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Cameron Leckie wins QLD Division Alan Rixon Memorial Medal for 2019

Tue 07, Jul 2020

 

Improving infiltration modelling for crusting soils

The Alan Rixon Memorial Medal is awarded by the Queensland Division of the Ag Institute Australia to the top final year student in Agricultural or Environmental Engineering at the University of Southern Queensland. It is awarded in the memory of Dr Alan Rixon, a CSIRO scientist then foundation member of the faculty at USQ who taught agricultural and soil science. The 2019 medal was presented to Cameron Leckie, who graduated from USQ with a Bachelor of Engineering (Honours) majoring in Agricultural Engineering. Cameron was honoured to receive the Alan Rixon Memorial Medal.

Image credit: 123rf.com

The following is Cameron’s story:

“I lived on a small sheep farm in country Victoria during my childhood years. After a 20-year diversion in the Australian Army I decided to change my career and commenced my mainly part time studies at USQ. My course was most enjoyable and provided wonderful experiences, highlighted by attending three Soil Judging Competitions (at Queenstown, New Zealand; Canberra; and Strathalbyn, South Australia) where university students from Australia and New Zealand classified soils and evaluated their suitability for differing land uses.

My Honours project was titled ‘Improving infiltration modelling for crusting soils.’ Modelling infiltration is extremely important in agronomy, mine site rehabilitation, ecology and water engineering. A major source of error in infiltration modelling is the impact of thin surface crusts which have very low porosity and consequentially reduce infiltration. Surface crusts can reduce infiltration by as much as 80% resulting in greater runoff and less profile water for plant growth. Many Australian agricultural soils are susceptible to surface crusting.

My project used a rainfall simulator provided by Landloch Pty Ltd, to create a surface crust and measure surface runoff. The properties of the surface crust were measured using X-ray Computed Tomography (CT), thus taking an X-ray of the soil samples. This data was then used to model infiltration using the software application HYDRUS-1D. I hypothesized that by measuring the density of the surface crust, the accuracy of the infiltration modelling would be increased.

Initially, I found that incorporating the density of the thin surface crust into HYDRUS-1D made little difference to the results. I then applied inverse modelling to identify model parameters which would improve the accuracy. Through this process I identified that the database within HYDRUS-1D overestimated the most important soil hydraulic property, saturated hydraulic conductivity, by three to four times. A new set of parameters were obtained which enabled accurate infiltration modelling. Given the small number of soil samples, types and vegetation cover, used in the project, further experimentation is required to validate the results. However, a key conclusion is that infiltration models which do not explicitly incorporate the impact of the surface crust could be overestimating infiltration/underestimating surface runoff by a large degree.

In 2020, I have commenced a PhD at the USQ, in which I aim to extend my study to spatially predict infiltration at the sub-paddock scale.”

Greyscale image of a soil core obtained from X-ray CT. Black areas within the soil matrix are the soil pores whilst the grey areas are the soil solids. At the very top of the soil is loose unconsolidated material. Immediately underneath this is the crust where very few pores exist. On average over 90% of the applied rainfall ended up as runoff highlighting the effectiveness of the crust in reducing infiltration.

 

 


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