A Big Data Approach to Forecasting Global Hydrological Extremes PhD
- Entry requirements:
- 3.5 years
- not available
- Reference number:
- Start date:
- 01 October 2018
- Is funding available?
- UK/EU fees:
- International fees:
- Application deadline:
- 22 January 2018
of research classed as 'internationally recgonised'
in the UK for Geography
The Complete University Guide 2018
in the UK for Geography
Guardian University Guide 2018
Loughborough University is a top-ten rated university in England for research intensity (REF2014) and an outstanding 66% of the work of Loughborough’s academic staff who were eligible to be submitted to the REF was judged as ‘world-leading’ or ‘internationally excellent’, compared to a national average figure of 43%.
In choosing Loughborough for your research, you’ll work alongside academics who are leaders in their field. You will benefit from comprehensive support and guidance from our Doctoral College, including tailored careers advice, to help you succeed in your research and future career.
Industry-standard streamflow forecasts use state-of-the art weather forecasts to drive hydrological models and predict hydrological extremes (floods and droughts) weeks to months before they occur. However, these traditional approaches are often computationally demanding and have limited skill, which hinders their uptake by end users. Now, with the advent of advanced statistical forecasting techniques alongside a range of Big Data sources (such as Earth Observation from satellite archives), it is possible to start exploring ‘intelligent’ approaches to forecast hydrological extremes. This project will evaluate the viability of skilful long-range statistical forecasting based on a range of Global Big Data sources, including climate forecasts, teleconnection indices, and Earth Observation data.
The research will involve accessing climate hindcasts (e.g. precipitation, temperature, sea surface temperature, atmospheric moisture) from a range of modelling centres (e.g. ECMWF, NOAA, and NASA), Earth Observation data from satellite archives (e.g. SMOS, Landsat, or Sentinel), and streamflow time series for catchments in different physical and climatic environments around the world. Seasonal streamflow extremes will be forecast using a range of statistical models in R, including machine learning models. The skill of the statistical forecasts will be compared with that of industry-standard forecasts.
This research will require a degree of quantitative expertise, strong analytical skills, understanding of time series analysis, and the ability to code in R or Python. The student will acquire state-of-the-art skills and knowledge of forecasting methodologies, data science and ‘Big Data’ analysis techniques.
The proposed approach opens the way for more computationally efficient flood and drought forecasting and is of practical interest to a broad range of end users and practitioners. The student will contribute to the dissemination and operationalisation of these new tools via presentations at national and international conferences, and via discussions with end-users and practitioners.
Fieldwork will include a secondment for the PhD student within the European Centre for Medium-Range Weather Forecasts (ECMWF), working alongside other streamflow forecasters. Training will be given to the student in the fundamentals of hydrological forecasting, climate informatics and data science. Support will be provided throughout the project by statisticians and computer scientists at ECMWF and Loughborough University.
Primary supervisor: Dr Louise Slater
Secondary supervisor: Professor Robert Wilby / Prof Christel Prudhomme
Applicants will normally need to hold, or expect to gain, at least a 2:1 degree (or equivalent) in Geography, Earth Science or Environmental Science. A Master’s degree and/or experience in a related area associated with the research will be an advantage.
Fees and funding
Tuition fees cover the cost of your teaching, assessment and operating University facilities such as the library, IT equipment and other support services. University fees and charges can be paid in advance and there are several methods of payment, including online payments and payment by instalment. Special arrangements are made for payments by part-time students.
The studentship is for 3.5 years and is intended to start in October 2018. The studentship provides a tax free stipend of £14,553 per annum (in 2017/18) for the duration of the studentship plus tuition fees at the UK/EU rate (£4,195 in 2017/18) and a research training support grant of £8,000. Please note that due to restrictions imposed by the funder only students with a UK/EU fee status will be considered for this position. Further guidance about eligibility is available at RCUK Terms & Conditions.
How to apply
To apply, you will need to;
- Complete a CENTA studentship application form in Word format which is available here.
- All applications should be made online. Under programme name, select “Geography”. During the online application process, upload the CENTA studentship application form as a supporting document.
- Please quote CENTA17-LU1 when completing your online application.
|Application deadline:||22 January 2018|
|Start date:||01 October 2018|
|Interview date:||Week beginning 12 February 2018|