Profiling Residential Water Consumption

Abstract

Understanding the factors that influence daily and weekly water consumption patterns in distribution systems is fundamental for both long term tasks, such as planning, design, expansion or rehabilitation of the systems, and short term tasks, such as routine system operation or emergency management. This paper describes the development of a Portuguese nationwide program for characterizing residential water consumption, through the use of a specific consumption data analysis protocol and the build-up of a database of demand patterns; and for associating it with a range of easily obtained, potential relatable factors that include the technical features of the network (e.g., service pressure, network state and maintenance level, use of household tanks), billing and customer statistics and a range of socialdemographic variables, such as age, social-economic level and mobility of consumers, age and type of buildings, and economic activities. The program is currently being test-run on a set of 20 metering districts from 9 water utilities, comprising a variety of network types and demand characteristics across representative urban areas of Portugal. The metering districts range in size from 2,000 to 12,000 connected properties, and have mostly been monitored since 2005 (in some cases, 2004). Total consumption is continuously monitored during the main seasonal scenarios (typically winter and summer) in the areas selected. Standardized daily demand patterns and consumption statistics are produced for each day of the week, as well as for each season, in case there is seasonality in the area. Social-demographic information is based on statistics obtained from the 2001 National Census for the basic statistical units, which are around 300 dwellings in size. After the initial run, the program is to be disseminated and made accessible to all water utilities willing to participate, on a voluntary basis and with data anonymity. This will be done mostly through a dedicated website containing the consumption database, together with query and analysis tools, as well as a supervised mechanism to submit new cases in standard format. It is believed that the publication of the result database and its continued growth will provide the water industry designers, consultants and managers with much more reliable and updated data on water consumption than previously available. It will also represent a means to estimate demand through correlation and profiling, in cases when there are no records to work from. The paper discusses the demand analysis performed, as well as the development of the set of potential explanatory factors (technical features of the network and social-demographic variables), and illustrates with the results obtained so far.

Water: consumption, usage patterns, and residential infrastructure. A comparative analysis of three regions in the Lima metropolitan area

“…Various studies were reviewed to develop each section of the survey, identifying variables related to the features of the house and its residents, the cost of water, consumption habits (Ojeda-De la Cruz et al, 2016), (Rajala & Katko, 2004), and the sanitary equipment's frequency of use. The following were also considered: the time factor (in water use and household members), the household's density, and its socio-economic profile (Cubillo et al, 2008;Domene & Saurí, 2006;Gogiel, 2011;González et al, 2008;Grafton et al, 2011;Loureiro et al, 2006;Borg et al, 2013;Grafton et al, 2011;U.S. Geological Survey, 2004).…”

“…Some surveys we reviewed organized the collection of information by breaking down water use, understanding the associated psychological issues, and assessing user behaviour (Shan et al, 2015). It is also worth including the month in which the survey was conducted and comparing it with the annual consumption to detect variability in consumption (Loureiro et al, 2006).…”

“…In terms of those occupying the household, the population can be floating or resident (Sánchez García & Blanco Jiménez, 2012) and of different sex or age ranges (Shan et al, 2015). Also, consumption patterns relate to socio-demographic levels, and the amount consumed per person is similar in many cases, especially among wealthier people (Loureiro et al, 2006), enabling us to extrapolate values in similar districts.…”

Analyzing Building-level Water Consumption Patterns Before and After the Pandemic: A Campus Case

“…Models must be developed to find the diurnal and annual maximum water demand (Gargano et al, 2017). Understanding the factors that influence daily and weekly water consumption patterns in distribution systems is critical for both long-term and short-term tasks such as system planning, design, expansion, or rehabilitation, as well as routine system operation and emergency management (Loureiro et al, 2008). Below are some possible remedial measures for the above-mentioned issues.…”

Public Attitudes towards Digital Water Meters for Households

“…Tailored messaging approaches, therefore, preferably use a minimum amount of customer's information. Traditional segmentation profiles in the field of water and energy conservation derive most support from socioeconomic factors [15,[45][46][47][48][49]. Socioeconomic factors, such as income, culture, religion, gender or ethnicity, may pose unwanted biases and-perhaps more importantly-people's beliefs and attitudes could be more distinctive, and therefore, more meaningful as a segmentation strategy.…”