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This dissertation consists of two topics. Chapter 1 examines the relationship between contingent commission use and underwriting performance as well as underwriting risk using data from 2005 to 2016. Top brokers were banned from receiving contingent commissions following the inquiry in 2004 led by Eliot Spitzer, former New York Attorney-General. But the ban raised concerns about whether it created a level playing field across the industry, as smaller brokers continued taking them. In addition, despite the possible conflicts of interest, contingent commissions have also been recognized as a way to better align agent and insurer incentives. Regulators agreed to relax the terms for the leading brokers in 2010, resulting in a less onerous compliance regime for contingent commission use. It is important to study the effectiveness of contingent commission use on improving underwriting performance. This study finds strong evidence supporting the hypothesis that contingent commissions’ usage is associated with better underwriting performance as well as lower underwriting risk. This study also finds a curvilinear relationship between underwriting performance and the level of contingent commission use. Chapter 2 investigates the impact of executive overconfidence on capital structure decisions and reinsurance purchases using a sample of 37 publicly-traded property-liability insurance groups for the period 2002 to 2016. This study finds that insurance firms with overconfident executives have significantly higher leverage ratios than those without overconfident executives. This study also finds evidence that insurance firms with overconfident executives cede more reinsurance, and this evidence is stronger for insurers with more limited business capacity than those with ample business capacity. The results of this study also indicate that overconfident executives prefer internal reinsurance to external reinsurance. This research provides evidence that personality traits of executive impact capital structure decisions and reinsurance purchases for insurance firms, which should be of interest to policyholders and regulators. / Business Administration/Risk Management and Insurance

Valves play a critical role in a water distribution system for subsystem isolation and flow or pressure control. Among them, subsystem isolation is required to repair or to rehabilitate a broken component and can be done by closing adjacent valves. To evaluate the role of valves, the concept of "Segment" is necessary. A segment consists of a set of pipes and nodes isolated together by closing adjacent valves when a pipe fails. An efficient algorithm to identify segments in a water distribution system is proposed. In addition, when a segment is isolated, an additional subsystem may be disconnected from water sources by the segment isolation. It is a topological unintended isolation. In addition, a hydraulic failure, in terms of pressure types of failures at demand nodes should be considered. These three account for the failure impact of a pipe. Placing valves efficiently improves the reliability of a water distribution system. However, the valve reliability itself is not 100%. Therefore, valve failure consequence should be explored in determining the locations of valves. For this purpose, three methodologies, namely segment-valve matrix algorithm, decision tree approach and simulation are proposed. Another consideration for placing valves is a strategic valving rule, namely N and (N-1) valving rules. Using a formulation for node reliability in terms of failing valves, the reliability difference between the two valving rules is evaluated. We also employ a mixed N and (N-1) valving rule. Another strategic valving rule, a segment size reducing approach minimizing the number of affected customers is proposed. The developed algorithms are utilized to build software, the Strategic Valve Management Model, to solve practical problems. The methodology is applied to three real water distribution systems. / Ph. D.

With development of renewable energies worldwide, power system is seeing higher penetration of Utility-scale photovoltaic (PV) farms at distributed level as well as transmission level. Power electronics converters present negative incremental impedance characteristics at their input while under regulated output control, which brings in the possibility of system instability. Recent evidence suggests that large-scale penetration of PV inverters increases the probability of instability. While IEEE standard 1547 newest version requires PV inverters to have reactive power control, there have been few investigations into the small-signal stability impact of PV inverters on distribution systems especially with reactive power control. In addition, the existing studies either use the conventional way of state space equations and eigenvalues or use time-domain simulation methodology, which are based on the assumptions that detailed models of the grid and the PV inverters are accessible. Different from the previous literatures, this research employs Generalized Nyquist Criterion (GNC) method based on measured impedances in d-q frames at connection interfaces. GNC method has the advantage that interconnection stability can be judged without knowing the grid and PV generator model details. This work first demonstrates the advantage of volt-var droop mode control among all different local reactive power control modes for PV inverters in the aspects of static impact on grid voltage profiles and power loss in a 12kV test-bed distribution system. Then it is discovered that d-q frame impedance of PV inverter under volt-var droop mode control shows a significant difference from other reactive power control modes. The d-q frame impedance derived from the small-signal model of PV generator is validated by both MATLAB simulation results and hardware experiments. Based on the d-q frame impedances, GNC is utilized to analyze the stability connection of a single PV farm and multiple PVs into the grid. GNC stability assessment results match with time-domain simulations and reveal the stability problem related to volt-var droop mode control. Furthermore, considering the unbalance of the distribution system, a new impedance model in d-q frame is proposed to capture both the dynamics of PV inverter operating in unbalanced points and the dynamics of three-phase unbalanced grid. The new impedance model is a combination of positive-negative sequence impedance and conventional d-q frame impedance. A procedure is designed for the measurement of the extended d-q frame impedance and the GNC application to predict small-signal stability of the unbalanced grid, which are justified by both time domain simulation and hardware experiments. / Doctor of Philosophy / To overcome the limited fossil fuel reserve on the earth and global warming, renewable energies become more and more popular worldwide. Centralized thermal power generators in the transmission system are gradually being replaced by distributed energy resources (DER) which are connection to the distribution system, bringing more challenges to the safe and stable operation of the power system. This work focuses on the small-signal stability impact of photovoltaic (PV) generators in the distribution system, which basically analyzes into whether the connection of PV generator to the distribution system will end up in an expected steady operation state with high resistance to any relatively small disturbances. The stability assessment tool is based on impedance measurement which treats both sides as black boxes and bridges the information gap between Utility operators and PV generator vendors. A major finding of this work is that while PV generators in the distribution system help to provide grid-support functions of voltage regulation, they may cause voltage small-signal stability problems due to the high grid impedance, which is worse if more PV inverters are put in parallel. Even PV farms connected to different branches of the complicated radial distribution system may have interactions with each other. So the design of control strategy and parameters of PV generator should consider the impact of other PV generators. GNC method based on impedances measurement is feasible and accurate for stability assessment of a distribution system with multiple PV farms. The impedance based method is upgraded and extended to be applied for the connection of power electronics devices to the three-phase unbalanced distribution systems.

Under the envisioned smart city paradigm, there is an increasing demand for the coordinated operation of our infrastructure networks. In this context, this thesis puts forth a comprehensive toolbox for the optimization of electric power and water distribution networks. On the analytical front, the toolbox consists of novel mixed-integer (non)-linear program (MINLP) formulations; convex relaxations with optimality guarantees; and the powerful technique of McCormick linearization. On the application side, the developed tools support the operation of each of the infrastructure networks independently, but also towards their joint operation. Starting with water distribution networks, the main difficulty in solving any (optimal-) water flow problem stems from a piecewise quadratic pressure drop law. To efficiently handle these constraints, we have first formulated a novel MINLP, and then proposed a relaxation of the pressure drop constraints to yield a mixed-integer second-order cone program. Further, a novel penalty term is appended to the cost that guarantees optimality and exactness under pre-defined network conditions. This contribution can be used to solve the WF problem; the OWF task of minimizing the pumping cost satisfying operational constraints; and the task of scheduling the operation of tanks to maximize the water service time in an area experiencing electric power outage. Regarding electric power systems, a novel MILP formulation for distribution restoration using binary indicator vectors on graph properties alongside exact McCormick linearization is proposed. This can be used to minimize the restoration time of an electric system under critical operational constraints, and to enable a coordinated response with the water utilities during outages. / Master of Science / The advent of smart cities has promoted research towards interdependent operation of utilities such as water and power systems. While power system analysis is significantly developed due to decades of focused research, water networks have been relying on relatively less sophisticated tools. In this context, this thesis develops Advanced efficient computational tools for the analysis and optimization for water distribution networks. Given the consumer demands, an optimal water flow (OWF) problem for minimizing the pump operation cost is formulated. Developing a rigorous analytical framework, the proposed formulation provides significant computational improvements without compromising on the accuracy. Explicit network conditions are provided that guarantee the optimality and feasibility of the obtained OWF solution. The developed formulation is next used to solve two practical problems: the water flow problem, that solves the complex physical equations yielding nodal pressures and pipeline flows given the demands/injections; and an OWF problem that finds the best operational strategy for water utilities during power outages. The latter helps the water utility to maximize their service time during power outages, and helps power utilities better plan their restoration strategy. While the increased instrumentation and automation has enabled power utilities to better manage restoration during outages, finding an optimal strategy remains a difficult problem. The operational and coordination requirements for the upcoming distributed resources and microgrids further complicate the problem. This thesis develops a computationally fast and reasonably accurate power distribution restoration scheme enabling optimal coordination of different generators with optimal islanding. Numerical tests are conducted on benchmark water and power networks to corroborate the claims of the developed formulations.

[EN] One of the main challenges of drinking water utilities is to ensure high quality supply, in particular, in chemical and microbiological terms. However, biofilms invariably develop in all drinking water distribution systems (DWDSs), despite the presence of residual disinfectant. As a result, water utilities are not able to ensure total bacteriological control. Currently biofilms represent a real paradigm in water quality management for all DWDSs. Biofilms are complex communities of microorganisms bound by an extracellular polymer that provides them with structure, protection from toxics and helps retain food. Besides the health risk that biofilms involve, due to their role as a pathogen shelter, a number of additional problems associated with biofilm development in DWDSs can be identified. Among others, aesthetic deterioration of water, biocorrosion and disinfectant decay are universally recognized. A large amount of research has been conducted on this field since the earliest 80's. However, due to the complex environment and the community studied most of the studies have been developed under certain simplifications. We resort to this already done work and acquired knowledge on biofilm growth in DWDSs to change the common approaches of these studies. Our proposal is based on arduous preprocessing and posterior analysis by Machine Learning approaches. A multi-disciplinary procedure is undertaken, helping as a practical approach to develop a decision-making tool to help DWDS management to maintain, as much as possible, biofilm at the lowest level, and mitigating its negative effects on the service. A methodology to detect the more susceptible areas to biofilm development in DWDSs is proposed. Knowing the location of these hot-spots of the network, mitigation actions could be focused more specifically, thus saving resources and money. Also, prevention programs could be developed, acting before the consequences of biofilm are noticed by the consumers. In this way, the economic cost would be reduced and the service quality would improve, eventually increasing consumers' satisfaction. / [ES] Uno de los principales objetivos de las empresas encargadas de la gestión de los sistemas de distribución de agua potable (DWDSs, del inglés Drinking Water Distribution Systems) es asegurar una alta calidad del agua en su abastecimiento, tanto química como microbiológica. Sin embargo, la existencia de biofilms en todos ellos, a pesar de la presencia de desinfectante residual, hace que no se pueda asegurar un control bacteriológico total, por lo que, hoy en día, los biofilms representan un paradigma en la gestión de la calidad del agua en los DWDSs. Los biofilms son comunidades complejas de microorganismos recubiertas de un polímero extracelular que les da estructura y les ayuda a retener el alimento y a protegerse de agentes tóxicos. Además del riesgo sanitario que suponen por su papel como refugio de patógenos, existen muchos otros problemas asociados al desarrollo de biofilms en los DWDSs, como deterioro estético del agua, biocorrosión y consumo de desinfectante, entre otros. Una gran cantidad de investigaciones se han realizado en este campo desde los primeros años 80. Sin embargo, debido a la complejidad del entorno y la comunidad estudiada la mayoría de estos estudios se han llevado a cabo bajo ciertas simplificaciones. En nuestro caso, recurrimos a estos trabajos ya realizados y al conocimiento adquirido sobre el desarrollo del biofilm en los DWDSs para cambiar el enfoque en el que normalmente se enmarcan estos estudios. Nuestra propuesta se basa en un intenso pre-proceso y posterior análisis con técnicas de aprendizaje automático. Se implementa un proceso multidisciplinar que ayuda a la realización de un enfoque práctico para el desarrollo de una herramienta de ayuda a la toma de decisiones que ayude a la gestión de los DWDSs, manteniendo, en lo posible, el biofilm en los niveles más bajos, y mitigando sus efectos negativos sobre el servicio de agua. Se propone una metodología para detectar las áreas más susceptibles al desarrollo del biofilm en los DWDSs. Conocer la ubicación de estos puntos calientes de biofilm en la red permitiría llevar a cabo acciones de mitigación de manera localizada, ahorrando recursos y dinero, y asimismo, podrían desarrollarse programas de prevención, actuando antes de que las consecuencias derivadas del desarrollo de biofilm sean percibidas por los consumidores. De esta manera, el coste económico se vería reducido y la calidad del servicio mejoraría, aumentando, finalmente, la satisfacción de los usuarios. / [CA] Un dels principals reptes dels serveis d'aigua potable és garantir el subministrament d'alta qualitat, en particular, en termes químics i microbiològics. No obstant això, els biofilms desenvolupen invariablement en tots els sistemes de distribució d'aigua potable (DWDSs, de l'anglès, Drinking Water Distribution Systems), tot i la presència de desinfectant residual. Com a resultat, les empreses d'aigua no són capaces de garantir un control bacteriològic total. Actualment el biofilms representen un veritable paradigma en la gestió de la qualitat de l'aigua per a tots les DWDSs. Els biofilms són comunitats complexes de microorganismes vinculats per un polímer extracel·lular que els proporciona estructura, protecció contra els tòxics i ajuda a retenir els aliments. A més del risc de salut que impliquen els biofilms, com a causa del seu paper com a refugi de patògens, una sèrie de problemes addicionals associats amb el desenvolupament del biofilm en els DWDSs pot ser identificat. Entre altres, deteriorament estètic d'aigua, biocorrosión i decadència de desinfectant són universalment reconeguts. Una gran quantitat d'investigació s'ha realitzat en aquest camp des dels primers anys de la dècada del 80. No obstant això, a causa de la complexitat de l'entorn i la comunitat estudiada, la major part dels estudis s'han desenvolupat sota certes simplificacions. Recorrem a aquest treball ja realitzat i a aquest coneixement adquirit en el creixement de biofilms en els DWDSs per canviar el punt de vista clàssic del biofilm en estudis en els DWDSs. La nostra proposta es basa en l'ardu processament previ i posterior anàlisi mitjançant enfocaments d'aprenentatge automàtic. Es va dur a terme un procediment multidisciplinari, ajudant com un enfocament pràctic per desenvolupar una eina de presa de decisions per ajudar a la gestió dels DWDS a mantenir, en la mesura possible, els biofilm en els nivells més baixos, i la mitigació dels seus efectes negatius sobre el servei. Es proposa una metodologia per detectar les àrees més susceptibles al desenvolupament de biofilms en els DWDSs. En conèixer la ubicació d'aquests punts calents de la xarxa, les accions de mitigació podrien centrar-se més específicament, estalviant recursos i diners. A més, els programes de prevenció es podrien desenvolupar, actuant abans que les conseqüències del biofilm es noten pels consumidors. D'aquesta manera, el cost econòmic seria reduït i la qualitat del servei podria millorar, finalment augmentant la satisfacció dels consumidors. / Ramos Martínez, E. (2016). Assessing biofilm development in drinking water distribution systems by Machine Learning methods [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/63257

The widespread integration of power converters in applications such as microgrids and data centers has introduced significant stability challenges. This dissertation presents a novel approach to modeling and comprehensive stability analysis for both single-phase and three-phase converters, addressing vital gaps in the existing literature. The first part of the dissertation (Chapters 2 to 4) focuses on single-phase power supply units, proposing an impedance model and a loop gain model based on dq-frame analysis. These models have been validated through extensive experimental testing, demonstrating their effectiveness in stability analysis across a range of system configurations, including single-phase, three-phase three-wire, and three-phase four-wire systems. The second part (Chapters 5 and 6) examines three-phase converters used for integrating renewable energy into microgrids. It introduces a grid-forming control, followed by a detailed investigation into its impedance modeling and stability assessment. This part specifically tackles the challenges posed by the appearance of right-half-plane poles in stability analysis, proposing a new stability margin index to address these issues. The efficacy of these research findings is further substantiated by the development and implementation of a Power-Hardware-in-the-Loop testbed, providing practical validation. Overall, this dissertation has enhanced the modeling, understanding, and management of stability issues in power electronics systems, offering valuable insights and methodologies that are likely to influence future research and development in the field. / Doctor of Philosophy / Power electronics play a crucial role in many of today's advanced technologies, including Renewable Energy (like wind and solar power), Electric Vehicles, Cloud Computing, and Artificial Intelligence. In renewable energy, power electronics are key for converting energy sources for efficient grid integration. Electric vehicles rely on power converter systems for charging their batteries and driving their motors. Similarly, in Cloud Computing and Artificial Intelligence, power electronics ensure that the computers and servers in data centers have a steady and reliable power supply for operation. However, using these advanced power electronics on a large scale, like in wind farms or data centers, can lead to challenges, including many reported system instability issues. These issues highlight the importance of a thorough analysis and understanding of the behavior and interaction of power electronics systems. In addressing these challenges, power electronics converters, conceptualized as a blend of circuits and control systems, demand comprehensive modeling from the ground up. Such modeling is essential to understanding their behavior, ranging from individual components to the entire system. This is key to establishing a clear connection between intricate design details and overall system performance. With power electronics systems becoming more complex and the continual emergence of new technologies, there remains a significant array of unanswered questions, especially in the domain of stability analysis for AC power electronics systems. This dissertation delves into two prominent modeling methods for stability analysis: impedance modeling and loop gain modeling. By exploring and addressing specific gaps identified in prior research, this work aims to contribute to a more profound understanding and enhanced application of these critical methods. The research presented in this dissertation is methodically divided into two main sections. The first section, including Chapter 2 to Chapter 4 is dedicated to exploring single-phase converter power supply units (PSUs) systems. This section introduces innovative models for analyzing their stability, applicable to single-phase PSUs in various system configurations, including both single-phase and three-phase setups. This modeling approach is a significant step forward in understanding and enhancing the stability of single-phase PSU loads. The second section, including Chapter 5 and Chapter 6, delves into the analysis of three-phase converters used in integrating renewable energy sources into microgrids. A notable feature of these converters is their grid-forming control mechanism, which includes a new frequency and power droop control loop. This part also explores modeling the impact of these converters on microgrid stability. Moreover, the issue of right-half-plane (RHP) poles in impedance analysis- a complex problem that can affect stability analysis is addressed. It proposes innovative methods for measuring stability in such conditions. In conclusion, this research made advancements in the modeling for stability analysis of power converter systems. For single-phase converters, the developed impedance model and loop gain model, based on dq-frame analysis, have been proven to be accurate. These models are versatile for stability analysis in various AC systems with single-phase PSU loads. In the study of three-phase converters, the grid-forming converter was successfully designed to support the grid as a distributed energy resource interface. This design contributes positively to microgrid stability. Furthermore, to address the presence of RHP poles in stability analysis, a new stability margin index was defined to better understand and manage these challenges. These findings represent important steps forward in the field of power electronics and contribute valuable insights for future research and development.

The design of water distribution systems has received a great deal of attention in the last three decades because of its importance to industrial growth and its crucial role in society for community health, firefighting capability, and quality of life. The cost of installing a water distribution system is typically in the tens of millions of dollars. These systems also account for the largest costs in the municipal maintenance budgets. Furthermore, existing systems are being burdened by increasing urban development and water use. All these factors cause the pipe sizing decisions to be a critical task in designing a cost effective water distribution system that is capable of handling the demand and satisfying the minimum pressure head and hydraulic redundancy requirements. A number of research efforts have focused on the least cost pipe sizing decision, each of them generating improved solutions for several standard test problems from literature, but so far, very little work has been done to test the quality of these solutions. In this thesis, two lower bounding schemes are proposed to evaluate the quality of these solutions. These lower bounding schemes make use of the special concave-convex nature of the nonlinear frictional loss terms. We show that the first is a dual to <i>Eiger et al.’s</i> [1994] bounding procedure while the second method produces far tighter lower bounds with comparable ease. Results on applying these lower bounding schemes to some standard test problems from literature are presented. The second lower bounding scheme is then embedded in a branch-and-bound procedure along with an upper bounding scheme by suitably restricting the flows at each node of the search tree. By branching successively, we attempt to narrow the gap from optimality to generate near optimal solutions to the least cost pipe sizing problem. This results in a comprehensive reduced cost network design that satisfies all pressure and flow requirements for realistically sized problems. The proposed method is applied to standard test problems from the literature. It is hoped that this method will provide a useful tool for city engineers to design a cost effective water distribution system that meets specified hydraulic requirements. / Master of Science

Islanding occurs when a connected load to the grid is disconnected from the grid and energized solely by local generators. Islanding can result in frequency and voltage instability, changes in current, and overall poor power quality. Poor power quality can interrupt industrial operations, damage sensitive electrical equipment, and induce outages upon the resynchronization of the island with the grid. This study proposes an islanding detection method employing Duffing oscillators to analyze fluctuations at the point of common coupling (PCC) under a high-noise environment, focusing on decreasing detection period, zero power mismatch nondetection zone, and power quality degradation. Unlike existing methods, which overlook the noise effect, this study mitigates noise impact on islanding detection. Power system noise in PCC measurements arises from switching transients, harmonics, grounding issues, voltage sags, voltage swells, electromagnetic interference, and power quality issues that affect islanding detection. Transient events, like lightning-induced traveling waves can also introduce noise levels exceeding the voltage amplitude, disturbing conventional detection techniques~cite{IEEE1313}. The noise interferes with measurements and increases the nondetection zone (NDZ), causing failed or delayed islanding detection. Duffing oscillator nonlinear dynamics enable detection capabilities at a high noise level. The proposed methods are designed to detect the PCC measurement fluctuations based on the IEEE standard 1547 through the Duffing oscillator. The basic idea is that the Duffing oscillator phase trajectory changes from periodic to chaotic mode and sends an islanded operation command to the inverter. The proposed islanding detection method can distinguish switching transients and faults from an islanded operation. / Master of Science / This study introduces a method to detect one of the important power grid issues, called islanding. Islanding occurs when a power grid section becomes isolated and continues to operate independently, leading to power quality problems and safety hazards. The method is developed using a Duffing oscillator that can detect special signals under a high-noise environment. The proposed method monitors electrical characteristics for islanding detection, including frequency, phase angle, and voltage amplitude. The method can quickly and accurately identify when an islanded operation occurs by analyzing these signals. This method combines the advantages of passive and active detection methods while avoiding common drawbacks, such as failed and delayed detection and power quality degradation. The proposed method is tested on a setup and meets IEEE standard 1547 criteria for safety and performance. The method is important because it detects islanded operations in a high-noise environment when the other methods cannot detect islanded operations correctly. The method maintains accuracy with decreased power quality degradation in noise. This method is a cost-effective solution for modern power grids increasingly integrating renewable energy resources.

In an era of pervasive water stress caused by population growth, urbanization, drought, and climate change, limiting the dissemination of microbial contaminants of emerging concern (MCECs) is of the utmost importance for the protection of public health. In this dissertation, two important subsets of MCECs, opportunistic pathogens (OP) and antibiotic resistant genes (ARG), are studied across several compartments of the urban water cycle, including surface water, stormwater, wastewater, recycled water, and potable water. Collectively, this dissertation advances knowledge about the occurrence of OPs and ARGs across these water systems and highlights trends that may be of value in developing management strategies for limiting their regrowth and transmission. Field studies of two surface water catchments impacted by stormwater runoff demonstrated the prevalence of ARGs in urban stormwater compared to pristine, unimpacted sites, or to days when no precipitation was recorded. The role of wastewater reuse in transmitting OPs and ARGs was also investigated. Traditional tertiary wastewater treatment plants producing water for non-potable use were found to be largely ineffective at removing ARGs, but plants using advanced oxidation processes or ozonation paired with biofiltration to produce direct potable reuse water were highly effective at removing ARGs. Non-potable reclaimed water consistently had greater quantities of sul1, a sulfonamide ARG, and Legionella and Mycobacterium, two OPs of significant public health concern, present than corresponding potable systems. Limited regrowth of OPs and ARGs did occur in simulated premise (i.e., building) plumbing systems operated with direct potable reuse waters, but regrowth was comparable to that observed in systems fed with potable water derived from surface or groundwater. Advancements were also made in understanding the role of several hypothesized driving forces shaping the antibiotic resistome in natural and engineered water systems: selection by antimicrobials and other compounds, horizontal gene transfer, and microbial community composition. Finally, whole-genome and metagenomic characterization were applied together towards profiling L. pneumophila in clinical and water samples collected from Flint, Michigan, where an economically-motivated switch to an alternative water source created conditions favorable for growth of this organism and likely triggered one of the largest Legionnaires' Disease outbreaks in U.S. history. / PHD / Population growth, urbanization, drought, and climate change have all driven many U.S. municipalities to utilize alternative water sources, such as recycled wastewater, to offset demand on traditional potable water sources. Many water providers have moved towards a modern paradigm of utilizing multiple available water sources, recognizing the interconnectedness of various components of the urban water cycle, leading to opportunities to improve sustainability, optimize infrastructure use, stimulate economic growth, increase coordination among water agencies, and identify new water resources from which to meet consumer needs. Though advancements in treatment technologies throughout the twentieth century have largely succeeded in eliminating waterborne disease outbreaks associated with contamination of municipal water supplies by fecal pathogens in developed countries, several microbial contaminants of emerging concern (MCECs) have garnered attention. Two major groups of MCECs are considered in this dissertation: antibiotic resistance, including antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARG), and opportunistic pathogens (OP), such as Legionella pneumophila, the causative agent of Legionnaires’ Disease. ARB are a rising cause of disease around the world and are a major challenge to modern medicine because they make antibiotics used for treatment ineffective. OPs, the leading cause of waterborne disease in the U.S. and other developed countries, have become prevalent in engineered water systems where low nutrient concentrations, warm water temperatures, and long stagnation times can facilitate their growth. Immunocompromised people, including smokers and the elderly, are especially vulnerable to infection with OPs. The role of the urban water cycle in facilitating the spread of these MCECs is not well understood. Here they were studied across several compartments of the urban water cycle, including surface water, stormwater, wastewater, recycled water (spanning a variety of intended uses, from non-potable to direct potable reuse), and potable water. Field studies were conducted of two watersheds impacted by stormwater runoff, one in the arid Colorado Front Range under conditions of a rare, 1-in-1,000 year rainfall event, and one in the humid climate of southwest Virginia, during three summer storms. Both studies demonstrated the prevalence of ARGs in urban stormwater compared to pristine, unimpacted sites, or to days when no precipitation was recorded. The role of wastewater reuse in transmitting OPs and ARGs was also investigated. Wastewater treatment plants producing water for non-potable use (i.e. applications such as irrigation, but not for human consumption) were found to be largely inefficient at removing ARGs, and this reclaimed water consistently had greater quantities of the sul1 ARG present than in corresponding potable systems. In these systems, genes associated with the OPs Legionella and Mycobacterium as well as total bacteria were more abundant in reclaimed water than in corresponding potable systems. In more advanced treatment plants utilizing advanced oxidation processes or ozonation paired with biofiltration to produce direct potable reuse water (i.e. water fit for human consumption), ARGs were very effectively removed by treatment, with abundances often found to be higher in corresponding potable waters derived from surface or groundwater. Limited regrowth of ARGs as well as OPs did occur in simulated home plumbing systems operated with these waters, but regrowth was comparable to that observed in systems fed with potable water derived from surface or groundwater. Finally, a study of L. pneumophila in the Flint, Michigan drinking water system during use of an alternative water source that has been identified as a likely cause of two Legionnaires’ Disease outbreaks revealed presence of multiple strains of the OP in the system. Genomic comparisons revealed that strains isolated from hospital and residential water samples were highly similar to clinical strains associated with the outbreaks. Advancements were also made in understanding the role of several hypothesized driving forces in shaping the antibiotic resistome in natural and engineered water systems: selection by antimicrobials and other compounds, horizontal gene transfer, and microbial community composition. Together, these chapters describe an advancement in knowledge regarding the occurrence of OPs and ARGs in a variety of water systems, and highlight trends that may be of value in developing management strategies for limiting regrowth or transmission of these bacteria in various compartments of the urban water cycle.