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The dynamics of urban water use are characterized by spatial and temporal variability that is influenced by associated factors at different scales. Thus it is important to capture the relationship between urban water use and its determinants in a spatio-temporal framework in order to enhance understanding and management of urban

The dynamics of urban water use are characterized by spatial and temporal variability that is influenced by associated factors at different scales. Thus it is important to capture the relationship between urban water use and its determinants in a spatio-temporal framework in order to enhance understanding and management of urban water demand. This dissertation aims to contribute to understanding the spatio-temporal relationships between single-family residential (SFR) water use and its determinants in a desert city. The dissertation has three distinct papers to support this goal. In the first paper, I demonstrate that aggregated scale data can be reliably used to study the relationship between SFR water use and its determinants without leading to significant ecological fallacy. The usability of aggregated scale data facilitates scientific inquiry about SFR water use with more available aggregated scale data. The second paper advances understanding of the relationship between SFR water use and its associated factors by accounting for the spatial and temporal dependence in a panel data setting. The third paper of this dissertation studies the historical contingency, spatial heterogeneity, and spatial connectivity in the relationship of SFR water use and its determinants by comparing three different regression models. This dissertation demonstrates the importance and necessity of incorporating spatio-temporal components, such as scale, dependence, and heterogeneity, into SFR water use research. Spatial statistical models should be used to understand the effects of associated factors on water use and test the effectiveness of certain management policies since spatial effects probably will significantly influence the estimates if only non-spatial statistical models are used. Urban water demand management should pay attention to the spatial heterogeneity in predicting the future water demand to achieve more accurate estimates, and spatial statistical models provide a promising method to do this job.
ContributorsOuyang, Yun (Author) / Wentz, Elizabeth (Thesis advisor) / Ruddell, Benjamin (Thesis advisor) / Harlan, Sharon (Committee member) / Janssen, Marcus (Committee member) / Arizona State University (Publisher)
Created2013
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Many studies have shown that access to healthy food in the US is unevenly distributed and that supermarkets and other fresh food retailers are less likely to be located in low-income minority communities, where convenience and dollar stores are more prevalent grocery options. I formed a partnership with Phoenix Revitalization

Many studies have shown that access to healthy food in the US is unevenly distributed and that supermarkets and other fresh food retailers are less likely to be located in low-income minority communities, where convenience and dollar stores are more prevalent grocery options. I formed a partnership with Phoenix Revitalization Corporation, a local community development organization engaged in Central City South, Phoenix, to enhance the community's capacity to meet its community health goals by improving access to healthy food. I used a community-based participatory approach that blended qualitative and quantitative elements to accommodate collaboration between both academic and non-academic partners. Utilizing stakeholder interviews, Nutrition Environment Measures Surveys (NEMS), and mapping to analyze the community's food resources, research revealed that the community lacks adequate access to affordable, nutritious food. Community food stores (n=14) scored an average of 10.9 out of a possible 54 points using the NEMS scoring protocol. The community food assessment is an essential step in improving access to healthy food for CCS residents and provides a baseline for tracking progress to improve residents' food access. Recommendations were drafted by the research partnership to equip and empower the community with strategic, community-specific interventions based on the research findings.
ContributorsCrouch, Carolyn (Author) / Harlan, Sharon (Thesis advisor) / Eakin, Hallie (Committee member) / Aftandilian, David (Committee member) / Arizona State University (Publisher)
Created2011