Predictive Modeling of Coastal
Nourishment Impacts
(WP 2.4)

Work Package 2 - Morphology

Illustration by: Joost Fluitsma

WP 2.4 – Predictive Modeling of Coastal Nourishment Impacts

To develop numerical models to predict the nourishment lifetime, the spreading of nourished sand and the cumulative impact on key coastal state indicators

 

Start & end date

Year 2 – year 6

Work package leader

University of Twente

Methodology

In this WP, a triple model approach will be followed to bridge the gap between the small, intra-wave sand grain scale (sub-millimeters, sub-seconds) relevant to sand transport, and the large-scale morphodynamics of the complete Dutch coast (100s of kms, decades). The complementary models will be developed, based on new data (Living Lab, WP1) and insights from WP 2.1 (morphodynamics) and WP 2.3 (sediment sorting effects).

At first, a detailed OpenFoam research model will be developed by PhD 1. It will describe intra-wave cross-shore sand transport and morphodynamics, accounting for the water-air interactions. This depth-resolving 2DV OpenFoam model is especially suitable to study wave bottom boundary layer processes, vertical turbulence and sand mixing, and effects of wave breaking (Kranenborg et al., 2022). This model will be used to unravel sand transport processes controlling cross-shore reshaping and spreading of nourished sediment.

Second, a more agile/versatile engineering model will be developed by PhD 2. This model will replicate the complex physics of cross- and alongshore nourishment morphodynamics in a simplified, wave-averaged way. We plan to develop a depth-averaged 2DH Delft3D model to compute the morphodynamics of the Dutch coast on a time-scale up to ~20 years (Luijendijk, 2021). This model will account for the dynamic beach-dune coupling, including wind-driven sand transport.

The final step in upscaling is the development of ShorelineS model by PhD 2. This new free-form coastline model is able to describe large coastal transformations based on relatively simple principles (Roelvink et al., 2020). ShorelineS models are easy to set-up and run, and are computationally very efficient. This allows us to study how inherent model and data uncertainties affect long-term morphodynamic predictions in a probabilistic framework (Kroon et al., 2020).

Finally, these models will compute the morphological development and impacts of different nourishment strategies. The computational results will be expressed in relevant coastal state indicators such as storm-induced dune erosion (safety against flooding), grain-size (important for the ecological values, WP 2.2), and beach width (recreation). These will be used as input to the serious game (WP 3.1), and to determine the spatial quality of nourished coastal landscapes and the social costs and benefits (WPs 3.2/3.3). This will feed the integral design of coastal nourishment strategies (WP 4).

Despite this approach, the model simulation results will always be uncertain and only reflect a part of the reality. Therefore, the translation of model results into the nourishment design & evaluation process within WP 4 will be guided by expert judgment from the SOURCE consortium, based on years of experience.

Description of research activities

Task 2.4a Development of the intra-wave research model
Task 2.4b Model application to unravel cross-shore reshaping and spreading of nourished sediment
Task 2.4c Use of the research model to inform the development of the engineering models
Task 2.4d Development of the engineering models (Delft3D, Shoreline) for decadal coastal morphodynamics
Task 2.4e Model application to understand how nourishments deform and affect the Dutch coastal system
Task 2.4f Computation of sand nourishment strategies and express model outcomes in coastal state indicators

Productive interactions (co-design and co-creation)

Svašek was and will be actively involved in the design and execution of the research, in particular related to the ShorelineS model in Tasks 2.4d and 2.4e. The other consultants, in particular Royal HaskoningDHV and WaterProof will be involved in developing, testing and applying predictive morphodynamic models. All stakeholders will be involved in defining sand nourishment strategies and relevant coastal state indicators to be predicted by the models (Task 2.4f).

Contribution to project (impact)

This WP will generate models that, for the first time, can predict the morphological development and impact of coastal nourishments reliably (Scientific breakthrough). It contributes to an improved understanding and modeling of the coastal ecosystem response to SLR and sand nourishments on a decadal time-scale (Output). This allows to explore a new methodology to design and plan nourishments (Outcomes), which is necessary to co-create multifunctional sand nourishment strategies for resilient dynamic coastal landscapes with high socio-economic and natural values (Societal Impact). All models (both the software, schematization and simulations) will be publicly available to support other and further (inter)national research and consultancy projects (Impact).

Key results

[Here the key results of this WP will be presented.]