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Woods Hole Coastal and Marine Science Center

Woods Hole Coastal and Marine Science Center > Sea-Level Rise Hazards and Decision Support > Research > Shoreline Change and Land Loss

Shoreline Change and Land Loss

One of the principal impacts of sea level rise will be the loss of land in coastal areas through erosion and submergence of the coastal landscape.  Erosion caused by higher sea level results from subjecting previously out-of-reach land to waves and currents, as well as to changes in storm characteristics also driven by climate change.  Much of the shore along the ocean coast and inland regions consists of landforms such as beaches, barrier islands, bluffs, and marshes that result from a dynamic interaction between the physical processes (waves and tides) and the geologic composition of a specific location (figure SC1).  It has long been recognized that changes in sea level drive changes in the location of these coastal landforms over centuries to millennia. Many of the changes observed over days to years are caused by storms or changes in the amount of sediment available to sustain the shore.

Because a range of factors -- that vary from location to location -- contribute to coastal landform changes, long-term predictions are inherently uncertain even if the forcing (sea level rise and storminess) are known. Despite the limitations to forecasting shoreline changes far into the future, there are basic data sets such as historic shoreline positions that can be used to identify and evaluate the potential for future changes. The USGS conducts research to develop historic shoreline data and quantify changes in shoreline positionStorm impacts to beaches and barrier islands are also a major USGS research focus.

The information from these existing research efforts provides a basis to assess the potential for future shoreline changes. The initial phase of our work focuses on evaluating the utility of Bayesian Network (BN) to predict long-term shoreline change associated with sea level rise along the Atlantic coast of the U.S. using the USGS Coastal Vulnerability Index data set.  The BN was used to define relationships between driving forces, geologic constraints, and shoreline response. Data used in the BN includes observations of local rates of relative sea level rise, wave height, tide range, geomorphic setting, coastal slope, and rate of historical shoreline change (figure SC2).

The BN was used to make probabilistic predictions of shoreline retreat in response to different future sea level rise rates and quantitative estimates of uncertainty in these predictions.  Results demonstrate that the probability of shoreline retreat increases with higher rates of sea level rise. In addition, when more specific information is included, specified by the selection of specific values for each variable, the probability of shoreline change can increase, indicating more confident predictions.  A comparison of observed and predicted rates of shoreline change indicated that the BN correctly predicts approximately 70% of the cases. In addition, the ability to determine the probability of a certain outcome allows the results to be presented using established terminology for uncertainty such as that used by the Intergovernmental Panel on Climate Change (IPCC) (figure SC3).

Photograph of over washed island

Figure SC1. Photo of northern Assateague Island showing fresh sandy washover deposits that resulted from overwash during strong storms. Overwash is an important process on barrier islands that moves sediment into the island interior and sometimes completely across the island. (J. Cohen, Virginia Tech).

Diagram of Bayesian Network relationships

Figure SC2. A graphical depiction of a Bayesian Network where arrows indicate relationships between variables. In this example, several variables are defined to have an influence on others, as well as the response variable, shoreline change rate.

Map showing shoreline probabilities

Figure SC3.  Probabilities of shoreline change calculated with a Bayesian Network informed by information regarding rate of long-term shoreline change, rate of long-term sea level rise, coastal slope, geomorphic setting, mean tidal range and mean wave height. The resulting probabilities can be expressed as likelihoods and described in terms used by the IPCC for climate change impacts. The map on the left shows the probability of shoreline erosion exceeding 2 meters per year. The map on the right shows the maximum probability for any of the shoreline change outcomes.

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Page Last Modified:Tuesday, 07-Jul-2015 13:50:04 EDT (GW)