Water resource management of the Snowy Mountains Hydro-electric Scheme catchment and the Murray-Darling River system - a new perspective on system reliability from drought history reconstruction. The Snowy Mountains Hydro-electric Scheme assists in underwriting the production of $3 billion of agricultural products in the Murray-Darling Basin each year by providing a reliable source of water west of the Great Dividing Range, while Hydro-electric generation from the Scheme is worth annually severa ....Water resource management of the Snowy Mountains Hydro-electric Scheme catchment and the Murray-Darling River system - a new perspective on system reliability from drought history reconstruction. The Snowy Mountains Hydro-electric Scheme assists in underwriting the production of $3 billion of agricultural products in the Murray-Darling Basin each year by providing a reliable source of water west of the Great Dividing Range, while Hydro-electric generation from the Scheme is worth annually several hundred million dollars and provides 70% of the renewable energy supplied to the eastern mainland grid, thereby avoiding 5Mt of carbon dioxide emissions each year. This study will ensure the ongoing sustainable and efficient management of the Schemes water resources in response to predicted climate variability and most importantly, severe drought. Read moreRead less
Optimal Source Control in Urban Water Cycle Management. Major opportunities exist to improve the management of the urban water cycle by better use of source control technology such as the use of rainwater tanks and water-sensitive design. This program will optimise the use of this technology at three scales, allotment, subdivision and regional, using genetic algorithms, parallel computing and shadow pricing. The aim is to minimise community lifecycle costs subject to sustainable use of ecosystem ....Optimal Source Control in Urban Water Cycle Management. Major opportunities exist to improve the management of the urban water cycle by better use of source control technology such as the use of rainwater tanks and water-sensitive design. This program will optimise the use of this technology at three scales, allotment, subdivision and regional, using genetic algorithms, parallel computing and shadow pricing. The aim is to minimise community lifecycle costs subject to sustainable use of ecosystems and maintenance of public health standards. The benefits include national savings of the order of $2 billion and significantly reduced demand on water supply and stormwater infrastructure and its supporting ecosystems.Read moreRead less
Reengineering a dynamic vegetation model to explore the stability of Australian terrestrial carbon. Overseas models do not represent Australian biophysical processes well: our flora and fauna are unique and our soils are old and nutrient poor. In contrast, the National Carbon Accounting System (NCAS) is a world-class framework for estimating current carbon processes. By building NCAS expertise into an overseas model of soil and vegetation processes we can develop the capacity to increase our con ....Reengineering a dynamic vegetation model to explore the stability of Australian terrestrial carbon. Overseas models do not represent Australian biophysical processes well: our flora and fauna are unique and our soils are old and nutrient poor. In contrast, the National Carbon Accounting System (NCAS) is a world-class framework for estimating current carbon processes. By building NCAS expertise into an overseas model of soil and vegetation processes we can develop the capacity to increase our confidence in future projections of carbon and vegetation change. Our proposal, linking Universities, CSIRO and the Australian Greenhouse Office establishes a team that is internationally competitive. It will enhance local expertise and local model development to ensure national policy development is underpinned by world-class science.Read moreRead less
Reconstructing pre-20th century rainfall, temperature and pressure for south-eastern Australia using palaeoclimate, documentary and early weather station data. South-eastern Australia is in the grip of a severe water crisis due to the worst drought in recorded history and increasing temperatures. This landmark project brings together a team of Australia's leading climate scientists, water managers and historians with the common goal of reconstructing south-eastern Australia's climate history. Th ....Reconstructing pre-20th century rainfall, temperature and pressure for south-eastern Australia using palaeoclimate, documentary and early weather station data. South-eastern Australia is in the grip of a severe water crisis due to the worst drought in recorded history and increasing temperatures. This landmark project brings together a team of Australia's leading climate scientists, water managers and historians with the common goal of reconstructing south-eastern Australia's climate history. The greatly extended record of annual rainfall and temperature variability will allow better planning for water storage and use, and improved testing of climate model simulations. Improving our understanding of the historical impacts of climate extremes on society will assist with planning for life in a hotter and drier future.Read moreRead less
Derivation of long-term hydroclimatic sequences for water resources engineering, management and planning. This project aims to develop in-situ reconstructions of flood and drought occurrence in the Sydney Warragamba catchment. The unique approach will utilise two complementary methods to provide robust insights into historic variability at the location of interest. The derived sequences will be used to augment the instrumental record, the sole basis for current drought risk assessment. A key out ....Derivation of long-term hydroclimatic sequences for water resources engineering, management and planning. This project aims to develop in-situ reconstructions of flood and drought occurrence in the Sydney Warragamba catchment. The unique approach will utilise two complementary methods to provide robust insights into historic variability at the location of interest. The derived sequences will be used to augment the instrumental record, the sole basis for current drought risk assessment. A key outcome will be an accurate appreciation of long-term drought occurrence. This will also provide a stronger basis for utilising climate information in guiding day-to-day reservoir and water supply management. The proxy histories are of key importance in estimating future flood and drought risk assessments for water resources management and planning.Read moreRead less
Using Advances in Bayesian Statistics to Estimate Australian Rainfall Variations in a Climate Change World. Modelling changes to rainfall patterns answers many important questions about changes in Australia's climate. This is essential to protecting our biodiversity and ensuring Australia's environmental sustainability. The project will address such issues as the extent to which the entire distribution of daily rainfall has changed over time, which areas of Australia have been most affected by t ....Using Advances in Bayesian Statistics to Estimate Australian Rainfall Variations in a Climate Change World. Modelling changes to rainfall patterns answers many important questions about changes in Australia's climate. This is essential to protecting our biodiversity and ensuring Australia's environmental sustainability. The project will address such issues as the extent to which the entire distribution of daily rainfall has changed over time, which areas of Australia have been most affected by this change and to what extent are these changes related to global climate indices. The latest advances in Bayesian statistics will be used to introduce flexibility and complexity into the model.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
A Bayesian Hierarchical Approach for Simulating Multi-time Scale Hydrological Variability for Water Resource Planning. Assessments of future drought risks are dependent on simulations of hydrological inputs provided by stochastic models. The current models are limited to simulating variability at a single time scale using only local observed hydrological data. This data has only limited information on the long-term climate variability which is the cause of long-term severe droughts. The proposed ....A Bayesian Hierarchical Approach for Simulating Multi-time Scale Hydrological Variability for Water Resource Planning. Assessments of future drought risks are dependent on simulations of hydrological inputs provided by stochastic models. The current models are limited to simulating variability at a single time scale using only local observed hydrological data. This data has only limited information on the long-term climate variability which is the cause of long-term severe droughts. The proposed research will develop a new Bayesian framework for simulating multi-time scale variability in hydrological data. This will enable the dynamic processes which simulate long-term variability to be identified using auxiliary information in an uncertainty framework. This will provide water resource planners with more accurate assessments of long-term drought risks.
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