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The AAPG/Datapages Combined Publications Database

Environmental Geosciences (DEG)

Abstract

 

Shoreline Position Prediction: Methods and Errors

Francis A. Galgano1 and Bruce C. Douglas2

1Department of Geography and Environmental Engineering, United States Military Academy, West Point, NY 10996
2Department of Geography, University of Maryland, College Park, MD 20742

Lieutenant Colonel Galgano is an assistant professor of Physical Geography in the Department of Geography and Environmental Engineering at the United States Military Academy, West Point, New York. LTC Galgano completed his doctoral research in the Laboratory for Coastal Research, University of Maryland, which included a comprehensive mapping of shoreline positions from Long Island, New York to Tybee Island, Georgia. At the United States Military Academy, he oversees the core curriculum course in physical geography and focuses his research efforts on assessing the impact of tidal inlets on adjacent shorelines and erosion hazard mapping and analysis.

Bruce C. Douglas holds the position of Senior Research Scientist in the Department of Geography at the University of Maryland, College Park. Prior to coming to the University in 1995, he was Director of the National Oceanic and Atmospheric Administration's National Oceanographic Data Center. He has published extensively on the subject of twentith century global sea level change and currently has a special interest in sea level rise and coastal processes. A graduate of University of California, Los Angeles, he is a Fellow of the American Geophysical Union and the International Association of Geodesy.

ABSTRACT

Beach erosion is ubiquitous along the U. S. East Coast— ~80–90% of the beaches are eroding. Federal and state agencies thus expend a great deal of effort to determine erosion rates for establishment of construction setback lines. Historical shoreline positions are used to calculate rates of change of beach width, but the temporal variability of shoreline position creates difficulties. In most places that are highly developed or likely to become so, the annual rate of beach erosion (order ~1 meter) is small compared to the accuracy of shoreline position measurement (order ~10 meters) or the seasonal-to-interannual and longer fluctuations of beach width (order tens of meters). This unfavorable signal-to-noise ratio makes determining the underlying long-term rate of erosion problematic from even half-century- long shoreline position records unless great care is taken. Making useful shoreline position predictions and their associated errors requires an understanding of the sources of temporal variability of shoreline position. We have used real shoreline position data in endpoint rate (difference of two shoreline positions divided by time) and linear regression analyses to demonstrate the essential features of the problem for several U.S. East Coast shorelines. The scatter in computed end point rates is so large at time scales <60–80 years that an arbitrary end point rate trend is as likely to be erosional as accretional, demonstrating that the end point rate method should not be used. Linear regression usually leads to much smaller errors in shoreline change rate, but significant errors in predicted position and especially the uncertainty of the prediction will result if storminfluenced shoreline positions are included in the computation.

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