Evaluating the use of Unmanned Aerial Vehicles (UAVs) for river flood flow measurement

Applications are invited for a University of Worcester fully-funded PhD studentship in collaboration with the Environment Agency.

Monitoring river flows (discharge) is essential for water resource management and flood forecasting. However, uncertainties in flow measurement are at their greatest when the river exceeds the banktop and water inundates the floodplain. In extreme flood flows, access to measurement sites can become difficult or impossible, and current meters and Acoustic Doppler Current Profilers sometimes cannot be used, as unsteady surface conditions and high levels of floating debris can endanger both measuring equipment and operators. The use of video imagery from drones or Unmanned Aerial Vehicles (UAVs) provides the opportunity to obtain data on surface flow velocity without requiring contact with the water surface. When combined with data on channel and floodplain morphology, this technique could potentially be used to estimate flood discharges.

Particle Imaging Velocimetry (PIV) is a measurement technique that uses digital video acquisition outside the flow current to track particles and measure turbulent flows. In recent years, several studies have assessed the viability of applying derivatives of PIV in natural water bodies to measure surface velocities over larger surface areas than small laboratory flumes, known as large-scale particle image velocimetry (LSPIV) (e.g. Muste et al., 2008; Le Coz et al., 2010; Detert and Weitbrecht, 2015) and Space-Time Image Velocimetry (STIV) (Fujita et al., 2015). Video imagery can be collected by attaching digital video cameras to fixed mounts on bridges or mobile tripods, or by using video footage collected by UAVs. This PhD project aims to assess the viability of using video footage for flood flow measurement by comparing data obtained from a fixed-mount and UAV across a range of flow conditions including both in-channel and overbank flows. Significant investment has been made recently in UAV equipment at the University of Worcester, including the purchase in 2016 of a DJI
Matrice 600 rotary-winged UAV dedicated to this research, with a 4K video camera and flight times of upto 35 minutes, and a c-Astral Bramor rtk fixed wing with a 24MP sensor for still images and flight times of upto 2.5 hours.

Training in piloting an UAV will be provided by a UK Civil Aviation Authority (CAA) approved National Qualified Entity and supplemented with in-house training. The work will be carried out in collaboration with and supported by the Environment Agency (EA) via provision of supervisory expertise and access to data and information collected by the EA. Where appropriate, collaborative field work with EA staff and ADCP flow sensors may also be possible.

This research is funded by the University of Worcester. The student will be expected to carry out their individual research study under the direction of Professor Ian Maddock (Director of Studies, University of Worcester), Dr Mark Corbett (University of Worcester) and Nick Everard (Environment Agency).

Applicants should have a First or Upper Second (2.1) Honours Degree, or expect to receive one by October 2016. Education to Masters Degree level in a relevant subject area would be advantageous. A sound understanding of quantitative research methods and in interest in river science and remote sensing is also essential. Applicants must also be able to undertake fieldwork on river systems in an organised and safe manner and learn how to fly an UAV. Excellent oral and written English are a must, as are a commitment and enthusiastic approach to completing a higher research degree.

For the full advertisement and for an application form visit: http://www.worcester.ac.uk/researchstudentships

For an informal discussion about the studentship please contact Professor Ian Maddock (email: [Email Address Removed])

For questions regarding the application process, please contact Katherine Bruce (email: [Email Address Removed] or tel: +44 1905 54 2182)

The closing date for applications is Wednesday 5th April 2017. Successful candidates will be invited for interview on the Tuesday 9th May 2017.