We are looking for an enthusiastic and motivated student to work on a  Nerc-DTP funded PhD project. The student will be based at the Centre for Ecology and Hydrology in Wallingford (Oxfordshire) and will work under the supervision on Dr Ilaria Prosdocimi and Prof. Thomas Kjeldsen (University of Bath).

http://www.findaphd.com/search/projectDetails.aspx?PJID=49945

The funding is only available to UK citizens or those who have been resident in the UK for a period of 3 years or more – candidates who do not meet these requirements cannot be considered for the post.

A short description of the project follows – for questions and applications please contact [log in to unmask]<mailto:[log in to unmask]>

The current generation of methods routinely used for estimating flood risk in UK catchments are based on assumptions of stationarity, i.e. no change in the climate and flood-generating process over time. However, the release of the latest IPPC report on climate change combined with the public perception of increasing flood risk has re-emphasised the importance of better understanding the stochastic patterns of extreme flood occurrence across time and space: the potential long-term changes in such stochastic structures are of particular interest.

Recent research has shown that the high variability of flood data, as recorded by more than 1000 gauging stations throughout the UK, does not allow for a sufficient understanding of long-term processes. In addition, the standard site-based hypothesis-testing framework routinely used across geophysical sciences for assessing the existence of change in environmental variables misrepresents the information required by decision-makers (Prosdocimi et al., 2013). Consequently, new methods are needed with the ability to include data from multiple sites, in order to provide a higher confidence for trend detection across a larger area and be more relevant for decision making.

This project will address these knowledge gaps by investigating the use of mixed effects models with a spatially varying covariance structure to develop a new spatial-temporal representation of extreme floods in UK catchments. In particular, the project will investigate:
- the strength of the correlation between nearby stations and stations connected through river network
- the potential change of such correlations through time and changes in the high flows spatial patterns
- the sensitivity of changes in flood flows to catchment characteristics such as topography, climate, soil, land-use and reservoir impoundments.
- the existence of seasonal differences in changes; especially it will be investigated if summer floods are becoming more prevalent.

Combined with a new testing framework, the outcome of the project will be a set of new models which are capable of dealing with changing extreme events, and which can provide flood managers with trend estimates better aligned to the actual needs for decision-making for adaptation to a changing environment.

The project will benefit from direct access to the extensive archive of time series of river flow available in the National River Flow Archive, hosted at CEH in Wallingford as well as the existing national spatial catchment datasets held at CEH on topography, climate, soil types, land-use (including urbanisation), and reservoirs.

Additional comments:
Due to the multidisciplinary topic of this project, applications from student with both a hydrological or statistical background will be considered. The delivery of the project will require an understanding of both statistical models and hydrological processes. Students should be prepared to learn about the components of the project they are less familiar with.

Some programming skills, preferably in R, are desirable.



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