Integrating numerical modeling and artificial intelligence for decision support systems to mitigate climate change in the Scheldt estuary

Mutual interactions between estuaries and climate change (CC) have recently been recognized. While CC can strongly affect the water quality and hydraulic processes of estuaries, the water bodies play a major role in carbon storage and emissions. In the case of the Scheldt, numerous projects have been conducted to develop means for CC prevention and adaptation but little attention has been paid to reduce the greenhouse gas (GHG) emissions from this estuary and its tidal artificial wetlands. In fact, these water bodies can significantly contribute to global warming via their GHG emissions that are foreseen to increase due to CC and human interventions. The main goal of this project is to develop an effective decision support tool for risk assessment of GHG emissions in the Scheldt under different CC scenarios, which can be extrapolated to any other estuaries. This tool will maximize the synergy between numerical modeling and artificial intelligence. Particularly, the numerical model, coupling the hydrodynamic processes and biogeochemical cycles of the Scheldt, will be used to predict its water quality and flow behavior under different CC scenarios. These predicted states will the inputs of a fuzzy model to qualitatively estimate the risk of the GHG emissions. As CC impacts have become increasingly severe on the Scheldt, novel measures for its CC mitigation are in urgent need. Thus, the results of this study will contribute to the sustainable management of the Scheldt estuary.