Linkage Infrastructure, Equipment And Facilities - Grant ID: LE100100094
Funder
Australian Research Council
Funding Amount
$110,000.00
Summary
Single-grain optically-stimulated luminescence and dosimetry instruments to service the Sydney metropolitan and greater New South Wales region. This equipment will support projects that address significant environmental challenges in Australia, such as climate change and variability, coastal management and sustainable river and water management, and that assess the impacts and consequences of these challenges for populations living in environmentally sensitive areas. These projects will build on ....Single-grain optically-stimulated luminescence and dosimetry instruments to service the Sydney metropolitan and greater New South Wales region. This equipment will support projects that address significant environmental challenges in Australia, such as climate change and variability, coastal management and sustainable river and water management, and that assess the impacts and consequences of these challenges for populations living in environmentally sensitive areas. These projects will build on established collaborations in Australia, Antarctica and the south-west Pacific and encourage new collaborations with south-east Asian, Egyptian and Argentinean researchers, which will promote Australian research on a world stage. The use of this equipment will also pioneer new dating methodologies to further enhance Australia's place at the forefront of geochronology.Read moreRead less
Improved seasonal rainfall prediction for grain growers using farm level data and novel modelling. Successful grain production, a key export commodity for Australia, depends heavily on reliable seasonal forecasts. However, the highly variable climate means that for Australia’s 25,000 grain growers current forecasts lack detail in space and time. Using a combination of fuzzy classification and artificial neural networks, this project will develop a locally detailed continuously updating data-driv ....Improved seasonal rainfall prediction for grain growers using farm level data and novel modelling. Successful grain production, a key export commodity for Australia, depends heavily on reliable seasonal forecasts. However, the highly variable climate means that for Australia’s 25,000 grain growers current forecasts lack detail in space and time. Using a combination of fuzzy classification and artificial neural networks, this project will develop a locally detailed continuously updating data-driven seasonal forecast system using high density climate data from the 17,000 Grain Growers Association members and climate drivers such as sea surface temperature from the Bureau of Meteorology. After validation against observed data, the forecasts will be delivered via a web-based portal to users.Read moreRead less