Publications
Following publications have been announced by our Institute of Coastal Systems – Analysis and Modeling. For further information please contact the marked authors resp. co-authors of the publications:
Pein, J., Staneva, J., Biederbick, J., & Schrum, C. (2025): Model-based assessment of sustainable adaptation options for an industrialised meso‑tidal estuary. Ocean Modelling, Vol 194, 102467, doi:10.1016/j.ocemod.2024.102467
Abstract:
Human-shaped estuaries play a vital role in supporting a range of economic, ecological and social functions. Such cultural landscapes often require enormous services, which may be provided at the expense of the ecological status and the ability to provide ecosystem services. This is exemplified by the estuaries of the German North Sea coast, of which the Elbe estuary is the most prominent and stands out as the largest and most consistently developed. The port of Hamburg, which is the primary economic driver in the region, has shaped the morphology of the surrounding water body. This has resulted in a number of hydrodynamic effects and sedimentological and ecological consequences, which have been well documented and subject to extensive debate. Despite this understanding, however, there is a tendency to propose solutions that are limited to the smallest local scales and are unable to mitigate the consequences of human interventions that have taken place or continue to take place at the estuarine and catchment scales. The lack of illustrative and quantitative scenario simulations and holistic assessments also hinders the ability to implement ambitious adaptation measures. To step forward, this study presents a model-based assessment including scenario simulations of four prototypical adaptation measures that are potentially capable of mitigating the problems of high turbidity, sedimentation and oxygen minimum without compromising coastal protection. The experimental design comprises a two-month morphodynamic simulation for each adaptation scenario and a one-year simulation of coupled hydrodynamics and ecology. The model simulations demonstrate that the proposed measures have the potential to reduce the siltation of the upper estuary, thereby reducing the need for extensive and costly maintenance dredging. Furthermore, the simulated measures also reduce the tidal range in the densely populated upper estuary, albeit to varying degrees. This also applies to mitigating the consequences of eutrophication, such as the oxygen content in the navigation channel. These differences, as well as the differing scale and effort associated with the four measures, form the basis of a final comparative evaluation based on universal sustainability criteria.
Dammak, N., Chen, W., & Staneva, J. (2025): Toward an AI-enhanced hydro-morphodynamic model for nature-based solutions in coastal erosion mitigation. Applied Ocean Research, Vol 154, 104326, doi:10.1016/j.apor.2024.104326
Abstract:
In the application of sustainable Nature-based Solution (NbS) for coastal engineering, a significant challenge lies in determining the effectiveness of these NbS approaches in mitigating coastal erosion. The efficacy of NbS is influenced by various factors, including the specific location, layout, and the scale of implementation. This study integrates artificial intelligence (AI) with hydro-morphodynamic numerical simulations to develop an AI-based emulator focused on predicting Bed Level Changes (BLC) as indicators of erosion and deposition dynamics. Specifically, we explore the influence of seagrass meadows, varying in starting depth (hs) and depth range (hr), on coastal erosion mitigation during storm events.
The framework leverages a hybrid approach combining the SCHISM-WWM hydrodynamic model with XBeach for simulating 180 depth range and starting depth combination (hr-hs) scenarios along the Norderney coast in the German Bight. A Convolutional Neural Network (CNN) architecture is employed with dual inputs—roller energy and Eulerian velocity—to predict BLC efficiently. The CNN demonstrates high accuracy in replicating spatial erosion patterns and quantifying erosion volumes, achieving an RMSE of 3.47 cm and an R² of 0.94 during validation.
This innovative integration of AI and NbS not only reduces computational costs associated with traditional numerical modelling but also enhances the feasibility of What-if Scenarios applications for coastal erosion management. The findings underscore the potential of AI-driven approaches to optimize seagrass transplantation layouts and inform sustainable coastal protection strategies effectively. Future advancements aim to further streamline model integration and scalability, thereby advancing NbS applications in enhancing coastal resilience against environmental stressors.
Silva, D.V. , Silva, T.L.V., Camargo, R., & Veleda, D. (2025): Influence of sea stratification and troposphere stability over the coastal squall lines of eastern Amazon. Clim Dyn 63, 8, doi:10.1007/s00382-024-07499-2
Abstract:
This study investigates the relationship between oceanic and atmospheric parameters and their relation with the occurrence of Coastal Squall Lines (CSL) in the Eastern Amazon. Utilizing a minimalist set of stability and stratification parameters, results indicate a significant coherence in the 8 and 12-month period in bulk parameters, potentially linked to the discharge of the Amazon River and the convective regime of Western Tropical Atlantic. A cross-wavelet analysis shed light on the relation of CSL frequency with the local and remote oceanic stratification and atmosphere stability parameters. Additionally, composite analyses reveal shifts in the distributions of these parameters during CSL occurrences, highlighting the sensitivity of CSL to environmental variables. The environmental variables rely on local and remote drivers, whose interactions still need to be fully addressed. Our results indirectly quantify how these drivers can explain the CSL frequency, with the advantage of bypassing a full assessment of submesoscale processes. These outcomes reveal the need to consider the influence of local shelf sea stratification to enhance the precision of CSL characterization, what can be used to improve the setup of atmospheric models. While this study covers this gap, further research considering the mechanistic approach is needed to improve the understanding of mesoscale convection at the Eastern Amazon.
Skogen, M.D., Aarflot, J.M., García-García, L.M., Ji, R., Ruiz-Villarreal, M., Almroth-Rosell, E., Belgrano, A., Benkort, D., Daewel, U., Edman, M., Friedland, R., Gao, S., Hill-Cruz, M., Hjøllo, S.S., Huret, M., Kellner, J.B., van Leeuwen, S., Lopez de Gamiz-Zearra, A., Maar, M., Mousing, E.A., Peck, M.A., Rollan, A.P., Sailley, S.F., Saraiva, S., Speakman, C., Troost, T., & Yumruktepe, V.C. (2024): Bridging the gap: integrating models and observations for better ecosystem understanding. Mar Ecol Prog Ser 739:257-268, doi:10.3354/meps14616
Abstract:
Our understanding of complex marine ecosystem dynamics is often hindered by significant uncertainties and issues of representativeness associated with models and observations. Both observations and models provide a limited view of real-world complexities depending on what is specifically measured or simulated. When used together, they provide the ability to gain a broader understanding of important ecological processes. How to properly integrate models and observations while utilizing the advantages of both approaches remains a challenge. In this paper, we draw attention to commonly overlooked limitations of both observations and models, and use examples to illustrate potential strategies to mitigate bias, properly interpret results, and help improve both models and observations. We emphasize that proper validation of all data sources (models and observations) is necessary in all marine ecosystem studies, with a careful assessment of the spatio-temporal scales that the data represent.
