PhD opportunity: Uncertainty in Predicting Soil Water and Plant Available Water at High-Resolution Scales


University of Southern Queensland


Toowoomba, Queensland

Salary etc:

Stipend (living allowance), valued at AUD $30,000 per annum, tax free.

Project summary

Soil moisture and plant available soil water (PAW) are foundational data to predict crop production and inform tactical and strategic decisions on farm management and system design. There are several methods to monitor or estimate soil water and PAW - e.g. sensors, proximal sensing, remote sensing, modelling (process based physical models artificial intelligence) across field and soil profile - each with their particular limitations and uncertainties.

This project is about the development of a scientific framework for modelling PAW at any point in space and time and in the soil profile, using hybrid approaches from process based physical models and Artificial intelligence. It will explore the different sources of data to build an optimum approach with high spatial and temporal resolution. It will explore the calibration of model parameters using the observation of different data sources using different techniques.

This PhD research will explore issues for uncertainty analysis of soil moisture and PAW at sub-paddock scale and implications of uncertainty from different observations and modelling approaches. How high spatial variabilities will constraint model calibration and accurate estimations.


Soil water, modelling, soil water balance, machine learning, crop, soil physics, hydrology


  • Stipend (living allowance), valued at AUD $30,000 per annum, tax free.
  • Full tuition fees for a period of 6 semesters (full-time equivalent). Domestic students will be allocated a Research Training Program (RTP) Fees Offset Place, whereas international students will be offered an International Fees Research Scholarship.
  • The maximum period of the award is three years.
  • Working in a research project gaining practical and industrial experience.


To be eligible applicants must:

  • be either an Australian citizen, permanent resident or international student;
  • not hold a qualification regarded by the USQ to be equivalent to a PhD;
  • have a qualification regarded by USQ to be equivalent, or at higher level to a Bachelor Degree with First Class Honours;
  • be eligible to be enrolled, full-time on-campus (Toowoomba) in a PhD;
  • not be in receipt of similar funding from the Australian Government;
  • be native English speakers and/or meet USQ’s English Language Requirements;

Selection Criteria

  • Background in soil physics, hydrology, engineering or natural science with a strong background in statistical analysis
  • Experience with modelling (including model calibration and uncertainty analysis) and machine learning is highly preferred
  • Familiar with at least one programing/scripting code e.g. R, python, C#
  • Excellent communication skills and ability to work in a team

How to apply:

View details

Date published:


NRMjobs Notice 20005319 - AHC51116 Diploma of Conservation & Land Management
NRMjobs Notice 20005014 - Australasian Weeds Conference
NRMjobs Notice 20006741 - Open Standards - Conservation Standards / Healthy Country Planning workshop
NRMjobs Notice 20006677 - Global Eco Asia-Pacific Tourism Conference
NRMjobs Notice 20004539 - Australasian Seed Science Conference - postponed to 5-9 September 2021
NRMjobs Notice 20004808 - 12th International Conference and Workshop on Lobster Biology & Management
NRMjobs Notice 20006274 - Automatic weed control tracking and reporting
NRMjobs Notice 20006335 - Online Course: How to be an Efficient Writer