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Uncertainty estimation and reduction in hydrological models (Advert Reference: FAC19/EE/MCE/FRANKS)

  • Full or part time
  • Application Deadline
    Monday, September 23, 2019
  • Competition Funded PhD Project (Students Worldwide)
    Competition Funded PhD Project (Students Worldwide)

Project Description

Recent advances in uncertainty estimation have included the development of techniques that seek to provide a ‘total error’ approach in that the different sources are all assessed (eg. BATEA, Kavetski et al.,2000). These techniques are highly computationally intensive whereas previous methodologies such as GLUE (Beven and Binley, 1992) are more readily applied. This project seeks to develop a new accessible framework whilst utilising the total error approach. This will be a simplified framework which will then be easily applied to hydrological model identification and uncertainty estimation whilst representing all sources of error and uncertainty.

The developed methodology will be applied to a range of case studies and will also be used to assess the issues of appropriate model selection and the role of data and other information in reducing uncertainty. This work builds on the prior research experience of the primary supervisor since 1997. Applicants should have a reasonable competence in programming and basic statistics.

The Principal Supervisor for this project is: Professor Stewart Franks

Please note eligibility requirement:
• Academic excellence of the proposed student i.e. 2:1 (or equivalent GPA from non-UK universities [preference for 1st class honours]); or a Masters (preference for Merit or above); or APEL evidence of substantial practitioner achievement.
• Appropriate IELTS score, if required.
• Applicants cannot apply for this funding if currently engaged in Doctoral study at Northumbria or elsewhere.

For further details of how to apply, entry requirements and the application form, see
https://www.northumbria.ac.uk/research/postgraduate-research-degrees/how-to-apply/

Please note: Applications that do not include a research proposal of approximately 1,000 words (not a copy of the advert), or that do not include the advert reference (e.g. FAC19/EE/MCE/FRANKS will not be considered.

Deadline for applications: 23 September 2019

Start Date: 1 March 2020

Northumbria University takes pride in, and values, the quality and diversity of our staff. We welcome applications from all members of the community. The University holds an Athena SWAN Bronze award in recognition of our commitment to improving employment practices for the advancement of gender equality and is a member of the Euraxess network, which delivers information and support to professional researchers.

Funding Notes

The studentship is available to Students Worldwide, and covers full fees and a full stipend, paid for three years at RCUK rates (for 2019/20, this is £15,009 p.a.)

References

Toward a reliable decomposition of predictive uncertainty in hydrological modeling: Characterizing rainfall errors using conditional simulation
Renard, B., Kavetski, D., Leblois, E., Thyer, M., Kuczera, G. & Franks, S., 25 Nov 2011, In : Water Resources Research. 47, 11, W11516.

Understanding predictive uncertainty in hydrologic modeling: The challenge of identifying input and structural errors
Renard, B., Kavetski, D., Kuczera, G., Thyer, M. & Franks, S., 1 May 2010, In : Water Resources Research. 46, 5, W05521.

Calibration of hydrologic models: The role of input errors
Kavetski, D. N., Franks, S. & Kuczera, G., 1 Jan 2000, Computational methods in water resources - Volume 1 - Computational methods for subsurface flow and transport. Bentley, L. R., Sykes, J. F., Brebbia, C. A., Gray, W. G., Pinder, G. F., Bentley, L. R., Sykes, J. F., Brebbia, C. A., Gray, W. G. & Pinder, G. F. (eds.). A.A. Balkema, p. 503-510

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