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Understanding and Quantifying Congo River channel to wetland water fluxes using hydrodynamic river modelling, remotely sensed terrain elevation and altimetry data.

School of Civil Engineering (part of EPS)

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Dr M Trigg No more applications being accepted Competition Funded PhD Project (Students Worldwide)

About the Project

The Congo River is the second largest river basin on the planet. It is one of the least researched basins due to its vast scale, access challenges and political stability issues. Increasingly, remote sensing is providing new tools to study this fascinating river system and uncover new river system understanding. This PhD will use a range of remote sensing methods to develop and apply terrain and water datasets with the specific aim of identifying the location and scale of water fluxes between the main river and the Cuvette Centrale wetland. The detail of this connectivity is currently unknown and remains one of the key unsolved hypotheses for the basin, as outlined by Alsdorf et al. (2016). Identifying these fluxes are key to understanding the ecology and hydrology of the basin’s environmentally crucial wetland systems.

This project builds on the experience and data available from two recent research projects, the Royal Society funded Congo River users Hydraulics and Morphology project (CRuHM) and the NERC funded CongoPeat project. The supervision team is drawn from these two projects and provides significant experience in the basin, both in terms of remote sensing and field work. The project will take advantage of two recent developments from these two projects and uniquely synthesise them for this research. As part of the CongoPeat project, there is ongoing work to develop a Digital Terrain Model of the Basin created using ICESat-2 returns with gaps in coverage filled by GEDI, ICESat, airborne LiDAR and TanDEM-X DSM measurements (combined with vegetation height estimates to get down to a DTM level) (Davenport et al. 2020). As part of the CRuHM project, a 2D hydrodynamic model of the main river channel (~1000 km in length) has been created using recently surveyed bathymetry and water elevation data (Carr et al. 2019). The model of the river will provide hydrodynamic water levels with which to study overbank fluxes onto the wetland terrain model. It will be expected that auxiliary remote sensing datasets and novel methods will be needed to validate the locations and scales of fluxes, for example using optical remote sensing of suspended sediment concentrations or side aperture radar to penetrate flooded vegetation.

Previous river modelling efforts have been limited to a 4 km resolution (O’Loughlin et al. 2020) which is inadequate for understand the details of these complex river-floodplain interactions, especially with an annual floodwave amplitude of only 3-4 m. The outcomes of this project will be the first ever coupled hi-resolution hydrodynamic model of the river channel and wetlands of the Central Congo River at a sub km scale. This research will provide a more detailed and accurate understanding of the water fluxes between the river and floodplain including a quantification of volumes, timings and locations of water transfer. Understanding these fluxes are integral to furthering our scientific knowledge related the hydrological, ecological and carbon cycles of the Cuvette Central as well as navigability of the main Congo River channel. The modelled water surface elevations will be used to provide calibration for new multi-channel river algorithms currently being developed to remotely measure global river flows using data from the NASA Surface Water and Ocean Topography (SWOT) satellite mission, which launches in 2021 (Members of the CRuHM project are partners with the NASA SWOT Science team).


Primary: Mark Trigg, [Email Address Removed], University of Leeds
Greta Dargie, University of Leeds
Ian Davenport, University of Edinburgh
Edward Mitchard, University of Edinburgh
External advisor: Raphael Tshimanga, CRREBaC, University of Kinshasa

You will be based at the University of Leeds

CongoPeat –

This PhD is part of the NERC and UK Space Agency funded Centre for Doctoral Training "SENSE": the Centre for Satellite Data in Environmental Science. SENSE will train 50 PhD students to tackle cross-disciplinary environmental problems by applying the latest data science techniques to satellite data. All our students will receive extensive training on satellite data and AI/Machine Learning, as well as attending a field course on drones, and residential courses hosted by the Satellite Applications Catapult (Harwell), and ESA (Rome). All students will experience extensive training on professional skills, including spending 3 months on an industry placement. See

Check for more information on funding and application process.

Funding Notes

This 3 year 9 month long NERC SENSE CDT award will provide tuition fees (£4,409 for 2020/21), tax-free stipend at the UK research council rate (£15,285 for 2020/21), and a research training and support grant to support national and international conference travel.


Alsdorf, D., Beighley, E., Laraque, A., Lee, H., Tshimanga, R., O’Loughlin, F., Mahé, G., Dinga, B., Moukandi, G. and Spencer, R.G., 2016. Opportunities for hydrologic research in the Congo Basin. Reviews of Geophysics, 54(2), pp.378-409.

Davenport, I.J., McNicol, I., Mitchard, E.T., Dargie, G., Suspense, I., Milongo, B., Bocko, Y.E., Hawthorne, D., Lawson, I., Baird, A.J. and Page, S., 2020. First Evidence of Peat Domes in the Congo Basin using LiDAR from a Fixed-Wing Drone. Remote Sensing, 12(14), p.2196.

Carr, A.B., Trigg, M.A., Tshimanga, R.M., Borman, D.J. and Smith, M.W., 2019. Greater water surface variability revealed by new Congo River field data: implications for satellite altimetry measurements of large rivers. Geophysical Research Letters, 46(14), pp.8093-8101.

O’Loughlin, F.E., Neal, J., Schumann, G.J.P., Beighley, E. and Bates, P.D., 2020. A LISFLOOD-FP hydraulic model of the middle reach of the Congo. Journal of Hydrology, 580, p.124203.
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