Bed variability in the surf zone at the storm- and seasonal time scale, mapped by Argus-video techniques
<p>Every five year the safety of coastal defence structures along the Dutch coast is evaluated based on model calculations. At present, the surf zone bathymetry measured during the 'summer' season (April-September) is used as an input condition for the models to evaluate safety during design storm conditions. This design storm is most likely to occur during the 'winter' season (October-March) and the question arises whether the summer profile is a correct input condition. In addition, the extent to which the bathymetry evolves during the storm itself is a relevant issue, because this evolution may possibly damp or reinforce the impact of the storm on the coast and its defence structures. The bathymetric data needed to answer the above questions is not easily obtained with traditional surveying techniques due to the generally rough wave and weather conditions in winter and the sheer impossibility to be physically present in the surf zone during storm events. Consequently, an alternative to these in situ surveying techniques is needed. In this study Argus video imagery in combination with inverse modelling techniques (SBM-2DH model) is used to map the surf zone bathymetry neÍu Egmond aan 7-Ee from September 1999 to June 2001. Next the bed variability at the seasonal- and storm time scale is analysed along a cross-shore transect. The most important observation with relevance for the 5-yearly evaluations of the coastal safety, is that the outer bar moves farther offshore during the winter period than can be derived from the annual surveys conducted during the summer period. The extent to which cross-shore positions of bars vary though a single storm event can not yet be assessed with sufficient accuracy, nor is the depth over the bar crest. This accuracy can be improved by upgrading the video-interpretation module of SBM-2DH, as well as by improving the calibration based on time series of bed level measurements at single points, such as provided by the ASM- instrument. Moreover, those time series will help build confidence in video-derived observations ofbed variability during storm events.</p>