The objective of this study is to quantify the accuracy of two engineering models for dune erosion (SBEACH and EDUNE), and to determine which of the two models is best suited for predicting barrier island vulnerability due to extreme storm events. The first model, SBEACH, computes sediment transport using empirically derived equations from two large wave tank experiments. The second model, EDUNE, theoretically relates excess wave energy dissipation in the surf zone to sediment transport. The first mechanism for model comparison is sensitivity testing, which describes the response of the model to empirical, physical, and hydrodynamic variables. Through sensitivity tests, it is possible to determine if responses to physical variables (e.g. grain size) and hydrodynamic variables (e.g. wave height) are consistent with theoretical expectations, and whether the function of each variable is properly specified within the governing equations.
With respect to empirical parameters, model calibrations are performed on multiple study sites in order to determine whether or not the empirical parameters are properly constrained. Finally, error statistics are generated on four study sites in order to compare model accuracy. Cross-shore profiles of dune elevation are extracted from coastal lidar (light detecting and ranging) surveys flown before and after the impact of major storm events. Three study sites are taken from 1998 lidar surveys of Assateague Island, MD in response to two large northeasters that produced significant erosion along the Assateague shoreline. Two additional study sites are obtained from 2003 lidar surveys of Hatteras Island, NC in response to erosion caused by Hurricane Isabel. Error statistics generated on these study sites suggest that the models are statistically equivalent in their ability to hindcast dune erosion due to extreme storm events.
Identifer | oai:union.ndltd.org:USF/oai:scholarcommons.usf.edu:etd-3876 |
Date | 01 June 2005 |
Creators | Fauver, Laura A |
Publisher | Scholar Commons |
Source Sets | University of South Flordia |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Graduate Theses and Dissertations |
Rights | default |
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