- An exciting opportunity to combine fieldwork and experimental modelling to quantify bedrock erosion processes at iconic landscape features (waterfalls)
- Great potential for new insights into landscape evolution over multiple temporal and spatial scales, particularly relating to the role of sediment and uplift rate
- The student will gain both strong practical and analytical expertise and experience a range of scientific disciplines
Waterfalls have long been considered iconic and popular features of any landscape (Gilbert, 1896), but are also critical in controlling the pace and pattern of landscape evolution over both short and long timescales (Baynes et al., 2015; 2018). Landscapes respond to changes in tectonic uplift via the upstream migration of waterfalls, which not only adjust the elevation of the river bed but also the adjoining hillslopes. Despite their importance for the evolution of landscapes, the physical processes that drive waterfall erosion remain poorly constrained with many studies favouring a simplified ‘stream power’ based approach despite recent work highlighting numerous and important complexities in the physical reality (e.g., Steer et al., 2019; Scheingross et al., 2019).
This PhD will harness laboratory modelling and fieldwork in a combined approach to tackle some outstanding questions that remain regarding waterfall processes and their role in landscape evolution. In particular, the role of varying bedload sediment supply (i.e., the ‘tools’ and ‘cover’ effects; Sklar and Dietrich 2001), lithology (strength and structure), and tectonic uplift rate (absolute and transient) on waterfall retreat rate, morphology, and the coupling between hillslopes and channels will be investigated using GIS-based topographic analyses (e.g., with the SWT algorithm; Hillier, 2008), field surveys and analogue modelling experiments.
Specific landscapes for field study will be determined by the student during the early stages of the project, but will include locations where different driving factors can be isolated and quantified, such as bedload sediment supply in the Rangitikei River, New Zealand (Baynes et al., 2020). Other field locations may also include the postglacial landscapes of the French Alps or Scotland, depending on Covid-19 travel restrictions. Unique analogue model experiments will be performed under controlled laboratory conditions (see Baynes et al., 2018 for an example) at the Université de Rennes 1 (France), allowing a range of different climate and tectonic scenarios to be tested and specific waterfall processes quantified including the role of flow hydraulics and sediment supply.
The findings from this project will lead to a step-change in the understanding of waterfall erosion processes, with exciting implications for the modelling of wider landscape evolution and interpreting past landscape change.
- Dynamic Earth
- Dr Edwin Baynes, Loughborough
- Dr John Hillier, Loughborough
- Dr Dimitri Lague, Université de Rennes 1, France
- Dr Philippe Steer, Université de Rennes 1, France
The PhD will implement a unique field and laboratory approach, exploiting geospatial, topographic and analogue model datasets. Topographic analysis using numerical algorithms and GIS to extract river profiles will identify the location and morphology of waterfalls in target landscapes (e.g., New Zealand, Alps, Scotland), and this dataset will be complemented by local lithological and sedimentary characteristics. The student will have undertake fieldwork to collect this dataset, including field mapping, grain size surveys and topographic surveys of the waterfalls themselves (e.g., using drones).
Analogue modelling of waterfall processes in controlled laboratory conditions will be performed during two placements at the Université de Rennes 1 (France) using the Bedrock River Experimental Incision Tank (see Baynes et al., 2018 for more details). Multi-temporal 3D topographic data will be collected from the experiments and will be coupled with a numerical hydrodynamic model to generate water depth and shear stress maps.
Training and skills
The project will forge strong skills in handling, organising and analysing large volumes of topographic and laboratory data. Training will be provided in topographic analysis techniques as well as necessary GIS and coding skills and field survey techniques as required. For the laboratory modelling, full training in the preparation, use and analysis of the experiments will be provided at Université de Rennes. Analysis and interpretation of the datasets will lead to the development of high-level skills in statistics. The combination of physical and numerical modelling, GIS, survey, coding, data handling and data analysis skills provides an outstanding training opportunity.
Partners and collaboration
The external international partners for this project are Dr Dimitri Lague and Dr Philippe Steer at Université de Rennes 1, France. They are internationally-leading researchers on bedrock river erosion processes, their wider role in mountain landscape evolution, and using high resolution topographic elevation data to extract information from landscapes. There will be multiple opportunities to visit and work with Dr Lague and Dr Steer on the laboratory modelling, and to engage and network with the wider Quantitative Geomorphology research group at the Université de Rennes 1, exploiting Dr Edwin Baynes well-established relationships with this group.
For further information about this project, please contact Dr Edwin Baynes (email@example.com). For enquiries about the application process, please contact the School of Social Sciences & Humanities (firstname.lastname@example.org). Please quote CENTA when completing the application form: http://www.lboro.ac.uk/study/apply/research/
The student will familiarise themselves with and use cutting edge computational topographic analysis packages (e.g., ‘SWT’; Hillier, 2008 and ‘LSDTopoTools’; Mudd et al., 2014). This analysis will examine a range of landscapes containing waterfalls, and will lead to the field site selection.
Fieldwork will take place to the selected field site to groundtruth the topographic analysis and collect field data related to sedimentary characteristics (e.g., grain size, lithology). The student will also visit Rennes to perform the first suite of laboratory experiments.
Follow-up visit to Rennes to perform final laboratory experiments, and development of waterfall erosion theory using synthesis of the laboratory data in the context of the field data and topographic analysis.
Baynes E.R.C., Attal M., Niedermann S., Kirstein L.A., Dugmore A.J., Naylor M. (2015) ‘Erosion during extreme flood events dominates Holocene canyon evolution in northeast Iceland’. Proceedings of the National Academy of Sciences 112 (8), 2355-2360.
Baynes E.R.C., Lague D., Attal M., Gangloff A., Kirstein L.A., Dugmore A.J. (2018) ‘River self-organisation inhibits discharge control on waterfall migration’. Scientific Reports 8, 2444,
Baynes E.R.C., Lague D., Steer P., Bonnet S., Illien L., (2020) ‘Sediment flux driven channel geometry adjustment of bedrock and mixed gravel‐bedrock rivers’. Earth Surface Processes and Landforms, https://doi.org/10.1002/esp.4996
Gilbert, G.K., (1896) ‘Niagara Falls and their History’. American Book Company, New York
Hillier, J. K., (2008) ‘Seamount (submarine volcano) detection and isolation with a modified wavelet transform’, Basin Research 20, pp. 555-573
Mudd, S.M., Attal., M., Milodowski, D.T., Grieve, S.W.D., Valters, D.A. (2014) ‘A statistical framework to quantify spatial variation in channel gradients using the integral method of channel profile analysis’, Journal of Geophysical Research: Earth Surface 119 (2), pp. 138-152
Scheingross, J.S., M.P. Lamb, and B. Fuller, 2019, ‘Self-formed bedrock waterfalls’, Nature, 567, pp. 229-233
Sklar L.S., Dietrich W.E., 2001. ‘Sediment and rock strength controls on river incision into bedrock’, Geology, 29: 1087–1090.
Steer P., Croissant T., Baynes E.R.C., Lague D. (2019) Statistical modelling of co-seismic knickpoint formation and river response to fault slip. Earth Surface Dynamics 7, 681-706,
The analogue modelling component using the laboratory facility in Rennes, France will take place in years 2 and 3 (i.e., 2022-2023) to minimise the potential for travel disruption. In the event of European travel not being possible, the flumes in the laboratory at Loughborough will be adapted to perform similar waterfall experiments, so the overall aim of the project will not be affected. Specific field sites will be determined at the start of the project. If overseas fieldwork (i.e. New Zealand/European Alps) is not possible, some of the many interesting waterfalls in the UK (Scotland, Northern England) will be used.