Rates of drainage network evolution measured with detrital data and inverse methods

Theme: Solid Earth Dynamics

Primary Supervisor:

Matthew Fox

Earth Sciences, UCL

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Secondary Supervisor:

Pieter Vermeesch

Earth Sciences, UCL

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Additional Supervisor(s):
Hugh Sinclair (Edinburgh)

Project Description:

The stability of the planform geometry of river networks is key to understanding sediment flux from mountain ranges, which has been used to constrain climate-erosion coupling. Recent research has indicated that river networks are dynamic features that adjust to changes in tectonics and lithology. In the Pyrenees, the exhumation of plutonic rocks has produced an enigmatic sinuous main drainage divide (Bernard et al., EPSL, 2019). It is unclear how quickly the landscape takes to respond to the appearance of these harder rocks and what this means for perceived changes in sediment flux to the Ebro Basin to the south and the Aquitaine Basin in the north.

This project will combine fieldwork in the Pyrenees, lab work at the London Geochronology Centre and numerical modelling. Three fieldwork campaigns are planned with the aim of collected modern sediment that is sourced from parts of the landscape driving divide migration. Laboratory work will use U-Pb geochrononology and apatite (U-Th)/He thermochronology to fingerprint the source of the sediments. We will also use cosmogenic nuclide concentrations to measure catchment wide erosion rates. Recently developed inverse methods will provide high resolution erosion rates models that can be related to divide migration. These will be combined with landscape evolution models that predict the changing drainage network and changes in flux to the surrounding foreland basins. Throughout the project there will be opportunities for the student to visit analytical labs and large national facilities in the UK, Europe and USA depending on project requirements.

Policy Impact of Research:

Erosion and weathering combine to stabilise Earth’s climate through geological time. Inability to predict erosion rates driven by divide migration leads to an incomplete understanding of Earth’s evolving climate. This project provides new insight into this complex process.

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