Close
PHD Project

October 10, 2017

Predicting Sediment Dynamics in Rivers Infested with Invasive Crayfish

Predicting Sediment Dynamics in Rivers Infested with Invasive Crayfish

Predicting when sediment will move in a river is fundamental to successful management of that river, which includes coping with floods, maintaining navigation, and preventing loss of banks through erosion. However, after over 100 years of research our models of sediment transport still do not perform well when applied to natural channels. Growing evidence suggests this may be at least partially because we have failed to take into account the effect that river-dwelling animals, especially invertebrates, can have on the mobility of the sediment on the river bed and banks. Signal Crayfish (Pacifastacus leniusculus) are an internationally significant invasive species that has serious detrimental impacts on native ecological communities. In addition, they can burrow extensively into river beds and banks, altering the structure and mobility of river sediments. In this project, you will use existing measurements of coarse and fine sediment transport in the presence of crayfish to adapt and construct sediment transport formulae to model sediment dynamics in rivers infested with crayfish. These models will be tested against field data collected during the project at sites in Northamptonshire in collaboration with the Environment Agency and experiments performed by you at the Royal Netherlands Institute for Sea Research. The resulting model will be used to investigate sediment transport and changing channel morphology under differing invasion scenarios. You will join an international network of academics and management professionals focusing on better integrating ecology into our knowledge of river processes and sediment transport and your pioneering work will contribute towards the shift from a purely hydraulics-based approach to erosion and deposition in rivers, to one that takes an eco-hydraulic perspective. Students will receive training at the University of Nottingham in all the required data-collection and analytical and modelling techniques, and participate in the structured NERC Envision training programme.

Applicants should hold a minimum of a UK Honours Degree at a good 2:1 level or equivalent in subjects such as Geography, Engineering, Mathematics, Environmental Science, Earth Science or Natural Sciences.

For further details please contact Dr Matthew Johnson, M.Johnson@nottingham.ac.uk or Prof. Nicholas Dodd, Nicholas.Dodd@nottingham.ac.uk.