Simon Fane

Simon Fane

Simon Fane, Australia.

Simon has nearly 20 years of experience in urban water. He is an expert in supply-demand planning, sustainable water management and options assessment with his PhD addressing these topics.
Simon has provided technical and policy advice to Commonwealth, State and Local Governments and water utilities across Australia. For the last five years Simon has been working for the NSW Government’s Metropolitan Water Directorate on the Metropolitan water Plan for Greater Sydney and related projects.
Prior to join the NSW Government, Simon was a Research Director at the Institute for Sustainable Futures, which is part of the University of Technology Sydney. At the Institute Simon led the urban water research area and managed a range of research and consulting projects.

Presentation Title:Assessing the impacts on supply; optimisation modelling, economic analysis and community engagement to support a decision for new environmental flows in Sydney.

The Metropolitan Water Plan is the NSW Government’s plan to ensure sufficient water to meet the needs of the people and environment of Greater Sydney. It was first developed in 2004 and the recent 2017 Plan is the fourth iteration. The 2017 Metropolitan Water Plan includes a decision to release variable environmental flows (e-flows) from Warragamba Dam; which is by far the largest dam in Sydney’s supply system and provides more than 80% of the city’s drinking water.  In the early 2000s the Hawkesbury-Nepean River Management Forum recommended the release of e-flows from all major storages on the River. By 2009 variable e-flows were occurring at all dams expect Warragamba Dam. A decision on e-flows from Warragamba Dam was deferred until both the benefits and the impacts on water supply where fully assessed. A hydro-economic model, Metronet, was developed that allowed automated optimization of Sydney’s water supply portfolio. A range of costs, including from a choice modelling study of households’ willingness to pay to avoid water restrictions, were included in the model. The optimization identified minimum expected cost portfolios (comprising a mix of operating and infrastructure options) for a range of e-flows scenarios at each given demand. By varying the demand, from current to levels that could occur decades into the future, it was possible to develop a picture of how the supply system might need to evolve for each e-flow scenario.The outputs of optimization modelling were included in economic analyses for each e-flow scenario. As all portfolios were optimized the approach minimized the cost impact of e-flows on supply into the future. Community consultation confirmed the trade-offs demonstrated in the economic analyses; the introduction of e-flows was seen to be worth a marginal increase in water bills and slightly more regular water restrictions.

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