Project Description
Stable isotopes d18O and d2H in the water cycle can be used as tracers in water resource management, climate research, food provenance and authenticity, and human and ecological forensics. Fractionation during phase changes and mixing through the hydrological cycle make d18O and d2H particularly useful as hydrological tracers.
In Sydney and other major cities in Australia, ANSTO has compiled an impressive tap water isotope dataset that can be used to understand water supply systems and, in turn, provide an input for the forensic and environmental use of stable isotope data.
This project is to take more than 15 years of tap water isotope data from two sites in Sydney to model catchment/dam water balance for Woronora/Sydney water supply catchments and use this to predict the isotope distribution in tap water broader Sydney Water supply system.
This project follows on from a UNSW honours project in 2022, which compiled much of the required data. The objective of this project is to do the quantitative analyses and modelling that will make this work ready for publication and demonstrate its utility for stakeholder Sydney Water and broadly for forensics applications.
If the student is interested in working on data from another city/ town, this may be possible.
Industry: Nuclear Science Technology
Study area: Environmental & Biological Science
Partner: ANSTO
Suburb: Lucas Heights, NSW
Why:
ANSTO are partners to the LIFT Project, funded by ANSTO and the Department of Industry, Science and Resources Women in STEM and Entrepreneurship (WISE) program.
LIFT is designed to offer women in STEM a portfolio of skills and opportunities, including industry engagement, entrepreneurship, leadership and community outreach.
Paid
Yes
Selection Criteria
If you’re a postgraduate research student who identifies as a woman, are studying a STEM FoR code and meet some or all the below we want to hear from you. We strongly encourage women, Indigenous and disadvantaged candidates to apply:
Required
- Proficient programming skills in Python or R.
- Experience with machine learning
Preferred
- An understanding of hydrological/catchment processes and water supply systems will be important.
- Helpful backgrounds include civil engineering, environmental engineering, environmental science, atmospheric science, climate science, geoscience, physics or chemistry.
Research Outcomes
Expected Milestones:
Month One
- Scope a suitable modelling approach and conceptual model in close collaboration with ANSTO supervisor(s).
- Inspect and compile the data from the original honours project and identify any additional data requirements / missing data.
Month Two
- Develop and test the modelling framework. Liaise with supervisor and Sydney Water stakeholders to obtain missing data.
Month Three
- Finalise modelling approach and produce model outputs, graphic and interpretations.
- Draft section to contribute to a journal publication.
The role of the intern in the publication will be at minimum co-author, but depending on skills and contribution there can be the potential to lead a publication beyond the internship period.
Other Information
The intern will receive $3,000 per month of the internship, usually in the form of scholarship payments, supported by the LIFT Project.
The intern is expected to undertake the iAccelerate Activate entrepreneurial training, the LIFT values and leadership retreat and community outreach as a condition of their scholarship. This may be asynchronous with their internship.
The intern will need to comply with ANSTO security clearance protocols, which can take 8-10 weeks once submitted. This should be factored into planning the internship commencement.
It is expected that the intern will primarily undertake this research project during regular business hours and maintain contact with their academic mentor throughout the internship either through face-to-face or phone meetings as appropriate.
The intern and their academic mentor will have the opportunity to negotiate the project’s scope, milestones and timeline during the project planning stage.
Please note, that applications are reviewed regularly and this internship may be filled prior to the advertised closing date if a suitable applicant is identified. Early submissions are encouraged.
Duration
12 weeks full time or 6 months part time, noting Wednesdays are to be kept free during iAccelerate's Activate session
Reference
ANSTO-Hughes-001
Application closing date
18 October 2024
Contact information
Georgia Watson