Table of Contents Web Site Title Page Introduction Risk Variables Data Ranking Coastal Vulnerability Index Results Discussion Summary References Woods Hole Field Center Home Page Coastal and Marine Geology Program Home Page U.S. Geological Survey with link to U.S.G.S. Home Page
 


National Assessment of Coastal Vulnerability to Sea-Level Rise: Preliminary Results for the U.S. Pacific Coast


Introduction



Recent estimates of future sea-level rise based on climate model output (Wigley and Raper, 1992) suggest an increase in global eustatic sea-level of between 15 and 95 cm by 2100, with a "best estimate" of 50 cm (IPCC, 1995). This is more than double the rate of eustatic rise for the past century (Douglas, 1997; Peltier and Jiang, 1997). Thus, sea-level rise will have a large, sustained impact on coastal evolution at the societally-important decadal time scale. For example, Zhang et al. (1997) showed that sea-level rise over the past 80 years at two locations on the U.S. East Coast contributed directly to significant increases in the amount of time the coast is subjected to extreme storm surges. From 1910-1920, the coast near Atlantic City, New Jersey was exposed to anomalously high water levels from extreme storms less than 200 hours per year, whereas during the early 1990's the coast was exposed to high water from storms of the same magnitude 700 to 1200 hours per year. Interestingly, the authors found that although storm surge varied a great deal on annual to decadal scales, there was no long-term trend showing increases in storm intensity or frequency that might account for the increasing anomalously high water levels. Zhang et al. (1997) concluded that the increase in storm surge exposure of the coast was due to sea-level rise of about 30 cm over the 80-year period. This finding suggests that the historical record of sea-level change can be combined with other variables (e.g., elevation, geomorphology, and wave characteristics) to assess the relative coastal vulnerability to future sea-level change.

The prediction of coastal evolution is not straightforward. There is no standard methodology, and even the kinds of data required to make such predictions are the subject of much scientific debate. A number of predictive approaches have been used (National Research Council, 1990), including:

  • extrapolation of historical data (e.g., coastal erosion rates),
  • static inundation modeling,
  • application of a simple geometric model (e.g., the Bruun Rule),
  • application of a sediment dynamics/budget model, or
  • Monte Carlo (probabilistic) simulation based on parameterized physical forcing variables.

Each of these approaches, however, has its shortcomings or can be shown to be invalid for certain applications (National Research Council, 1990). Similarly, the types of input data required vary widely, and for a given approach (e.g. sediment budget), existing data may be indeterminate or may simply not exist (Klein and Nicholls, 1999). Furthermore, human manipulation of the coast in the form of beach nourishment, construction of seawalls, groins, and jetties, as well as coastal development itself, may dictate federal, state and local priorities for coastal management without proper regard for geologic processes. Thus, the long-term decision to renourish or otherwise engineer a coastline may be the primary determining factor in how that coastal segment evolves.

Back to Top

Although a viable, quantitative predictive approach is not available, the relative vulnerability of different coastal environments to sea-level rise may be quantified at a regional to national scale using basic information on coastal geomorphology, rate of sea-level rise, past shoreline evolution, and other factors. This approach combines the coastal system's susceptibility to change with its natural ability to adapt to changing environmental conditions, and yields a relative measure of the system's natural vulnerability to the effects of sea-level rise (Klein and Nicholls, 1999). The overall goal of this study is to develop and utilize a relatively simple, objective method to identify those portions of the U.S. coast at risk and the nature of that risk (e.g., inundation, erosion, etc.). The long-term goal of this study is to predict future coastal changes with a degree of certainty useful for coastal management, following an approach similar to that used to map national seismic and volcanic hazards (e.g., Miller, 1989; Frankel et al., 1996; Hoblitt et al. 1998). This information has immediate application to many of the decisions our society will be making regarding coastal development in both the short- and long-term.

This study involves two phases. The first phase, presented in this report for the U.S. Pacific Coast and a previous report for the U.S. Atlantic Coast (Thieler and Hammar-Klose, 1999), involves updating and refining existing databases of geologic and environmental variables, such as that compiled by Gornitz and White (1992). The variables included in this database are geomorphology, regional coastal slope, rate of relative sea-level rise, shoreline erosion and accretion rates, tide range and mean wave height. For all of the variables in this data set, updated or new data exist and are included in this analysis. The second phase of the project has two components. The first component entails integrating model output such as eustatic, isostatic, and short-term climatic sea-level change estimates in order to assess the potential impacts on the shoreline due to these changes. The second component involves developing other databases of environmental information, such as relative coastal sediment supply, as well as including episodic events (hurricane intensity, track, and landfall location, Nor'easter storm intensity data, and El Niño-related climate data such as short-term sea-level rise), and human influences (e.g., coastal engineering such as beach nourishment).

Back to Top

In this preliminary report, the relative vulnerability of different coastal environments to long-term sea-level rise is quantified for the U.S. Pacific Coast. This initial classification is based upon variables such as coastal geomorphology, regional coastal slope, rate of sea-level rise, wave and tide characteristics, and historical shoreline change rates. The combination of these variables and the association of these variables to each other furnishes a broad overview of regions where physical changes are likely to occur due to sea-level rise.




Previous Page  Contents  Back to Top  Title Page  Next Page

 Introduction  Risk
Variables
 Data
Ranking
 C.V.I.  Results  Discussion  Summary  References

[an error occurred while processing this directive]