DustWatch Australia: wind erosion modelling for sustainable land management

DustWatch Australia: wind erosion modelling for sustainable land management

About the project

During the last decade, wind erosion of soils has removed millions of tonnes of valuable topsoil from Australia’s agricultural and pastoral lands, reducing capacity to produce food and affecting the economy. The loss of topsoil can also negatively affect biodiversity, the climate and air and water quality.

During an Australian dust storm on 23 September 2009, more than 2.5 million tonnes of soil was blown off the Australian coast. The economic impact of this event on the NSW economy alone was conservatively estimated to be almost $300 million.

In the future the problem could get worse. The 2013 report on ‘Australia’s Capacity to Monitor Wind Erosion’ (Leys et al., 2009) states: “Projected climate change scenarios indicate that climate conditions will make wind erosion more prevalent unless land management practices can be further improved to maintain higher levels of ground cover.”

DustWatch Australia has taken a collaborative approach to understanding wind erosion and is bringing together relevant data sets, modelling those data and making the information openly available. Griffith University, Australian National University (ANU) and the University of Southern Queensland (USQ) focus on northern Australia and support a national DustWatch website, while the NSW Office of Environment and Heritage (NSW OEH) maintains the southern DustWatch network of DustTrak wind erosion sensors.

The Federal Government ‘Caring for Our Country Program’ supported three nationally funded projects: Community DustWatch (led by NSW OEH), Wind Erosion Histories (led by Griffith), and Modelled Wind Erosion (led by USQ).

Model input data comes from a range of sources, including satellite images from the MODIS Rapid Response Project (NASA), which are processed into a groundcover index by CSIRO Land and Water. Fire data is available from the Fire Information for Resource Management System (FIRMS), and Australia’s Bureau of Meteorology and the U.S. National Oceanic and Atmospheric Administration (NOAA) provides climate and atmospheric data.

These diverse and large data sets did create data management issues for DustWatch Australia. “We were generating more modelling data than we could handle on in-house systems at either USQ or Griffith,” said Dr Harry Butler, DustWatch Australia’s Data Manager/Modeller and a USQ Senior Lecturer in the School of Agricultural, Computational and Environmental Sciences.

“We had to deal with large atmospheric and remote sensing data sets as inputs, and output several variables at high spatial and temporal to observe trends from the model. All of which need to be available to confirm modelling results and ensure that model runs can be reproduced.”

Dr Butler found the answer to his data management needs in QRIScloud, which he used to store raw data. The modelled outputs from this data was then made publicly available on the DustWatch website. “The separation of the two sites ensures the security of the original data,” said Dr Butler.

Raw data from QRIScloud is also shared with colleagues at Griffith University for studies of the influence of aeolian dust on marine ecosystems in the Great Barrier Reef, the Tasman Sea and the Southern Ocean.

“QRIScloud is allowing us to handle much bigger data sets than if we had to use purely in-house systems. This is giving us an edge in developing methods for handling periods when remote sensing data is not available, i.e. prior to the 1980s,” said Dr Butler.

“We have been able to process data for a 13-year period at a relative high spatial (10km) and temporal (monthly) resolution. This has enabled the group to start research into the long-term dust climate of Australia and the impact that climate variability has on erosion levels within Australia.”

Dr Butler and the DustWatch team are currently working on extending the modelling side of the project to pre-1980 periods, firstly from 1948, and finally, and hopefully, from 1910 to the present day.

“Extending the modelling range by about 100 years will provide a better picture of the severity and extent of Australia’s wind erosion history. This, coupled with improvements in long-range future climate forecasting models, will allow researchers and policymakers to make better targeted investments to prevent the negative impacts of wind erosion on Australia’s economy,” Dr Butler said.

Further reading:

Butler, Harry J. and Shao, Yaping and Leys, John F. and McTainsh, G. H. (2007) Modelling wind erosion at national and regional scale using the CEMSYS model: national monitoring and evaluation framework, prepared for the National Land & Water Resources Audit. Technical Report. National Land and Water Resources Audit, Canberra, Australia.

Leys, J., Butler, H, Strong, C., McTainsh, G. (2013), Australia’s Capacity to Monitor Wind Erosion: Final Synthesis Report for Projects. Office of Environment and Heritage, Sydney. 45pp.

Leys, J., Smith, J., MacRae, C., Rickards, J., Yang, X., Randall, L., Hairsine, P., Dixon, J., McTainsh, G., 2009. Improving the Capacity to Monitor Wind and Water Erosion: A Review. Department of Agriculture, Fisheries and Forests, Australian Government, Canberra, p. 160.

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