Abstract
The ability to accurately predict beach morphodynamics is of primary interest for coastal scientists and managers. With this goal in mind, a stochastic model of a sandy macrotidal barred beach is developed that is based on cross-shore elevation profiles. Intertidal elevation was monitored from monthly to annually for 19 years through Real Time Kinematics-GPS (RTK-GPS) and LiDAR surveys, and monthly during two years with an RTK-GPS. In addition, during two campaigns of about two weeks, intensive surveys on a daily basis were performed with an RTK-GPS on a different set of profiles. Based on the measurements, space and time variograms are constructed in order to assess the spatial and temporal dependencies of these elevations. A separable space-time covariance model is then built from them in order to generate a large number of plausible future profiles at arbitrary time instants t+τ, starting from observed profiles at time instants t. For each simulation, the total displaced sand volume is computed and a distribution is obtained. The mean of this distribution is in good agreement with the total displaced sand volume measured on the profiles, provided that they are lower than 45 m3/m. The time variogram also shows that 90% of maximum variability is reached for a time interval τ of three years. These results demonstrate how the temporal evolution of an integrated property, like the total displaced sand volume, can be estimated over time. This suggests that a similar stochastic approach could be useful for estimating other properties as long as one is able to capture the stochastic space-time variability of the underlying processes.
Highlights
Beaches act as a natural buffer to protect hinterland against significant waves and coastal erosion as well as flooding
Depending on the date and the time of measurements, the length of the profiles built by combining Light Detection And Ranging (LiDAR) and Real Time Kinematics (RTK) GPS measurements may vary
The findings, the matching of observed and predicted volume changes, suggest that beach elevation could benefit from being modeled as a stochastic process
Summary
Beaches act as a natural buffer to protect hinterland against significant waves and coastal erosion as well as flooding. Prediction of beach morphology remains a challenge due to the complex processes between forcing factors and sediment transport occurring on a broad range of temporal and spatial scales. These processes can involve regular seasonal events (tidal cycles, current patterns) or stochastic events, like storms. The beach profile response may be related to the existing coastal state and to the forcings operating on varied spatial and temporal scales [5,6,7]. On short-time scale, ranging from hours to months, wave storms hitting the coast may be the dominant processes that impact the beach changes and sediment transport processes, while sea level change and sediment fluxes play a more important role on longer-time scale. In developing models for predicting beach morphology, it is crucial to distinguish between behaviour and evolution
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