Browsing by Subject "Water resources management"

Sustainable water management is needed to ensure quality supplies of our vital water resources in the face of growing human demand for water, high levels of pollution, and increasing spatial and temporal variability associated with climate change. An integrated approach to water management is recommended to address current water challenges, which are often interrelated with other environmental, economic and social issues. Universities and colleges have missions, resources, and contexts that could enable them to lead the process of developing and applying sustainable and integrated water resource management (IWRM). The opportunity to exemplify integrated water management has grown as institutions of higher education have made progress towards incorporating environmental sustainability into teaching, research, and campus operations. This dissertation examines the issue of campus water management at institutions of higher education through a review of campus sustainability literature, a survey of sustainability and facilities managers, and case studies of three campus water-related projects.

Findings from the review of campus sustainability literature and websites suggests water is less of a campus management priority than issues such as energy and climate change; furthermore, where water is addressed, the focus is on water conservation, while water quality management is overlooked. IWRM is not explicitly discussed in the campus sustainability literature reviewed, though principles relevant to IWRM are included in some campus sustainability declarations and programs. Results from the survey substantiate the findings from literature review that water management is less of an institutional priority than energy management and water quality management is often underemphasized in campus management. According to the survey respondents, campus water management at the institutions represented was on average just adequately managed and institutions were minimally prepared to deal with several types of future water problems. Facilities managers tended to rate their institution's water management as slightly more effective compared to sustainability coordinators. Many campuses relied on top-down, engineering based water management approaches, rather than integrated and interdisciplinary water management. Individual initiatives, municipal codes and policies, campus community sustainability awareness, and campus environmental projects served as drivers for more sustainable water management, while budget constrains were a common barrier. Logistic regression analysis of the survey data revealed that institutions featuring stream and wetland restoration projects had greater odds of being described as having a developed watershed plan and taking into consideration multidisciplinary approaches to water management.

Case studies showed that wetland creation and restoration projects can serve as effective teaching and research laboratories for institutions of higher education, but that none of the studied cases fully exemplified IWRM in their operation. Of the three cases studied, the Stream and Wetland Assessment Management Park project at Duke University most closely demonstrated a campus project designed and developed to address water problems in the campus watershed, while also offering an effective outdoor teaching and research laboratory for hundreds of students, professionals, and researchers. The Olentangy River Wetland Research Park case at Ohio State University exemplified the potential for wetland creation and restoration projects to serve as a facility for educating thousands of students and visitors, training dozens of water experts, and influencing wetland and water resource management beyond the campus. The Radford University Stormwater Treatment Wetland Project case illustrated the potential for institutions with limited space and resources to establish effective outdoor teaching laboratories using environmental features already present or in development on campus.

Findings from the review, survey and case studies all point toward the need and opportunity for institutions of higher education to make greater efforts at implementing and promoting sustainable and integrated water resource management. Literature review and survey findings reveal that water is frequently overlooked as environmental resource at universities and colleges, while other environmental issues such as energy, climate change and recycling are prioritized in sustainability plans and efforts. Universities and colleges have made progress addressing water conservation, while water quality and stormwater need further attention and an integrated approach for more effective management.

Studies on the effect of regime type on public goods provision have tended to take a quantitative, cross-national approach to examining the relationship between regime type and access to public goods, and have demonstrated that democracies produce better public goods outcomes than non-democracies for a variety of theoretical reasons, including politics being more competitive in democracies, democracies needing to appease a greater proportion of their population, and re-election incentives. Such studies, however, have not aimed to understand which segments of the population receive access to benefits and the literature examining this question has tended to focus on the distribution of benefits in democracies. As such, little is known about how authoritarianism itself affects the distribution of public services.

This dissertation examines how inequalities in access to drinking water and wastewater services arise in authoritarian regimes. In examining Egypt during the period of 1882 to 2015, and using archival documents, census data, electoral returns, and interviews, I find that the groups that are prioritized for receiving access to drinking water and wastewater services differ across the different regimes within this time period, as they are a product of the goals that leaders are seeking to achieve and the structure of the authoritarian political system that is implemented, which affects elite composition, the degree of influence that leaders have over policymaking, and the regime’s relationship with the mass public.

I also find that in the aftermath of the Arab Uprisings, self-undermining policy feedbacks, which occur when those who are not benefitting from government policy that is currently in place push for significant changes in policy, can affect the state’s response to expressed discontent regarding the state of public services, but that democratization is not necessarily correlated with greater investment in public services.

Overall, the findings emphasize that political will plays an important role in affecting the distribution of public services in an authoritarian setting.

In this work, we offer readers the ability to numerically simulate flow through a sudden expansion themselves. We choose to study the sudden expansion due to its prevalence in engineered and natural water distribution networks (i.e., pipes and rivers, respectively). The simulation is written in the Wolfram Language, also known as Mathematica. The symbolic nature of this programming language enables readers to implement physical theory directly, resulting in a highly readable numerical flow solver; a stark contrast with commonplace commercial flow solvers, which operate like “black box” technologies, and low-level programming languages, which require an advanced level of syntax knowledge and programming proficiency. Upon completion of this laboratory exercise, users should be able to: (i) describe the main principles underpinning the numerical simulation of non-linear models, (ii) apply numerical models to investigate the accuracy of simplified analytical models, (iii) demonstrate a beginner-level understanding of Mathematica and, more broadly, symbolic coding environments, (ii) and most generally, (iv) understand the proper context for physical and numerical experimentation. The novelty of this work is attributed to the fact that no such simulation tool is detailed and provided in the literature for readers to utilize and alter at their discretion.

This work was developed and undertaken in collaboration with my co-authors, Dr. Anil Ganti (A.G.), and Dr. Zbigniew Kabala (Z.J.K), my master’s advisor. Author contributions are as follows: conceptualization, Z.J.K.; methodology, A.H.F, A.G. and Z.J.K.; software, A.H.F and A.G.; validation, A.H.F, A.G. and Z.J.K.; formal analysis, A.H.F; investigation, A.H.F, A.G. and Z.J.K.; resources, Z.J.K; data curation, A.H.F, A.G. and Z.J.K.; writing—original draft preparation, A.H.F and Z.J.K.; writing—review and editing, A.H.F, A.G. and Z.J.K.; visualization, A.H.F.; supervision, Z.J.K.; project administration, A.H.F and Z.J.K.

Partial funding for this project has been received from Duke University Undergraduate Program Enhancement Fund (UPEF) grant 399-000226.

Diverse ways of knowing have been recognized by scholars in many disciplines to contribute creative perspectives and novel problem-solving approaches. In the environmental sciences, those dependent on natural resources and working daily with those resources are in one of the best positions to observe and learn from subtle changes in the environment. In the coastal marine and estuarine environment, these experiential knowledge holders are the fishers and their families. In North Carolina, these fishers live in historic villages and, with scientists and policymakers, serve as the downstream stakeholders in watershed management. These three stakeholder groups all have perspectives to contribute to research and management of water quality in the watershed. This dissertation starts by documenting definitions and perspectives of water quality from these three stakeholder groups, establishing the base of information from which future research and management takes place. It then specifically addresses the details of negotiating co-production of knowledge through an ethnographic account of a collaborative research project investigating water pollution. The process of information sharing was highlighted during this process by a facilitated workshop asking participants to reflect upon their collective understanding of water quality more broadly and to plan a research project resulting from a new shared, understanding. The third component of my investigation of different ways of knowing uses North Carolina's Fishery Resource Grant program, which funds collaborative research between fishers and scientists, as a case study of an institution supporting co-produced knowledge about water quality and how the structure of collaboration in funded projects affects the success of the program both scientifically and socially. Together, the three chapters tell a story about the diverse forms of knowledge regarding water quality and how they might work together to better understand the causes and effects of water quality as well as tailor solutions to fit this better understanding. Though the story is of one case, specific to water quality and the coastal communities that depend on it, the story is also one of few optimistic cases in environmental science.

Fossil fuels continue to be a major component of the energy economies in North America, accounting for 60% of electricity generation in the U.S. Recent incidences (i.e. spills) and limited regulation of the fossil fuel industry has generated public concern about the risks fossil fuel development pose to water resources. Previous studies have identified negative impacts on water quality associated with the storage and disposal of coal combustion residuals, oil sands process-affected water, and oil and gas wastewater, as well as leaking of methane to groundwater in areas of hydraulic fracturing. In addition, contamination of water resources from natural (geogenic) sources has also been observed in many of the areas associated with fossil fuel development. Since naturally occurring saline water is common in some regions associated with fossil fuel explorations, delineating the effects of anthropogenic contamination sources is a major challenge for evaluating the impact of fossil fuel development on water quality.

This thesis investigates the geochemical and isotopic characteristics of wastewater from coal combustion residual storage ponds, unconventional oil and gas exploration, and oil sands mining, in an attempt to evaluate the use of geochemical and isotopic tracers to identify fossil fuel-associated wastewaters in the environment. This includes the investigation of (1) halogen (Br, I) and ammonium contents of oil and gas wastewater (OGW);(2) the lithium isotope ratios in OGW and coal combustion residuals; and (3) the inorganic geochemistry and boron, strontium and lithium isotope ratios of oil sands processed-affected water (OSPW). In three case studies, these geochemical and isotopic tools were integrated into comprehensive geochemical frameworks that investigated the (1) leaking of coal ash ponds to surface and groundwater in the southeastern United Sates; (2) geochemistry of groundwater in an area of shale gas development in West Virginia through time and space; and (3) evaluation of the sources of molybdenum in contaminated groundwater in southeastern

Wisconsin and possible links to coal ash surface disposal. These investigations illustrate a range of situations in which isotopic fingerprinting provided a unique geochemical tool that can successfully identify fossil fuel-related wastewater in the environment. These studies have also demonstrated the environmental impact upon releasing of fossil fuels wastewater to the environment. The case studies support the use of geochemical and isotope tools as robust methods to not only identify contamination of water resources by fossil fuel-related activities, but also to distinguish wastewater contamination from naturally occurring contamination in areas of fossil fuel development. These studies highlight the benefit of using a suite of geochemical tools when investigating water quality impacts.

Periods of drought and low streamflow can have profound impacts on both human and natural systems. People depend on a reliable source of water for numerous reasons including potable water supply and to produce economic value through agriculture or energy production. Aquatic ecosystems depend on water in addition to the economic benefits they provide to society through ecosystem services. Given that periods of low streamflow may become more extreme and frequent in the future, it is important to study the factors that control water availability during these times. In the absence of precipitation the slower hydrological response of groundwater systems will play an amplified role in water supply. Understanding the variability of the fraction of streamflow contribution from baseflow or groundwater during periods of drought provides insight into what future water availability may look like and how it can best be managed. The Mills River Basin in North Carolina is chosen as a case-study to test this understanding. First, obtaining a physically meaningful estimation of baseflow from USGS streamflow data via computerized hydrograph analysis techniques is carried out. Then applying a method of time series analysis including wavelet analysis can highlight signals of non-stationarity and evaluate the changes in variance required to better understand the natural variability of baseflow and low flows. In addition to natural variability, human influence must be taken into account in order to accurately assess how the combined system reacts to periods of low flow. Defining a combined demand that consists of both natural and human demand allows us to be more rigorous in assessing the level of sustainable use of a shared resource, in this case water. The analysis of baseflow variability can differ based on regional location and local hydrogeology, but it was found that baseflow varies from multiyear scales such as those associated with ENSO (3.5, 7 years) up to multi decadal time scales, but with most of the contributing variance coming from decadal or multiyear scales. It was also found that the behavior of baseflow and subsequently water availability depends a great deal on overall precipitation, the tracks of hurricanes or tropical storms and associated climate indices, as well as physiography and hydrogeology. Evaluating and utilizing the Duke Combined Hydrology Model (DCHM), reasonably accurate estimates of streamflow during periods of low flow were obtained in part due to the model’s ability to capture subsurface processes. Being able to accurately simulate streamflow levels and subsurface interactions during periods of drought can be very valuable to water suppliers, decision makers, and ultimately impact citizens. Knowledge of future droughts and periods of low flow in addition to tracking customer demand will allow for better management practices on the part of water suppliers such as knowing when they should withdraw more water during a surplus so that the level of stress on the system is minimized when there is not ample water supply.

Natural steroidal estrogen hormones in swine wastes generated from Concentrated Animal Feeding Operations (CAFOs) have become a potential pollutant to many aquatic environments due to their adverse impacts on the reproductive biology of aquatic organisms. In North Carolina, the swine CAFO industry is a major agricultural economic enterprise that is responsible for the generation of large volumes of waste. However, there is limited scientific understanding regarding the concentration, fate, and transport of the estrogenic compounds from these swine facilities into terrestrial and aquatic environments. To address this issue, my research involved the development and application of integrated Bayesian networks (BNs) models that can be used to better characterize and assess the generation, fate, and transport of site-specific swine CAFO-derived estrogen compounds. The developed model can be used as decision support tool towards estrogen risk assessment. Modularized and melded BN approaches were used to capture the predictive and casual relationships of the estrogen budget and its movement within and between the three major systems of a swine farrowing CAFO. These systems include the animal barns, the anaerobic waste lagoon, and the spray fields. For the animal barn system, a facility-wide estrogen budget was developed to assess the operation-specific estrogen excretion, using an object-oriented BN (OOBN) approach. The developed OOBN model provides a means to estimate and predict estrogen fluxes from the whole swine facility in the context of both estrogen type and animal operating unit. It also accounts for the uncertainties in the data and in our understanding of the system. Next, mass balance melding BN models were developed to predict the natural estrogen fates and budgets in two lagoon compartments, the slurry and the sludge storage. This involved utilizing mass balance equations to account for the mechanisms of flushing, sorption, transformation, settling, and burial reactions of estrogen compounds in the slurry and sludge storages. As an alternative approach, a regression based BN melding approach was developed to both characterize estrogen fate and budgets as a result of the sequential transformation processes between natural estrogen compounds and to assess the seasonal effects on the estrogen budgets in the two different lagoon compartments. Finally, a dynamic BN model was developed to characterize rainfall-driven estrogen runoff processes from the spray fields. The dynamic BN models were used to assess the potential risk of estrogen runoff to adjacent waterways. In addition, the dynamic model was used to quantify the effects of manure application rates, rainfall frequency, the time of rainfall and irrigation, crop types, on-farm best management practices, seasonal variability, and successive rainfall and manure application events on estrogen runoff.

The model results indicate that the farrowing barn is the biggest contributor of total estrogen as compared to the breeding and gestation operating barns. Once the estrogen reaches the anaerobic lagoon, settling and burial reactions were shown to be the most significant factors influencing estrogen levels in the slurry and sludge, respectively. The estrogen budgets in the lagoon were also found to vary by season, with higher slurry and sludge estrogen levels in the spring as compared to the summer. The risk of estrogen runoff was predicted to be lower in the summer as compared to the spring, primarily due to the spray field crop management plans adopted. The results also indicated that Bermuda grass performed more favorably when compared to soybean, when it came to retaining surface water runoff in the field. Model predictions indicated that there is a low risk of estrogen runoff losses from the spray fields under multiple irrigation and rainfall events, unless the time interval between irrigation was less than 10 days and/or in the event of a prolonged high magnitude rainstorm event. Overall, the estrone was the most persistent form of natural estrogens in the three major systems of the swine farrowing CAFO.

The demand for water and energy increases as the world's population grows. Unfortunately, many people have limited access to these two very necessary resources. In order to solve this dire issue, industry leaders, governments, scientists, and researchers have been developing and improving various technologies that show promise for being able to sustain the demand for energy and water of a growing population. One method that has proven effective in supplying water to regions that lack potable water is desalination. However, this process requires a great amount of energy to produce enough clean drinking water for a given population. The research described in this work focuses on improving the energy efficiency and productivity of desalination through cogeneration, e.g. combined heat and power (CHP). The cogeneration system consists of a polymer electrolyte membrane (PEM) fuel cell coupled with a direct contact membrane distillation (DCMD) desalination system in a bottoming cycle. For this study, the cogeneration system was modeled mathematically and computationally using the quasi-2-D PEM fuel cell model described in Hotz et al., 2006, Int. J. Heat Mass Transfer [1]. The computational model will be used to create a physical prototype for testing. The computational model has shown that using a PEM fuel cell is an effective system for cogeneration with a DCMD desalination unit. However, the low operating temperatures of the device limit the overall performance and efficiency of the cogeneration system.

As climate change and growing demand exacerbate water scarcity, it will become more imperative than ever to remediate our natural resources and treat our waste streams. This is especially true if we are to successfully provide clean water for all and ensure the future of endangered species and habitats. Thus, we look to surface water treatment technologies (e.g., granular media and filtration membranes) and groundwater remediation strategies (e.g., the vertical circulation well, rapidly pulsed pump and treat, and bioremediation) to add to our freshwater stores and reduce environmental pollution.

Complicating the matter is the fact that both surface water treatment and groundwater remediation are reliant, to varying degrees, on flow through porous media. Even without the added complexities of multiphase flows, immiscible fluids, and the time-dependent processes associated with chemical reactions and biofouling, characterizing flow through porous media, properly, is a cumbersome and arduous task. Heterogeneities in the morphology of the medium range from the pore scale, to, in the case of groundwater flows, meters. Resulting is a random distribution of the shape, size, and connectivity of the pore space. To quantify flow through porous media, researchers are forced to either make a set of simplifying assumptions, some more appropriate than others, or more recently, use black-box machine learning models that have little basis in the physicality of the flow. In this work, we choose to focus on one of the standard assumptions researchers make when calculating the pore-scale velocity (i.e., the supposed “static” nature of flow porosity). In relaxing this assumption, we provide a paradigm shift in the modeling of flows through porous media. We apply our theory to flow through and along the walls of microporous membranes, granular media, and aquifer substrates.

We choose to study pore-scale flow velocity because it is an essential parameter in determining transport through porous media, but it is often miscalculated. Researchers use a static porosity value to relate volumetric or superficial velocities to pore-scale flow velocities. We know this modeling assumption to be an oversimplification. The porosity conducive to flow, what we define as hydrodynamic porosity, exhibits a quantifiable dependence on Reynolds number (i.e., pore-scale flow velocity) in the laminar flow regime. This fact remains largely unacknowledged in the literature. In this work, we quantify the dependence of hydrodynamic porosity on Reynolds number via numerical flow simulation at the pore scale. We demonstrate that, for the tested flow geometries, hydrodynamic porosity decreases by as much as 42% over the laminar flow regime. Moreover, hydrodynamic porosity exhibits an exponential dependence on Reynolds number. The fit quality is effectively perfect, with a coefficient of determination of approximately 1 for each set of simulation data. We then demonstrate the applicability of this model by validating a high fit quality for a range of rectangular and non-rectangular cavity geometries. Finally, we show that this exponential dependence can be easily solved for pore-scale flow velocity using only a few Picard iterations, even with an initial guess that is over 10 orders of magnitude off. Not only is this relationship a more accurate definition of pore-scale flow velocity, but it is also a necessary modeling improvement that can be easily implemented.

In the chapters that follow our introduction of hydrodynamic porosity, we apply the concept to subsurface flow modeling for groundwater remediation via the vertical circulation well and flows over patterned membrane surfaces for surface water treatment – supposing that a hydrodynamic porosity parameter could be defined for the surface pattern of a membrane and then correlated to the rate of particle deposition (and therefore fouling) at the membrane surface.

In the future, we aim to explore the applicability of the hydrodynamic porosity model to microporous membrane wall flows. Although the characteristic length scale of the membrane wall is admittedly much smaller than the characteristic length scale of granular media, microporous membranes, like granular media, have dead-end pores. Thus, it remains necessary to determine the effect of these dead-end pore volumes on membrane wall flows. Preliminary experimental data previously collected from a hollow-fiber ultrafiltration membrane will be used to verify our numerical results.

Following our study of steady flows, we pivot to the analysis of rapidly pulsed flows and the mixing mechanisms these flows induce at the pore scale (i.e., the deep sweep and vortex ejection) in cavities and other effectively immobile zones. These mechanisms have been shown to significantly reduce contaminant recovery time in media with significant immobile zone volume. This finding suggests substantial cost-savings for treatment and remediation methods that utilize rapidly pulsed flows.

Regarding groundwater remediation, we estimate that the cost savings from utilizing rapidly pulsed flows could be on the order of magnitude of 100 billion USD. But this calculation assumes that we can remediate the entirety of a contaminated groundwater matrix with the mixing mechanisms induced by rapidly pulsed pump-and-treat. In application, induced oscillations will only reach a small volume of the flow field before dissipating to a negligible amplitude. Equally important, these oscillations will only induce a deep sweep or vortex ejection if the mean pore-scale flow velocity is above a Reynolds number of 0.1. Following, we use our model of hydrodynamic porosity to determine the magnitude of the volume we expect to benefit from rapidly pulsed pumping in a vertical circulation well.

Finally, given the similarity in characteristic length scale, we liken flow in the dead-end pore space of groundwater matrices, to flow past the channels in patterned membrane surfaces. We find that for the studied surface pattern, the vortex ejection and deep sweep are still present in highly laminar flows (i.e., a Reynolds number of 1600 for pipe flows). We hypothesize that these mechanisms can prevent particle deposition at the membrane surface, and when used as a cleaning mechanism, can remove loose deposits that would otherwise adhere to the membrane surface. It is also likely that these mechanisms would speed up the regeneration of fouled granular media used to remove suspended solids, microorganisms, and organics (i.e., sand and granulated activated carbon) from wastewater.

Assessing the quality of groundwater in a given aquifer can be an expensive and time-consuming process. An effort is made in this thesis to predict several water quality parameters, namely Fe, Cl, SO4, and total hardness (as CaCO3), from the easily measured properties total dissolved solids (TDS) and electrical conductivity (EC). This is achieved by establishing functional relationships between the four quality parameters, TDS, and EC using multiple linear regression (MLR) and artificial neural network (ANN) models. Data for these variables were gathered from five unrelated groundwater quality studies. Results indicate that the ANN models produced more accurate functions than MLR, showcasing the strength of ANN’s in predictive applications. Analysis of the relative importance of each parameter illustrates that total hardness (CaCO3) is most influential in determining TDS, while sulphate is most influential on EC. These results could have a significant impact on the future of groundwater quality assessments.

Global climate is predicted to have significant impacts on the chemical, biological, and physical characteristics of wetlands and the watersheds in which they are contained. In particular, climate prediction models suggest a significant increase in extreme precipitation events - both more frequent and more intense flood and drought occurrences. A wetland model that incorporates surfacewater-groundwater interactions (WETSAND2.0) was used to investigate the potential impacts of these stochastically generated extreme events on wetland flow regimes in an urban watershed. The results predict increases in streamflow and flooding as well as drought conditions on a near yearly basis. However, the model also shows that the impact on the Sandy Creek-Duke University watershed will not be as extreme as many suggest. Although flooding will occur, it will be relatively minor and comparable to historic flows. And although droughts are also predicted, the balance of wet and dry in this wetland watershed can actually be a positive for the environment. Therefore watersheds, no matter the spatial scale, must be analyzed individually. Although some comparisons can be made between similar regions, the effects of extreme precipitation events vary greatly depending on watershed characteristics.

The majority of medium- to large-sized municipal water utilities in the United States rely on the 4 trillion USD municipal bond market to finance all or a portion of their operations, maintenance, and capital improvements. Despite the scale and power of the bond market in setting the guardrails for water utilities and local government services, there are limited studies that center municipal bonds in local water management. This dissertation analyzes how the municipal bond market drives and responds to municipal characteristics as expressed through water utility finance. Through empirical, heuristic, and statistical methods, I show that 1) utilities servicing distressed communities are trading off financial risk for affordability risk, 2) nonpayment is only material for water utility finance if nonpayment elasticity exists, and 3) the bond market does not price physical climate risk but does apply a racial yield penalty. The findings have implications for the management of local water utilities as well as broader implications for how infrastructure finance intersects with water management across the U.S.

Modeling studies predict that droughts and hotter water and air temperatures caused by climate warming will reduce the efficiency (η) of thermoelectric plants by 0.12-0.45% for each 1°C of warming. In Chapter 2, we evaluate these predictions using historical performance data for 39 open- and closed-loop, coal and natural gas plants from across the U.S., which operated under daily and seasonal temperature fluctuations multiples greater than future average warming projections. Seven to fourteen years of hourly water (Tw), dry-bulb air (Ta) and wet-bulb air (Twb) temperature recordings collected near each plant are regressed against efficiency to attain estimates of ∆η per 1°C increase. We find reductions in η with increased Tw (for open-loop plants) up to an order of magnitude less than previous estimates. We also find that changes in η associated with changes in Ta (open-loop plants) or Twb (closed-loop plants) are not only smaller than previous estimates but also variable, i.e. η rises with Ta or Twb for some plants and falls for others. Our findings suggest that thermoelectric plants, particularly closed-loop plants, should be more resilient to climate warming than previously expected. Moreover, our results raise questions regarding the relative impacts of climate change-induced drops in water availability versus increases in ambient temperatures on the ability of thermoelectric power plants to generate power.

In Chapter 3, we explore and compare the effects of decreased water availability and increased water temperature on once-through power plants, which are expected to suffer more of the impacts of climate change than recirculating plants. Currently, little is known about which of the constraints, water temperature or availability, has a greater impact on power generation, and how these impacts and trends may vary with plant age, nameplate capacity, fuel type, generator technology, and location. We apply seven years of historical data from 20 once-through coal and natural gas plants into a thermoelectric power generation model to simulate how changes in various external parameters (water temperature, temperature regulations, and water availability) can affect the usable capacity of these plants. We find that depending on the plant, streamflow can contribute to 0-35% of the capacity reduction, while temperature can contribute 0-17% and regulations 48-100%. We also observe that power plants located on smaller water bodies (i.e., <3000 m^3/s in this study) are more likely to be severely impacted in future climate extreme events than plants located in other areas, regardless of power plant technology.

The fourth and final chapter of this dissertation diverges from the previous chapters and examines the processes that influence the evolution of fluvio-deltaic systems at passive continental margins. Depositional and erosional patterns that were previously believed to be entirely produced by externally-derived (allogenic) processes are now being recognized as patterns that can develop from autogenic interactions (e.g., channel avulsion and delta lobe switching). In this work, we are interested in understanding how traditional, allogenically-based interpretations of these systems change when we incorporate the impacts of autogenic processes. We introduce a novel first-order numerical basin-filling model to address this question. This model differs from previous work in that external inputs (i.e., subsidence rate, base level change, sediment supply) as well as streamwise and cross-stream transport coefficients can be adjusted to simulate basins that are dominated by allogenic processes (i.e., subsidence, eustasy, and sediment supply), laterally-moving autogenic processes, or a combination of both. Because of this, the model can be used to track how autogenic and allogenic processes interact to impact the evolution of fluvio-deltaic systems as more and more autogenic forcing is introduced. Our ability to identify, separate, and understand the geomorphic and stratigraphic signals of internally-derived processes from those of external controls is critical for better understanding shelf development.