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

Soil moisture and plant available soil water (PAW) is a 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 & artificial intelligent) across filed and soil profile, each with their particular limitations and uncertainties. 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 approach. How high spatial variabilities will constraint model calibration and accurate estimations.  
  • 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.