Chapter 2
Modeling Water Demands in Premise Plumbing Systems
Publication: Premise Plumbing Modeling
Abstract
Premise plumbing modeling entails the simulation and analysis of hydraulic and water quality conditions that exist throughout the piping network inside a building. These pipes deliver clean water to the occupants and carry wastewater away from the premises. The focus of this chapter is on the clean water component. A key aspect of the premise plumbing scenarios is modeling the stochastic water demand patterns. The chapter also focuses on indoor water use, excluding fire suppression systems. Instantaneous peak water demand is a key parameter for premise plumbing design, governing the size of service lines, flow meters, water heaters, treatment devices, pipe diameters, and other hydraulic appurtenances in the water supply system for the building. Software models (e.g., SIMDEUM) can simulate fixture-level water use on a very fine time scale (down to 1 s) based on typical occupant behavior in residential and commercial buildings.
Get full access to this article
View all available purchase options and get full access to this chapter.
References
Adamowski, J. F. 2008. “Peak daily water demand forecast modeling using artificial neural networks.” J. Water Resour. Plann. Manage. 134 (2): 119–128.
Agudelo-Vera, C. M., K. J. Keesman, A. R. Mels, and H. H. M. Rijnaarts. 2013. “Evaluating the potential of improving residential water balance at building scale.” Water Res. 47 (20): 7287–7299.
Alvisi, S., M. Franchini, and A. Marinelli. 2003. “A stochastic model for representing drinking water demand at residential level.” Water Resour. Manage. 17 (3): 197–222.
Alvisi S., M. Franchini, C. Luciani, I. Marzola, and F. Mazzoni. 2021. “Effects of the COVID-19 lockdown on water consumptions: Northern Italy case study.” J. Water Resour. Plann. Manage. 147 (11). https://doi.org/10.1061/(ASCE)WR.1943-5452.0001481.
Arbués, F., M. Á. Garcı´a-Valiñas, and R. Martı´nez-Espiñeira. 2003. “Estimation of residential water demand: A state-of-the-art review.” J. Socio-Econ. 32 (1): 81–102.
AWWA (American Water Works Association). 1975. Sizing water service lines and meters. 1st ed. Manual of Water Supply Practices, M22. Denver: AWWA.
AWWA. 2004. Sizing water service lines and meters. 2nd ed. Manual of Water Supply Practices, M22. Denver: AWWA.
AWWA. 2014. Sizing water service lines and meters. 3rd ed. Manual of Water Supply Practices, M22. Denver: AWWA.
Bailey, O., T. Arnot, E. Blokker, Z. Kapelan, et al. 2019. “Developing a stochastic sewer model to support sewer design under water conservation measures.” J. Hydrol. 573: 908–917.
Bailey, O., T. C. Arnot, E. J. M. Blokker, Z. Kapelan, et al. 2020. Predicting impacts of water conservation with a stochastic sewer model.” Water Sci. Technol. 80 (11): 2148–2157.
Beal, C. D., and A. S. Rodney. 2014. “Identifying residential water end uses underpinning peak day and peak hour demand.” J. Water Resour. Plann. Manage. 140 (7): 04014008.
Benazzi, R. B., L. Guss, R. J. Orend, R. S. Wyly, T.P. Konen 1976. “Water requirements and procedures for estimating the demand for water in buildings.” In Proc., Int. Symp. on Water Supply and Drainage in Buildings, Sept 28-30. National Bureau of Standards Special Publication 553, Washington, DC: US Government Printing Office.
Blokker, E. J. M. 2010. Stochastic water demand modelling for a better understanding of hydraulics in water distribution networks. Delft, Netherlands: Delft University of Technology.
Blokker, E. J. M., C. Agudelo-Vera, A. Moerman, P. van Thienen, et al. 2017. “Review of applications for SIMDEUM, a stochastic drinking water demand model with a small temporal and spatial scale.” Drinking Water Eng. Sci. 10 (1): 1–12.
Blokker, E. J. M., H. Beverloo, A. J. Vogelaar, J. H. G. Vreeburg, et al. 2011a. “A bottom-up approach of stochastic demand allocation in a hydraulic network model; a sensitivity study of model parameters.” J. Hydroinf. 13 (4): 714–728.
Blokker, E. J. M., E. J. Pieterse-Quirijns, J. H. G. Vreeburg, and J. C. van Dijk. 2011b. “Simulating nonresidential water demand with a stochastic end-use model.” J. Water Resour. Plann. Manage. 137 (6): 511–520.
Blokker, E. J. M., J. H. G. Vreeburg, H. Beverloo, M. Klein Arfman, et al. 2010a. “A bottom-up approach of stochastic demand allocation in water quality modelling.” Drinking Water Eng. Sci. 3 (1): 43–51.
Blokker, E. J. M., J. H. G. Vreeburg, S. G. Buchberger, and J. C. van Dijk. 2008. “Importance of demand modelling in network water quality models: A review.” Drinking Water Eng. Sci. 1 (1): 27–38.
Blokker, E. J. M., J. H. G. Vreeburg, and J. C. van Dijk. 2010b. “Simulating residential water demand with a stochastic end-use model.” J. Water Resour. Plann. Manage. 136 (1): 19–26.
Blokker, M., I. Vloerbergh, and S. Buchberger. 2012. “Estimating peak water demands in hydraulic systems II—Future trends.” In Proc., 14th Int. Symp. on Water Distribution Systems Analysis, Sept 24-27, Adelaide, Australia.
Buchberger, S. G., E. J. M. Blokker, and D. Cole. 2012. “Estimating peak water demands in hydraulic systems I—Current practice.” In Proc., 14th Int. Symp. on Water Distribution Systems Analysis, Sept 24-27, Adelaide, Australia.
Buchberger, S. G., J. T. Carter, Y. H. Lee, and T. G. Schade. 2003. Random demands, travel times, and water quality in dead ends. Denver: American Water Works Association Research Foundation.
Buchberger, S. G., T. Omaghomi, T. Wolfe, J. Hewitt, et al. 2017. Peak water demand study—Probability estimates for efficient fixtures in single and multi-family residential buildings. Executive Summary. Ontario, CA: International Association of Plumbing and Mechanical Officials.
CHIPS and Science Act. 2022. H.R. 4346, 117th Congress (2021–2022): CHIPS and Science Act. Congress.gov. Washington, DC: Library of Congress.
Cole, D. P. 2012. Determining fixture units for high efficiency fixtures. Ontario, CA: International Association of Plumbing and Mechanical Officials.
Cole, G., and R. A. Stewart. 2013. “Smart meter enabled disaggregation of urban peak water demand: Precursor to effective urban water planning.” Urban Water J. 10 (3): 174–194.
Coomes, P., R. Rockawasy, J. Rivard, and B. Kornstein. 2009. “North America residential water usage trends since 1992.” J. Am. Water Works Assoc. 103 (2): 76–89.
Creaco, E., E. J. M. Blokker, and S. Buchberger. 2016. “Comparison of water demand pulse generation models” In Proc., 14th Int. Conf. on Computing and Control for the Water Industry, CCWI2016, November 7-9, Amsterdam, The Netherlands.
Creaco, E., M. Blokker, and S. Buchberger. 2017. “Models for generating household water demand pulses: Literature review and comparison.” J. Water Resour. Plann. Manage. 143 (6): 04017013.
DeOreo, W. B., and P. W. Mayer. 2012. “Insights into declining single-family residential water demands.” J. Am. Water Works Assoc. 104 (6): E383.
Diamond, R., and M. Moezzi, 2004. “Changing trends: A brief history of the US household consumption of energy, water, food, beverages and tobacco.” Energy 300: 400.
Dos Santos, C. C., and F. A. J. Pereira. 2014. “Water demand forecasting model for the metropolitan area of Sao Paulo, Brazil.” Water Resour. Manage. 28(13): 4401–4414.
Downing, T. E., R. E. Butterfield, B. Edmonds, J. W. Knox, et al. 2003. CCDeW: Climate change and the demand for water. Oxford, UK: Stockholm Environment Institute.
Elías-Maxil, J., J. P. van der Hoek, J. Hofman, and L. Rietveld. 2014. “A bottom-up approach to estimate dry weather flow in minor sewer networks.” Water Sci. Technol. 69 (5): 1059–1066.
García, V., R. García-Bartual, E. Cabrera, F. Arregui, et al. 2004. “Stochastic model to evaluate residential water demands.” J. Water Resour. Plann. Manage. 130 (5): 386–394.
Gato, S., N. Jayasuriya, and P. Roberts. 2007. “Temperature and rainfall thresholds for base use urban water demand modelling.” J. Hydrol. 337 (3–4): 364–376.
Goodchild, C. W. 2003. “Modelling the impact of climate change on domestic water demand.” J. Chartered Inst. Water Environ. Manage. 17 (1): 8–12.
Grafton, R. Q., M. B. Ward, H. To, and T. Kompas. 2011. “Determinants of residential water consumption: Evidence and analysis from a 10-country household survey.” Water Resour. Res. 47 (8). https://doi.org/10.1029/2010WR009685.
Griffin, R. C., and C. Chang. 1991. “Seasonality in community water demand.” West. J. Agric. Econ. 16 (2): 207–217.
Hobbs, I., M. Anda, and P. A. Bahri. 2019. “Estimating peak water demand: Literature review of current standing and research challenges.” Results Eng. 4: 100055. https://doi.org/10.1016/j.rineng.2019.100055.
Hofman, J., M. Bloemendal, B. Wols, C. Agudelo-Vera, et al. 2014. Modelling of thermal energy balance in sewer systems. New York: City University of New York.
Hunter, R. B. 1940. Methods of estimating loads on plumbing systems. Rep. No. BMS65. Washington, DC: US National Bureau of Standards.
IAPMO (International Association of Plumbing and Mechanical Officials). 2018. Uniform plumbing code. Vol. 1, Ontario, CA: IAPMO.
IAPMO. 2021. Uniform plumbing code. Vol. 1. Ontario, CA: IAPMO.
IAPMO 2023. “Water demand calculator.” https://www.iapmo.org/water-demand-calculator/.
Jack, L., and B. Whorlow. 2017. LUNA project: An assessment of the validity of the loading units method for sizing domestic hot and cold water services. London: Chartered Institute of Plumbing and Heating Engineering.
Lee, J., and S. Tanverakul. 2015. “Water price elasticity analysis in CA.” J. Water Supply Res. Technol. AQUA 64 (2): 211–218.
Maddaus, M. L., and W. O. Maddaus. 2008. “Using an end-use model to quantify demand hardening long-term conservation programs.” In Proc., 2008 AWWA Water Sources Conf. Reno, Nevada. http://www.awwa.org.
Mayer, P., S. Davis, S. Buchberger, and C. Douglas. 2020. Assessing water demand patterns to improve sizing of water meters and service lines. WRF Rep. No. 4689. Denver: Water Research Foundation.
Mayer, P. W., D. Bennett, W. B. DeOreo, and E. Towler. 2006. “Third-party billing of multifamily customers presents new challenges to water providers.” J. Am. Water Works Assoc. 98 (8): 74–82.
Mayer, P. W., E. Towler, and W. B. DeOreo. 2004. “National multiple family submetering and allocation billing program study.” Oakland, CA: Aquacraft and East Bay Municipal Utility District.
McNeil, D. 2020. “Coronavirus has become a pandemic, W.H.O. says.” The New York Times. Accessed May 18, 2020. https://www.nytimes.com/2020/03/11/health/coronavirus-pandemic-who.html.
Moerman, A. 2013. Drinking water temperature modeling in domestic systems. Delft, Netherlands: Delft University of Technology.
Moerman, A., E. J. M. Blokker, J. Vreeburg, and J. P. van der Hoek. 2014. “Drinking water temperature modelling in domestic systems.” In Proc., 16th Int. Symp. on Water Distribution Systems Analysis, July 14-17, Bari, Italy.
NRC (National Research Council). 1974. Water distribution and supply within buildings: National research needs. USNCCIB Counterpart Commission to CIB W-62. Washington, DC: National Academy of Sciences.
Olmstead, S. M., W. M. Hanemann, and R. N. Stavins. 2007. “Water demand under alternative price structures.” J. Environ. Econ. Manage. 54 (2): 181–198.
Olmstead, S. M., and R. N. Stavins. 2009. “Comparing price and non-price approaches to urban water conservation.” Water Resour. Res. 45 (4): W04301.
Omaghomi, T., S. G. Buchberger, D. Cole, J. Hewitt, et al. 2020. “Probability of water fixture use during peak hour in residential buildings.” J. Water Resour. Plann. Manage. 146 (5): 04020027.
Persily, A., D. Yashar, N. M. Ferretti, T. Ullah, et al. 2020. Measurement science research needs for premise plumbing systems. NIST Tech. Note 2088. Washington, DC: US Dept. of Commerce.
Pieterse-Quirijns, E. J., C. M. Agudelo-Vera, and E. J. M. Blokker. 2012. “Modelling sustainability in water supply and drainage with SIMDEUM®.” In Proc., CIB W062, 38th Int.l Symp. on Water Supply and Drainage for Buildings. August 27-30, Edinburgh, Scotland.
Pieterse-Quirijns, E. J., E. J. M. Blokker, E. van der Blom, and J. H. G. Vreeburg. 2013. “Non-residential water demand model validated with extensive measurements and surveys.” Drinking Water Eng. Sci. 6 (2): 99–114.
Pieterse-Quirijns, I., A. Moerman, E. Slingerland, W. de Groote, M. Blokker. 2015. “Sustainable design of building's installations by taking into account real drinking water use.” In Proc., 32nd International Conference of CIB W78, October 27-29, Eindhoven, The Netherlands.
Rawls, C., T. Borisova, S. Berg, and J. Burkhardt. 2010. “Incentives for residential water conservation: Water price, revenue, and consumer equity in Florida.” In Proc., Southern Agricultural Economics Association Annual Meeting. February 6-9, 2010, Orlando, Florida.
Sociaal en Cultureel Planbureau. 2005. Tijdsbestedingsonderzoek 2005 [computer file]. Den Haag: Data Archiving and Network Services.
Staddon, C. 2010. Do water meters reduce domestic consumption? A summary of available literature. Working paper. Bristol, UK: Dept. of Geography and Environmental Management, University of the West of England.
Steele, A. 1982. Engineered plumbing design. 2nd ed. Elmhurst, IL: Construction Industry Press.
Tanverakul, S., and J. Lee. 2015. “Impacts of metering on residential water use in California.” J. Am. Water Works Assoc. 107 (2): 69–75.
Tanverakul, S. A., and J. Lee. 2016. “Decadal review of residential water demand analysis from a practical perspective.” Water Pract. Technol. 11 (2): 433–447.
Teodoro, M. P. 2002. “Tailored rates.” J. Am. Water Works Assoc. 94 (10): 54–64.
Tzatchkov, V. G., and S. G. Buchberger. 2006. “Stochastic demand generated unsteady flow in water distribution networks.” In Water Distribution System Analysis, edited by S. G. Buchberger, R. M. Clark, W. M. Grayman, and J. G. Uber. Reston, VA: ASCE.
US Department of Labor; Bureau of Labor Statistics. 2008. “American time use survey home page.” Accessed June 1, 2020. http://stats.bls.gov/tus/.
Wistort, R. A. 1994. “A new look at determining water demands in building: ASPE direct analytic method.” In Proc., 14th American Society of Plumbing Engineers Convention, October 23-26, 1994, Kansas City, MO, 17–34.
Xenochristou, M., C. Hutton, J. Hofman, and Z. Kapelan. 2020a. “Water demand forecasting accuracy and influencing factors at different spatial scales using a Gradient Boosting Machine.” Water Resour. Res. 56 (8): e2019WR026304.
Xenochristou, M., and Z. Kapelan. 2020. “An ensemble stacked model with bias correction for improved water demand forecasting.” Urban Water J. 17 (3): 212–223.
Xenochristou, M., Z. Kapelan, and C. Hutton. 2020b. “Using smart demand metering data and customer characteristics to investigate the influence of weather on water consumption in the UK.” J. Water Resour. Plann. Manage. 146 (2). https://doi.org/10.1061/(ASCE)WR.1943-5452.0001148.
Zlatanović, L., A. Moerman, J. P. van der Hoek, J. Vreeburg, et al. 2017. “Development and validation of a drinking water temperature model in domestic drinking water supply systems.” Urban Water J. 14 (10): 1031–1037.
Information & Authors
Information
Published In
Premise Plumbing Modeling
Pages: 7 - 35
Editors: Juneseok Lee, Ph.D., P.E., D.WRE, Jonathan B. Burkhardt, Ph.D., Steven Buchberger, Ph.D., P.E., Walter Grayman, Ph.D., P.E., D.WRE, Terranna Haxton, Ph.D., Robert Janke, Regan Murray, Ph.D., and William E. Platten III, Ph.D.
ISBN (Online): 978-0-7844-8510-1
Copyright
© 2023 American Society of Civil Engineers.
History
Published online: Oct 13, 2023
ASCE Technical Topics:
- Architectural engineering
- Building systems
- Engineering fundamentals
- Environmental engineering
- Hydraulic models
- Infrastructure
- Models (by type)
- Pipeline systems
- Pipelines
- Plumbing
- Simulation models
- Water and water resources
- Water demand
- Water management
- Water pipelines
- Water quality
- Water supply
- Water supply systems
- Water treatment
- Water treatment plants
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.