DECIPHERING THE INFLUENCE OF STORMS ON THE HISTORICAL SHORELINE RECORD

High water line (HWL) positions of historical shoreline databases reflect a snapshot of the conditions that preceded the shoreline measurement. The time measurements are often controlled for the effects of processes operating on known temporal scales (e.g., tidal cycles, winter/summer profiles). These databases also commonly contain HWL positions surveyed immediately following major coastal storms to document damages. Occasionally, a database may contain 1-2 shorelines collected months to years after a storm to document beach recovery. In evaluating long-term shoreline change trends (>50 years), discussion has emerged as to whether or not to include these post-storm, or “storm-influenced,” positions in rate calculations. If such positions are included, several questions emerge: What severity of an event or timing of the subsequent HWL measurement produces a “storm-influenced” shoreline? At what point following a storm does the shoreline position cease to be influenced by that event? Given the number of small storms that occur annually (or the number of large storms occurring in the far-field), can any shoreline position be completely free of storm influence?

Answers to these questions are being sought through development of an a priori method capable of quantifying storm magnitude and the impact of any given storm or collection of storms on the beach. Geo-rectified aerial photography of the HWLs at a specific time over 600 km of the mid-Atlantic coast provided a response variable. Storm magnitude was quantified using two published methods: (1) the "Erosion Potential Index" (Zhang, 1998), based on storm surge height, tide heights above mean higher high water, and storm duration; and (2) the "Dolan-Davis Index" (Dolan and Davis, 1992) which uses wave energy from >1,200 hindcasted storms at Cape Hatteras. The results from this study showed that the time lag between the shoreline's position and storm date has a larger influence on a post-storm shoreline position than storm energy or erosion potential. Additionally, both storm indices predict the variability in shoreline position residuals equally as well, suggesting that the shoreline impact is insensitive to the two methods used to quantify storm magnitude. This research raises questions regarding the methods used to quantify storm magnitude as well as when a storm ceases to influence the shoreline.