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  NERC RED-ALERT CDT: Monitoring source to sink across the catchment for improved river water quality


   Cardiff School of Earth and Environmental Sciences

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  Dr Rupert Perkins, Dr C Wilson, Dr L Bryant, Prof Peter Kille  No more applications being accepted  Competition Funded PhD Project (Students Worldwide)

About the Project

Background

The Natural Environment Research Council funded RED ALERT Centre for Doctoral Training  https://www.bath.ac.uk/centres-for-doctoral-training/nerc-centre-for-doctoral-training-in-real-time-digital-water-based-systems-red-alert-cdt/ will provide training in water-based early warning systems for environmental and public health protection focused around 4 UK and 3 international Living Labs aimed to provide the in-depth knowledge and enable a step-change in managing environmental and public health.

Understanding how river water quality is affected by pollution from farming, home discharges and runoff from roads and urban areas is fundamental to implementing the right solutions to tackling water pollution in freshwater systems and optimising water treatment. Understanding the linkage between water quality trends with seasonality, pulse events and long-term climate change is complex.

Project aims and methods

This project will focus on the Rivers Taff and Ely and upstream reservoirs. Project partner, Welsh Water have an existing network of online profilers in two main water supply reservoirs and in situ monitors in the Taff/Ely catchment. These data will be augmented by spot-sampling along the catchment in response to rainfall events and periods of low and high river flows and reservoir storage level. This project will develop algorithms to identify a ‘calendar’ of water quality patterns to inform ‘live’ optimisation of downstream water treatment works and provide an early warning system of changes that will impact treatment capabilities. Additionally, regulatory monitoring parameters such as pH, conductivity, DO, temperature, ammonia, nitrate and phosphate, will be examined to see if these parameters can indicate changes in other parameters, such as pesticides, aromatic compounds. Effectively, can more-easily and rapidly in situ monitoring act as proxy data for other pollutants? Can the monitoring data in consort be used to define sources of pollutants and hence be used to provide evidence for intervention solutions? The project aims to have outputs that will inform on potential land management changes needed to reduce the risks at source and inform long-term planning and action. This project will have synergy with existing collaboration between project partners analysing reservoir water quality, including in situ vertical profiling, and will also benefit from existing work by Cardiff University (Perkins and Kille) on the River Wye utilising a combination of water quality monitoring, eDNA profiling and citizen science data.

 The successful candidate will join a vibrant research community across three Schools at Cardiff University, Engineering, Biosciences, Earth Sciences, and project partners Bath University and Welsh Water. The project combines award winning research by Perkins (NERC Impact Award 2023; Citizen Science water quality monitoring) and Wilson (Institution of Civil Engineers Research Award 2022; flow monitoring in freshwater systems). During the project, training will be given through the Water RI Early Career Researcher Training involving both academic and social events; Training within the Post Graduate Schools of Earth and Environmental Sciences, Biosciences and Engineering; Particle Image Velocimetry training; molecular analysis and water quality measurements; short term placements within Welsh Water Catchment Management team.

Candidate requirements

Candidates wishing to apply should have a background in one or more of the following areas: freshwater biology, aquatic biochemistry, modelling monitoring datasets. Candidates will need to demonstrate a sound knowledge in one of these fields and ideally a good level of knowledge in the others. Candidates should also demonstrate a wider knowledge of the importance of water quality monitoring data and its uses and a keen interest in working on data with applied end user use. Candidates should also evidence ability to disseminate research findings or a keen interest in publishing their work.

Entry Requirements

Candidates should have a minimum of an upper second class (2.1) degree in a related subject and preferably have a masters qualification or relevant experience.

HOW TO APPLY:

In order to formally apply for the PhD you will need to go to the following web page:

https://www.cardiff.ac.uk/study/postgraduate/research/programmes/programme/earth-sciences

In the black box on the right of the page please select the following options:

Doctor of Philosophy

Full or Part Time

1st October 2024 (or relevant start date)

Click on ‘Apply now’

Please ensure that you include the ‘Project Title’ you are applying for and supervisor, and that you add ‘source of funding’ under source of funding.

Biological Sciences (4) Environmental Sciences (13)

Funding Notes

The successful candidate will receive a minimum stipend of £19,237 per year for living costs, which is paid in regular instalments, and financial support for tuition fees (minimum £4,786 per year) paid directly to the host institution.

References

Perkins et al. 2019.
J. Env. Management https://www.sciencedirect.com/science/article/pii/S0301479719305900
Spears et al, 2012
https://link.springer.com/chapter/10.1007/978-94-007-4333-5_4
Hooper et al. 2023
https://www.sciencedirect.com/science/article/pii/S0043135423001288
Samadi, V. S., Tabas, S. S., Wilson, C. A. M. E. and Hitchcock, D. R. 2024. Regression-based machine learning approaches for daily streamflow modeling. In: Corzo Perez, G. and Solomatine, D. P. eds. Advanced Hydroinformatics: Machine Learning and Optimization for Water Resources. John Wiley & Sons, pp. 129-147., (10.1002/9781119639268.ch5)
Lofty, J., Muhawenimana, V., Wilson, C. A. M. E. and Ouro, P. 2022. Microplastics removal from a primary settler tank in a wastewater treatment plant and estimations of contamination onto European agricultural land via sewage sludge recycling. Environmental Pollution 304, article number: 119198. (10.1016/j.envpol.2022.119198)

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