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Near Real-Time Multiscale Hybrid Surface Water Flooding Risk Forecasting. PhD in Engineering (NERC GW4 + DTP)

  • Full or part time
  • Application Deadline
    Monday, January 06, 2020
  • Competition Funded PhD Project (European/UK Students Only)
    Competition Funded PhD Project (European/UK Students Only)

Project Description

Lead Supervisor
Dr Albert Chen, Department of Engineering, Centre for Water Systems, College of Engineering, Mathematics and Physical Sciences, University of Exeter

Additional Supervisors
Dr Steven Cole, Centre for Ecology & Hydrology
Prof Slobodan Djordjevic, Department of Engineering, Centre for Water Systems, College of Engineering, Mathematics and Physical Sciences, University of Exeter
Mr Robert Moore, Centre for Ecology & Hydrology

Location: University of Exeter, Streatham Campus, Exeter, EX4 4QJ

This project is one of a number that are in competition for funding from the NERC GW4+ Doctoral Training Partnership (GW4+ DTP). The GW4+ DTP consists of the GW4 Alliance of research-intensive universities: the University of Bath, University of Bristol, Cardiff University and the University of Exeter plus five unique and prestigious Research Organisation partners: British Antarctic Survey, British Geological Survey, Centre for Ecology & Hydrology, the Natural History Museum and Plymouth Marine Laboratory. The partnership aims to provide a broad training in the Earth, Environmental and Life sciences, designed to train tomorrow’s leaders in scientific research, business, technology and policy-making. For further details about the programme please see

For eligible successful applicants, the studentships comprises:

- An stipend for 3.5 years (currently £15,009 p.a. for 2019/20) 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.
- Travel and accommodation is covered for all compulsory DTP cohort events.
- No course fees for courses run by the DTP

We are currently advertising projects for a total of 10 studentships at the University of Exeter

Project Background

Flood impacts over the past two decades have affected 2.3bn people resulting in an estimated total damage cost of £500bn. The Committee on Climate Change estimates that total expected annual damages from flooding and coastal change (for the whole UK, excluding groundwater) for the present day as £1.1bn, which could increase to £1.7bn and £2.8bn by the 2080s under 2°C and 4°C climate change projections, respectively, assuming no population growth and continuing adaptation at current levels.

To mitigate the impact of flooding, various measures have been proposed to enhance the preparedness and protection of societies against flooding. Most of these measures rely on flood forecasting to deploy resources and implement actions at the right locations and times.

The Grid-to-Grid (G2G) model has been adopted operationally for countrywide fluvial and pluvial flood forecasting across Britain. Surface water flooding risk is evaluated based on matching the G2G modelled surface runoff with a pre-simulated Impact Library.

Project Aims and Methods

The project aims to develop a hybrid modelling approach, coupling with environmental observations and weather forecasting, to nowcast and forecast flooding and its impact across multiple scales (national, regional, catchment-wide, and local community) to support decision-making for different stakeholders.

The aim of the project is to dynamically link the national-scale Grid-to-Grid hydrological model (typically applied at a 1km resolution) with the detailed urban flood model (with 10m or finer spatial resolution) in highly urbanised areas to better simulate the influences of urban features (e.g. drainage network, buildings) on surface water propagation. Further, the flood modelling results will be combined with socio-economic datasets to forecast flood risk - to human safety, critical infrastructure and services, properties and communities - to develop prototype tools for alerting the public that are at high risk and support emergency response actions to mitigate the hazard impact.

The candidate will be able to discuss with the supervisors how to shape the final research direction of the project and co-design the hybrid modelling framework for real-time applications.

Funding Notes

NERC GW4+ funded studentship available for September 2020 entry. For eligible students, the studentship will provide funding of fees and a stipend which is currently £15,009 per annum for 2019-20.


References / Background reading list

1. Cabinet Office (2016) National Flood Resilience Review.
2. Chen et al. (2012) Multi-layered coarse grid modelling in 2D urban flood simulations. Journal of Hydrology, 470–471, 1-11.
3. Chen et al. (2016) From hazard to impact: flood damage assessment tools for mega cities, Natural Hazards, 82(2), 857-890.
4. Chen et al. (2016) Modelling the discharge via displacement of manhole covers during extreme flood events with dual drainage simulations. Urban Water Journal, 13(8), 830-840.
5. Cole et al. (2016) Real-time forecasts of flood hazard and impact: some UK experiences [in special issue: 3rd European Conference on Flood Risk Management (FLOODrisk 2016)] E3S Web of Conferences, 7, 18015. 11pp.
6. Cole and Moore (2008) Distributed hydrological modelling using weather radar in gauged and ungauged basins. In: International Symposium on Weather Radar and Hydrology, Grenoble, 10-12 March 2008.
7. Cole et al. (2010) The Grid-to-Grid Model for nationwide flood forecasting and its use of weather radar. In: Workshop on Polarimetric weather radar for quantitative precipitation estimation, University of Bristol, 28 July 2010.
8. Flack et al. (2019) Recommendations for improving integration in national end-to-end flood forecasting systems: an overview of the FFIR (Flooding From Intense Rainfall) Programme. Water, 11, 725.
9. Guidolin et al. (2016) A weighted cellular automata 2D inundation model for rapid flood analysis. Environ. Modell. & Soft., 84, 378–394.
10. Risk of flooding from surface water - understand and using the map

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