RISER: resilient information systems for emergency response. This project will help to provide emergency managers, responders, and the general public in Australia with access to more timely and relevant information during an emergency. The project will improve the resilience of emergency information systems to the unplanned component failures and uncertain data sources that arise during a disaster.
From hazard identification to risk management. From hazard identification to risk management. This project aims to explore health risks from water- and sediment-borne bacteria to recreational users of urban rivers, using a suite of novel molecular microbiological and in-vitro assays and microbial risk assessment modelling. This project also aims to develop source tracking methods to mitigate and manage these risks. The number of bacterial-related water-borne outbreaks associated with recreationa ....From hazard identification to risk management. From hazard identification to risk management. This project aims to explore health risks from water- and sediment-borne bacteria to recreational users of urban rivers, using a suite of novel molecular microbiological and in-vitro assays and microbial risk assessment modelling. This project also aims to develop source tracking methods to mitigate and manage these risks. The number of bacterial-related water-borne outbreaks associated with recreational activities is rising, but waterway managers are under pressure to re-open these rivers for recreation. The project is expected to benefit urban communities by ensuring waterway managers make informed decisions about river recreation.Read moreRead less
Integrating satellite observations into environmental accounts. Accounting for biomass, water and ecosystem helps to manage and protect Australia's natural capital. Existing data provide only limited information, but this project will build on recent advances in satellite observation and model-data fusion technology to produce national accounts with unprecedented detail, for each year since 1990.
A new-generation flood forecasting system using observations from space. Floods are dangerous and expensive, costing Australia more than any other cause of natural disaster. This project will use satellite measurements of soil moisture and rainfall along with computer models to improve the Bureau of Meteorology’s predictions of floods in rivers. Better flood forecasts will reduce costs and save lives.
Revolutionising water-quality monitoring in the information age. In today’s information age, automated low-cost sensors distributed in the environment have the potential to revolutionise the way we monitor and manage air, water and soil. This project aims to develop novel statistical methods to detect anomalies in the data generated from these in-situ sensors with computationally efficient modelling on river networks through space and time, with the applied goals of automating anomaly detection ....Revolutionising water-quality monitoring in the information age. In today’s information age, automated low-cost sensors distributed in the environment have the potential to revolutionise the way we monitor and manage air, water and soil. This project aims to develop novel statistical methods to detect anomalies in the data generated from these in-situ sensors with computationally efficient modelling on river networks through space and time, with the applied goals of automating anomaly detection in water-quality data and generating predictions of sediment and nutrient concentrations throughout river networks in near-real time. This will represent a fundamental increase in scientific knowledge, which will be immediately useful in the domains of aquatic science, environmental monitoring, and statistics.Read moreRead less
Biodiversity indicators for better conservation decisions. This project aims to test, design and select biodiversity indicators to support conservation. Reliable and sensitive biodiversity indicators are critical to track progress towards conservation targets, but the ability of most biodiversity indicators to reveal trends needed by decision-makers is untested. This project will test indicators to monitor biodiversity change at local to global scales, by sampling ecosystem models to evaluate ho ....Biodiversity indicators for better conservation decisions. This project aims to test, design and select biodiversity indicators to support conservation. Reliable and sensitive biodiversity indicators are critical to track progress towards conservation targets, but the ability of most biodiversity indicators to reveal trends needed by decision-makers is untested. This project will test indicators to monitor biodiversity change at local to global scales, by sampling ecosystem models to evaluate how indicator design, data bias and environmental variability affect performance. Project outcomes are expected to ensure that that data collected to monitor and assess the state of Australia’s environment are informative, cost-effective and robust. This is expected to have implications for predicting and measuring effects of policy such as the Convention on Biological Diversity.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE130100040
Funder
Australian Research Council
Funding Amount
$450,000.00
Summary
Integrated Greenhouse Gas Measurement System (IGMS) for monitoring agricultural emissions at field to regional scales. Measurement of greenhouse gases is critical to Australia’s obligations to reduce carbon emissions. The measurement facility will provide urgently needed accurate emission data from Australian agriculture to establish emission baselines and develop methods to extend the point-scale measurements to whole farm, regional and national scales.
Predicting water quality at the catchment scale: learning from two decades of monitoring. Poor water quality affects many rivers and receiving waters such as the Great Barrier Reef and Gippsland Lakes. This project aims to use Bayesian hierarchical models of statewide water quality data to quantify the effects of a range of factors on stream water quality including climate, land use, river flow, vegetation cover, etcetera. The analysis intends to extract information from the entire data set rath ....Predicting water quality at the catchment scale: learning from two decades of monitoring. Poor water quality affects many rivers and receiving waters such as the Great Barrier Reef and Gippsland Lakes. This project aims to use Bayesian hierarchical models of statewide water quality data to quantify the effects of a range of factors on stream water quality including climate, land use, river flow, vegetation cover, etcetera. The analysis intends to extract information from the entire data set rather than concentrating on individual sites. It intends to underpin a new predictive capacity including response to land use and management changes and climatic variations based on long-term data sets, as well as a water quality prediction capability. It is intended that the models developed will jointly model a range of inter-related water quality parameters.Read moreRead less
Finding lost dust storms: re-evaluation of the last 20 years of meteorological records to advance wind erosion mapping in Australia. The Dust Event Database (DEDB) at Griffith University is the only long term (1960 - present) record of wind erosion in Australia. It is used in many studies of the impact of dust on the terrestrial, atmospheric and marine environments as well as in studies of urban and regional air pollution and environmental health. Through this project, the revision of the DEDB w ....Finding lost dust storms: re-evaluation of the last 20 years of meteorological records to advance wind erosion mapping in Australia. The Dust Event Database (DEDB) at Griffith University is the only long term (1960 - present) record of wind erosion in Australia. It is used in many studies of the impact of dust on the terrestrial, atmospheric and marine environments as well as in studies of urban and regional air pollution and environmental health. Through this project, the revision of the DEDB will provide new knowledge on these impacts of wind erosion processes and will inform environmental policy through its contributions to the Caring for Our Country Program, the national State of the Environment, and the Australian Centre for Rangeland Information Systems.Read moreRead less
Adaptive management of native vegetation condition. Environmental managers face severe uncertainty about how to best restore native habitats. This project will develop an adaptive strategy to improve vegetation management decisions by integrating expert knowledge with monitoring. This will improve the efficiency of management and provide an example of 'learning by doing' in two case study regions.