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assumptions <strong>and</strong> it is recognized that changes in some of these assumptions could impact the<br />

results.<br />

One of the central efforts of the research project was to disaggregate each property’s<br />

water use data into seasonal <strong>and</strong> non-seasonal (outdoor <strong>and</strong> indoor) use. This process was not<br />

necessary for properties equipped with separate irrigation meters, but it was necessary for the<br />

rest of the properties, <strong>and</strong> was accomplished by using the established method of average winter<br />

consumption (AWC). However, because many of the properties are located in warm regions,<br />

manager survey results indicated that irrigation occurred 12 months out of the year at some of the<br />

properties. This reduces the accuracy of the indoor/outdoor disaggregation <strong>and</strong> hence some<br />

outdoor dem<strong>and</strong> may still be include in the indoor use estimates for these properties.<br />

Similarly, at some properties indoor water use for common area such as offices, meeting<br />

rooms, <strong>and</strong> other facilities may be included in the indoor per unit calculation. However, the<br />

manager survey sought information on some of these potential common area water uses <strong>and</strong><br />

every effort was made to correct for these uses during the statistical modeling effort.<br />

Exhaustive effort was made to select study sites that were geographically balanced,<br />

however, the 13 study sites that participated in this project are weighted towards the West <strong>and</strong><br />

Southwest regions of the U.S. Many of these study sites have a historic interest in dem<strong>and</strong><br />

planning <strong>and</strong> management <strong>and</strong> have instituted water conservation <strong>program</strong>s, which often include<br />

public information campaigns. These factors should be considered as possible behavioral<br />

influences, <strong>and</strong> might cause these results to differ from a <strong>national</strong> response.<br />

The concentration of impact properties at each study site also varied considerably. For<br />

example, in the postcard survey, Austin had 233 RUBS properties, while Hillsborough County<br />

only had 3 RUBS properties. This could cause results to be weighted towards the areas of<br />

greater concentration.<br />

Finally, this research study relied heavily on survey data. Even with a careful design,<br />

survey questions can be subject to interpretation. For example, by comparing the written survey<br />

responses with the actual site visits, it was found that there is some confusion among property<br />

managers in distinguishing between total-capture <strong>and</strong> partial-capture <strong>submetering</strong>. We have<br />

attempted to acknowledge discrepancies like this where applicable, <strong>and</strong> they are noted in the text.<br />

4

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