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Award details

University of Exeter funding: NERC GW4+ DTP PhD studentship

Your Roof as a Raingauge: Finding Value in Ubiquitous Sensor Networks - Engineering PhD studentship (NERC GW4+ DTP funded) Ref: 4018

About the award

Supervisors

Lead Supervisor: Dr Peter Melville-Shreeve,  Lecturer, University of Exeter, College of Engineering Maths and Physical Sciences, Engineering Management Research Group & Centre for Water Systems

Co-Supervisor: Dr Kemi Adeyeye, Senior Lecturer, Department of Architecture & Civil Engineering, Centre for Advanced Studies in Architecture (CASA) & Water Innovation and Research Centre (WIRC)

 

Location: Streatham Campus, University of Exeter - Exeter, Devon.

This project is one of a number that are in competition for funding from the NERC Great Western Four+ Doctoral Training Partnership (GW4+ DTP).  The GW4+ DTP consists of the Great Western Four alliance of the University of Bath, University of Bristol, Cardiff University and the University of Exeter plus five Research Organisation partners:  British Antarctic Survey, British Geological Survey, Centre for Ecology and Hydrology,  the Natural History Museum and Plymouth Marine Laboratory.  The partnership aims to provide a broad training in earth and environmental sciences, designed to train tomorrow’s leaders in earth and environmental science. For further details about the programme please see http://nercgw4plus.ac.uk/

For eligible successful applicants, the studentships comprises:

  • An stipend for 3.5 years (currently £15,285 p.a. for 2020-21) in line with UK Research and Innovation rates
  • Payment of university tuition fees;
  • A research budget of £11,000 for an international conference, lab, field and research expenses;
  • A training budget of £3,250 for specialist training courses and expenses.
  • Up to £750 for travel and accomodation for compulsory cohort events.


Project details

Weather nowcasting refers to short-range forecasting i.e. based on data from the very recent past, the present and the immediate future, to understand an ongoing event or phenomenon. Early, timely and high frequency information becomes available which can be interpreted and translated in an agile fashion. Or considered and iterated with pre-existing data set to present a complete picture that can be explored at different scales of granularity.  Data streams from car fleets, building sensors and targeted deployment of environmental sensing represent a key element of the fourth industrial revolution. The Internet of Things (IoT) gives decision makers an ever-increasing opportunity to gather high resolution data to make informed decisions. As the “Digital 4.0” revolution continues apace, transformative change in the way we gather data, produce insight, and take action will see autonomous cars providing valuable nowcast data from their windscreen mounted rainfall sensors. Meanwhile, water level sensors in water butts can monitor rainfall gathered at houses across a city and function as a rain gauge.  Environmental monitoring data is no-longer centrally captured by water companies or weather service providers. The challenge posed revolves around the question: How can disparate open source data feeds be gathered and managed to create value in the years ahead?

Project Background

Weather nowcasting refers to short-range forecasting i.e. based on data from the very recent past, the present and the immediate future, to understand an ongoing event or phenomenon. Early, timely and high frequency information becomes available which can be interpreted and translated in an agile fashion. Or considered and iterated with pre-existing data set to present a complete picture that can be explored at different scales of granularity.  Data streams from car fleets, building sensors and targeted deployment of environmental sensing represent a key element of the fourth industrial revolution. The Internet of Things (IoT) gives decision makers an ever-increasing opportunity to gather high resolution data to make informed decisions. As the “Digital 4.0” revolution continues apace, transformative change in the way we gather data, produce insight, and take action will see autonomous cars providing valuable nowcast data from their windscreen mounted rainfall sensors. Meanwhile, water level sensors in water butts can monitor rainfall gathered at houses across a city and function as a rain gauge.  Environmental monitoring data is no-longer centrally captured by water companies or weather service providers. The challenge posed revolves around the question: How can disparate open source data feeds be gathered and managed to create value in the years ahead?
 

Project Aims and Methods

This proposed project broadly aims to: 1. investigate the opportunities offered by weather nowcasting to support a more accurate design of rainwater recycling and surface water management solutions. At present, system design can be based on data from weather stations that are quite distant from the site. Therefore, design estimations may not represent the onsite reality. 2. Investigate the extent to which the infrastructure can facilitate a more localised warning system for hazardous events. 3. Propose outputs to support the Met Office as well as local providers to coordinate and collaborate to deliver weather services that can be more tailored to direct public, businesses and agricultural needs etc.
The PhD project aligns with NERC’s Environmental Informatics theme, relating to the creation, collection, storage, processing, modelling, interpretation, display, and dissemination of rainfall data. The candidate will gather data and identify potential “unseen value” from ongoing pilot projects to explore best practice. Through literature review, active research into machine learning techniques (such as random forest regression) and attendance at global events, the candidate will identify and classify these data channels and conceptualise an open source decision support tool that brings data into one place. The goal of the decision support tool will be to support city managers and planners to improve management practices for example to help manage flooding by integrating actively controlled stormwater technologies.The student will be expected to work with our network of consultants, developers, IoT companies and building managers to shape and re-focus the goal during the first year of the project.

4018_NERC

Can we access novel data feeds (e.g. from autonomous cars) to improve rainfall nowcasts? (Source: Nature: link below)

 

4018_NERC2

 

Can low power devices monitor and control our sewers to reduce pollution and flooding?

 

Candidate requirements

The candidate must have achieved, or be expected to achieve, a first class or 2:1 degree or equivalent in Meteorology, Mathematics, Physics, Engineering, Computer Science, or a related branch of the physical or mathematical sciences. A Master’s level qualification with previous experience of conducting independent research is desirable. Knowledge of scientific programming languages (e.g., MATLAB, Python, IDL, R) and an ambition to work towards the development of decision support and analytics tools would be advantageous. Candidates with industry experience are encouraged to apply.

Collaborative partner

The successful candidate will have access to an extensive network of collaborative partners via the supervisor’s networks including the Chartered Institute of Water and Environmental Management,  The Water Efficiency Network and the extensive stakeholder network of the Water Innovation Research Centre at the University of Bath. 

Training

Support and training courses will be available from GW4 partners and it is anticipated that the candidate will take an active role in attending and supporting the GW4 Water Security Alliance.

Background reading and references

Online Links:

Your Roof as a Raingauge?

Windscreen Wipers and Nowcasting

References:

Lebedev, V., Ivashkin, V., Rudenko, I., Ganshin, A., Molchanov, A., Ovcharenko, S., ... & Solomentsev, D. (2019, July). Precipitation nowcasting with satellite imagery. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining(pp. 2680-2688).
Riede, H., Acevedo-Valencia, J. W., Bouras, A., Paschalidi, Z., Hellweg, M., Helmert, K., ... & Nachtigall, J. (2019). Passenger car data–a new source of real-time weather information for nowcasting, forecasting, and road safety.
Du, H., Bandera, C. F., & Chen, L. (2019). Nowcasting methods for optimising building performance.
Shapovalov, V. A. (2019, June). Technology Nowcasting of Dangerous Weather Phenomena. In IOP Conference Series: Earth and Environmental Science (Vol. 272, No. 3, p. 032031). IOP Publishing.
Al-Rousan, N., & Al-Najjar, H. (2020). Nowcasting and forecasting the spreading of novel coronavirus 2019-nCoV and its association with weather variables in 30 Chinese Provinces: A case study. Available at SSRN 3537084

Useful links

For information relating to the research project please contact the lead Supervisor via pm391@ex.ac.uk
Prospective applicants: For information about the application process please contact the Admissions team via pgrenquiries@exeter.ac.uk.   Each research studentship project advertisement has an ‘Apply Now’ button linking to an application portal.  Please note that applications received via other routes including a standard programme application route will not be considered for the studentship funding.

Eligibility

NERC GW4+ DTP studentships are open to UK and Irish nationals who, if successful in their applications, will receive a full studentship including payment of university tuition fees at the home fees rate.

A limited number of full studentships are also available to international students which are defined as EU (excluding Irish nationals), EEA, Swiss and all other non-UK nationals.  For further details please see the NERC GW4+ website.

Those not meeting the nationality and residency requirements to be treated as a ‘home’ student may apply for a limited number of full studentships for international students. Although international students are usually charged a higher tuition fee rate than ‘home’ students, those international students offered a NERC GW4+ Doctoral Training Partnership full studentship starting in 2021 will only be charged the ‘home’ tuition fee rate (which will be covered by the studentship). International applicants need to be aware that you will have to cover the cost of your student visa, healthcare surcharge and other costs of moving to the UK to do a PhD. More information on this is available from the universities you are applying to (contact details are provided in the project description that you are interested in

The conditions for eligibility of home fees status are complex and you will need to seek advice if you have moved to or from the UK (or Republic of Ireland) within the past 3 years or have applied for settled status under the EU Settlement Scheme.
 


 

Entry requirements

Applicants should have obtained, or be about to obtain, a First or Upper Second Class UK Honours degree, or the equivalent qualifications gained outside the UK.   Applicants with a Lower Second Class degree will be considered if they also have Master’s degree.  Applicants with a minimum of Upper Second Class degree and significant relevant non-academic experience are encouraged to apply.

All applicants would need to meet our English language requirements by the start of the  project http://www.exeter.ac.uk/postgraduate/apply/english/.

 

How to apply

In the application process you will be asked to upload several documents.  Please note our preferred format is PDF, each file named with your surname and the name of the document, eg. “Smith – CV.pdf”, “Smith – Cover Letter.pdf”, “Smith – Transcript.pdf”.

  • CV
  • Letter of application outlining your academic interests, prior research experience and reasons for wishing to undertake the project.
  • Transcript(s) giving full details of subjects studied and grades/marks obtained.  This should be an interim transcript if you are still studying.
  • If you are not a national of a majority English-speaking country you will need to submit evidence of your current proficiency in English.

Reference information
You will be asked to name 2 referees as part of the application process, however we will not expect receipt of references until after the shortlisting stage. Your referees should not be from the prospective supervisory team.

If you are shortlisted for interview, please ensure that your two academic referees email their references to the pgr-recruitment@exeter.ac.uk, 7 days prior to the interview dates.  Please note that we will not be contacting referees to request references, you must arrange for them to be submitted to us by the deadline.

References should be submitted by your referees to us directly in the form of a letter. Referees must email their references to us from their institutional email accounts. We cannot accept references from personal/private email accounts, unless it is a scanned document on institutional headed paper and signed by the referee.

All application documents must be submitted in English. Certified translated copies of academic qualifications must also be provided.

The closing date for applications is Friday 8 January 2021 2359 GMT .  Interviews will be held between 8th and 19th February 2021.  For more information about the NERC GW4+ DPT please visit https://nercgw4plus.ac.uk

If you have any general enquiries about the application process please email pgrenquiries@exeter.ac.uk.  Project-specific queries should be directed to the lead supervisor.


Data Sharing
During the application process, the University may need to make certain disclosures of your personal data to third parties to be able to administer your application, carry out interviews and select candidates.  These are not limited to, but may include disclosures to:

  • the selection panel and/or management board or equivalent of the relevant programme, which is likely to include staff from one or more other HEIs;
  • administrative staff at one or more other HEIs participating in the relevant programme.

Such disclosures will always be kept to the minimum amount of personal data required for the specific purpose. Your sensitive personal data (relating to disability and race/ethnicity) will not be disclosed without your explicit consent.

Summary

Application deadline:8th January 2021
Value:£15,285 per annum for 2020-21
Duration of award:per year
Contact: PGR Enquiries pgrenquiries@exeter.ac.uk