HR: 0800h
AN: H31E-1351    [Abstracts]
TI: Quantifying Coastal Change Patterns Using LIDAR
AU: * Tebbens, S F
EM: sarah.tebbens@wright.edu
AF: DWright State Universityepartment of Physics, 3640 Colonel Glenn Hwy, Dayton, OH 45435 United States
AU: Murray, A
EM: abmurray@duke.edu
AF: Division of Earth and Ocean Sciences, Nicholas School of the Environment and Earth Sciences/ Center for Nonlinear and Complex Systems Duke University, Box 90230, Durham, NC 27708 United States
AU: Ashton, A D
EM: andrew.ashton@duke.edu
AF: Division of Earth and Ocean Sciences, Nicholas School of the Environment and Earth Sciences/ Center for Nonlinear and Complex Systems Duke University, Box 90230, Durham, NC 27708 United States
AU: Ashton, A D
EM: andrew.ashton@duke.edu
AF: Woods Hole Oceanographic Institution, 360 Woods Hole Rd, Woods Hole, MA 02543 United States
AU: Ashton, A D
EM: andrew.ashton@duke.edu
AF: USGS Woods Hole, 384 Woods Hole Rd, Woods Hole, MA 02543 United States
AB: Shorelines undergo continuous change, primarily in response to the action of waves. New technologies including LIDAR surveys are just beginning to reveal surprising shoreline behaviors over a range of space and time scales (e.g. List and Farris, 1999; Tebbens et al, 2002). This early stage of coastal physical science calls for further documentation and analysis of the range of phenomena involved. Wavelt analysis of the changes along the North Carolina Outer Banks, USA, over a single annual interval (Tebbens et al., 2002) quantify statistics including: 1) the amount of shoreline change as a function of alongshore length scale; 2) the distribution of the alongshore-lengths of contiguous zones of erosion and accretion; and 3) the distribution of the magnitudes of erosion and accretion occurring during a time interval. The statistics of the patterns of shoreline varied among the different coastline segments measured. Because these these shoreline segments have different orientations, they are affected by different effective wave climates. Analyses over other time intervals test whether the statistics and the variations from one coastline segment to another are robust. The work also tests a hypothesis and potential model for the main cause of these observed shoreline behaviors. The statistics describing the patterns of shoreline change vary as a function of regional wave climate, suggesting the hypothesis that these changes are driven chiefly by gradients in alongshore transport associated with subtle deviations from a smooth shoreline. Recent work has shown that when waves approach shore from deep water at relative angles greater than approximately 45°, shoreline perturbations grow, causing alongshore-heterogeneous shoreline changes on any scale at which perturbations exist (Ashton et al., 2001). Waves approaching from deep-water angles closer to shore-normal tend to smooth out the shoreline. The patterns of alongshore change over some extended time period will result at least partly from the interactions between these roughening and smoothing influences, which will depend on the regional wave climate, including the relative proportions of high and low wave-approach angles. A model treating alongshore transport (Ashton et al., 2001; Ashton et al., 2003a; Ashton et al., 2003b) predicts the observed trend with shoreline orientation (regional wave climate) in one of the statistics in the previous analysis (Tebbens et al, 2002).
DE: 1815 Erosion
DE: 1855 Remote sensing (1640)
DE: 4217 Coastal processes
DE: 4440 Fractals and multifractals
DE: 4475 Scaling: spatial and temporal (1872, 3270, 4277)
SC: Hydrology [H]
MN: Fall Meeting 2005