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2: Coastal Processes

Asbury H. Sallenger, Jr., and C. Wayne Wright

U.S. Geological Survey, Florida Integrated Science Center, St. Petersburg, Florida

The USGS National Assessment of Coastal Change Hazards Project investigates the impacts of extreme storms with the ultimate objective of improving predictive capabilities. For the past decade, on the U.S. Pacific, Atlantic, and Gulf of Mexico coasts, we have used airborne lidar to acquire pre- and post-storm topography to quantify changes to impacted beaches, dunes, barrier islands, and sea cliffs. With its rapidity of acquisition and very high density, lidar has revolutionized the quantification of storm-induced coastal change. These data are being used to test state-of-the-art coastal-change models so that the magnitudes and spatial variability of future impacts can be understood and predicted.

Most recently, the National Assessment has focused on understanding hurricane impacts along the southeast coast of the U.S. For example, in 2004, we responded to all four of the hurricanes that made landfall in Florida. Each of these storms and their impacts were unique. Average shoreline change varied from approximately +1 to -20 m, and sand volume change ranged from -11 to -66 m3/m. This variability in coastal change could not be simply explained by hurricane intensity, as described by the Saffir-Simpson Hurricane Scale. In fact, the most intense storm of the season, Hurricane Charley at Category 4, resulted in the lowest mean shoreline change, while the least intense, Hurricane Frances at Category 2, resulted in the second greatest mean shoreline retreat. In 2005, we determined that a barrier island off the eastern flank of Louisiana lost 86% of its surface area during Hurricane Katrina. Further, over 50% of the island’s shore continued to erode rapidly for at least two years after the storm, pushing the island toward failure and ultimate disappearance.

Contact Information: Asbury H. Sallenger, Jr. , U.S. Geological Survey, Florida Integrated Science Center, 600 4th St. South, St. Petersburg, FL 33701; phone: 727-803-8747 x3015; email: asallenger@usgs.gov

Hilary F. Stockdon, David M. Thompson, and Kara J. Doran

U.S. Geological Survey, Florida Integrated Science Center, St. Petersburg, Florida

Along much of the East and Gulf Coasts of the United States, hurricanes have been responsible for some of the most dramatic changes to our coastal environments – from the creation of large overwash deposits to the opening of new inlets. Strong winds associated with these tropical storms bring large waves and storm surges that force significant changes on fragile barrier islands. The impact of a hurricane on a beach is highly variable over both large and small stretches of coast. This spatially variable response to storms is partly due to longshore variability of the pre-storm beach morphology combined with variability in the offshore physical forcing. Using a storm-impact scaling model that compares the relative elevations of barrier-island morphology and storm-induced water levels, we can define the potential vulnerability of our Nation’s barrier islands to extreme coastal change during a hurricane landfall.

The vulnerability of Gulf and southeast Atlantic barrier-island beaches to inundation and associated extreme coastal change during a direct hurricane landfall is assessed by comparing the elevations of storm-induced mean-water levels (storm surge and wave setup) to the elevations of the crest of the primary sand dune that defines the beach system. Storm-induced mean-water levels for Category 1-5 hurricanes are calculated as the sum of SLOSH (Seas, Lakes, and Overland Surges from Hurricanes) modeled storm surge and parameterized wave setup, based on SWAN models of maximum wave height for each category storm. Dune elevations are measured every 20 m along the coast with lidar surveys of beach topography. Maps detailing the inundation potential, the difference between the water level and dune elevations, for each category storm can be used by coastal managers to determine the relative vulnerability of barrier islands and to assess areas of a coastal community that are more susceptible to inundation and extreme storm-induced change.

Contact Information: Hilary Stockdon, U.S. Geological Survey, Florida Integrated Science Center, 600 4th Street South, St. Petersburg, Florida; phone: 727-803-8747; email: hstockdon@usgs.gov

Thomas J. Smith III, U.S. Geological Survey, Florida Integrated Science Center, St. Petersburg, Florida

Quiescent coastlines throughout the world’s tropics and subtropics are dominated by mangrove forests. Unfortunately, mangroves are disappearing at an alarming rate due to development in the coastal zone, and they are considered a threatened marine ecosystem. Mangroves provide goods and services to humans including: provision of forest products, improved water quality, stabilization of shorelines, and support of commercial and recreational fisheries. Another service claimed for mangroves is that of providing protection from storm surges and tsunamis. Following the 2004 hurricane season in Florida and the tsunami in south Asia, numerous claims of a protective role for mangroves have been made. But is it real? What types of data have been put forward in support of this function?

I conducted a thorough review of the literature concerning mangrove forests to examine the history of the “Protection” paradigm. More importantly, I examined the types of data, and their analyses, that have been put forward to support the paradigm. One recent method of examining this question has involved the use of computer models of tsunamis and tsunami run-up (i.e. how far the tsunami moves inland). These models contain parameterizations of mangrove forest structure, including measures of average stem diameter and stem density, in order to calculate frictional resistance. Do the models accurately capture how real mangrove forests are structured? During the literature review I also searched for papers that reported values for mangrove forest structure, including stem diameters, stand densities, and basal areas.

Results of the literature search were revealing. Older books (prior to 1975) did not mention protection as a role played by mangrove forests. With two exceptions, neither did the early literature. Two short notes, published together in 1971, appear to be the source of the Protection paradigm. The authors had been requested to survey the mangroves in the mouth of the Ganges delta (the Sunderbans) following a catastrophic cyclone which had killed 500,000 – 750,000 people. Both authors very clearly stated that mangroves would not have stopped 9 m storm surges nor have provided complete protection, yet they are routinely quoted as saying the opposite.

Data from >200 mangrove stands world-wide show a fractal geometry: average stem diameter is significantly and negatively correlated with average stem density (r2=.80). The parameterization of mangroves in hydrodynamic models was found to be unrepresentative of real-world forests. In one of the models that claimed a dampening of a tsunami by mangroves, the forest was modeled with a stem density of 160,000 stems/ha and a basal area of 804 m2/ha. No mangrove forest anywhere in the world has this structure. I must conclude that the “protective” function of mangroves is unsubstantiated at the present time.

Contact Information: Thomas J. Smith III, U.S. Geological Survey, Florida Integrated Science Center, 600 4th St. South, St. Petersburg, FL 33701; phone: 727-803-8747; email: Thomas_J_Smith@usgs.gov

Peter Howd and David Thompson

U.S. Geological Survey, Florida Integrated Science Center, St. Petersburg, Florida

The response of our sand-fronted coasts to extreme storms has been predicted, with statistical skill, by the Sallenger scale of coastal vulnerability in a series of papers by Stockdon and coauthors. This response classification scheme compares the extremes of the highest runup (tide+surge+ setup+ swash) to the pre-storm elevations of the dune toe and dune crest to predict one of four response categories for the dune – no change, scarping, overwash, and total inundation. While this simplistic model has been shown to have predictive skill, we recognize that changes to the beach and dune, and the timing of those changes during the storm, may provide important feedback to the observed response. Accurate representation of the beach-and-dune response should improve our skill in predicting coastal vulnerability.

An ongoing research topic is the usefulness of time-dependent dune-erosion models in improving the statistical accuracy of our vulnerability predictions. Available models for this task range from highly parameterized and very fast implementations such as EDUNE and SBEACH, to much more complete (and slower) XBEACH and Delft 3D. This presentation will evaluate the skill of the simple models in predicting the post-storm beach-and-dune profile, followed by an unverified XBEACH model simulation of Hurricane Ivan’s landfall on the Florida Panhandle in 2004. We will conclude with a brief discussion of the types of field observations needed to properly evaluate the time-dependent model skill (i.e., the observations we must make during the storm itself).

Contact Information: Peter Howd, ETI Professionals, Inc., Florida Integrated Science Center, 600 4th Street South, St. Petersburg, FL 33701; phone: 727-803-8747; email: phowd@usgs.gov

Nathaniel G. Plant and Kara J. Doran

U.S. Geological Survey, Florida Integrated Science Center, St. Petersburg, Florida

The processes that drive coastal evolution in response to a large variation in weather conditions are extremely sensitive to small changes in bathymetry and topography. This is particularly true for barrier island response. In this case, the local dune height has been identified as a key morphodynamic variable that controls barrier island responses, which range from minor erosion, to massive erosion, even when faced with extreme storms. Even if we had perfect models for predicting flows due to waves and winds and correspondingly perfect models for predicting sediment transport, uncertainties in the initial geomorphic variables would likely lead to large uncertainties in the predicted evolution. Because existing flow and sediment-transport models are not perfect, there are large uncertainties in all aspects of morphodynamic-prediction.

Figure 1. Schematic diagram of probabilistic barrier island prediction.

A probabilistic approach is required to cope with the uncertainties associated with morphodynamic prediction. We use a Bayesian network to learn the predictable part of coastal evolution in a test case based on data collected prior to and immediately after the landfall of Hurricane Ivan. The model predicts both the most likely responses as well as uncertainty of the predictions (Figure 1). The approach assimilates both model predictions and field observations. Predictions take the form of probability distributions for a reduced set of key variables. Dune height was the primary variable, but it was discovered that dune width was also important to accurately predict the response. We demonstrate the model accuracy and some interesting applications.

Contact Information: Nathaniel G. Plant, U.S. Geological Survey, Florida Integrated Science Center, 600 4th Street South, St. Petersburg, FL 33701; phone: 727-803-8747; email: nplant@usgs.gov

David P. Krabbenhoft, U.S. Geological Survey, Wisconsin Water Science Center, Middleton, Wisconsin

Mercury is a potent neurotoxin and its contamination of the environment has been a high-profile issue for the past two decades, as evidenced by issuance of widespread advisories (nearly all US states) for unsafe mercury levels in sport fish from inland waters and coastal regions. Based on rapidly improving scientific understanding of this problem for inland systems, many states are now moving forward with proposing mercury TMDLs. The same cannot be said for coastal and marine ecosystems, where far less mercury research has occurred; as a result, our scientific understanding of the critical factors controlling nearly ubiquitous elevated mercury levels in marine food webs remains poor. Especially wanting is a basic understanding of the sites and controlling factors of methylmercury, the most toxic and bioaccumulative form of mercury in the environment. This observation is especially noteworthy because a vast majority of human exposure to methylmercury results from the consumption of marine fish and shellfish. At the present time, the entire US coastline for the Gulf of Mexico is listed under a mercury advisory, yet very little is know regarding the important mercury sources, cycling, and bioaccumulation. Thus, a coordinated, multidisciplinary, and integrated mercury research program is needed for the Gulf of Mexico. Elements of such a program would include assessments of sources and transport (atmospheric, tributaries, and point sources), controls on methylation, and bioaccumulation pathways. Although some recent mercury research in this region has provided some insights into potentially important factors such as the hypoxic zone, exacerbated atmospheric loading rates, and elevated methylmercury abundance in coastal streams, we still lack an overall coordinated plan for scientific investigation. Such a program could ultimately address the question of whether it is feasible to reduce mercury concentrations of Gulf of Mexico food webs using human intervention.

Contact Information: David P. Krabbenhoft, U.S. Geological Survey, Wisconsin Water Science Center, 8505 Research Way, Middleton, WI 53562; phone: 608-821-3843; fax: 608-821-3817; email: dpkrabbe@usgs.gov