Project Background
Fluvial system sustainability is vital for a half billion riparian residents of global river floodplains and deltas, and it requires knowledge and understanding of the land surface changes through time in response to anthropogenic and climatic forcing. Germane to such understanding are high quality topographic data enabling the quantification of surface morphology and change, which are essential for understanding responses of lowland sedimentary systems to these forcings. However, global topographic data are of insufficient quality and resolution, creating major challenges for managing lowland river-floodplain complexes in large alluvial rivers. This scarcity of topographic data is especially applicable to low-gradient tropical rivers where 1) accurate topographic survey data are scarce, 2) floodplains have significant vegetation precluding satellite observation of surfaces, and 3) previous global data (eg., SRTM) are technically limited in terms of accuracy and resolution for geomorphic applications. The TanDEM-X high-resolution SAR mission (directory.eoportal.org/web/eoportal/satellite-missions/t/tandem-x) offers a way forwards, especially when paired with remote sensing data and machine learning statistical methods.
Our exploratory work with the high-resolution (~12m) TDX product in Amazonia and SE Asia has identified means to remove trees using a combination of tomographic analysis, remote sensing, and machine learning using GPUs – producing bare earth DEMs for fluvial systems that can be verified for locations where we have field survey and Lidar data from prior and current NERC, NSF, and NASA-funded projects. The PhD student would focus on the refinement and application of these novel data and techniques towards quantifying the topography and evolution of project rivers – the lower Mekong River and large portions of the Amazon, major river systems that can be used to calibrate and test these approaches in coordination with ongoing NERC-funded research. Following this verification and refinement against available data, the student would work with the supervisorial team to identify and pursue a range of intriguing scientific questions for additional research locations, thus providing the PhD candidate flexibility and intellectual independence to realize their own interests and pursue new opportunities for transformative research.
The project will appeal to candidates skilled with GIS analysis of topographic datasets, and who are interested in novel spatial analysis of the expressions of and controls on large river morphodynamics – candidates are encouraged to contact the lead supervisor to discuss specific scientific and technical opportunities for this PhD research.
Exeter is a Russel Group research-intensive university located in a beautiful, semi-rural setting, yet just 2 hours by train from London. We are an international leader in environmental research, Geography is ranked in the top 5 globally (ARWU 2020), and we have close links to the MET Office/Hadley Centre’s climate research into river systems and the Global Systems Institute, offering additional educational and collaborative opportunities for the prospective student.
Project Aims and Methods
After refining the analytical methods for study areas with suitable field data, the PhD research would focus on quantifying the floodplain topography and gradients that drive flow, sediment transport, and river evolution for research sites, providing novel scientific insight into the functioning of fluvial systems. To further evaluate observed relationships, the student would work closely with the supervisorial team to design the reminder of their PhD research. For example, potential causal mechanisms identified for study rivers could be tested using models for fluvial morphodynamics (both standard and Exeter research models). Measurements and predictions could be verified against extensive Exeter field datasets available for the study systems and elsewhere, with possibilities for fieldwork. The ultimate aim of this PhD will be to produce generic findings about the functioning and complex evolution of large river systems that are suitable for publication in prominent journals, preparing the student for further career success.
Candidate requirements
Skills for topographic analysis and remote sensing are required. Modelling and coding skills would also be beneficial, along with a passion for river science.
Training
We will provide a high spec workstation plus training for analysing project data. Exeter provides expert technical support for GIS, specialist software such as Delft-FM, HSTAR, and machine learning models, along with the necessary computer resources. There may be opportunities for the student to assist with NERC-funded survey(s) of river bed and floodplain topography along large rivers in South America.
Useful links
https://geography.exeter.ac.uk/staff/index.php?web_id=Rolf_Aalto
http://geography.exeter.ac.uk/staff/index.php?web_id=Barend_Van-Maanen
http://geography.exeter.ac.uk/staff/index.php?web_id=Andrew_Nicholas
https://www.cardiff.ac.uk/people/view/808751-singer-michael
How to apply
In order to formally apply for the PhD Project you will need to go to the following web page.
https://www.exeter.ac.uk/study/funding/award/?id=4243
The closing date for applications is 1600 hours GMT on Friday 10th January 2022.
Interviews will be held between 28th February and 4th March 2022.
If you have any general enquiries about the application process please email [Email Address Removed] or phone: 0300 555 60 60 (UK callers) or +44 (0) 1392 723044 (EU/International callers). Project-specific queries should be directed to the main supervisor
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