Testing Bayesian Network-based management frameworks for controlling nitrate contamination in groundwater
The PhD project focuses on improving the understanding and the control of nitrate contamination in groundwater using a novel probabilistic framework. Nitrate is one of the most common diffuse pollutants found in groundwater. Protecting groundwater in areas that are at risk with regards to nitrate contamination is crucial as contaminated groundwater presents a threat for drinking water supplies and surface water ecosystems. However, identifying and managing such areas involves dealing with a large variety of sources of contamination and is often hampered by limited availability of both hydrogeological and water quality monitoring data. The research aims to develop a Bayesian Network (BN) framework, a novel probabilistic method for assessing and mapping of groundwater vulnerability to nitrate contamination. The advantage of the BN approach is that it allows for data gaps and the uncertainties that such vulnerability assessments are usually faced with. Ultimately, the BN approach will be applied in the project to examine different management schemes for controlling nitrate contamination in groundwater.
This project represents an exciting opportunity for someone to join the active and expending research group of the Northern Rivers Institute (NRI) with collaboration with the James Hutton Institute (JHI). The NRI is a centre of research excellence in environmental hydrology which delivers internationally leading hydrological science to help underpin sustainable water management. NRI undertakes fundamental research to help understand the hydrological functioning of catchments and aquifers as well as the resilience of water resources to global changes and pollutions. The JHI is an international research centre in environmental sciences that delivers key scientific outputs to policymakers, works closely with stakeholders and is engaged with end-users particularly in the field of environmental risk assessment and management, including the contamination of water resources.
The PhD project focuses on improving the understanding and the control of nitrate contamination in groundwater using a novel probabilistic framework.
Nitrate is one of the most common diffuse pollutants found in groundwater and is considered a major environmental and health problem. Protecting groundwater in areas that are vulnerable to nitrate contamination is crucial as contaminated groundwater presents a risk to drinking water supplies and may cause eutrophication of surface-water ecosystems. As part of the EU Nitrates Directive, member states are required to designate nitrate vulnerable zones (NVZs) to areas where there is a serious threat to the water environment from nitrates.
However, characterizing and managing groundwater contamination involves dealing with many different sources of contamination (agricultural/domestic, point/diffuse) and is often hampered by limited availability of both hydrogeological and water quality monitoring data. In addition, management of nitrate contamination is typically faced with conflicting interests (environmental, economic and social)
The research aims to develop a Bayesian Network (BN) framework, combining hydrogeological and socio-environmental factors, as a novel probabilistic method for assessing and mapping of groundwater vulnerability to nitrate contamination. Ultimately, it will examine different management schemes for controlling nitrate contamination. The BN approach allows for data gaps and the uncertainties that such groundwater vulnerability assessments are faced with. The approach will initially be developed and applied to the Ythan catchment, a strategic monitored catchment in Scotland and a designated NVZ, where extensive databases are available. Funding permitting, it will be extended to an additional well-documented region, with contrasting physical setting and socio-environmental drivers.
The project will involve interdisciplinary training in hydrogeological analysis of complex groundwater systems; in BN modelling and environmental computer-based decision-support systems; and in linking environmental processes of agricultural diffuse pollution with socio-economic science. The student will be primarily based at UoA with regular placements in JHI.
Essential Background: Equivalent of 2.1 Honours Degree in Earth and environmental sciences; Civil, environmental or water engineering
Knowledge of: Hydrogeology, Hydrology, Basic geostatistics, Geological environments, Water resources engineering, Environmental management
The other supervisors on this project are Dr Mads Troldborg, Information and Computational Sciences Group and Dr Andy Vinten, Social, Economic and Geographical Sciences Group (externals), James Hutton Institute (JHI), Aberdeen
The successful applicant will be expected to provide the funding for Tuition fees, living expenses and maintenance. Details of the cost of study can be found by visiting www.abdn.ac.uk. There is NO funding attached to this project. You can find details of living costs and the like by visiting http://www.abdn.ac.uk/international/finance.php.
This project is advertised in relation to the research areas of the discipline of Geosciences.
Formal applications can be completed online: http://www.abdn.ac.uk/postgraduate/apply. You should apply for PhD in Geography, to ensure that your application is passed to the correct College for processing. Please ensure that you quote the project title and supervisor on the application form.
Informal inquiries can be made to Dr J C Comte ([email protected]) with a copy of your curriculum vitae and cover letter. All general enquiries should be directed to the Graduate School Admissions Unit ([email protected]).