Intelligent Water Decisions
The Intelligent Water Decisions group develops tools, technology and insights to help society better manage its most precious resource—water.
Our researchers solve problems relating to the design, operation, monitoring and management of water supply and treatment processes and facilities, in all contexts—urban, industrial and agricultural. Our research is used throughout Australia and worldwide by government water and environmental agencies, water utilities and consultancies, and other research organisations.
The Intelligent Water Decisions group’s particular research focuses include:
- short- and long-term catchment forecasting
- holistic decision-making approaches (including Bayesian), incorporating risk, deep uncertainty, and climate-driven compound events’ impact
- optimising ‘smart’ water distribution system infrastructure, including its design, operation, monitoring and maintenance.
Our research and development has delivered many real-world benefits. For example, it has contributed to:
- water supply and sewerage system optimisation tools, estimated to have saved water utilities and their customers hundreds of millions of dollars worldwide
- sophisticated non-invasive pipe condition assessment tools (p-CATTM), now commercialised by Sydney-based Detection Services
- improved seasonal streamflow forecasts for the Australian Bureau of Meteorology, through software and modelling tools
- the Australian Rainfall and Runoff national guideline document, data and software suite, the de facto standard for hydrological engineering in Australia
- decision-support systems, used to assess policy and planning options for natural hazard mitigation
- the recovery of South Australian riverine areas
- SA Water’s Smart Water Network monitoring and analysis program, preventing water main bursts in Adelaide’s central business district
- planning and optimisation for SA Water's hydropower facilities
- smart-water-meter analytics, enhancing short- and long-term demand prediction through better understanding water-use drivers.
We have expertise across a wide range of areas. Many of our researchers are available to assist with research project supervision for Master of Philosophy and Doctor of Philosophy students.
Research team Expertise Professor Michael Goodsite Professor Martin Lambert Professor Holger Maier Machine learning; Optimisation; Decision support Professor Angus Simpson Hydraulic modelling and optimisation of water networks; Smart water network asset investigation by transient analysis; Hydrological rainfall/runoff modelling Professor Dmitri Kavetski Hydrological modelling; Uncertainty analysis; Optimisation Associate Professor Seth Westra Hydrology; Water resources; Climate risk Associate Professor Mark Thyer Catchment modelling; Risk and uncertainty; Smart water Dr Aaron Zecchin Hydraulic transient analysis; Evolutionary computational strategies; Smart water networks Dr Michael Leonard Environmental modelling; Risk assessment; Extremes Emeritus Professor Graeme Dandy Water resources management; Optimisation; Artificial intelligence techniques Honorary Visiting Research Fellow Trevor Daniell Hydrology; Floods; Droughts Adjunct Associate Professor Hedwig van Delden Dr Bree Benett Dr Matthew Gibbs Dr David McInerney Graeme Riddell
We collaborate with various industry and government organisations, including:
- 3S Consult (Germany)
- Australian Bureau of Meteorology
- Australian Energy and Water Exchanges initiative
- Australian Water Association
- BMT WBM
- Bushfire and Natural Hazards CRC
- Detection Services
- Geoscience Australia
- Hydrology and Risk Consulting (HARC)
- International Centre of Excellence in Water Resources Management (ICEWaRM)
- Melbourne Water
- Murray-Darling Basin Authority
- National Committee on Water Engineers from Engineers Australia
- Natural Resources Management boards
- SA Department of Environment and Water
- SA Water
- Stormwater Management Associations
- Sydney Water
- WA Water Corporation
- Water Industry Alliance
- Water Research Australia
We advise on, and lead, projects relating to:
- flood and drought risk
- climate change impacts
- water distribution system operation and maintenance
- catchment modelling and prediction
- non-invasive pipe condition assessment using fluid transients.
Neural Network Excel Add-in
We have been researching the use of artificial neural networks (ANNs) for water resources modelling applications, such as flow forecasting, water quality forecasting and water treatment process modelling. A generic framework for the development of ANN models for water resources applications is outlined below.
User-friendly software has been created to allow users to apply several ANN model development techniques that have been developed through this research. The software is an add-in for Microsoft Excel® that implements the main steps in ANN model development, from data pre-processing, through to ANN training and validation; all within the Excel application environment.
The core of the software has been developed in C++, so that the software combines fast computation with the ease and convenience of pre- and post- analysis of data within an Excel workbook.