Morphodynamic patterns of the German Wadden Sea and predictability

Poster
In session Postersession No. 2 , Sept. 3, 2025, 18:15 – 19:00
Exact timing: 18:15 – 19:00

Based on statistical analysis combined with numerical modeling and machine learning, We investigated annual- to decadal-scale morphodynamic patterns of the German Wadden Sea and their predictability at the relevant scales. Results from the multivariate EOF (Empirical Orthogonal Function) analysis of the annual bathymetry data spanning from 1998 till 2022 and potential related drivers and environmental factors (tidal range, storm surge level and frequency, sediment properties and longshore currents) provide insights into morphodynamic patterns of the study area. Both extreme water levels (storm surges) and tidal range show a significant positive correlation with the magnitude of morphological changes, indicating their important role in controlling sediment transport and morphological evolution. Coastal longshore currents exhibit a correlation with the movement of tidal channels which are continuously migrating and deepening in the East and North Frisian regions and oscillating in the estuarine areas (Ems, Wesser and Elbe). Numerical modeling was then applied to derive a process-based understanding of the feedback mechanisms between the physical drivers and the morphology of the Wadden Sea. Finally, state-of-the-art machine learning approaches were used to explore the predictability of morphological change of the Wadden Sea and compared with numerical predictions to identify the strengths and weakness of both methods.