Protecting the iconic red gum and other floodplain forests in the Murray Darling Basin requires a good understanding of the long term water needs and how this interacts with climate and flow variability. More specifically it requires understanding how these vegetation communities balance the use of possible saline groundwater with very irregular fresh flooding water and rainfall. Using large scale modelling, this project aims to deliver management options for environmental flows by linking satellite data with field observations in a spatio-temporal model.
The variable climate and streamflow in the Murray Darling Basin has shaped the structure and pattern of vegetation in the landscape. The long term ecological patterns result in ecosytem services through storage of flood water, feedback of moisture to rainfall and filtering of sediment. Surprisingly, little is known about these interlinked dynamics and their function across multiple scales, and in particular up to whole of basin and landscape scales. Here we aim to develop and verify a spatio-temporal landscape model, related to earlier ecohydrological work. This model aims to incorporate the important link between groundwater, flooding and vegetation growth in semi-arid inland Australia. Using available field and satellite data for verification we will predict responses in vegetation structure and density under changing climate, changing flood frequency and groundwater levels. The outcomes will highlight opportunities for vegetation management in relation to salinity and water sharing. This work builds on previous research in the area of ecohydrology (Vervoort and van der Zee 2008; 2009; van der Zee et al. 2014), and will use field data collected by different collaborating researchers.
There are strong opportunities to interact with international researchers (particularly the Netherlands) and in Australia and CSIRO. The project involves a significant focus on analytical modelling using R (www.r-project.org), or Python and Google Earth Engine in both space and time. Different satellite data products would be used to extend the modelling over large spatial areas.
van der Zee, S.E.A.T.M., Shah, S.H.H., Vervoort, R.W., 2014. Root zone salinity and sodicity under seasonal rainfall due to feedback of decreasing hydraulic conductivity. Water Resour. Res., 50(12): 9432-9446. DOI:10.1002/2013WR015208 Vervoort, R.W., van der Zee, S.E.A.T.M., 2008. Simulating the effect of capillary flux on the soil water balance in a stochastic ecohydrological framework. Water Resour. Res., 44: W08425. DOI:doi:10.1029/2008WR006889 Vervoort, R.W., van der Zee, S.E.A.T.M., 2009. Stochastic soil water dynamics of phreatophyte vegetation with dimorphic root systems. Water Resour. Res., 45: W10439. Vervoort, R.W., van der Zee, S.E.A.T.M., 2012. On stochastic modelling of groundwater uptake in semi-arid water-limited systems: root density and seasonality effects. Ecohydrology, 5(5): 580-595. DOI:10.1002/eco.1288
We are seeking a PhD candidate to work on this project in the area of ecohydrology – competitive scholarships are available from the Faculty of Agriculture, Food & Natural Resources and the University. International students would require an EIPRS or USYDIS or similar scholarship. The ideal student should have a background in engineering, science or agriculture with strengths in mathematics or physics and experience in computer programming.
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.
The opportunity ID for this research opportunity is 1077