1. Figure 1. Average water use for residential users in the U. S
Figure 1. Average water use for residential users in the U.S. and Canada
Source: Adapted from AWWA (1999), 1,188 households in 12 U.S. and Canadian cities

2. Figure 2. Distribution of residential daily water use
Sources: USA: AWWA (1999); Jordan: Griffin (2005), 308,000 customers

3. Figure 3. Average residential water use in various U. S
Figure 3. Average residential water use in various U.S. cities and foreign countries
Sources: Vickers (2001), p. 13; Hussien (2002); Jayyoussi (1998)

4. Figure 4. Hourly variation in water use
Percent of Average Day
Time of Day
Sources: Linsley et al (1992), p. 505.

5. Table 1. Shower use data for Salt Lake City, Utah (n=25 households)
(Compiled from DeOreo et al., (2011). "Analysis of Water Use In New Single Family Homes", Salt Lake City Corporation and U.S. EPA, Boulder, CO, USA.

6. Table 2. Plant factors for common residential plant types along the Wasatch Front, UT (Rosenberg et al., 2011)

7. Table 3. Water use factors for different land uses in San Francisco, CA

8. Table 4. Typical Hardware Costs and Flow Rates for Water Conserving Technologies

9. Table 5. Comparison of different methods to estimate water demands
Advantages
Disadvantages A.
Demand forecasting
Estimate both current and future water use
Simple, easy to calculate
Uses average values
Requires understanding of future trends B.
End-use estimation
Detailed, household specific
Can also estimate conservation-action effectiveness
Used to derive distribution of use or effectiveness
Assumes some implicit behaviors for each household member
Further analysis required to calculate average use among population C.
Plant water need
Disaggregate by crop and landscape plant type
Weather (ET) adjusted
Irrigation behavior may differ from plant water need D.
Land-use based forecasts
Can spatially disaggregate use
GIS software to help
Need to estimate water-use factors for each land type
How to project future land use? E.
Econometric regression
Typical economist approach
Can test or refute hypothesis
Outputs elasticity associated with each explanatory factor
Requires large household dataset
Explanatory variables often confounded, including water price under block rate structures
Difficult to account for conservation