HR: 0800h
AN: OS21B-1221    [Abstracts]
TI: Morphologic evolution: nonlinear coupling between cross-shore and alongshore variability and the incident wave field
AU: * Plant, N G
EM: nplant@nrlssc.navy.mil
AF: Naval Research Labortary, Code 7440.3, Stennis Space Center, MS 39529 United States
AU: Holland, K T
EM: tholland@nrlssc.navy.mil
AF: Naval Research Labortary, Code 7440.3, Stennis Space Center, MS 39529 United States
AU: Holman, R A
EM: holman@coas.oregonstate.edu
AF: Oregon State University, Ocean Admin Bldg, Corvallis, OR 97331 United States
AB: The morphodynamic state classification of beach morphology recognizes that there is a strong interaction between an existing beach morphology, the incident wave conditions, and the subsequent beach evolution. This interaction leads to, for instance, hysteresis where the change in beach patterns under increasing wave energy is not simply reversed under decreasing wave energy. However, attempts to skillfully model this effect have had only limited success. Failure to predict beach state changes likely resulted from inadequate spatial or temporal resolution of observations, qualitative definitions of beach states, and over-simplified representations of the evolution model. Using a combination of surveyed bathymetry and remote sensing data of the nearshore we have developed a method to estimate high resolution bathymetry over a spatially extensive region. The method has been applied to the nearshore region at Duck, NC, yielding a 3-dimensional data cube (i.e., elevation as a function of time and cross-shore and alongshore position) during episodes of dramatic morphologic change. This data set allows unprecedented high resolution analysis of morphologic evolution. Quantitative measures of the morphologic state (e.g., temporal and spatial variation in bar position) are extracted from the data cube. The morphodynamic state is then predicted using nonlinear forecasting techniques, which to exploit the strong coupling between morphology and incident wave conditions. We demonstrate the predictive skill of this approach.
DE: 4546 Nearshore processes
DE: 3020 Littoral processes
DE: 3022 Marine sediments--processes and transport
SC: Ocean Sciences [OS]
MN: 2004 AGU Fall Meeting