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and behaviors) correspond and how their association with other factors informs the
implementation of the most effective strategies for conservation or other environ-
mental planning objectives.
Analysis of urban-environmental systems requires the integration of data
to reflect both physical attributes and subjective human understanding, and
by extension, the use of quantitative and qualitative research techniques. While
social surveys often collect ordinal data to capture people's subjective perspectives
on the environment, integrated analyses with other data types (such as continu-
ous water use records or categorical variables for the presence or absences of
flood irrigation) is necessary to capture diverse, observable human-environment
conditions. Some statistical models and multivariate tests may be appropriate for
such analyses, but scale discrepancies or limited sample sizes may render only
qualitative analysis feasible. With metered water demand at the neighborhood
scale, we were only able to examine 16 neighborhoods for the fully integrated
portion of our analyses. As a result, we developed a typology using a richly
descriptive, case study approach in which we compiled an array of information
on the intensive sites for which we had data on both perceived and metered water
use. To achieve our main goal of identifying neighborhoods where perceptions do
and do not match consumption, we coupled this analysis with a simple cross-
tabulation after reclassifying the two different variables into relatively low, aver-
age, and high rates of usage.
Our combined methods of data collection and analysis reflect what was possible
given the nature and availability of the variables used to capture environmental
perceptions and actual conditions. Though the generalizations we can make based
on conducting inferential statistics are limited by our focus on 16 neighborhoods
(i.e., as the primary unit of analysis), the mixed-methods approach involving
quantitative and qualitative techniques was essential for overcoming data
limitations. Further, the explanatory power of our integrated analysis was bolstered
by interpreting our findings in light of related studies (for example, Wentz and
Gober 2007 ) that have analyzed the same or similar data in distinctive ways.
Broadly, such approaches—engaging in “thick description” with multiple sources
of information—are constructive for understanding highly contextual and multi-
scalar human-environment dynamics (Adger et al. 2003 ).
2.6 Conclusions
Though our sample size does not allow us to make sweeping generalities, our
typology reveals interesting patterns in perceived water use, actual demand, and
neighborhood characteristics. The relationships between perceived versus actual
water use were common across the household- and neighborhood-level analyses of
perceptions. Even though the associated correlations were not statistically signifi-
cant at either scale, the fact that many neighborhoods cognitively underestimate
demand while others overestimate or accurately perceive consumption rates is
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