Geoscience Reference
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recognition of its utility has expanded to embrace the ability of mixed methods to
substantively provide a more comprehensive understanding of complex human-
environmental phenomena.
Ruddell (
2009
), for example, compared qualitative judgments captured by
survey data to quantitative measures of environmental conditions—specifically
temperature—across diverse neighborhoods in the Phoenix region. In parti-
cular, survey respondents noted whether they perceive their neighborhood to be
more, less, or as hot as other neighborhoods in the region during 2005. Findings
revealed the lack of a statistically significant relationship between qualitative
judgments and quantitative temperatures at the aggregate regional scale, but a
strong, positive correlation prevailed at the localized neighborhood scale. These
results suggest that human-environment relationships may vary depending on the
scale of analysis, with stronger relationships between perceptions and actual envi-
ronmental conditions at the relatively proximate, neighborhood scale.
The relationship between perceptions and actual human-environmental
conditions may depend on the nature of the phenomena being studied. For example,
the relationship between perceived versus actual water use may deviate from
climate conditions, for which local experiences of heat might render perceptions
similar to actual temperature patterns. With respect to water use, however, we
expect varying relationships between perceptions and actual demand.
Mixed-methods approaches are important for understanding complex human
environment relations. Such information can inform planning and decision making.
By bringing together data on water use rates, re-lated human-ecological judgments,
and other determinants of consumption, our study highlights opportunities for
mixed methods research while supporting urban planning and demand management
efforts. In addition to obvious strengths, mixed-methods approaches pose substan-
tial obstacles (Johnson and Onwuegbuzie
2004
). To provide insights on how to
integrate disparate, multidisciplinary ideas, datasets, and analytical perspectives,
we also reflect upon the challenges for mixing methods herein. First, though, we
explain why we focus on particular drivers of demand, including perceptions and
social-structural characteristics of households and parcels.
2.2.2 Determinants of Water Demand
Previous research has investigated the determinants of water demand, concentrating
on the relationship between metered water use and household and parcel-level
characteristics. Our approach draws upon past work by examining three critical
determinants of demand—affluence, housing age, and landscape vegetation.
We also integrate attitude theory by considering cognitive judgments about water
use as another factor potentially influencing local water use rates. As further
explained in the following sections, we then consider which types of conservation
