Testing the robustness of the base-line data required to assess and mitigate flood risk in lacustrine environments using multi-proxy evidence

PLEASE APPLY ONLINE TO THE SCHOOL OF ENGINEERING, PROVIDING THE PROJECT TITLE, NAME OF THE PRIMARY SUPERVISOR AND SELECT THE PROGRAMME CODE "EGPR" (PHD - SCHOOL OF ENGINEERING)

This is a project within the multi-disciplinary EPSRC and ESRC Centre for Doctoral Training (CDT) on Quantification and Management of Risk & Uncertainty in Complex Systems & Environments, within the Institute for Risk and Uncertainty. The studentship is granted for 4 years and includes, in the first year, a Master in Decision Making under Risk & Uncertainty. The project includes extensive collaboration with prime industry to build an optimal basis for employability.

Projected flooding caused by climate and land-use changes represents a major threat to tens of millions of people worldwide, and assets worth billions are at risk from increased flooding. Successful adaptation to this threat requires an improved understanding of process-responses at a catchment scale. Conventional flood histories derived from gauging station records in the UK have an average length of ~30 years, with few sites providing long term records. Geomorphological and documentary records are unique in the way they extend both temporal and spatial information about floods. Historical flood patterns have been assessed back to AD 1200 using documentary accounts, providing detailed high resolution flood records, while sediment archives from river floodplain and lakes offer the potential to extend flood histories even further. Research of this nature is crucial because at present understanding of flood risk in the UK is heavily constrained by the length and quality of the flood record; how can you judge what is a 1 in 200 year flood when the evidence-base is so short?

This research will build on ongoing research examining depositional lacustrine environments and the opportunities these environments present in constructing robust chronologies for the sedimentary archives. Recent work (Schillereff et al., 2014) has demonstrated an approach to obtaining flood frequency and magnitude data from an unexploited resource, the largely visually-homogeneous, organic sediments that typify most temperate lakes. The geochemical composition and end-member modeling of sediment data discriminates the signature of infrequent, coarse-grained flood deposits from seasonal and longer-term allogenic (enhanced discharge and sediment supply during winter) and autogenic (summer productivity, thermal mixing) depositional processes. Sediment sequences can be calibrated to local river discharges, illustrating that hydrological thresholds censor event signature preservation, permitting the identification of event threshold (discharge) and process characterization, which are essential precursors to discerning flood magnitude from sediment archives.

The proposed project will examine the transferability of this approach and explore the potential to develop new statistical approaches to estimating flood frequency from sedimentary sequences, incorporating both climatic variability and landscape change evidenced within sedimentary lacustrine sequences.

Implications: The overall objective is to produce longer proxy flood records that will potentially comprise an invaluable baseline dataset against which to examine the hydrological implications of projected climate change and to develop more informed development practices enabling the robust integration of these multiple sources of evidence.

Any special features: (e.g. equipment, collaboration, industrial links, underpinning expertise)

The project requires a good analytical background, curiosity, creativity and a strong interest to work in a multi-disciplinary set-up. Applicants should have a background in the Environmental Sciences or Engineering (preferably Civil or Systems Engineering) or in other relevant fields. A combined education in these fields would be an advantage. This project will involve working on lakes, applicants should be able to swim.

The student will join a multi-disciplinary research group in the Institute for Risk and Uncertainty.