As regional drought conditions continue deteriorating around the world, residential water use has been brought into the built environment spotlight. Nevertheless, the understanding of water use behavior in residential buildings is still limited. This paper presents data analytics and results from monitoring data of daily water use (DWU) in 50 single-family homes in Texas, USA. The results show the typical frequency distribution curve of the DWU per household and indicate personal income, education level and energy use of appliances all have statistically significant effects on the DWU per capita. Analysis of the water-intensive use demonstrates the residents tend to use more water in post-vacation days. These results help generate awareness of water use behavior in homes. Ultimately, this research could support policy makers to establish a water use baseline and inform water conservation programs.
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Abdallah AM, Rosenberg DE (2012). Heterogeneous residential water and energy linkages and implications for conservation and management. Journal of Water Resources Planning and Management, 140: 288–297.
Aquacraft (2015). Application of end use study data for development of residential demand models. Available at http://www.aquacraft.com/wp-content/uploads/2015/09/Residential-Models.pdf.
Balling RC, Gober P, Jones N (2008). Sensitivity of residential water consumption to variations in climate: An intraurban analysis of Phoenix, Arizona. Water Resources Research, 44: W10401.
Breyer B, Chang H, Parandvash GH (2012). Land-use, temperature, and single-family residential water use patterns in Portland, Oregon and Phoenix, Arizona. Applied Geography, 35: 142–151.
Bullock DC, Peebles RW, Smith HH (1980). Water usage patterns in the U.S. Virgin Islands. Water Resources Research Center, Caribbean Research Institute, College of the Virgin Islands.
Campbell HE, Johnson RM, Larson EH (2004). Prices, devices, people, or rules: The relative effectiveness of policy instruments in water conservation. Review of Policy Research, 21: 637–662.
Cardell-Oliver R, Wang J, Gigney H (2016). Smart meter analytics to pinpoint opportunities for reducing household water use. Journal of Water Resources Planning and Management, 142(6): 04016007.
Chang H, Parandvash GH, Shandas V (2010). Spatial variations of single-family residential water consumption in Portland, Oregon. Urban geography, 31: 953–972.
Chu J, Wang C, Chen J, Wang H (2009). Agent-based residential water use behavior simulation and policy implications: A case-study in Beijing City. Water Resources Management, 23: 3267–3295.
Cominola A, Giuliani M, Piga D, Castelletti A, Rizzoli AE (2015). Benefits and challenges of using smart meters for advancing residential water demand modeling and management: A review. Environmental Modelling & Software, 72: 198–214.
Corral-Verdugo V, Bechtel RB, Fraijo-Sing B (2003). Environmental beliefs and water conservation: An empirical study. Journal of Environmental Psychology, 23: 247–257.
Cosgrove WJ, Rijsberman FR (2000). World Water Vision: Making Water Everybody’s Business. London: Earthscan Publications.
DeOreo WB, Heaney JP, Mayer PW (1996). Flow trace analysis to assess water use. Journal—American Water Works Association, 88(1): 79–90.
DeOreo WB, Mayer PW (1994). Project report: A process approach for measuring residential water use and assessing conservation effectiveness. City of Boulder Office of Water Conservation, Boulder, CO, USA.
DeOreo WB, Mayer PW, Martien L, et al. (2011). California singlefamily water use efficiency study. Aquacraft Water Engineering and Management, Boulder, CO, USA. Available at http://water.cityofdavis.org/Media/PublicWorks/Documents/PDF/PW/Water/Documents/California-Single-Family-Home-Water-Use-Efficiency-Study-20110420.pdf
Dong B, Li Z, Mcfadden G (2015). An investigation on energy-related occupancy behavior for low-income residential buildings. Science and Technology for the Built Environment, 21: 892–901.
Fox C, McIntosh BS, Jeffrey P (2009). Classifying households for water demand forecasting using physical property characteristics. Land Use Policy, 26: 558–568.
Grafton RQ, Ward MB, To H, Kompas T (2011). Determinants of residential water consumption: Evidence and analysis from a 10- country household survey. Water Resources Research, 47: W08537.
Harlan SL, Yabiku ST, Larsen L, Brazel AJ (2009). Household water consumption in an arid city: Affluence, affordance, and attitudes. Society and Natural Resources, 22: 691–709.
Heberger M, Cooley H, Gleick P (2014). Urban water conservation and efficiency potential in California. Available at http://www.nrdc.org/water/files/ca-water-supply-solutions-urban-IB.pdf
Hong T, Taylor-Lange SC, D’Oca S, Yan D, Corgnati SP (2016). Advances in research and applications of energy-related occupant behavior in buildings. Energy and Buildings, 116: 694–702.
House-Peters LA, Chang H (2011). Urban water demand modeling: Review of concepts, methods, and organizing principles. Water Resources Research, 47: W05401.
Inman D, Jeffrey P (2006). A review of residential water conservation tool performance and influences on implementation effectiveness. Urban Water Journal, 3: 127–143.
Kenney DS, Goemans C, Klein R, Lowrey J, Reidy K (2008). Residential water demand management: Lessons from Aurora, Colorado. Journal of the American Water Resources Association, 44: 192–207.
Kontokosta CE, Jain RK (2015). Modeling the determinants of largescale building water use: Implications for data-driven urban sustainability policy. Sustainable Cities and Society, 18: 44–55.
Lutz J (2012). Hot water draw patterns in single-family houses: findings from field studies. Lawrence Berkeley National Laboratory, LBNL Paper LBNL-4830E. Available at http://escholarship.org/uc/item/2k24v1kj.
Malinowski PA, Stillwell AS, Wu JS, Schwarz PM (2015). Energy-water nexus: Potential energy savings and implications for sustainable integrated water management in urban areas from rainwater harvesting and gray-water reuse. Journal of Water Resources Planning and Management, 141(12): A4015003.
Maupin MA, Kenny JF, Hutson SS, Lovelace JK, Barber NL, Linsey KS (2014). Estimated use of water in the United States in 2010. Reston, VA, USA: U.S. Geological Survey.
Mayer PW (2009). Water efficiency benchmarks for new single-family homes. Aquacraft Water Engineering and Management, Boulder, CO, USA. Available at http://www.watersmartinnovations.com/documents/pdf/2009/sessions/T-1009.pdf
Mayer PW, DeOreo WB, Opitz EM, et al. (1999). Residential end uses of water. AWWA Research Foundation and American Water Works Association, Denver, CO, USA.
Mazzanti M, Montini A (2006). The determinants of residential water demand: Empirical evidence for a panel of Italian municipalities. Applied Economics Letters, 13: 107–111.
Ouyang Y, Wentz EA, Ruddell BL, Harlan SL (2013). A multi-scale analysis of single-family residential water use in the Phoenix metropolitan area. Journal of the American Water Resources Association, 50: 448–467.
Papakostas KT, Papageorgiou NE, Sotiropoulos BA (1995). Residential hot water use patterns in Greece. Solar Energy, 54: 369–374.
Polebitski AS, Palmer RN, Waddell P (2011). Evaluating water demands under climate change and transitions in the urban environment. Journal of Water Resources Planning and Management, 137: 249–257.
Praskievicz S, Chang H (2009). Identifying the relationships between urban water consumption and weather variables in Seoul, Korea. Physical Geography, 30: 324–337.
Richter CP (2010). Automatic dishwashers: Efficient machines or less efficient consumer habits? International Journal of Consumer Studies, 34: 228–234.
Rosenberg DE, Madani K (2014). Water resources systems analysis: A bright past and a challenging but promising future. Journal of Water Resources Planning and Management, 140: 407–409.
Sanders R (1987). The Pareto principle: Its use and abuse. Journal of Services Marketing, 1(2): 37–40.
Schleich J, Hillenbrand T (2009). Determinants of residential water demand in Germany. Ecological Economics, 68: 1756–1769.
Suero FJ, Mayer PW, Rosenberg DE (2012). Estimating and verifying United States households’ potential to conserve water. Journal of Water Resources Planning and Management, 138: 299–306.
Tinker A, Bame S, Burt R, Speed M (2005). Impact of “non-behavioral fixed effects” on water use: Weather and economic construction differences on residential water use in Austin, Texas. Electronic Green Journal, 1(22). Available at http://escholarship.org/uc/item/7rh33286.
USGS (2015). State drought information. U.S. Geological Survey, U.S. Department of the Interior. Available at http://waterwatch.usgs.gov/index.php?r=us&m=dryw.
Wentz EA, Wills AJ, Kim WK, Myint SW, Gober P, Balling Jr RC (2014). Factors influencing water consumption in multifamily housing in Tempe, Arizona. The Professional Geographer, 66: 501–510.
WHO, UNICEF (2015). Progress on sanitation and drinking water: 2015 update and MDG assessment. World Health Organization. Available at http://apps.who.int/iris/bitstream/10665/177752/1/9789241509145_eng.pdf?ua=1.
Willis RM, Stewart RA, Panuwatwanich K, Jones S, Kyriakides A (2010). Alarming visual display monitors affecting shower end use water and energy conservation in Australian residential households. Resources, Conservation and Recycling, 54: 1117–1127.
Yan D, O’Brien W, Hong T, Feng X, Gunay BH, Tahmasebi F, Mahdavi A (2015). Occupant behavior modeling for building performance simulation: Current state and future challenges. Energy and Buildings, 107: 264–278.
Zar JH (1972). Significance testing of the Spearman rank correlation coefficient. Journal of the American Statistical Association, 67: 578–580.
Zhang HH, Brown DF (2005). Understanding urban residential water use in Beijing and Tianjin, China. Habitat International, 29: 469–491.
This work is supported by the Assistant Secretary for Energy Efficiency and Renewable Energy of the U.S. Department of Energy under contract number DE-AC02-05CH11231. It is also part of the research activities of International Energy Agency Energy in Buildings and Communities Program Annex 66, definition and simulation of occupant behavior in buildings. The source data were provided by Pecan Street, Inc. (http://www.pecanstreet.org/), headquartered in Austin, TX. The authors thank this nonprofit research institute for allowing us access to their subscriber water usage database.
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Xue, P., Hong, T., Dong, B. et al. A preliminary investigation of water usage behavior in single-family homes. Build. Simul. 10, 949–962 (2017). https://doi.org/10.1007/s12273-017-0387-7
- water usage behavior
- daily water use
- data analytics
- occupant behavior
- residential water consumption