Proximal soil sensing for improved delineation of contaminated sites

Summary

There are many thousands of contaminated soil sites across urban and rural Australia. These sites contaminated with metals and/or organics pose a potential threat to human health. Detection and remediation of such sites are expensive. Through a novel proximal soil sensing method combined with data –fused soil inference and optimised sampling and mapping, it is possible to efficiently identify those areas of any site requiring remediation. This will reduce the barrier to detection and remediation considerably hastening the removal of this health risk.

Supervisor(s)

Professor Alex McBratney

Research Location

Sydney Institute of Agriculture

Program Type

PHD

Synopsis

While we can collect detailed soil information at limited locations and interpolate the values across space and time, in some instances it would be more beneficial if we can directly measure soil information at a fine spatial scale (e.g. measurement every 10 metres). Proximal soil sensing acquires information about soil through the use of sensors that are placed in proximity to the soil in situ, in contrast to remote sensing. This work will investigate the use of proximal soil sensing in soil contamination assessment. Main objectives are the firstly the development of a soil inference system with associated measurement technology that can estimate a range of possible contaminants at any location. The aim will be to generate spatial soil information with a resolution that is required for remediation of contaminated sites.

Additional Information

Additional supervisors, Professor Budiman Minasny and Associate Professor Thomas Bishop

This project involves field, laboratory and modelling work. The student will acquire valuable knowledge and skills in the areas of soil spectroscopy and inference system. The student will also be expected to further develop skills in modern statistical and spatial data analysis and scientific publication. 
HDR Inherent Requirements 

In addition to the academic requirements set out in the Science Postgraduate Handbook, you may be required to satisfy a number of inherent requirements to complete this degree. Example of inherent requirement may include:

- Confidential disclosure and registration of a disability that may hinder your performance in your degree;
- Confidential disclosure of a pre-existing or current medical condition that may hinder your performance in your degree (e.g. heart disease, pace-maker, significant immune suppression, diabetes, vertigo, etc.);
- Ability to perform independently and/or with minimal supervision;
- Ability to undertake certain physical tasks (e.g. heavy lifting);
- Ability to undertake observatory, sensory and communication tasks;
- Ability to spend time at remote sites (e.g. One Tree Island, Narrabri and Camden);
- Ability to work in confined spaces or at heights;
- Ability to operate heavy machinery (e.g. farming equipment);
- Hold or acquire an Australian driver’s licence;
- Hold a current scuba diving license;
- Hold a current Working with Children Check;
- Meet initial and ongoing immunisation requirements (e.g. Q-Fever, Vaccinia virus, Hepatitis, etc.)

You must consult with your nominated supervisor regarding any identified inherent requirements before completing your application.

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Keywords

proximal soil sensing, soil contamination, spatial statistics, uncertainty assessment

Opportunity ID

The opportunity ID for this research opportunity is: 1833

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