The University of Adelaide
Thyer_KeyDriversHouseholdWaterUse_AWAConference.pdf (818.44 kB)

Identifying Key Drivers of Household Water Use in South Australia: Practical Implications

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posted on 2016-07-05, 22:40 authored by Mark ThyerMark Thyer, Nicole Arbon, Darla Hatton McDonald, Martin Lambert
This study identified the key drivers of household water use in a South Australia. This was undertaken by analysis of a unique database of high resolution water use measurements and surveys on household demographics, behaviour and attitudes of a representative group of 150 households in metropolitan Adelaide. High resolution monitoring was undertaken between March 2013 to February 2014. Flow trace analysis determined the individual indoor end-uses (shower, toilets etc) for a two week period in winter 2013. Key drivers for indoor end use were: (1) High variability in end-uses between households and householders themselves do not provide reliable estimate of their own end-use proportions. Householders need more information to identify water saving opportunities (2) Water efficient appliance uptake is approx. 50% with further potential savings of 19L/p/day (15% of indoor). As efficient washing machines are the largest contributor increasing their uptake will enhance water savings. (3) Distinct households usage types (related to income/age/attitude – e.g. the “pensioner” effect) with different water usage patterns and water saving opportunities were identified. This requires a targeted approach for demand management. Analysis of drivers for seasonal water use  (40% of total household use) identified that it increased with increasing property area (+25%), decreased with decreasing income (-20%) and increased with increase age (+11%). Analysis of peak day demands showed a consistent pattern that a small proportion (20%) of households made large contribution (50%) to the total demand on peak demand days. This presents an opportunity to reduce water infrastructure costs by developing targeted strategies to reduce the peak. Predictive modelling illustrated the Behavioural End Use Stochastic Simulator (BESS) provided reliable predictions of end-uses using local end-use information. Using BESS predictions 50% of the water use reduction during the 2007-2009 drought was attributed to uptake of water efficient appliances. Using BESS predictions demand management (uptake of water efficient appliances) was estimated to reduce residential water use by 7% in the short-term, reducing to 4% in the longer term due to “demand hardening”.


Goyder Institute for Water Research