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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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Environmental heat is a growing concern in cities as a consequence of rapid urbanization and climate change, threatening human health and urban vitality. The transportation system is naturally embedded in the issue of urban heat and human heat exposure. Research has established how heat poses a threat to urban inhabitants

Environmental heat is a growing concern in cities as a consequence of rapid urbanization and climate change, threatening human health and urban vitality. The transportation system is naturally embedded in the issue of urban heat and human heat exposure. Research has established how heat poses a threat to urban inhabitants and how urban infrastructure design can lead to increased urban heat. Yet there are gaps in understanding how urban communities accumulate heat exposure, and how significantly the urban transportation system influences or exacerbates the many issues of urban heat. This dissertation focuses on advancing the understanding of how modern urban transportation influences urban heat and human heat exposure through three research objectives: 1) Investigate how human activity results in different outdoor heat exposure; 2) Quantify the growth and extent of urban parking infrastructure; and 3) Model and analyze how pavements and vehicles contribute to urban heat.

In the urban US, traveling outdoors (e.g. biking or walking) is the most frequent activity to cause heat exposure during hot periods. However, outdoor travel durations are often very short, and other longer activities such as outdoor housework and recreation contribute more to cumulative urban heat exposure. In Phoenix, parking and roadway pavement infrastructure contributes significantly to the urban heat balance, especially during summer afternoons, and vehicles only contribute significantly in local areas with high density rush hour vehicle travel. Future development of urban areas (especially those with concerns of extreme heat) should focus on ensuring access and mobility for its inhabitants without sacrificing thermal comfort. This may require urban redesign of transportation systems to be less auto-centric, but without clear pathways to mitigating impacts of urban heat, it may be difficult to promote transitions to travel modes that inherently necessitate heat exposure. Transportation planners and engineers need to be cognizant of the pathways to increased urban heat and human heat exposure when planning and designing urban transportation systems.

ContributorsHoehne, Christopher Glenn (Author) / Chester, Mikhail V (Thesis advisor) / Hondula, David M. (Committee member) / Sailor, David (Committee member) / Pendyala, Ram M. (Committee member) / Arizona State University (Publisher)
Created2019
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A mathematical approach was developed to evaluate the resilience of coupled power-water networks using a variant of contingency analysis adapted from electric transmission studies. In particular, the “what if” scenarios explored in power systems research were extended and applied for coupled power-water network research by evaluating how stressors and failures

A mathematical approach was developed to evaluate the resilience of coupled power-water networks using a variant of contingency analysis adapted from electric transmission studies. In particular, the “what if” scenarios explored in power systems research were extended and applied for coupled power-water network research by evaluating how stressors and failures in the water network can propagate across system boundaries and into the electric network. Reduction in power system contingency reserves was the metric for determining violation of N-1 contingency reliability. Geospatial considerations were included using high-resolution, publicly available Geographic Information System data on infrastructure in the Phoenix Metropolitan Area that was used to generate a power network with 599 transmission lines and total generation capacity of 18.98 GW and a water network with 2,624 water network lines and capacity to serve up to 1.72M GPM of surface water. The steady-state model incorporated operating requirements for the power network—e.g., contingency reserves—and the water network—e.g., pressure ranges—while seeking to meet electric load and water demand. Interconnections developed between the infrastructures demonstrated how alternations to the system state and/or configuration of one network affect the other network, with results demonstrated through co-simulation of the power network and water network using OpenDSS and EPANET, respectively. Results indicate four key findings that help operators understand the interdependent behavior of the coupled power-water network: (i) two water failure scenarios (water flowing out of Waddell dam and CAP canal flowing west of Waddell dam) are critical to power-water network N-1 contingency reliability above 60% power system loading and at 100% water system demand, (ii) fast-starting natural gas generating units are necessary to maintain N-1 contingency reliability below 60% power system loading, (iii) Coolidge Station was the power plant to most frequently undergo a reduction in reserves amongst the water failure scenarios that cause a violation of N-1 reliability, (iv) power network vulnerability to water network failures was non-linear because it depends on the generating units that are dispatched, which can vary as line thermal limits or unit generation capacities are reached.
ContributorsGorman, Brandon (Author) / Johnson, Nathan G (Thesis advisor) / Seager, Thomas P (Committee member) / Chester, Mikhail V (Committee member) / Arizona State University (Publisher)
Created2020