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A promising way to address the growing demand for water supply and improve the liveability of cities is to invest in decentralised multifunctional urban water technologies. However, the adoption of multifunctional water technologies is a complex issue that requires cross-disciplinary approaches. This paper uses an agent-based model that integrates economic and environmental factors to explore and simulate the decision-making and interactions of two types of agents: a regulator and households. The model is applied to evaluate strategies to increase the adoption of rainwater tanks in a suburb of Melbourne, a city that has often suffered from severe droughts. The model was able to replicate the uptake of rainwater tanks by households for 2005–2014, the period known as the ‘Millennium Drought’. Results indicate that using economic instruments alone may have been insufficient to promote the adoption of rainwater tanks, and that water restrictions have had a major impact on the uptake. [ABSTRACT FROM AUTHOR]

A spatial model is presented, based on urban planning concepts for abstracting urban form characteristics in new and existing areas. Requiring input maps of land use, elevation, population and parameters from planning regulations, the model conceptualises (on a spatial grid) attributes including impervious fraction, allotment geometry and roof areas among other relevant characteristics for integrated urban water management. The model is calibrated to three different Melbourne districts, varying in size (10–60 km 2 ) and land use. Performance was evaluated by comparing modelled outputs with observations of total dwelling count, employment and spatial distribution of impervious fraction and residential roof areas. Results not only highlight reasonably good prediction, particularly with spatially variable indicators such as imperviousness across all case studies, but also logical contrasts and consistency in the chosen planning parameters across the different case study districts. Discrepancies highlight aspects needing improvement and potential for exploring auto-calibration and model sensitivity. [ABSTRACT FROM AUTHOR]