Shoreline variability from days to decades: Results of long-term video imaging Public Deposited

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  • The present work characterizes the time-space scales of variability and forcing dependencies of a unique 26 year record of daily to hourly shoreline data from a steep beach at Duck, North Carolina. Shoreline positions over a 1500 m alongshore span were estimated using a new algorithm called ASLIM based on fitting the band of high light intensity in time exposure images to a local Gaussian fit, with a subsequent Kalman filter to reduce noise and uncertainty. Our findings revealed that the shoreline change at long times scales dominates seasonal variability, despite that wave forcing had only 2% variance at interannual frequencies. The shoreline response presented 66% of the variance at interannual scales. These results were not expected since from wave forcing it would have been expected that the shoreline response should similarly lack interannual variability, but we found it to be dominated by this scale. The alongshore-mean shoreline time series revealed no significant annual cycle. However, there are annual oscillations in the shoreline response that are coherent with wave forcing and deserves further explanations. The pier was found to have a significant influence on shoreline behavior since restricts the seasonal longshore transport between the sides, resulting in a seasonally reversing sediment accumulation. Thus, there is a significant annual peak in shoreline variability that is coherent with the annual forcing but becomes insignificant in the longshore-average.
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  • Pianca, C., Holman, R., & Siegle, E. (2015). Shoreline variability from days to decades: Results of long‐term video imaging. Journal of Geophysical Research: Oceans, 120(3), 2159-2178. doi: 10.1002/2014JC010329
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  • 120
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  • 3
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  • Support for Cassia Pianca was provided by Sao Paulo Research Foundation (FAPESP-2010/13083-3). Support for Rob Holman was provided by the Office of Naval Research, Award number N000141010932. Eduardo Siegle is sponsored by a CNPq research fellowship.
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