Supervisors: Francesca Pianosi (UoB), Ross Woods (UoB), Rob Lamb (JBA Trust)
Contact email: Francesca.Pianosi@bristol.ac.uk
Location: Bristol
Project Rational: Hydrology is inherently uncertain. Uncertainties include those associated with knowledge, models and data. Those uncertainties have important real-world implications because hydrology underpins many decisions relating to flooding, including flood defense design, flood mapping, real-time forecasting and long-term planning for climate change resilience.
The UK government spends around £1bn each year on flood protection; the decisions on where and how to spend this depend strongly on assessments which are highly uncertain: for example, the impact of climate change on future flood hazard, the effectiveness of proposed flood mitigation measures, and the costs of future flood damage.
More robust investment decisions can be made by considering these uncertainties, reducing them when possible, and acknowledging them when they are irreducible – for example by looking for investment options that achieve an acceptable performance across a wide range of future uncertain scenarios, rather than options that are optimal under any particular scenario.
This project will address the broad question of how to better quantify and use uncertain flood information when making investment decisions about hydrometeorological flood resilience. A key step in this will be identifying dominant sources of uncertainty, and in particular noting which characteristics of place determine the relative sizes of different sources of uncertainty.
Methodology: In flood risk management, hydrological data and analysis typically takes place within a “chain” of models and analytical processes. Different modelling chains are relevant for different flood risk management applications, although most consider hydro/hydrometeorological hazard, hydraulic and/or infrastructure systems and flood impacts. Examples that the student may use include FEH, PDM, JFlow, HEC-RAS, MCM.
To analyze the propagation of uncertainties through such complex modelling chains, we can use statistical techniques such as uncertainty and global sensitivity analysis (Wagener and Pianosi, 2019) and address questions like: Which model inputs mostly contribute to the uncertainty in model predictions, and where should we focus efforts for uncertainty reduction? How robust are model predictions to modelling assumptions, and to what extent would model-informed decisions change if different assumptions were made? What are the tipping points that, if crossed, would enable reaching required performance targets, and what investment options are most likely to ensure reaching those targets against uncertainty?
Some initial investigation has been attempted in applied research (EA, 2022), revealing the practical relevance of understanding the relative importance of different uncertainties in the modelling chain, and highlighting the need for more general and advanced approaches, making this a suitable challenges for a PhD study.
Background Reading:
Wagener, T., Pianosi, F. 2019 What has Global Sensitivity Analysis ever done for us? A systematic review to support scientific advancement and to inform policy-making in earth system modelling. Earth-science reviews. 194. 1-18. https://doi.org/10.1016/j.earscirev.2019.04.006
Wilby, R.L. and Dessai, S., 2010 Robust adaptation to climate change, Weather, https://doi.org/10.1002/wea.543
Environment Agency, 2022. Relative importance of the hydrological uncertainties within the flood modelling chain: Technical Report. https://engageenvironmentagency.uk.engagementhq.com/20280/widgets/57541/...
FLOOD-CDT
This PhD is being advertised as part of the Centre for Doctoral Training for Resilient Flood Futures (FLOOD-CDT). Further details about FLOOD-CDT can be seen here https://flood-cdt.ac.uk. Please note, that your application will be assessed upon: (1) Motivation and Career Aspirations; (2) Potential & Intellectual Excellence; (3) Suitability for specific project and (4) Fit to FLOOD-CDT. So please familiarise yourselves with FLOOD-CDT before applying. During the application process candidates will need to upload:
• a 1 page statement of your research interests in flooding and FLOOD-CDT and your rationale for your choice of project;
• a curriculum vitae giving details of your academic record and stating your research interests;
• name two current academic referees together with an institutional email addresses; on submission of your online application your referees will be automatically emailed requesting they send a reference to us directly by email;
• academic transcripts and degree certificates (translated if not in English) - if you have completed both a BSc & an MSc, we require both; and
• a IELTS/TOEFL certificate, if applicable.
Please upload all documents in PDF format. You are encouraged to contact potential supervisors by email to discuss project-specific aspects of the proposed prior to submitting your application. If you have any general questions please contact floodcdt@soton.ac.uk.
Apply
Apply for this PhD here: https://www.bristol.ac.uk/geography/courses/postgraduate/physphd.html
