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Applications are now open for PhD studentships starting in October 2018. 

Please read the recruitment introduction for more information about eligibility, how to apply, and possibilities for further funding.

The deadline for applications is 8 January 2018.

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HE_UENV18EE

HE_UENV18EE - Extremes of water availability and water quality under climate change: sensitivity to rainfall resolution (CASE studentship with Anglian Water)

Project description

Selected other project supervisors:
Professor Tim Osborn (UEA)

Background, Objectives and Methodology
Climate change has posed a serious challenge to the water security of many regions around the world. Robust assessment of the impacts of climate change, especially changes in the extremes, on regional water resources in terms of both water quantity and water quality is essential to their sustainable management and the development of effective regional climate change response programs.

The objectives are:

  1. Develop an enhanced hydrological model to simulate the movement of water and the multi-media transport and transformation of water pollutants;
  2. Evaluate the impacts of the temporal resolution of rainfall on the simulation performance of the model; and
  3. Evaluate the impacts of climate change on regional water availability and water quality.

Two catchments will be selected from the UK and China. Particular emphasis will be placed on extreme rainfall events and their impacts on catchment runoff and water quality. To evaluate the impacts of climate change on regional water security, rainfall projections of high temporal resolutions by different Regional Climate Models under various climate change scenarios will be used as inputs to the hydrological model. Climate change impacts will be compared and the potential reasons and implications for differences will be explored. Study results will provide valuable scientific evidence for water companies and river basin authorities to develop effective adaptive programs in response to climate change.

Training
Through the course of this PhD project, you will gain (1) knowledge in climate change and modelling, hydrological processes and nutrients transport; (2) skills in advanced computer programming, model optimisation algorithms, data management, and statistical analysis; (3) industry experience through working with the CASE partner - Anglian Water (AW); (4) overseas experience through working with Fudan University, Shanghai, China; (5) understanding in decision making through working with AW in England and Huai River Basin authorities in China.

Person specification
Degree in Earth and Environmental Sciences, Geography, Civil Engineering, Applied Mathematics or Computer Science.

Funding
This project has been shortlisted for funding by the EnvEast NERC Doctoral Training Partnership, comprising the Universities of East Anglia, Essex and Kent, with over twenty other research partners. Undertaking a PhD with the EnvEast DTP will involve attendance at mandatory training events throughout the course of the PhD.

Shortlisted applicants will be interviewed by EnvEast on 12/13 February 2018.

Selected candidates who meet RCUK’s eligibility criteria will be awarded a NERC studentship - in 2017/18, the stipend is £14,553. Ordinarily, EnvEast studentships are for 3.5 years, although longer awards may be made to applicants from quantitative disciplines who have limited experience in the environmental sciences, to allow them to take appropriate advanced-level courses in the subject area.

In most cases, UK and EU nationals who have been resident in the UK for 3 years are eligible for a stipend. For non-UK EU-resident applicants NERC funding can be used to cover tuition fees, RTSG and training costs, but not any part of the stipend. Individual institutes may, however, elect to provide a stipend from their own resources.

This PhD studentship is expected to begin in September/October 2018. Both full-time and part-time study are possible (those planning to study part-time may wish to discuss this with the supervisor before applying).

References

  1. Xiaoying Yang, Qun Liu, Guangtao Fu, Yi He, Xingzhang Luo, Zheng, Spatiotemporal Patterns and Source Attribution of Nitrogen Load in a River Basin with Complex Pollution Sources, Water Research, 2016, 94:187-199
  2. Xiaoying Yang, Qun Liu, Yi He, Xingzhang Luo, Xiaoxiang Zhang, Comparison of Daily and Sub-Daily SWAT Models for Daily Streamflow Simulation in the Upper Huai River Basin of China, Stochastic Environmental Research and Risk Assessment, 2016, 30(3):959-972