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The impact of sea level rise (SLR) on the future morphological development of the Wadden Sea (North Sea) is investigated by means of extensive process-resolving numerical simulations. A new sediment and morphodynamic module was implemented in the well-established 3D circulation model GETM. A number of different validations are presented, ranging from an idealized 1D channel over a semi-idealized 2D Wadden Sea basin to a fully coupled realistic 40-year hindcast without morphological amplification of the Sylt-Rømøbight, a semi-enclosed subsystem of the Wadden Sea. Based on the results of the hindcast, four distinct future scenarios covering the period 2010-2100 are simulated. While these scenarios differ in the strength of SLR and wind forcing, they also account for an expected increase of tidal range over the coming century. The results of the future projections indicate a transition from a tidal-flat-dominated system toward a lagoon-like system, in which large fractions of the Sylt-Rømøbight will remain permanently covered by water. This has potentially dramatic implications for the unique ecosystem of the Wadden Sea. Although the simulations also predict an increased accumulation of sediment in the back-barrier basin, this accumulation is far too weak to compensate for the rise in mean sea level. [ABSTRACT FROM AUTHOR]

After the dramatic eutrophication-induced decline of intertidal seagrasses in the 1970s, the Wadden Sea has shown diverging developments. In the northern Wadden Sea, seagrass beds have expanded and become denser, while in the southern Wadden Sea, only small beds with low shoot densities are found. A lack of documentation of historical distributions hampers conservation management. Yet, the recovery in the northern Wadden Sea provides opportunity to construct robust habitat suitability models to support management., We tuned habitat distribution models based on 17 years of seagrass surveys in the northern Wadden Sea and high-resolution hydrodynamics and geomorphology for the entire Wadden Sea using five machine learning approaches. To obtain geographically transferable models, hyperparameters were tuned on the basis of prediction accuracy assessed by non-random, spatial cross-validation. The spatial cross-validation methodology was combined with a consensus modelling approach., The predicted suitability scores correlated amongst each other and with the hold-out observations in the training area indicating that the models converged and were transferable across space. Prediction accuracy was improved by averaging the predictions of the best models., We graphically examined the relationship between the consensus suitability score and independent presence-only data from outside the training area using the area-adjusted seagrass frequency per suitability class (continuous Boyce index). The Boyce index was positively correlated with the suitability score indicating the adequacy of the prediction methodology., We used the plot of the continuous Boyce index against habitat suitability score to demarcate three habitat classes - unsuitable, marginal and suitable - for the entire international Wadden Sea. This information is valuable for habitat conservation and restoration management., Divergence between predicted suitability and actual distributions from the recent past indicates that unaccounted factors limit seagrass development in the southern Wadden Sea., Synthesis and applications. Our methodology and data enabled us to produce a robust and validated consensus habitat suitability model. We identified highly suitable areas where intertidal seagrass meadows may establish and persist. Our work provides scientific underpinning for effective conservation planning in a dynamic landscape and sets monitoring priorities. [ABSTRACT FROM AUTHOR]