Sediment transport and morphodynamic evolution inside plant canopies supporting nature-based coastal engineering solutions (EPSRC DTP PhD studentship) (2021-2025)
The UK Government’s Resilient Nation prosperity outcome recognises the need to implement climate-adaptive and sustainable nature-based coastal defences. Coastal ecosystems such as saltmarshes, mangroves and seagrass beds, which often form the boundary between land and the sea, are known to contribute to attenuate waves and currents thus providing natural barriers against coastal erosion and flooding. To integrate these natural systems to coastal defence schemes and harness their ability to attenuate wave and currents, dynamical interactions between the complex hydro-sediment-plant spheres should be understood. This project will investigate the interplay between waves, sediment and coastal plant canopies using physical model testing in the coastal engineering laboratory of the Faculty of Science and Engineering of Swansea University, covering a vast range of hydrodynamic conditions and both rigid and flexible plant species. The results will then form the basis for developing a new computational model to simulate wave attenuation and seabed change within plant canopies and, provide vital information and the ability to simulate coastal erosion and flood mitigation effects of marine ecosystems.
Artificial Intelligence-assisted decadal scale beach change forecasting (EPSRC DTP/JBA Consulting PhD studentship) (2023-2027)
Annual UK cost of flood and coastal erosion damage is estimated at £540 million. Sea level rise and extreme weathers associated with climate change rapidly increases coastal erosion and flooding, and economic impacts. The UK Government’s Resilient Nation prosperity outcome recognises the need to implement climate-adaptive, safe, and sustainable coastal management, focusing on natural processes. Planning and implementation of sustainable adaptation requires new, efficient tools to predict decadal-scale coastal change. The uncertainty that is inherent in coastal behaviour means that these must be built on advanced technologies such as Artificial Intelligence (AI) to allow efficient and robust testing against multiple scenarios. This project will make a major contribution to tackle this challenge and train and validate an efficient AI tool to emulate time-dependent, decadal-scale coastal morphodynamic change by adopting a sequential learning AI emulation framework. A well-validated high-fidelity process-based coastal computational model, driven by multiple decadal-scale continuous stochastic time series of sea states, generated using a Monte Carlo approach, will provide synthetic beach change data for training and validation of the AI emulator and address the widely accepted data-scarcity issue. The emulator will be a powerful surrogate to computationally costly conventional modelling approaches for predicting decadal-scale beach change at local and global scale, and a tool to discover nature-based, climate-resistant coastal management interventions.
Artificial Intelligence-assisted saltmarsh flood mitigation assessment (Leverhulme Trust) (2024-2027)
Coastal and estuarine flooding will affect at least fifteen percent of the global population and cost approximately £50 billion annually by 2050. Some coastal communities and infrastructure are likely to be unviable unless measures are taken to defend them from flooding and erosion urgently. As the current approach for coastal flood mitigation involving hard defences is increasingly becoming unfit for the purpose, the urgency of implementing environmentally sustainable flood risk management approaches has been globally acknowledged. Funded by the Leverhulme Trust, this interdisciplinary project will utilise emerging Artificial Intelligence (AI) techniques to address this need and support the design and development of sustainable nature-based coastal flood mitigation solutions that can offer significant co-benefits to the environment and the society.
