. Elevations are expressed in meters above sea level. Immediately along the coast, the DEM has 10-meter cells that are accurate within one-tenth of a meter. Cells further inland are 30 meters per side and accurate within one meter.

To compare the SLOSH model output to the DEM, I matched the vertical datum of the DEM to that of the SLOSH model, and I converted SLOSH values from feet to meters. For each hurricane category, I mapped the areas where storm surge heights were greater than surrounding elevation values. Because high-elevation barriers can prevent the propagation of flood waters, I excluded from the at-risk zone any low-lying area that initially appeared to be at risk of flooding but was completely surrounded by higher, non-flooded land.

After mapping the flood-risk zone for each hurricane category, I added 30,60, and 90cm to the SLOSH model output. I then repeated the analysis for each sea-level rise scenario.

Other aspects of my project include: using socioeconomic data to calculate and map social vulnerability, mapping the locations of certain critical facilities in relation to present and possible-future storm-surge flood-risk zones, and considering possible population-growth scenarios.

Sources:

Jelesnianski, C., Chen, J., and Shaffer, W., 1992. SLOSH: Sea, Lake, and Overland Surges from Hurricanes. NOAA Technical Report , NWS 48.

Najjar, R.G., Walker, H.A., Anderson, P.J., Barron, E.J., Bord, R.J., Gibson, J.R., Kennedy, V.S., Knight, C.G., Megonigal, J.P., O'Connor, R.E., Polsky, C.D., Psuty, N.P., Richards, B.A., Sorenson, L.G., Steele, E.M., Swanson, R.S., 2000. The Potential Impacts of Climate Change on the Mid-Atlantic Coastal Region. Climate Research 14: 219-233.

National Assessment Synthesis Team, United States Global Change Research Program, 2000. Climate Change Impacts on the United States: The Potential Consequences of Climate Variability and Change (Overview) . Cambridge University Press, Cambridge, UK.

National Hurricane Center, 2004. Hurricane Awareness: Storm Surge. Available at: http://www.nhc.noaa.gov/HAW2/english/storm_surge.shtml

National Weather Service, 2004. Hurricane Storm Surge Forecasting. Available at: http://www.nws.noaa.gov/tdl/marine/hursurge.htm

Wu, S.Y., Yarnal, B., and Fisher, A., 2002. Vulnerability of Coastal Communities to Sea-Level Rise: a Case Study of Cape May County, New Jersey, USA. Climate Research 22: 255-270.