Developing groundwater management solutions that keep taps flowing while ensuring wetlands stay wet
This project will focus on addressing the trade-off often observed between the demand for drinking water and the need to maintain groundwater-dependent ecosystems, a delicate balance plagued by uncertainty and jeopardized by climate change.
Our success with managing complex hydrogeological systems is predicated on our ability to make reliable predictions about future system behaviour. A well-accepted method for making such predictions is through integrated hydrogeological modelling.
Various entities, including the water utility and the state government of Western Australia, rely on model predictions to support important groundwater management decisions, such as allocation planning. However, to date, decisions are too often made with a single deterministic model simulation, ignoring the impacts of uncertainty associated with hydrologic properties and fluxes. This approach runs the risk of making poor decisions with adverse impacts on both our water supply and the environment.
This project will focus on new technologies for hydrogeologic modelling and uncertainty quantification in an effort to improve water security in Western Australia and beyond. Successful applicants will not only have the opportunity to work closely with the Department of Water and Environmental Regulation and the Water Corporation of Western Australia, but also the opportunity to work with scientists abroad.
As part of this project the successful PhD applicant will:
- Use state-of-art software (e.g., PEST++, FloPy, etc.) and high-performance supercomputers to address both conceptual and predictive uncertainty in hydrogeological systems
- Develop new technologies and workflows for model development using GIS platforms
- Address the representation of complex structures in hydrogeologic models including, pinched-out aquifers, groundwater recharge mechanisms, etc.
- Siade, A. J., Hall, J., and Karelse, R. N. (2017). A practical, robust methodology for acquiring new observation data using computationally expensive groundwater models. Water Resources Research, 53.
- Siade, A.J., Cui, T., Karelse, R.N., Hampton, C., (2020). Reduced-Dimensional Gaussian Process Machine Learning for Groundwater Allocation Planning using Swarm Theory. Water Resources Research, 56.
- Siade, A. J., Rathi, B., Prommer, H., Welter, D., & Doherty, J. (2019). Using heuristic multi-objective optimization for quantifying predictive uncertainty associated with groundwater flow and reactive transport models. Journal of Hydrology, 577, 123999.
I am a Hydrogeologist with broad research interests including, groundwater hydrology, contaminant transport, uncertainty assessment, data worth and design, and environmental decision support. I’m particularly interested in developing techniques to improve our understanding of natural systems such that the risks of adverse anthropogenic impacts on these systems are minimised.
Funding and Collaborations
Funding - This PhD position is fully-funded through a research agreement with the Department of Water and Environmental Regulation with a stipend of $45k pa.
- Department of Water and Environmental Regulation
- Water Corporation
- Collaborators interested in this research project can email firstname.lastname@example.org
How to Apply
- To be accepted into the Doctor of Philosophy, an applicant must demonstrate they have sufficient background experience in independent supervised research to successfully complete, and provide evidence of English language proficiency
- Requirements specific to this project - A desire and capacity to develop quantitative hydrogeology modelling skills ranging from uncertainty assessment, to risk, to the optimal design of field-based monitoring networks aimed at reducing uncertainty through the acquisition of new system information. A familiarity with programming languages (e.g., C++, Python, etc.) and GIS will be desirable.
Submit enquiry to research team leader
- Contact the research team leader by submitting an Expression of Interest form via the button below
- After you have discussed your project with the research team leader, contact email@example.com to proceed with your application