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- All Subjects: Phoenix (Ariz.)
- All Subjects: Water resources development
- Genre: Academic theses
- Creators: Alfaisal, Faisal M
- Creators: Alozie, Nicholas O
Description
Government performance and accountability have grown to be predominant areas within public administration literature over the last forty years. The research presented in this dissertation examines the relationship between citizen satisfaction and local government performance. Citizen review of service delivery provides vital feedback that facilitates better resource management within local government. Using data from a single jurisdiction, two aspects of citizen satisfaction are reviewed. This includes citizen review of overall city performance, and citizen satisfaction with individual service delivery. Logit regression analysis is used to test several factors that affect citizen evaluation of service delivery in local government, while ordinary least squares regression is used to test the relationship between personal factors and citizen evaluation of specific local services. The results generated four major findings that contribute to the scholarly body of knowledge and local government knowledge application. First, citizens who are predisposed to supporting the local jurisdiction are more likely to rate service delivery high. Second, customer service is important. Third, those who experience government services similarly will collectively react similarly to the service experience. Finally, the length of residency has an impact on satisfaction levels with specific services. Implications for the literature as well as for practice are discussed.
ContributorsMcNamara, Catherine (Author) / Alozie, Nicholas O (Thesis advisor) / Cayer, Joseph (Thesis advisor) / Lucio, Joanna (Committee member) / Arizona State University (Publisher)
Created2012
Description
Imagine you live in a place without any storm water or wastewater systems!
Wastewater and storm water systems are two of the most crucial systems for urban infrastructure. Water resources have become more limited and expensive in arid and semi-arid regions. According to the fourth World Water Development Report, over 80% of global wastewater is released into the environment without adequate treatment. Wastewater collection and treatment systems in the Kingdom of Saudi Arabia (KSA) covers about 49% of urban areas; about 25% of treated wastewater is used for landscape and crop irrigation (Ministry of Environment Water and Agriculture [MEWA], 2017). According to Guizani (2016), during each event of flooding, there are fatalities. In 2009, the most deadly flood occurred in Jeddah, KSA within more than 160 lives lost. As a consequence, KSA has set a goal to provide 100% sewage collection and treatment services to every city with a population above 5000 by 2025, where all treated wastewater will be used.
This research explores several optimization models of planning and designing collection systems, such as regional wastewater and stormwater systems, in order to understand and overcome major performance-related disadvantages and high capital costs. The first model (M-1) was developed for planning regional wastewater system, considering minimum costs of location, type, and size sewer network and wastewater treatment plants (WWTPs). The second model (M-2) was developed for designing a regional wastewater system, considering minimum hydraulic design costs, such as pump stations, commercial diameters, excavation costs, and WWTPs. Both models were applied to the Jizan region, KSA.
The third model (M-3) was developed to solve layout and pipe design for storm water systems simultaneously. This model was applied to four different case scenarios, using two approaches for commercial diameters. The fourth model (M-4) was developed to solve the optimum pipe design of a storm sewer system for given layouts. However, M-4 was applied to a storm sewer network published in the literature.
M-1, M-2, and M-3 were developed in the general algebraic modeling system (GAMS) program, which was formulated as a mixed integer nonlinear programming (MINLP) solver, while M-4 was formulated as a nonlinear programming (NLP) procedure.
Wastewater and storm water systems are two of the most crucial systems for urban infrastructure. Water resources have become more limited and expensive in arid and semi-arid regions. According to the fourth World Water Development Report, over 80% of global wastewater is released into the environment without adequate treatment. Wastewater collection and treatment systems in the Kingdom of Saudi Arabia (KSA) covers about 49% of urban areas; about 25% of treated wastewater is used for landscape and crop irrigation (Ministry of Environment Water and Agriculture [MEWA], 2017). According to Guizani (2016), during each event of flooding, there are fatalities. In 2009, the most deadly flood occurred in Jeddah, KSA within more than 160 lives lost. As a consequence, KSA has set a goal to provide 100% sewage collection and treatment services to every city with a population above 5000 by 2025, where all treated wastewater will be used.
This research explores several optimization models of planning and designing collection systems, such as regional wastewater and stormwater systems, in order to understand and overcome major performance-related disadvantages and high capital costs. The first model (M-1) was developed for planning regional wastewater system, considering minimum costs of location, type, and size sewer network and wastewater treatment plants (WWTPs). The second model (M-2) was developed for designing a regional wastewater system, considering minimum hydraulic design costs, such as pump stations, commercial diameters, excavation costs, and WWTPs. Both models were applied to the Jizan region, KSA.
The third model (M-3) was developed to solve layout and pipe design for storm water systems simultaneously. This model was applied to four different case scenarios, using two approaches for commercial diameters. The fourth model (M-4) was developed to solve the optimum pipe design of a storm sewer system for given layouts. However, M-4 was applied to a storm sewer network published in the literature.
M-1, M-2, and M-3 were developed in the general algebraic modeling system (GAMS) program, which was formulated as a mixed integer nonlinear programming (MINLP) solver, while M-4 was formulated as a nonlinear programming (NLP) procedure.
ContributorsAlfaisal, Faisal M (Author) / Mays, Larry W. (Thesis advisor) / Mascaro, Giuseppe (Committee member) / Fox, Peter (Committee member) / Arizona State University (Publisher)
Created2019