| The thesis develops an integrated approach to model heterogeneous household water and energy end-uses and their linkages. The approach considers variations in behavioral and technological water-and-energy-use factors that affect indoor residential water- and energy-use in the U.S. Here, we use a recent, large, national, disaggregated household dataset of potable hot and cold water end-uses collected from eleven cities. We also use national energy data to estimate heterogeneous energy-uses for household water appliances including toilets, showers, faucets, clothes-washers, and dishwashers. First, probability distributions of water- and energy-use factors are identified, correlated, and compared among study sites. Then Monte Carlo simulations are used to calculate probability distributions for estimated households' water-and-energy-uses. Finally, linear regressions are used to find the relative effects of water and energy factors on household energy-use. Results show that water and energy distributions among households are heavily skewed, with the largest 14.6% of the users consuming 30.5% and 33.1% of water and energy, respectively. Water heater dispense temperature followed by faucet flowrate have the highest relative effect on household energy-use and should be targeted to reduce household energy use. The approach improves prior homogenous and deterministic water-energy models and can help utilities select and size cost-effective collaborative water and energy conservation actions. |
