Industry Laureate Fellowships - Grant ID: IL230100175
Funder
Australian Research Council
Funding Amount
$3,763,434.00
Summary
Combatting wildlife crime and preventing environmental harm. Wildlife crime is one of the greatest threats to environmental and human security across the globe. In Australia, the illegal harvesting, killing, and trade of wild animals and plants endangers the country’s unique biodiversity and poses serious biosecurity risks to natural and agricultural systems. This Fellowship will deliver the intelligence tools and technologies, in wildlife forensics and cyber security, that are required for step ....Combatting wildlife crime and preventing environmental harm. Wildlife crime is one of the greatest threats to environmental and human security across the globe. In Australia, the illegal harvesting, killing, and trade of wild animals and plants endangers the country’s unique biodiversity and poses serious biosecurity risks to natural and agricultural systems. This Fellowship will deliver the intelligence tools and technologies, in wildlife forensics and cyber security, that are required for step-change reductions in wildlife crime in Australia, and Asia-Pacific. The project will establish new approaches for raising public awareness of the dangers of wildlife crime and provide much needed stewardship to protect Australia’s environmental assets and natural capital from current and future threats.Read moreRead less
A robust integrated streamflow forecasting framework for Australian water information and management agencies. This project aims to deliver an accurate and reliable seasonal streamflow forecasting system for Australian water users by developing a flexible rainfall-runoff modelling approach integrated into a Bayesian inference and prediction framework. These scientific developments aim to significantly advance the operational capabilities of the Australian Bureau of Meteorology to deliver robust ....A robust integrated streamflow forecasting framework for Australian water information and management agencies. This project aims to deliver an accurate and reliable seasonal streamflow forecasting system for Australian water users by developing a flexible rainfall-runoff modelling approach integrated into a Bayesian inference and prediction framework. These scientific developments aim to significantly advance the operational capabilities of the Australian Bureau of Meteorology to deliver robust streamflow forecasts to water agencies such as South East Queensland Water and others across Australia. Accurate predictions of future water flows are of tremendous value to urban and rural Australian communities whose economic prosperity, water security and social well-being depend on reliable estimates of water availability.Read moreRead less
Delivering robust hydrological predictions for Australia’s water challenges. This project aims to build a virtual hydrological laboratory to identify the best hydrological models that maximise predictive performance in a range of catchments, accounting for their dominant hydrological processes and data availability. New process-informed hydrological model structures will be developed using this virtual laboratory to embody our best understanding of hydrological processes and data from real catch ....Delivering robust hydrological predictions for Australia’s water challenges. This project aims to build a virtual hydrological laboratory to identify the best hydrological models that maximise predictive performance in a range of catchments, accounting for their dominant hydrological processes and data availability. New process-informed hydrological model structures will be developed using this virtual laboratory to embody our best understanding of hydrological processes and data from real catchments. The expected outcomes include major improvements in hydrological predictions for Australian catchments. This project will provide major benefits to irrigators, water authorities and engineers, who rely on hydrological predictions for sustainable water management in the highly-variable, semi-arid Australian climate.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE150100047
Funder
Australian Research Council
Funding Amount
$540,000.00
Summary
A multi-frequency microwave radiometer system for environmental research. A multi-frequency microwave radiometer system for environmental research: A new capability for airborne remote sensing of key environmental variables will be established. The unique P-, Ku- and Ka-band passive microwave radiometer system will provide information on soil moisture, surface temperature and vegetation, and allow for a new satellite concept to be demonstrated. By combining with an existing L-band radiometer, da ....A multi-frequency microwave radiometer system for environmental research. A multi-frequency microwave radiometer system for environmental research: A new capability for airborne remote sensing of key environmental variables will be established. The unique P-, Ku- and Ka-band passive microwave radiometer system will provide information on soil moisture, surface temperature and vegetation, and allow for a new satellite concept to be demonstrated. By combining with an existing L-band radiometer, data can be collected simultaneously at P-, L-, Ku- and Ka-bands, with increased spatial resolutions accordingly. The shorter wavelength, but higher spatial resolution data can be used to enhance the spatial resolution of the longer wavelength data, resulting in a capability to derive long wavelength observations from space at unprecedented spatial resolution.Read moreRead less
Robust streamflow predictions by improving the identification of hydrological model structure. This project aims to provide Australian environmental agencies, design engineers and policy-makers with robust methods that better utilise observed environmental data and process understanding to produce hydrological models with stronger scientific basis and improved operational predictive ability in gauged and ungauged catchments.
Stochastic modelling of fractures in crystalline rock masses for hot dry rock enhanced geothermal systems. Hot dry rock geothermal energy will contribute significant base-load power to the nation without producing greenhouse gas emissions. This research will contribute to the optimal design of fracture generation programmes to create effective artificial reservoirs in geothermal systems, which is crucial to successful geothermal energy production.
Groundwater flow age distributions: Understanding open pit mine hydrology. This project aims to improve the estimation of the age of groundwater. Understanding groundwater age is critical for sustainable management and environmental tracers are increasingly used for this purpose. However, groundwater samples are inevitably mixtures of water of different ages. Since for most tracers the relationship between tracer concentration and age is not linear, different tracers can produce different mean a ....Groundwater flow age distributions: Understanding open pit mine hydrology. This project aims to improve the estimation of the age of groundwater. Understanding groundwater age is critical for sustainable management and environmental tracers are increasingly used for this purpose. However, groundwater samples are inevitably mixtures of water of different ages. Since for most tracers the relationship between tracer concentration and age is not linear, different tracers can produce different mean ages for the sample. This project aims to determine whether it is possible to determine moments of the groundwater age distributions from measurements made with different environmental tracers. The project also aims to examine whether the degree of heterogeneity within the aquifer can be determined from the disparity between ages obtained with different tracers. This project aims to tackle the largest problem with using groundwater chemistry to estimate water age – that mixing processes in the subsurface are never known. Solving this problem will allow much more accurate estimates of groundwater velocity and aquifer recharge rates. The groundwater industry contributes an estimated $6.8 billion per annum to the Australian economy, and this project will contribute to the sustainable management of the groundwater resource.Read moreRead less
East Australian climate extremes through the Holocene. The project aims to document climate variability in eastern Australia over the Holocene, the last 11,500 years. It seeks to develop Australia’s two highest-resolution Holocene climate records using novel techniques to infer past rainfall, temperature and evaporation. The project will combine the expertise of international drought and climate specialists with novel techniques developed by the Australian investigators to derive an unparalleled ....East Australian climate extremes through the Holocene. The project aims to document climate variability in eastern Australia over the Holocene, the last 11,500 years. It seeks to develop Australia’s two highest-resolution Holocene climate records using novel techniques to infer past rainfall, temperature and evaporation. The project will combine the expertise of international drought and climate specialists with novel techniques developed by the Australian investigators to derive an unparalleled record of drought duration, frequency and intensity. In particular, the project aims to determine the frequency, duration and causes of mega-droughts in eastern Australia, of which little is known. Expected project outcomes include improved decision making capacity for natural resource management, and planning.Read moreRead less
A Machine Learning driven flow modelling of fragmented rocks in cave mining. The project aims to develop an integrated method that uses micro scale and macro scale information to predict block scale behaviour so that a better cave mining design can be established. The role of various mineral composition on the energy storage and fracture properties of rocks will be investigated to examine rock fragmentation for block cave mining. Later Machine Learning based models will be developed to establis ....A Machine Learning driven flow modelling of fragmented rocks in cave mining. The project aims to develop an integrated method that uses micro scale and macro scale information to predict block scale behaviour so that a better cave mining design can be established. The role of various mineral composition on the energy storage and fracture properties of rocks will be investigated to examine rock fragmentation for block cave mining. Later Machine Learning based models will be developed to establish various predictive models for Block Scale rock mass behaviour and caveability of ore deposit. Finally, we will develop a new constitutive model based on a dual damage concept that will capture the rock fragmentation and simulate the cave propagation in a large scale mine layout using Smoothed-particle hydrodynamics.Read moreRead less