Project highlights
- An exciting opportunity to learn and develop innovative remote sensing and topographic tools to quantify postglacial processes at the landscape scale
- Great potential for new insights into landscape evolution over multiple temporal and spatial scales, particularly relating to the role of coupling between river and hillslope processes.
- The student will gain both strong remote sensing and analytical expertise and experience a range of scientific disciplines
Overview
Emerging post-glacial landscapes are highly dynamic and transient, with periglacial and fluvial processes at work in settings that exhibit a strong legacy of recent glaciation (Baynes et al., 2015). Under a changing climate and with the resulting potential for rapid and ice-loss, an increasing number of landscapes are under threat of transitioning from glacial to post-glacial conditions. The impact on landscape morphology (such as valley shape) and landscape processes (within channels and on hillslopes), remains unknown (Dadson and Church, 2005; Shugar et al., 2017) but could be important for understanding emerging geohazards such as landsliding (Schonfeldt et al., 2020) or glacial lake outburst floods (Cook et al., 2018) due to heightened rates of erosion focused in particular areas.
This PhD will harness innovative GIS-based remote sensing and topographic analysis methods to explore the typical morphological signature of emerging post-glacial landscapes, such as the regions that surround the Greenland Ice Sheet that are characterised by historic and ongoing ice-mass loss (Figure 1). The analysis will identify and highlight regions undergoing rapid landscape change in response to the transition to post-glacial conditions. Where possible, rates of landscape change will be calculated using existing geochronological estimates for the timing of deglaciation (e.g., radiocarbon ages of sediments or cosmogenic exposure ages of rock surfaces). The morphology and processes of emerging post-glacial landscapes (e.g., Greenland) will also be compared to established post-glacial landscapes (e.g., Scotland; Jansen et al. 2011), allowing a space-for-time analysis of landscape evolution following the transition from glacial to post-glacial environments.
The findings from this project will lead to a step-change in the understanding of dynamic and emerging landscapes that are under threat from a changing climate. There are exciting implications for associated analysis of geohazards and insights into expected future rates of landscape change.
Figure 1: Sentinel 2 image of Northern Greenland, showing an emerging post-glacial landscape with glacial valleys now impacted by fluvial and periglacial processes
Host
Loughborough UniversityTheme
- Dynamic Earth
Supervisors
Project investigator
Dr Edwin Baynes, Loughborough ([email protected])
Co-investigators
Dr Jeff Evans, Loughborough ([email protected])
How to apply
- Each host has a slightly different application process.
Find out how to apply for this studentship. - All applications must include the CENTA application form. Choose your application route
Methodology
The primary methodology for this PhD will be mapping of glacial and post-glacial landforms (Chandler et al. 2018) using high-resolution satellite images (e.g., Sentinel 2 imagery) in a GIS environment, combined with innovative topographic analysis of landscapes using established numerical algorithms and Digital Elevation Models (e.g., Topotoolbox; Schwanghart and Scherler, 2014). The topographic analysis will extract the locations of fluvial knickpoints at the base of valleys, quantify the size and shape of valleys and wider landscape roughness. These metrics will indicate the degree of emerging post-glacial landscape evolution (in Greenland) and be compared to similar metrics extracted from established post-glacial landscapes (e.g., Scotland).
Training and skills
Students will be awarded CENTA2 Training Credits (CTCs) for participation in CENTA2-provided and ‘free choice’ external training. One CTC equates to 1⁄2 day session and students must accrue 100 CTCs across the three years of their PhD.
The project will forge strong skills in handling, organising, and analysing large volumes of topographic and remotely sensed data. Training will be provided in topographic analysis techniques as well as necessary GIS and coding skills as required. Analysis and interpretation of the datasets will lead to the development of high-level skills in statistics. The combination of GIS, topographic analysis, coding, data handling and data analysis skills provides an outstanding training opportunity.
Further details
For further information about this project, please contact Dr Edwin Baynes ([email protected]) or Dr Jeff Evans ([email protected]). For general information about CENTA and the application process, please visit the CENTA website: http://www.centa.org.uk/. For further enquiries about the application process, please contact the School of Social Sciences & Humanities ([email protected]).
If you wish to apply to the project, applications should include:
- A CENTA application form, downloadable from: CENTA application
- A CV with the names of at least two referees (preferably three and who can comment on your academic abilities)
- Submit your application and complete the host institution application process via: http://www.lboro.ac.uk/study/apply/research/. Please quote CENTA23_LU7 when completing the application form.
Applications to be received by the end of the day on Wednesday 11th January 2023.
Possible timeline
Year 1
The student will familiarise themselves with and use cutting edge computational topographic analysis packages (e.g., ‘Topotoolbox’; Schwanghart and Scherler, 2014). This analysis will examine a range of regions of Greenland.
Year 2
Mapping of glacial and post-glacial landforms from satellite imagery to ground-truth the results from the topographic analysis. Comparisons to be made between post-glacial landscapes at different stages of post-glacial evolution (e.g., Greenland and Scotland).
Year 3
Synthesis of post-glacial landscape evolution processes and timescales for development of a conceptual and process-based model.
Further reading
Journal:
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.
Chandler, B. et al. (2018) ‘Glacial geomorphological mapping: A review of approaches and frameworks for best practice.’ Earth Science Reviews 185, 806-846
Cook, K., Andermann, C., Gimbert, F., Adhikari, B.R., Hovius, N. (2018) ‘Glacial lake outburst floods as drivers of fluvial erosion in the Himalaya’. Science 362 (6410), 53-57
Dadson, S., Church, M. (2005) ‘Postglacial topographic evolution of glaciated valleys: a stochastic landscape evolution model’. Earth Surface Processes and Landforms 30 (11), 1387-1403
Jansen, D., Fabel, D., Bishop, P., Xu, S., Schnabel, C., Codilean, A.T., (2011) ‘Does decreasing paraglacial sediment supply slow knickpoint retreat’, Geology 39; 543-546
Schonfeldt, E., Panek, T., Winocur, D., Silhan, K., Korup, O. (2020) ‘Postglacial Patagonian mass movement: From rotational slides and spreads to earthflows’. Geomorphology 367, 107316
Schwanghart, W., Scherler, D. (2014) ‘TopoToolbox 2 – MATLAB-based software for topographic analysis and modeling in Earth surface sciences’, Earth Surface Dynamics, 2, 1-7. [DOI: 10.5194/esurf-2-1-2014]
Shugar, D.H., Clague, J.J., Best, J.L., Schoof, C., Willis, M.J., Copland, L., Roe, G.H. (2017) ‘River piracy and drainage basin reorganization led by climate-driven glacier retreat’. Nature Geoscience 10, 370-375.
COVID-19
The project is primarily desk-based using existing satellite imagery and topographic datasets with no essential fieldwork, so there would be no impact of a pandemic on data collection or research aims. In the event of any lockdown, remote access to an office computer will enable the analysis to be carried out as planned.