Coastal Vulnerability to Sea-Level Rise: A Preliminary Database for the U.S. Atlantic, Pacific, and Gulf of Mexico Coasts

Coastal Changes Due to Sea-Level Rise:

One of the most important applied problems in coastal geology today is
determining the physical response of the coastline to sea-level rise.
Predicting shoreline retreat, beach loss, cliff retreat, and land loss rates is
critical to planning coastal zone management strategies and assessing
biological impacts due to habitat change or destruction. Presently, long-term
(>50 years) coastal planning and decision-making has been done piecemeal, if at
all, for the nation's shoreline (National Research Council, 1990; 1995).
Consequently, facilities are being located and entire communities are being
developed without adequate consideration of the potential costs of protecting
or relocating them from sea-level rise related erosion, flooding and storm
damage.

Recent estimates of future sea-level rise based on climate modeling (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).

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: 1.
extrapolation of historical data (for example, coastal erosion rates); 2.
static inundation modeling; 3. application of a simple geometric model (for
example, the Bruun Rule); 4. application of a sediment dynamics/budget model;
or 5. 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 (for example, 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.

Variables Affecting Coastal Vulnerability:

We use here a fairly simple classification of the relative vulnerability of
different U.S. coastal environments to future rises in sea-level. 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 vulnerability classification is based upon the relative
contributions and interactions of six variables:

1. Tidal range, which contributes to inundation hazards.

2. Wave height, which is linked to inundation hazards.

3. Coastal slope (steepness or flatness of the coastal region), which is linked
to the susceptibility of a coast to inundation by flooding and to the rapidity
of shoreline retreat.

4. Shoreline erosion rates, which indicate how the given section of shoreline
has been eroding.

5. Geomorphology, which indicates the relative erodibility of a given section
of shoreline.

6. Historical rates of relative sea-level rise, which correspond to how the
global (eustatic) sea-level rise and local tectonic processes (land motion such
as uplift or subsidence) have affected a section of shoreline.

The input data for this database of coastal vulnerability have been assembled
using the original, and sometimes variable, horizontal resolution, which then
was resampled to a 3-minute grid cell. A data set for each risk variable is
then linked to each grid point. For mapping purposes, data stored in the
3-minute grid is transferred to a 1:2,000,000 vector shoreline with each
segment of shoreline lying within a single grid cell.

[Summary provided by the USGS.]