From an increasing awareness of the risks posed by climate change emerge the need to model potential impacts on coasts at a high spatial resolution, broad spatial scales, and time scales that correspond to the widely used IPCC sea-level rise scenarios. Little previous work has been carried out at this scale in the UK. This thesis investigates the potential of ‘reduced complexity’ models as a tool to represent mesoscale impacts of sea-level rise on UK estuarine environments. The starting point for this work is the Sea Level Affecting Marshes Model (SLAMM), which has been widely used in the USA. The SLAMM source code is first modified to accommodate the different tidal sedimentary environments and habitats found in the UK, and evaluated in a pilot study of the Newtown estuary, Isle of Wight. The modified SLAMM is then applied to the more complex environments of the Suffolk estuaries and the Norfolk barrier coast in order to evaluate its ability to produce meaningful projections of intertidal habitat change under the UKCP09 scenarios. Validation is also attempted against limited known historic changes, while a comparison of the SLAMM outputs to a GIS-based approach is also undertaken. Given sufficient sedimentation data, this approach produces robust projections in landform and habitat change at a whole estuary scale, with visually powerful outputs to convey possible future changes to stakeholders and policy makers. Although the nature of the SLAMM outputs is more sophisticated than the GIS-based approach, SLAMM is shown to have some limitations. The most serious of them lies in the empirical nature of the various sub-models of intertidal deposition and erosion. Whilst these can be calibrated to give meaningful results for saltmarsh, the lack of a robust formulation for tidal flats means that SLAMM is unable to resolve key landform and habitat transition in estuaries.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:668460 |
| Date | January 2015 |
| Creators | Pylarinou, A. |
| Publisher | University College London (University of London) |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://discovery.ucl.ac.uk/1468970/ |
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