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    Effectiveness of smart-meter based consumption feedback in curbing household water use: Knowns and unknowns

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    This is the author accepted manuscript. The final version is available from the American Society of Civil Engineers via the DOI in this record.Adaptive approaches are required to counteract the mounting threats to water security. Demand management will feature centrally in such adaptation. The increase in use of smart meter technology offers an improved way for utilities to gauge consumer demand and to supply consumers with consumption feedback in (near) real-time. Such feedback can decrease the discrepancies between perceived and actual water usage. In contrast to the energy sector, however, where the advantages associated with smart meter consumption feedback are extensively documented, few studies have focused on the usefulness of such feedback when it comes to managing water consumption. This review assesses the evidence base for the effectiveness of water usage feedback technology in encouraging water conservation. The review highlights the potential value of high-granular smart-meter feedback technology in managing domestic water consumption. Findings from the papers included in this review (N = 21) indicate that feedback was associated with decreases of between 2.5% and 28.6% in water use, with an average of 12.15% (SD = 8.75). A single paper reported a 16% increase in consumption associated with smart-meter feedback. The benefits for water utilities are highlighted, but the costs for utilities need to be considered further. Overall, more work is needed to conclusively pinpoint the most effective type of feedback in terms of information content and granularity, frequency of delivery and medium, and how water consumption is linked to energy consumption. This information is needed to make concrete recommendations to the water industry about the costs and benefits of investment in smart metering and consumer feedback.This research received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under the iWIDGET project, grant agreement no. 318272. An earlier version of this paper was published in the conference proceedings of the 2014 Water Distribution Systems Analysis Conference (Sonderlund et al., 2014, Procedia Engineering, 89, 990-997)
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