Using flotsam lines for improving predictions of hydraulic loads on coastal dikes
G.J.W. van Lente (TU Delft - Civil Engineering & Geosciences)
V. Vuik – Mentor (TU Delft - Coastal Engineering)
M Kok – Mentor (TU Delft - Hydraulic Structures and Flood Risk)
R Slomp – Mentor
G. Ph Van Vledder – Mentor (TU Delft - Environmental Fluid Mechanics)
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Abstract
Flotsam lines may arise on coastal dikes after a storm surge. These lines are generated when material due to debris accumulation on the foreshore has been transported onto the dike surface by wave run-up. Hydraulic engineers who used flotsam line measurements, interpreted a flotsam line as a line which is marking the highest wave run-up. In the past, flotsam lines were used to assess the safety of coastal dikes along the Wadden Sea. Currently, models (SWAN and WAQUA) fulfil this function and this may result in losing the value of flotsam lines. This study aims to rediscover the value of flotsam lines.
The objective of this study was to shed light on the value of flotsam lines. Using the spatial information obtained from flotsam levels it is investigated whether flotsam levels can be used to assess the quality of models (SWAN and WAQUA). This was done by calculating flotsam lines using a sequence of models and wave run-up formulas and then compare to measured flotsam lines. This study showed that the upper side of the flotsam line marked the maximum wave run-up in case of a small layer of flotsam. Besides, a relative thick layer of flotsam was able to absorb the force of the wave run-up and remained in position. This means that the amount of flotsam can disturb the wave run-up and eventually flotsam levels. It also was determined that the analysis of (calculated) flotsam lines gives an indication of the performance of the applied set of models (SWAN and WAQUA) and wave run-up formulas, provided that a systematic comparison between modelled and measured data is performed. A large database of detailed flotsam lines with corresponding storm conditions (water level, wave conditions, wind, etc) can provide valuable information to low costs. This database can be used to detect spatial variations which might give more insight in certain processes during storm conditions