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Updated: Jul 27, 2026

Kinematic History of a Salient-recess Junction Explored through a Combined Approach of Field Data and Analog Sandbox Modeling
Published on: August 5, 2016
A comparative analysis of dune toe extraction methodologies and implications for assessment of foredune dynamics
Alex Smith1, Jacob Lehner2, Charlotte Wills2
1Department of Earth and Environmental Sciences, University of Waterloo, 200 University Ave. W, Waterloo, ON N2L 3G1, Canada.
Abstract:
An acceleration in Sea Level Rise (SLR) and change in storm activity is likely to increase erosion and flood hazards over the coming decades, representing a significant economic burden and threat to coastal environments globally. Foredune systems may mitigate hazards by providing a natural flood protection to back barrier resources, but only if they can maintain their volume and elevation in pace with SLR and changing storm climates. The beach-dune interface, or dune toe (dt), is an important process boundary that has been used to classify and assess the resiliency of coastal landscapes, however, concerns with inconsistent methodologies have been raised in several recent works. This study provides the first comparative analysis of dt extraction methodologies, discusses the potential impacts on coastal research, and presents the Minimum Averaged Relative Relief (MARR) machine learning model aimed at improving the consistency of dt classifications. Results indicate that interannual horizontal (±29 m) and vertical positions (±1.5 m) of dt predictions are significantly different and the consistency in classifications range widely between approaches and study sites. Overall, MARR was the most consistent displaying its potential to provide an improved methodology for comparisons between sites. Over a period of decades, a disparity in the rates of change in the horizontal (±1 m/y) and vertical (±14 mm/y) dt position were also significantly different among methodologies, which can lead to a divergence in vulnerability of predicted dt elevations (-1 to +1.5 m) relative to a 1-100-year extreme sea level event by 2100. These findings suggest that studies focused on the dt may not be directly comparable, and there is a further need to improve the repeatability and transferability of all coastal landscape classifications and metrics to better inform coastal management and address uncertainties of foredune response to changing sea levels and storm climates.
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