Abstract:

Cascading failures across a network propagate localized issues to more broad and potentially unexpected failures in the network. In power networks, where load must be delivered in real-time by a generation source, network layout is an important part of cascading failure analysis. In lieu of real power network data protected for security reasons, we can use synthetic networks for academic purposes in developing a validating methodology. A contingency analysis technique is used to identify cascading failures, and this involves randomly selecting initial failure points in the network and observing how current violations propagate across the network. This process is repeated many times to understand the breadth of potential failures that may occur, and the observed trends in failure propagation are analyzed and compared to generate recommendations to prevent and adapt to failure. Emphasis is placed on power transmission networks where failures can be more catastrophic.

Abstract:

Cascading failures across a network propagate localized issues to more broad and potentially unexpected failures in the network. In power networks, where load must be delivered in real-time by a generation source, network layout is an important part of cascading failure analysis. In lieu of real power network data protected for security reasons, we can use synthetic networks for academic purposes in developing a validating methodology. A contingency analysis technique is used to identify cascading failures, and this involves randomly selecting initial failure points in the network and observing how current violations propagate across the network. This process is repeated many times to understand the breadth of potential failures that may occur, and the observed trends in failure propagation are analyzed and compared to generate recommendations to prevent and adapt to failure. Emphasis is placed on power transmission networks where failures can be more catastrophic.

Life Cycle Assessment (LCA) results are typically presented using default visualization and communication approaches without acknowledging: the goals of the end-user, the end-user’s level of knowledge in LCA, the qualitative explanation supporting the visual, and the uncertainty in the process. The motivating hypothesis of this research is that the way practitioners communicate and visualize LCA results poses a risk to the interpretations of the end-users, especially when the goal of the study is not of focus when designing the visuals. Different LCA goals, whether it is for comparisons, hotspot identifications, or environmental declarations, require different visualization designs. To test this, studies were conducted with a variety of participants by giving them several visual representations of LCA results and asking them to share their interpretations of them. The participants’ interpretations of each visual were compared to the opinions of a panel of LCA experts and to the author’s intended use of it. This research gives insight on where misalignments or enhancements in the interpretation of results can occur based on the visual representations used in a certain goal category and the other factors previously mentioned. The results also provided three more key findings: 1) The majority of visuals that accurately presented and communicated the results were in the same goal category that the authors intended the visuals to be used for, suggesting that visuals are more effective when designed with the goal of the study in mind. 2) Several visuals suggested misconceptions in the presentation of results which included a misconception of the participants, a misconception of the authors, or a misconception between all groups. 3) None of the visuals in the environmental declarations category received a consensus from the panel of experts that they were well-suited for that purpose which suggests a significant research gap in accurately visualizing results for these purposes. These results aided the development of guidance documents to suggest both what to consider and what to avoid based on the goal of the study. The findings from this study can assist in bridging the gap in communication between the practitioner and the end-user.

Weather radars provide quantitative precipitation estimates (QPEs) with seamless spatial coverage that can complement limitations of sparse rain gage measurements, including those affecting intensity-duration-frequency (IDF) relations used for infrastructure design. The goal of this M.S. thesis is to assess the ability of 4-km, 1-h QPEs from the Stage IV analysis of the Next-Generation Radar (NEXRAD) network to reproduce the statistics of extreme precipitation (P) in central Arizona, USA, using a dense network of 257 rain gages as reference. The generalized extreme value (GEV) distribution is used to model the frequency of annual P maximum series observed at gages and radar pixels for durations, d, from 1 to 24 h. Estimates of P quantiles from radar QPEs are negatively biased (-20% – -30%) for d = 1 h. The bias tends to 0 and errors are small for d ≥ 6 h, independently of the return period. The presence of scaling for the GEV location and scale parameters, needed to apply IDF scaling models, was found for both radar and gage products. Regional frequency analysis methods combined with bias correction of the GEV shape parameter allow reducing the statistical uncertainty and providing seamless spatial distribution of P quantiles at daily and subdaily durations that address limitations of current IDF relations in southwestern U.S. based on NOAA Atlas 14.

Cities are facing complex problems in urban water management due to unprecedented changes in climate, natural and built environment. The shift in urban hydrology from pre-development to post-development continues to accelerate the challenges of managing excess stormwater runoff, mitigating urban flood hazards and flood damages. Physically based hydrologic-hydraulic stormwater models are a useful tool for broad subset of urban flood management including risk and hazard assessment, flood forecasting, and infrastructure adaptation decision making and planning. The existing limitations in data availability, gaps in data, and uncertainty in data preclude reliable model construction, testing, deployment, knowledge generation, effective communication of flood risks, and adaptation decision making. These challenges that affect both the science and practice motivate three chapters of this dissertation. The first study conducts diagnostic analysis of the effects of stormwater infrastructure data completeness on model’s ability to simulate flood duration, flooding flow rate; and assesses the combined effects of data gaps and model resolution to simulate flood depth, extent and volume (chapter 2). The analysis showed the significance of complete stormwater infrastructure data and high model resolution to reduce error, bias and uncertainty; this study also presented an approach for filling infrastructure data gaps using available data and design standards. The second study addresses the lack of long-term hydrological observation in urban catchment by investigating the process and benefits of leveraging novel data sources in urban flood model construction and testing (chapter 3). A proof-of-concept demonstrated the application and benefits of leveraging novel data sources for urban flood monitoring and modeling. Furthermore, it highlights the need for developing and streamlining novel data collection infrastructure. The third study applies the hydrologic-hydraulic model as an adaptation planning tool and assess the effects of uncertainty in design precipitation estimates and land use change on the optimal configuration of green infrastructure (chapter 4). Several uncertainties affect infrastructure decision making as showed by variation in optimal green infrastructure configuration under precipitation estimates and land use change. Thus, the study further highlights the need of flexible planning process in infrastructure decision making.

The Water-Energy Nexus (WEN) is a concept that recognizes the interdependence of water and energy systems. The Phoenix metropolitan region (PMA) in Arizona has significant and potentially vulnerable WEN interactions. Future projections indicate that the population will increase and, with it, energy needs, while changes in future water demand are more uncertain. Climate change will also likely cause a reduction in surface water supply sources. Under these constraints, the expansion of renewable energy technology has the potential to benefit both water and energy systems and increase environmental sustainability by meeting future energy demands while lowering water use and CO2 emissions. However, the WEN synergies generated by renewables have not yet been thoroughly quantified, nor have the related costs been studied and compared to alternative options.Quantifying WEN intercations using numerical models is key to assessing renewable energy synergy. Despite recent advances, WEN models are still in their infancy, and research is needed to improve their accuracy and identify their limitations. Here, I highlight three research needs. First, most modeling efforts have been conducted for large-scale domains (e.g., states), while smaller scales, like metropolitan regions, have received less attention. Second, impacts of adopting different temporal (e.g., monthly, annual) and spatial (network granularity) resolutions on simulation accuracy have not been quantified. Third, the importance of simulating feedbacks between water and energy components has not been analyzed. This dissertation fills these major research gaps by focusing on long-term water allocations and energy dispatch in the metropolitan region of Phoenix. An energy model is developed using the Low Emissions Analysis Platform (LEAP) platform and is subsequently coupled with a water management model based on the Water Evaluation and Planning (WEAP) platform. Analyses are conducted to quantify (1) the value of adopting coupled models instead of single models that are externally coupled, and (2) the accuracy of simulations based on different temporal resolutions of supply and demand and spatial granularity of the water and energy networks. The WEAP-LEAP integrated model is then employed under future climate scenarios to quantify the potential of renewable energy technologies to develop synergies between the PMA's water and energy systems.

Climate change has necessitated the transition from non-renewable energy sources such as coal, oil, and natural gas to renewable, low-carbon energy sources such as solar, wind, and hydroelectric. These energy sources, although much better equipped to reduce carbon-induced climate change, require materials that pollute the environment when mined and can release toxic waste during processing and disposal. Critical minerals are used in low-carbon renewable energy, and they are subject to both the environmental issues that accompany regular mineral extraction as well as issues related to scarcity from geopolitical issues, trade policy, and geological rarity. Tellurium is a critical mineral produced primarily as a byproduct of copper and used in cadmium-telluride (CdTe) solar panels. As these solar panels become more common, the problems that arise with many critical minerals’ usage (pollution, unfair distribution, human health complications) become more apparent. Looking at these issues through an energy justice framework can help to ensure availability, sustainability, inter/intragenerational equity, and accountability, and this framework can provide a more nuanced understanding of the costs and the benefits that will accrue with the transition to low-carbon, renewable energy. Energy justice issues surrounding the extraction of critical minerals will become increasingly prevalent as more countries pledge to have a zero-carbon future.

Sustainable food systems have been studied extensively in recent times and the Food-Energy-Water (FEW) nexus framework has been one of the most common frameworks used. The dissertation intends to examine and quantitatively model the food system interaction with the energy system and the water system. Traditional FEW nexus studies have focused on food production alone. While this approach is informative, it is insufficient since food is extensively traded. Various food miles studies have highlighted the extensive virtual energy and virtual water footprint of food. This highlights the need for transport, and storage needs to be considered as part of the FEW framework. The Life cycle assessment (LCA) framework is the best available option to estimate the net energy and water exchange between the food, energy, and water systems. Climate plays an important role in food production as well as food preservation. Crops are very sensitive to temperature changes and it directly impacts a crop’s productivity. Changing temperatures directly impact crop productivity, and water demand. It is important to explore the feasibility of mitigation measures to keep in check increasing agricultural water demands. Conservation technologies may be able to provide the necessary energy and water savings. Even under varying climates it might be possible to meet demand for food through trade. The complex trade network might have the capacity to compensate for the produce lost due to climate change, and hence needs to be established. Re-visualizing the FEW nexus from the consumption perspective would better inform policy on exchange of constrained resources as well as carbon footprints. This puts the FEW nexus research space a step towards recreating the FEW nexus as a network of networks, that is, FEW-e (FEW exchange) nexus.

As urban populations rapidly increase in an era of climate change and multiple social and environmental uncertainties, scientists and governments are cultivating knowledge and solutions for the sustainable growth and maintenance of cities. Although substantial literature focuses on urban water resource management related to both human and ecological sustainability, few studies assess the unique role of waterway restorations to bridge anthropocentric and ecological concerns in urban environments. To address this gap, my study addressed if well-established sustainability principles are evoked during the nascent discourse of recently proposed urban waterway developments along over fifty miles of Arizona’s Salt River. In this study, a deductive content analysis is used to illuminate the emergence of sustainability principles, the framing of the redevelopment, and to illuminate macro-environmental discourses. Three sustainability principles dominated the discourse: civility and democratic governance; livelihood sufficiency and opportunity; and social-ecological system integrity. These three principles connected to three macro-discourses: economic rationalism; democratic pragmatism; and ecological modernity. These results hold implications for policy and theory and inform urban development processes for improvements to sustainability. As continued densification, in-fill and rapid urbanization continues in the 21st century, more cities are looking to reconstruct urban riverways. Therefore, the emergent sustainability discourse regarding potential revitalizations along Arizona’s Salt River is a manifestation of how waterways are perceived, valued, and essential to urban environments for anthropocentric and ecological needs.

Fossil fuel CO2 (FFCO2) emissions are recognized as the dominant greenhouse gas driving climate change (Enting et. al., 1995; Conway et al., 1994; Francey et al., 1995; Bousquet et. al., 1999). Transportation is a major component of FFCO2 emissions, especially in urban areas. An improved understanding of on-road FFCO2 emission at high spatial resolution is essential to both carbon science and mitigation policy. Though considerable research has been accomplished within a few high-income portions of the planet such as the United States and Western Europe, little work has attempted to comprehensively quantify high-resolution on-road FFCO2 emissions globally. Key questions for such a global quantification are: (1) What are the driving factors for on-road FFCO2 emissions? (2) How robust are the relationships? and (3) How do on-road FFCO2 emissions vary with urban form at fine spatial scales?

This study used urban form/socio-economic data combined with self-reported on-road FFCO2 emissions for a sample of global cities to estimate relationships within a multivariate regression framework based on an adjusted STIRPAT model. The on-road high-resolution (whole-city) regression FFCO2 model robustness was evaluated by introducing artificial error, conducting cross-validation, and assessing relationship sensitivity under various model specifications. Results indicated that fuel economy, vehicle ownership, road density and population density were statistically significant factors that correlate with on-road FFCO2 emissions. Of these four variables, fuel economy and vehicle ownership had the most robust relationships.

A second regression model was constructed to examine the relationship between global on-road FFCO2 emissions and urban form factors (described by population

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density, road density, and distance to activity centers) at sub-city spatial scales (1 km2). Results showed that: 1) Road density is the most significant (p<2.66e-037) predictor of on-road FFCO2 emissions at the 1 km2 spatial scale; 2) The correlation between population density and on-road FFCO2 emissions for interstates/freeways varies little by city type. For arterials, on-road FFCO2 emissions show a stronger relationship to population density in clustered cities (slope = 0.24) than dispersed cities (slope = 0.13). FFCO2 3) The distance to activity centers has a significant positive relationship with on-road FFCO2 emission for the interstate and freeway toad types, but an insignificant relationship with the arterial road type.