P.H.P. Overes,1,2*, B.W. Borsje1, A.P. Luijendijk2, S.J.M.H. Hulscher1
1 University of Twente; 2 Deltares
*corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
The pressure on the offshore area is increasing at an unprecedented pace due to (a.o.) ambitious green energy goals. To facilitate the construction and maintenance of offshore developments, such as wind farms, detailed bed level predictions are required. The presence of tidal sand waves, which can be found on sandy seabeds throughout the world, increases the uncertainty in these predictions significantly. Sand waves can grow up to 25% of the water depth, have wavelengths of hundreds of meters and migrate with several meters per year. Migration and deformation of these dynamic bed forms may pose a threat to all kinds of offshore constructions. To predict future sand wave dynamics, currently data-driven methods are used. Application of process-based numerical models could increase the accuracy of these predictions and give insight into the related uncertainties. Furthermore, these types of models provide a solution for data-scarce areas and can show the effect of extreme events on sand waves.
Applying numerical models to sand wave cases has proven to be difficult. Challenges include the need for small horizontal and vertical grids sizes and related long computation times. To tackle this problem, sand wave models have been applied in simplified set-up. These models, such as the one by Campmans et al. (2018), have a 2DV set-up, excluding the along crest direction. However, in measurements we observe significant changes in the sand wave bathymetry along the crest, e.g. changes in orientation and height and bifurcations (see Figure 1A). Moreover, the influence of sand banks on sand waves (see Leenders et al., 2021) cannot be included in these types of models, due to the difference in orientation between these bedforms (see Figure 1B). Finally, engineering interventions can often not be simplified to a 2DV problem. Including this third dimension is thus vital for qualitative predictions of future sand wave field bathymetries.
The aim of this study is to increase our understanding of the dynamics of real-life sand wave fields and to develop efficient ways to predict their dynamics for engineering applications. By applying the newly developed Delft3D Flexible Mesh (FM) software, the efficiency of our models increases significantly. 3D sand wave field models with realistic hydrodynamic forcing are now within reach. By studying multiple sand wave sites with varying amounts of 3D sand wave features, insight is gained into the interaction between the 3D morphology and local tidal currents. The resulting bed levels indicate the ability of the model to predict sand wave field dynamics on decadal timescales. We conclude that including the along-crest direction in sand wave models is vital to accurately predict future bed level evolution. The 3D sand wave field model offers us the opportunity to gain insight into highly 3D cases. Moreover, using this model we are able to simulate the development and impact of engineering interventions, such as the fill-up of a cable trench.
Figure 1: Measured sand wave bathymetry in the North Sea with 3D features (A) and underlying sand bank (B)
References
Campmans G.H.P., Roos, P.C., De Vriend, H.J., Hulscher, S.J.M.H. (2018). The Influence of Storms on Sand Wave Evolution: A Nonlinear Idealized Modeling Approach. Journal of Geophysical Research: Earth Surface 123(9), 2070-2086. https://doi.org/10.1029/2018JF004616
Leenders S., Damveld J. H., Schouten J., Hoekstra R., Roetert T. J., Borsje B. W. (2021). Numerical modelling of the migration direction of tidal sand waves over sand banks. Coastal Engineering 163, 103790. https://doi.org/10.1016/j.coastaleng.2020.103790
