This thesis focuses on enhancing the predictive accuracy of the ShorelineS one-dimensional (1D) coastline model, which is used to simulate coastal evolution. The research primarily addresses the limitation of ShorelineS, which excludes cross-shore sediment redistribution, impacting its ability to predict coastal changes, as demonstrated in the case of the Bacton Sandscaping project.

The Bacton Sandscaping project was designed to counter coastal erosion threatening the Bacton Gas Terminal, a crucial part of the UK's energy infrastructure. Instead of traditional hard engineering solutions, a soft approach, inspired by the Dutch Sand Engine, was chosen. This method involves depositing a large volume of sand along the coast, which is gradually redistributed by natural forces to offer long-term protection. Despite the project’s success, challenges were identified in modeling the coastline's evolution, particularly with ShorelineS, which only considers longshore sediment transport. This thesis explores how incorporating cross-shore redistribution into ShorelineS can improve its predictive capability, especially for large-scale nourishment projects like Bacton.

The research begins by evaluating ShorelineS in its current form, comparing modeled and observed coastline changes. The model tends to underestimate erosion near the gas terminal and overestimate sediment distribution to nearby villages, leading to inaccuracies. To address this, a redistribution factor (R-factor) is introduced, which adjusts the model based on observed cross-shore changes. The R-factor is applied to the terminal section, improving predictions slightly, though overall performance remains limited due to the model's sediment conservation assumptions.

The study concludes that cross-shore redistribution significantly affects coastline evolution, as seen in the Bacton case. Although the R-factor improves predictions somewhat, the limitations of ShorelineS, such as its sediment retention assumptions and the CERC2 transport equation, suggest that further model refinements are necessary. Future research should explore alternative approaches to cross-shore redistribution, more frequent coastline updates, and sensitivity analyses to enhance the model's accuracy in predicting the evolution of mega nourishment projects.