A Calibrated Shoreline Change Model for the Southeast Atlantic Ocean Coast of Virginia

Date of Award

Spring 1998

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Civil & Environmental Engineering

Program/Concentration

Civil Engineering

Committee Director

David R. Basco

Committee Member

A. Osman Akan

Committee Member

Donald J. P. Swift

Call Number for Print

Special Collections LD4331.E54 V36

Abstract

The idea that the long-term historic shoreline change at a given site is mainly caused by spatial gradients in the net longshore sediment transport is generally accepted. The position changes of the coastline can therefore be modeled by calculating the coastal erosion or accretion from the longshore sediment transport. This study used the GENESIS software program, one-line model, to simulate and calibrate the long-term shoreline change of the southeast coast of Virginia from 1925 to 1980. The study reach covers 45- km from Cape Henry to the Virginia-North Carolina border.

This study experienced the lack of certain important historic data covering the period of simulation ( almost 5 5 years) data maps of historic shoreline movements in the study area from the NOAA/NOS-CERC cooperative study, the 20-year offshore wave hindcast including hurricanes (1976-1995) of the Wave Information Study (WIS) Station 58 and the neighbor Stations 57 and 59, and the present bathymetic data from Virginia Institute of Marine Science (VIMS) were employed to simulate and calibrate the model. The results yield some agreement of the average shoreline change rates in the area at Sandbridge with those of the historic records. The disparity in time of the shoreline positions, the wave climates and the bathymetry is one of the factors causing the incorrect shoreline positions at some locations, especially at Dam Neck. Proper selection of the wave case in the wave time series, employing varying wave height gradients along the offshore boundary before transforming the waves, and using the appropriate transportation coefficient's values in the model helps to improve the model calibration.

Rights

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DOI

10.25777/pt1r-wa97

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