Understanding and Quantifying Congo River to wetland water fluxes using river modelling with remotely sensed terrain and altimetry data
Supervisors: Mark Trigg(University of Leeds) Greta Dargie(University of Leeds), Edward Mitchard(University of Edinburgh)
External advisor: Raphael Tshimanga(University of Kinshasa)
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 to build a hydrodynamic river model 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 fundamental to our understanding the ecology and hydrology of the basin’s environmentally crucial wetland.
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 of remote sensing and field work. 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 bathymetric and water elevation survey of the river channel was undertaken (Carr et al. 2019). You will develop a 2D hydrodynamic river model of the channel and the wetland with a suitable St-Venant numerical solver. Further remote sensing datasets and novel methods will be used 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.
This research will provide our first understanding of the water fluxes between the river and floodplain; including volumes, timings and locations of water transfers. The modelled water surface elevations will also be used to calibrate new multi-channel algorithms being developed using data from the NASA Surface Water and Ocean Topography (SWOT) satellite mission, launched in December 2022. SWOT uses a Bayesian-AMHG-Manning (BAM) algorithm to determine river flow from remotely sensed water elevations (Hagemann et al. 2017), buthas only been demonstrated for single channel rivers. There is also the opportunity to assimilate SWOT data directly in the hydrodynamic model to provide flood and navigation forecasting in real time.
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.