Temporal case study of household behavioural response to Cape Town's “Day Zero” using smart meter data

Abstract

Faced with the threat of "Day Zero", when it was feared that Cape Town's taps could run dry, consumers reduced household water usage from 540 to 280 litres per household per day over the 36 months between January 2015 and January 2018. This paper describes the events that prompted this reduction. We look at how changes in water use were affected by official announcements and by public engagement with this news via the social media activity and internet searches. We analysed the water usage of a subset of middle to high income households where smart hot and cold water meters were installed. For hot water usage patterns we compared meter readings with that in another area unaffected by the drought. We further map our cold water smart meter readings against that of the City of Cape Town's municipal data for domestic freestanding households-a sample of more than 400,000 households. We found that the introduction of Level 5 restrictions had a perverse effect on consumption, possibly due to confusing messages. The most dramatic change in behaviour appears to have been instigated by a media storm and consequent user panic after the release of the City's Critical Water Shortages Disaster Plan in October 2017. However, contradictory communication from national and provincial government eroded some of this gain. The paper concludes with recommendations for demand management in a similar future scenario.

Saving water at Cape Town schools by using smart metering and behavioural change

“…Findings have been similar in the water demand management literature, where usage feedback is usually either mail-based (Aitken et al, 1994;Brick et al, 2018;Datta et al, 2015;Ferraro et al, 2011;Ferraro and Price, 2013;Geller et al, 1983;Kurz et al, 2005), or provided by smart water meters (Booysen et al, 2019b;Erickson et al, 2012;Fielding et al, 2013;Liu et al, 2016;Petersen et al, 2007). Mail-based usage feedback is often provided through the existing utility bill infrastructure, thus minimising intervention costs (Sønderlund et al, 2014).…”

How much energy can optimal control of domestic water heating save?

“…If the residual warm water in the piping is at a lower temperature than the TC set point, the net losses will be significantly less: the average volume used per user was 142 L/day with an average of 7.5 events/day, which means as much as 10 % of usage would have resulted in usage losses. As an example of unintended use, we have anecdotal evidence of users of a smart EWH controller who became aware that their casual workers were unnecessarily washing cars or cleaning floors with hot water -behaviour that was quickly remedied (Roux and Booysen, 2017;Booysen et al, 2019). It may be argued that this control is essentially the same as setting the thermostat to a lower temperature, but the EM control does better than just supplying a lower temperature on occasion; it ensures that hot water is delivered when needed.…”

“…3 Energy-matched hot water used in situation with purported savings 4 Electrical energy savings split into reduced thermal losses and reduced alternative losses. (Roux et al, 2018;Booysen et al, 2019). We add an additional constraint to evaluate the energy impact of ensuring daily Legionella sterilisation in the energy-matched strategy, which operates at a lower temperature.…”

Fees and governance: Towards sustainability in water resources management at schools in post-apartheid South Africa

“…Since the schools are responsible for their own water bills, albeit indirectly in some cases, any money that is unnecessarily spent on water reduces the already constrained resources available for education-related expenses. A study by Ripunda and Booysen (2018) highlighted the severity of water wastages in the province's schools, by showing that a single primary school used as much as 35 kL per day, the equivalent of more than 100 households (Booysen et al, 2019b). The study further demonstrated that significant savings are possible through raising awareness and influencing water usage behaviour.…”

“…It is known that service providers and users require accurate and timely usage of information and billing to influence prudent user behaviour and to effectively predict and manage demand. Despite this need, municipalities in developing countries struggle to capture and report on water usage, often relying on estimates of water usage for the billing process (Booysen et al, 2019a;Booysen et al, 2019b;Parks et al, 2019). The result is that users often receive actual billing information two months or more after usage, resulting in undetected leaks and broken feedback information loops.…”