Representing low-frequency variability in hydro-climatic simulations for water resources planning and management in a changing climate. Simulating local hydro-climatology under likely climate change allows risk assessment of existing and future water infrastructure, along with the planning protocols needed to adapt to the changes ahead. This study aims to develop the tools needed to simulate local hydro-climatology, providing a basis for securing water for the generations to come.
Impact of reforestation on the mitigation of climate extremes in eastern Australia resulting from global warming. This project will provide new information for climate change policy development and the goal of an Environmentally Sustainable Australia. It has a strong policy-management imperative, investigating the need for the maintenance and restoration of healthy native vegetation cover as part of Australia’s climate change mitigation and adaptation strategies. Our previous research has shown ....Impact of reforestation on the mitigation of climate extremes in eastern Australia resulting from global warming. This project will provide new information for climate change policy development and the goal of an Environmentally Sustainable Australia. It has a strong policy-management imperative, investigating the need for the maintenance and restoration of healthy native vegetation cover as part of Australia’s climate change mitigation and adaptation strategies. Our previous research has shown that land clearing has contributed to climate change, including more severe and persisting droughts, in eastern Australia. Successful implementation of the research findings will lead to an increased ability of regional landscapes to buffer against a more extreme future climate driven by increased concentrations of greenhouse gases.Read moreRead less
Adaptive ecotyping of the toxic cyanobacterium Cylindrospermopsis raciborskii to predict its invasive capacity. We change the world while other organisms adapt to these new conditions. Cyanobacteria (blue green algae) increasingly dominate water bodies that were previously free of these harmful blooms. To minimise the spread of these algae, this project will study the genetic basis that determines how rapidly they can evolve and adapt to a changing planet.
Bad tastes, odours and toxins in our drinking water reservoirs: are benthic cyanobacteria the culprits? Cyanobacteria (blue-green algae) produce toxins and bad tastes that contaminate drinking water sources, cause public concern about water quality. This project will address a critical knowledge gap by investigating species that grow on the sediments of reservoirs, thus providing more comprehensive management solutions to the water industry.
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
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
The characterisation of wastewater distribution patterns for the production of decision support systems for pathogenic risk analysis in water catchments. The project will aim to collate data and map base-level distribution patterns of molecular and microbial markers of human sewage and natural/agricultural contamination with reference to diurnal and seasonal fluctuations. These data will then be used to develop decision support systems that predict contaminant dispersion and identify high-risk c ....The characterisation of wastewater distribution patterns for the production of decision support systems for pathogenic risk analysis in water catchments. The project will aim to collate data and map base-level distribution patterns of molecular and microbial markers of human sewage and natural/agricultural contamination with reference to diurnal and seasonal fluctuations. These data will then be used to develop decision support systems that predict contaminant dispersion and identify high-risk contamination sources. The diurnal collection of data is expected to show significant variations in the measured parameters associated with time of day, light intensity and temperature. Mapping of the sewage and nutrient loads throughout the year will provide base line data for identifying potential hotspots for targeting system upgrades or improved management programs.Read moreRead less
Understanding cultural and ecological triggers for policies against water catchment degradation. You cannot step into the same river twice. This project aims to understand the co-evolution of science, culture and management policy in water catchment for improving the predictability and preciseness of the water management policy.
A framework for model emulation and ensemble modelling. For improved water resource management there is a need for further development of appropriate hydrologic models. This project will undertake a collection of hydrologic modelling activities performed at multiple catchments in Australia. A modeling framework that is flexible, extendible and accounts for potential forecast uncertainties will be developed.
Better water management through more focus on ecological and social sciences. Current water resources management, focusing on gains of economic efficiency in the short term under the assumption of steady-state conditions, has generally failed to respond to both catchment environmental degradation and to the increasing complexity of human–environment interactions. This project will develop a new approach to water resources management by relating management practices based on ecological understand ....Better water management through more focus on ecological and social sciences. Current water resources management, focusing on gains of economic efficiency in the short term under the assumption of steady-state conditions, has generally failed to respond to both catchment environmental degradation and to the increasing complexity of human–environment interactions. This project will develop a new approach to water resources management by relating management practices based on ecological understanding to the social mechanisms behind these practices at water catchments. It will improve the predictability and precision of water resources management and increase our ability to maintain our options for a sustainable future. This will have a profound effect on catchment sustainability, a globally significant problem.Read moreRead less