Reprinted with permission from Plumbing Manufacturers International/January 2021 Ripple Effect.
Hunter’s Curve, an 80-year-old chart used to predict peak water demand in plumbing systems, has been applied as the foundation for many of today’s plumbing codes. While it has been a dependable tool, Hunter’s Curve was recently modernized – with a new methodology and new features added to IAPMO’s Water Demand Calculator – to consider current trends for more efficient plumbing fixtures and lower flow rates. Dr. Steven Buchberger, professor of civil and environmental engineering at the University of Cincinnati, first addressed this topic during his presentation on “Hunter’s Curve Meets March Madness: Estimating Peak Demands in Premise Plumbing Systems” at PMI’s Manufacturing Success Conference on Nov. 11, 2020.
Seductive simplicity can lead to misapplication
When Roy Hunter published his “Methods for Estimating Loads and Plumbing Systems” in December 1940, he recognized three key parameters to estimate peak water demand in a building: 1) the number of fixtures in a building, 2) a plumbing fixture’s water flow, and 3) the probability a fixture would be in use, noted Buchberger. Hunter focused on the “big three” fixtures: a flush-valve toilet, a flush-tank toilet, and a bathtub.
“Hunter’s Curve is very simple to use and the simplicity can be seductive,” Buchberger said. “It also can be misapplied.”
He explained that one of the assumptions Hunter used in developing the curve was that a plumbing system was operating under congested conditions, such as with a line of individuals waiting to use the restroom. This scenario is common at halftime at a basketball arena. However, congested conditions would likely not be appropriate if applied to an apartment complex, for example.
Attempts to recalibrate approach bring progress
Over the past 40 years, experts have made some ad-hoc adjustments to Hunter’s Curve. Buchberger mentioned Dr. Alfred Steele, who applied some modifications in 1982, writing in his book “Engineered Plumbing Design” that it was safe to reduce the values obtained by use of Hunter’s Curve by 40%.
Major changes to plumbing fixtures took place when Congress passed the Energy Policy Act of 1992, mandating use of water-conserving fixtures in buildings. That legislation resulted in sizable reductions in water flow rates and water volume used.
Buchberger highlighted IAPMO’s recent efforts to recalibrate Hunter’s approach. He discussed how he served on the IAPMO committee that developed a probability model to predict peak demands according to the number of plumbing fixtures to be installed in a building. He noted that the resulting new methodology would be included in the 2021 edition of the American Water Works Association’s M22 Manual, which covers how to size water service lines and meters.
The committee was able to tap into a large national database of residential water use — with information from over 60 cities in nine states and more than 1,000 single-family households. The group discovered a lot of variation between today’s fixture use and the water demand Hunter studied 80 years ago. For example, Buchberger said that Hunter calculated an almost 7% chance of water running from a home’s bathtub while IAPMO’s new model reduces that chance to 1%.
He offered several additional examples of various scenarios using single-family homes and large apartment complexes to illustrate the probability of water stagnation and the implications for pipe sizing.
IAPMO’s Water Demand Calculator
IAPMO’s work resulted in the development of a residential Water Demand Calculator that anyone can download for free. The calculator, available as an iPhone or Android app or an Excel spreadsheet, lists plumbing fixtures and appliances with entries for number of fixtures, probability of use, flow rates, and maximum recommended fixture flow rates to estimate peak water supply demand loads for sizing water distribution systems.
New calculator features include a drop-down menu that lets users select between a single and multifamily building and additional computed information on peak conditions to be displayed, such as the average number of simultaneous busy fixtures being used at any moment during the peak period – known as the Hunter Number.
