Shore nourishments have been carried out worldwide for several decades and are nowadays seen as an almost routine coastal protection measure. However, the recent paradigm shift to an Integrated Coastal Zone Management (ICZM) and to an Ecosystem Approach to Management (EAM) requires new concepts, models and tools for the implementation of more sustainable and environmentally friendly shore nourishments. The interdisciplinary research project STENCIL aimed at making a first step towards the long-term goal of es- tablishing an EAM for shore nourishments. Joining the expertise of coastal engineers, ge- ologists and ecologists, the project has provided improved tools and methods for the pre- diction of coastal hydro- and morphodynamics and related ecological impacts. A combination of field measurements, laboratory experiments and analytical as well as nu- merical models has resulted in valuable new data sets. This paper summarizes the most important scientific outcomes of the project, like the use of Artificial Neural Networks (ANN) to overcome weaknesses of current hydrodynamic numerical modelling tools; the analysis and interpretation of long-term beach profile data using a newly developed data- driven methodology, allowing for a better assessment of the morphological development of beach and foreshore nourishments; the improvement of a sediment transport model for mixed sand based on a unique large-scale experiment in the Large Wave Flume (GWK) carried out within the project; an impact assessment of dredging activities around Sylt, based on six extensive survey cruises at the sand extraction sites “Westerland II & III”; and the application of the hydrotoxicology method for the same study site to determine the influence of sand extraction on chemical-physical water quality parameters and the ecotox- icological potential. These interdisciplinary project results were combined with a compre- hensive state of the art review in a SWOT analysis for shore nourishments, which shall provide a tool for decision-makers and a basis for upcoming research projects addressing the identified knowledge gaps.