GSA Annual Meeting, November 5-8, 2001

Paper No. 0
Presentation Time: 9:30 AM

IMPROVING THE DETERMINATION OF SHORELINE CHANGE WITHIN NATIONAL SEASHORES


LIST, Jeffrey H., FARRIS, Amy S. and WEBER, Kathryn Konicki, US Geol Survey, 384 Woods Hole Rd, Woods Hole, MA 02543-1598, jlist@usgs.gov

Accurate information on long-term shoreline change trends is fundamental to the management of coastal resources in National Seashores, as well as for estimating the sediment budget and evaluating processes responsible for long-term coastal change. Quantifying long-term (decadal or longer) shoreline change involves many challenges related both to the basic definition of shoreline position and to the short-term variability of shoreline position. To address these issues, we initiated a prototypical shoreline measurement program within the Cape Cod National Seashore (CACO) and the Cape Hatteras National Seashore (CAHA) using a ground-based GPS survey system that quantifies shoreline position as the mean high water (MHW) contour's intersection with the beach foreshore.

The measurement program consists of bi-weekly surveys along 45 km of ocean coast within CACO since 1998 and monthly surveys along 130 km of northern North Carolina coast (including 70 km of CAHA) initiated in 1999. This intensive series of measurements provides unprecedented information on short-term shoreline position variability driven by storms, the seasonality of storm groups, and the evolution of mega-cusp type shoreline features. Treating this short-term variability as system noise, we evaluate the statistical significance of long-term change and consider the advantages of spatial and temporal averaging.

We show that without averaging, long-term shoreline change must exceed 40 m to be significant in some areas. Spatial or temporal averaging of shoreline position, however, greatly reduces the noise of the system. With noise reduction, smaller shoreline changes are more likely to be statistically significant, permitting the use of a shorter time interval for shoreline change and increasing the chances that measured change rates reflect current trends. We provide an example demonstrating the advantages of temporal averaging using our North Carolina data combined with 1970's beach profiles collected by the U.S. Army Corps of Engineers, and suggest an optimal methodology for monitoring coastal change within National Seashores.