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.
Development of a generic catchment classification framework in hydrology. Hydrologic models play a vital role in water resource planning and management, but identification of a suitable model for a given catchment remains a basic problem. This research develops a generic framework to classify catchments into groups and sub-groups, and will offer a significantly better way for hydrologic model development and application.
Water availability and demand: better forecasts, better management. This project aims to improve Australia’s capability in the provision and use of water forecasts for managing water resources. The current water forecasts are not fully utilised by water agencies as they are not sufficiently comprehensive and advanced. This project expects to achieve a step change in the uptake and utility of hydro-climate forecasts through an extensive partnership of leading researchers and operational agencies ....Water availability and demand: better forecasts, better management. This project aims to improve Australia’s capability in the provision and use of water forecasts for managing water resources. The current water forecasts are not fully utilised by water agencies as they are not sufficiently comprehensive and advanced. This project expects to achieve a step change in the uptake and utility of hydro-climate forecasts through an extensive partnership of leading researchers and operational agencies of hydro-climate forecasting, with federal, state and regional water agencies.Read moreRead less
A decadal to inter-decadal streamflow prediction system. This project will develop the first ever decadal streamflow prediction system for Australia, leading to predictions of streamflow for the next 10 years and beyond that take into account both natural climatic variability (driven by factors such as the El Nino Southern Oscillation) and changing greenhouse gas concentrations due to a warming planet.
Uncertainty quantification in terrestrial hydrologic systems. This project aims to develop a framework to simulate, quantify and analyse the uncertainty in streamflow and vegetation dynamics via approximate Bayesian computation. Water is a fundamental resource, and a difficulty in water resource management is to make predictions in a changing environment. Uncertainties in predictions of natural systems due to observational and model error make this more difficult. It is anticipated that the resu ....Uncertainty quantification in terrestrial hydrologic systems. This project aims to develop a framework to simulate, quantify and analyse the uncertainty in streamflow and vegetation dynamics via approximate Bayesian computation. Water is a fundamental resource, and a difficulty in water resource management is to make predictions in a changing environment. Uncertainties in predictions of natural systems due to observational and model error make this more difficult. It is anticipated that the results from this project will advance uncertainty analysis in hydrology and help understand how different types of data and information can inform model characterisation. This will be useful in providing vital information on the attributes and extent of uncertainty to inform water resources analysis, management and decision making.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
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
Optimal trade-offs for managing environmental water in inland wetlands. This project aims to optimise long-term water trade-offs in inland wetlands on managed catchments, without compromising their environmental value. These managed wetlands compete for water allocations with irrigation and other uses. Realistic predictions of wetland status will be achieved through the development and integration of an ecohydrological model and a water management decisions model. Application of the tools will i ....Optimal trade-offs for managing environmental water in inland wetlands. This project aims to optimise long-term water trade-offs in inland wetlands on managed catchments, without compromising their environmental value. These managed wetlands compete for water allocations with irrigation and other uses. Realistic predictions of wetland status will be achieved through the development and integration of an ecohydrological model and a water management decisions model. Application of the tools will improve existing decision support models to help analyse the effects of individual local management decisions on the long-term evolution of the system and the effects of changes in operation policies and climate over the long term. The project will provide critical new information for the improved prediction of wetlands evolution and as a consequence better management.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.