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Discover more about the EPSRC Centres for Doctoral Training at the University
of Leeds


EPSRC Centre for Doctoral Training in Fluid Dynamics

A new computational flow foundation for satellite measurement of river flow


Dr Mark Trigg (School of Civil Engineering) - lead academic supervisor, Dr Daniel Ruprecht (Mechanical Engineering) and Dr Mark Smith (School of Geography)


Environmental Flows


Long term reliable measurement of river flows is crucial for water resource and flood management. Historically, flows are derived from measured water levels at a river gauging station, however, the setup and long term maintenance of river gauges can be costly and coverage is lacking for much of the globe. Satellite remote sensing of river flows is a new research field, with the exciting prospect of addressing some of the challenges related to river flow measurement globally and has important applications in both global flood modelling and flood early warning. However, with new measurement methods come new challenges in terms of understanding exactly what is being measured and what the uncertainties are in using this type of data, compared to traditional river flow data.
Traditionally, flows are derived from measured water levels at a gauging station using a calibrated relationship between river level and flow, known as a stage discharge equation (SDE). This fundamental relationship has been long established for point based measurement of flows, but satellite measurements have a much larger “footprint” than a single point on a river and the water “signal” is actually a composite of whole river reach hydraulics (e.g. 1km to 10km in length). This means that the traditional assumptions used to derive flows from water levels do not apply to satellite based measurements, and the appropriate “measurement-flow” relationships need to be derived from the first principles of open channel flow hydraulics. Unfortunately this fundamental research has not yet been undertaken for satellite measurement of flows and the remote sensing community currently uses a point based approach, with limited success.

This PhD project will explore the hydraulic foundations of the “signal to flow” relationships for remote sensing virtual gauges through theoretical analysis and computation flow modelling of rivers.