Sub-weekly to interannual variability of a high-energy shoreline |
| |
| Authors: | Jeff E Hansen Patrick L Barnard |
| |
| Institution: | 1. University of California Santa Cruz, Department of Earth and Planetary Sciences, 1156 High St., Santa Cruz, CA 95064, United States;2. United States Geological Survey, Pacific Science Center, 400 Natural Bridges Drive, Santa Cruz, CA 95060, United States |
| |
| Abstract: | Sixty-one Global Positioning System (GPS), sub-aerial beach surveys were completed at 7 km long Ocean Beach, San Francisco, CA (USA), between April 2004 and March 2009. The five-year time series contains over 1 million beach elevation measurements and documents detailed changes in beach morphology over a variety of spatial, temporal, and physical forcing scales. Results show that seasonal processes dominate at Ocean Beach, with the seasonal increase and decrease in wave height being the primary driver of shoreline change. Storm events, while capable of causing large short-term changes in the shoreline, did not singularly account for a large percentage of the overall observed change. Empirical orthogonal function (EOF) analysis shows that the first two modes account for approximately three-quarters of the variance in the data set and are represented by the seasonal onshore/offshore movement of sediment (60%) and the multi-year trend of shoreline rotation (14%). The longer-term trend of shoreline rotation appears to be related to larger-scale bathymetric change. An EOF-based decomposition technique is developed that is capable of estimating the shoreline position to within one standard deviation of the range of shoreline positions observed at most locations along the beach. The foundation of the model is the observed relationship between the temporal amplitudes of the first EOF mode and seasonally-averaged offshore wave height as well as the linear trend of shoreline rotation. This technique, while not truly predictive because of the requirement of real-time wave data, is useful because it can predict shoreline position to within reasonable confidence given the absence of field data once the model is developed at a particular site. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
