Search

Demand projections indicate that Oahu's natural ground water supply will be fully developed by the year 2000. Supplementary water resources will need to be developed in keeping with the growth of the economy and population. The author, chairman of the Honolulu Board of Water Supply, authoritatively discusses types of ground water in Hawaii, and areas of interest in water development throughout the Islands. This is followed by an in-depth historical accounting of Oahu's water supply system. The present water resources, population, land use situation, and projects for the future are examined. The Board of Water Supply, which has amply provided Oahu with high quality water, has carried out its responsibilities inefficiently. Management, in terms of utilizing computer technology, is indicated to deal with increasing problems. The issue of whether to combine water supply operations with sewerage functions is presented. Institutional responses to water supply needs, desalination, water recycling and treatment, and energy are other topics thoroughly treated. Although technological innovations can be used to increase supply, specific development projects, conservation measures, and institutional reform are recommended to meet Oahu's water supply needs beyond the year 2020. An extensive bibliography of published and unpublished materials is included. (BP)

The reported study was conducted to determine the extent to which active participants of a Citizen's Advisory Committee (CAC) were representative of the general public in land and water resource attitudes. All 39 members of the Maumee River Basin Level B CAC and a random sample of 400 Basin residents were given a Likert-type scale to measure their attitudes about land and water resources, the effectiveness of governmental leaders and agencies with these resources, and the role that citizens and the government should have in land and water resource decisions. Demographic data were also collected. Although the CAC members were not demographically reflective of the general public of the Basin, it was concluded that they were reflective of the public in terms of attitudes toward land and water resources and the role of government and the citizen in land and water resource decisions. (MR)

Reported is a study of a preference input form as a means of obtaining input for incorporating advisory committee preferences into the planning process for water resource management. Two input forms were used at eastern and western Study Area Committee (SAC) meetings, for study area 8 of the Comprehensive Water Quality Management Plan (COWAMP) in northwestern Pennsylvania. Problems in organization and administration of the study were encountered and are discussed. Results indicate that the groups favored moderate management policies the most and that even though the groups ranked certain amenities desirable, those same amenities received moderate management policy ratings. (MR)

Described is an analysis of variables potentially influential in public participation processes associated with Federally-funded projects in water resources, wastewater management, and highway construction. Methodology involved three phases: (1) a review of public participation literature to inductively identify variables present or recommended for presence in public participation activities; (2) organization of the 161 variables identified into sets describing potential elements and potential outcomes of public participation; and (3) analysis of 105 case studies of public participation for the presence and absence of the 161 variables. An analysis work sheet facilitated documentation of the occurrence of variables in each case study examined. The researcher used frequency and correlational computations to identify variables which merited further analysis. These variables were selected according to their frequency of documentation, frequency of significant correlations, and magnitude of correlations. Conclusions drawn from the examination of relationships among variables emphasized the importance of maintaining two-way communication between agency and participants and identified factors associated with undesired outcomes of public participation efforts. (Author/WB)

This study on climate change Loss and Damage (L&D) covers the three significant knowledge gaps in the 'L&D Work Programme' of the United Nations Framework Convention on Climate Change (UNFCCC). These are i) providing a universal definition of damage, ii) codifying a robust assessment methodology, and iii) and offering perspectives on how L&D analysis can be practically implemented. Water resources are situated at the centre of this thesis because the analysis contained herein illustrates that two-thirds of all-natural disasters worldwide are water-related. The concept of L&D is the latest addition to the UNFCCC's work programme. However, multiple meetings of the Conference of the Parties (COP) have highlighted the need for deeper understanding and common terms of reference. Using the Systematic Review technique revealed how L&D is different from climate impact and why the conventional mitigation and adaptation approaches are not adequate. It illustrates how empirical evidence is needed to augment theory. A candidate universal definition was developed drawing on place-based analysis in one of the world's great river basins, the Ganges-Brahmaputra-Meghna (GBM) mega-basin, with a particular focus on Bangladesh. The narrative of this thesis begins with the global drivers of change (e.g. emission scenarios), cascading through regional climatic indices (e.g. temperature and precipitation anomalies) down to the local level impacts - where L&D is experienced. Parametric trend analysis reveals that the intensity and frequency of all water-related hazards, i.e. hydrological, climatological, and metrological hazards, are significantly increasing. A modified normalised economic analysis of these water-related disasters was undertaken revealing financial costs of c. US$1.7 trillion over the last three decades, effectively US$30 billion a year and rising. Similarly, if the total number of people affected by the disaster and the total number of people killed in the disaster are used as proxy indicators for damage and loss, South Asia emerges as an L&D hotspot in terms of human suffering. This result justifies the selection of the GBM for the regional and local focus in this thesis. In terms of economic losses, North America stands out from all other regions. Aggravating climatic risks in physically and politically diverse GBM basin are highly contentious issues around equitable and sustainable transboundary water management. This study set up a regional level hydrological model in the GBM basin using the semi-distributed hydrological model SWAT. Water availability indicators, such as 'Blue Water' availability , show that by 2100 many new areas will experience water stress and security issues. The modelling showed that monsoonal floods and water scarcity during the dry season will both intensify and extend significantly by the end of this century. Hazard analysis shows that the likelihood of disastrous flooding in the GBM basin will increase by 80 per cent by the 21st century, with flood duration prolonged and its delayed recession aggravating direct risks to people and indirect risks associated with food (crop) insecurity. In addition, drought will increase in several river basins, of which 'Green Water' availability will become a significant presenting issue in the lower Brahmaputra basin in Bangladesh. Because the Ganges Basin has the most hydrological regulation through structural interventions, this system is especially vulnerable. An extensive field campaign was undertaken across five regions in Bangladesh, exploring current and future L&D in terms of people and local places. This sought to capture the experiences of living with environmental change and explore coping and adaptation measures at the community and family level to address them. These case studies cover the prevalence of rapid onset (such as seasonal floods, flash floods and storm surges) and slow-onset event (such as sea level races, salinity intrusions and drought) in the selected areas. Statistically robust sampling and questionnaires survey of 506 households showed all are exposed to climate-related shocks and stressors, of which 91% of households suffer from L&D despite adopting some coping or adaptation strategies. The mean annual economic loss per household is c.US$2,500/yr, which exceeds the mean annual per capita GDP in Bangladesh (US$2,100). It implies that their earnings are not adequate to cover up the disaster L&D, so they rely heavily on various financial assistance such as loans and external aids. A recurrent pattern was the erosion of adaptive capacity erodes over time, meaning families cannot recover between shocks. Drawing from more than one hundred in-depth interviews, the human face of L&D was elucidated. Rich qualitative insights confirmed that conventional water management infrastructures such as embankments for protection against flood and storm surge are inadequate to ensure safety and security of life and livelihood to families. Further, long-term environmental impacts of structural adaptation options often outweigh their benefits. One of the main reason's households cannot address L&D is the lack of entitlement to land and essential lifeline services such as clean drinking water, sanitation, access to electricity, food security. Therefore, crafting strategies for a water management solution that addresses the entitlement right of the affected households are critical to addressing L&D. Because of the persistent and indeed deteriorating geopolitical disputes over transboundary water rights and the slow progress of UNFCCC processes, it is unclear that global initiatives will reach the most marginalised families over short to medium timescales. As a result, the final section of this thesis used an action-based research approach to demonstrate the concept of a 'flood resilient home'. A prototype flood resilient home, in particular, was designed to address entitlement concerns by incorporating sustainable livelihood, food and nutrition safety, potable water, waste management, and renewable energy features, allowing a family to live their lives uninterrupted both during the disaster and non-disaster periods. In the event of a disaster and the rest of the year, it will provide a family with enhanced protection and give access to other lifeline services, generating goods and services of US $ 2,100 a year. The intersectional analysis highlighted the importance of empowering women to address L&D. The potential of this concept received the prestigious UN Risk Award 2019 and a Commendation in the Times Higher Education Awards 2019, as 'research project of the year' in the arts and social sciences category.

Due to increasing demographic pressures and widespread mismanagement, Pakistan is experiencing a severe water crisis. The mismanagement of Pakistan's resources is linked to its legacy of colonialism. Failures to reign in the stranglehold of the rural elite or invest in transformative policies is leading to a downward spiral of poverty linked to environmental degradation (European Commission 2007). However, Pakistan is rarely included in studies of IWRM, this is in spite of knowledge gaps on the potential for a more tailored forms of IWRM in countries containing semi-feudal setups and colonial based systems of water management. The research question for this study therefore focuses on aspects of IWRM that can be tailored to Pakistan's country context using the agricultural provinces of Punjab and Sindh as case studies. Due to the emphasis on shifting away from universal approaches, a significant portion of the study analyses the type and causes of water problems and existing legislation and institutions for water management in Pakistan. Field research is utilised to further contribute to identified gaps in IWRM literature. This field research is in the form of key informant interviews with government officials, an institutional assessment of Farmers Organisations and Water User Associations, and focus group discussions with farming communities. The study finds major flaws in Pakistan's water agreements, funding systems, and institutional framework leading to operational problems. It finds that institutions created under participatory irrigation policies have made political alliances in order to function exacerbating biases in water allocations. The study concludes that for IWRM to be effective, it must be accompanied by land redistribution to weaken the political power of landlords, legislative changes to improve the transparency of voting, improved regulations, strengthened enforcement, and greater clarity in water agreements. Donor expectations on the role of women in irrigation management must also be more realistic if they are to be represented. The study finds that due to the severity of current problems, if changes are not implemented, Pakistan will confront increasing political instability in the coming years.

In the water utility sector, traditional asset management focusses on the maintenance and provision of physical assets (infrastructure) that allow water companies to deliver their services, meet their customers’ expectations and achieve their economic objectives. Nevertheless, the serviceability of the sector heavily depends on natural elements (e.g. rain, land). The importance of Natural Capital (i.e. the natural systems and their deriving ecosystem services) has been at the core of policy recommendations which have shaped regulatory changes in the water sector of England and Wales. Water companies are now required to explicitly account for and report their inter-dependencies on the natural environment and adopt systems-oriented approaches in their Asset Management Programmes (AMPs). These reforms will enable the sector to become resilient to the environmental and societal challenges faced at urban and rural contexts. Responding to the regulatory demands, the research introduces a novel and structured approach for integrating natural capital in the asset management portfolio of the water industry. The work is built on a transdisciplinary research framework and demonstrates that a new scale needs to be considered for the implementation of Holistic Asset Management: the water basin or catchment. A Catchment Metabolism modelling schema was created, grounded on the principles of Integrated Catchment Management and ecosystems services. The schema is based on the robust synthesis of concepts, tools and methods from a spectrum of disciplines. These include Industrial Ecology, Water Accounting, Environmental Regional Input-Output Analysis, hydrology, software engineering and functional modelling. Catchment Metabolism introduces a holistic perspective in asset management and expands its scope. The schema enables the conceptualisation, modelling and management of catchments as complex asset systems. It, thus, forms the ground for structured collaboration among experts for integrated water resources planning and decision-making. The schema allows for the design and implementation of catchment-based strategies and the assessment of their environmental performance. An industrial case study for a pilot catchment system (Poole Harbour Catchment) is used to demonstrate the application of the Catchment Metabolism. Alternative strategies for nitrogen pollution mitigation are assessed. The application of winter cover crops across the catchment appears to be the optimum strategy. The case study demonstrates the practical and modular implementation of the schema, reveals its methodological strengths and limitations and evaluates its applicability in the asset management planning and decision-making of the water sector.

Water resources managers are required to develop comprehensive water resource plans based on severely uncertain information of the effects of climate change on local hydrology and future socio-economic changes to localised demand. In England and Wales, current water resource planning methodologies include a headroom estimation process separate from water resources simulation modelling. This process quantifies uncertainty based on only one point of an assumed range of deviations from the expected climate and projected demand 25 years into the future. The research presented herein addresses this problem by developing an integrated the Water Resources Planning Robustness Assessment (WRP-RA) method based on Information-Gap Decision Theory (IGDT) to quantitatively assess the robustness of various supply side and demand side management options over a broad range of plausible futures. Findings show that beyond the uncertainty range explored with the headroom method, a preference reversal can occur, i.e. some management strategies that underperform at lower uncertainties, outperform at higher levels of uncertainty. Also, some management strategies that perform relatively well within the headroom range of uncertainty, fail just beyond this range. Additionally, this thesis demonstrates that when 50% or more of the population adopts demand side management in the form of efficiency related measures and/or innovative options such as rainwater collection and/or greywater reuse, the robustness of a management strategy can be greatly improved as can its ability to recover after a drought episode. The use of Multi-Criteria Decision Analysis shifts the focus away from reservoir expansion options and large-scale river abstractions that perform best in regards to water availability, to strategies that include innovative demand side management actions of rainwater collection and greywater reuse as well efficiency measures along with more traditional supply-side schemes. Therefore, this thesis illustrates how the WRP-RA can offer a comprehensive picture of the relative robustness of management strategies to more extreme supply/demand futures. The knowledge of which options and collections of options perform better in response to higher demands and lower supplies offers insight into more secure long term investment strategies.

The approach to water management worldwide is currently in transition, with a shift from centralised infrastructures to greater consideration of decentralised technologies, such as rainwater harvesting (RWH). Initiated by recognition of drivers, including water demand, increasing risk of ground-water pollution and flooding, the value of RWH is filtering across the academic-policy boundary. However, in Nigeria, implementation of sustainable water management (SWM), such as RWH systems, is inefficient social, environmental and technical barriers, concerns and knowledge gaps exist, which currently restrict its widespread utilisation. This inefficiency contributes to water scarcity, water-borne diseases, and loss of lives and property due to flooding. Meanwhile, several RWH technologies have been developed to improve SWM through both demand and storm-water management. Such technologies involve the use of storage tanks, surface water reservoirs and ground-water recharge pits as storage systems. A framework was developed to assess the significance and extent of water management problems, match the problems with existing RWH-based solutions and develop a robust ready-to-use multi-criteria analysis tool that can quantify the costs and benefits of implementing several RWH-based storage systems. The methodology adopted was the mixed method approach, involving a detailed literature review, followed by a questionnaire survey of 1067 household respondents, 135 Nigerian Architects and Civil Engineers and focus group discussion with Stakeholders. A total of 1042 sets of data were collected through a questionnaire survey and analysed using SPSS, Excel and selected statistical methods to derive weightings of the attributes for the tool. Following this, three case studies were selected to collect data for hydrological modelling using the RainCycle model. From the results it is found that the most important barrier constraining sustainable RWH regime in Ibadan was obsolete and insufficient operational equipment, followed by poor renumeration of water corporation staff and misuse of available funds. In addition, the measure of importance of storage capacity was established, with the highest score of 4.5 which reflects the general inadequacy of storage as a major barrier to the adoption of RWH as a sustainable water management method. Further, respondents’ major health hazards associated with drinking contaminated water was established. A larger proportion (61.2%) of respondents chose prevalence of typhoid fever; some have a prevalence of diarrhea (19.4%), while few of respondents’ water sources is free from water-borne diseases (2.3%). The tool developed is an integrated platform of related evaluation techniques, including Whole Life Cycle Cost Analysis and Multi-Attribute Utility Theory. The tool uses data including cost and quantities of materials for building a RWH storage system and quantifies the cost and benefits of alternative RWH-based systems that can improve project management. This tool is novel, given its integration of the analytical techniques mentioned above and application for selecting the most appropriate RWH-based SWM systems. The implementation of the tool is envisaged to provide an objective platform for the quantification of the costs and benefits of RWH-based systems prior to implementation.

Hyporheic exchange in streams supports many important ecosystem services but can also contribute to legacy pollution, by trapping less reactive contaminants in streambed sediments that are then slowly released back to the stream over time. In this study we evaluated three different analytical representations of the backward transit time distribution (bTTD) of water leaving the hyporheic zone, corresponding to different mechanisms for how water and solutes in hyporheic zone storage are sampled for outflow: (1) uniform sampling (exponential bTTD), plug-flow sampling (Dirac delta bTTD), and preferential sampling of either young or old water (Gamma bTTD). Using the Method of Moments, these three bTTDs were tested against data from 47 previously published hyporheic exchange experiments conducted in laboratory flumes over a range of flow conditions, sediment grain sizes, and bedform sizes and types. Based on measures of model fit and parsimony (AICc), in all 47 experiments hyporheic exchange was best represented by either the Gamma or exponential distributions. Further, values for key process variables, including hyporheic exchange flux and the Gamma distribution's shape parameter are correlated with readily measured field variables, including mean grain diameter of the streambed, streambed roughness, and mean stream discharge and velocity. This work advances understanding of hyporheic exchange processes and their representation in models of pollutant fate and transport in streams.

Access to daily stream flow data, at the river reach scale is a central component of many aspects of water resource and water quality management. However, the majority of river reaches within the UK are ungauged. Hence, there is an operational requirement for a quick, consistent and reliable method for simulating historical stream flow records within ungauged catchments. The overall objective of this research has been to develop a rainfall runoff model for predicting natural daily stream flows within a catchment without recourse to the calibration of model parameters against observed stream flow data. Implicit within this objective is a requirement that the model parameters can be estimated from readily available data describing the physical characteristics of the catchment. The fundamental approach to the research has been to develop and calibrate suitable models within a large, representative sample of UK catchments and to subsequently develop predictive, statistical relationships for estimating model parameters from the climatic and physiographic characteristics of the catchments. The predictive capacity of the regionalised model forms has been extensively evaluated through comparisons with gauged flow data, calibrated models and existing industry-standard methods for estimating historical flow time series within ungauged catchments. The regionalised model forms developed represent a significant advance over existing, low-cost methods for estimating historical flow regimes within ungauged river catchments. The errors in the simulated stream flows are sufficiently small for the techniques to be a useful aid in the management of water resources within the UK.

The Colorado River supplies water for over 40 million people throughout the North American Southwest, a region that has experienced prolonged stress on water resources for more than two decades. Through the lens of critical physical geography, this research synthesizes a physical and social science approach to explicate the many human and physical distinctions that are fueling the overuse of this waterway. The Southwest region economically benefits from settler colonialism yet lacks inclusivity of access to natural resources, including water. An investigation into the intricate dynamics of land use, water policy, and climate change in the Colorado River Basin provides a holistic understanding of environmental and climate disparities gripping parts of the region. Mixed-methods consisting of a correlation and trend analysis, along with a policy analysis, were employed to identify these evolving issues. Hydroclimatological patterns over the 1956-2022 period reveal disconcerting trends, further aggravating water supply. Historical water policies from 1922-1968 demonstrate their misalignment with evolving river dynamics and contribute to inequities in resource allocation. By extracting historic to modern-day climate and adaptation data, the evidence of this study leads to the conclusion that previous andmodern-day policy not only is unsuitable to withstand the future of climate-induced changes to the hydrologic health of the river, but the impact of water scarcity faced by Indigenous communities across the North American Southwest could persist. The study emphasizes the ongoing importance for policies to be more attuned to the shifting climate and landscape while ensuring equitable resource access for all.

The principal goal of the current research is to develop and improve weir-based energy dissipator designs at the outlets of circular culverts. In the present case, we are interested in full-length weirs and staggered weirs. A review of related literature was completed and reported; a test facility was carefully designed and constructed to collect flow information in a basin downstream of a model broken-back circular culvert; instrumentation was installed to measure discharges, streamwise depths, and velocities. Both full-length and staggered weirs were tested over a range of discharges and tailwaters. The two types of weirs were subjected to two types of tests: (1) tailwater-independent tests and (2) tailwater-influenced tests. The tested weir heights ranged from D/8 to 4D/8, in which D is the culvert diameter. Data was processed to assess energy dissipation and hydraulic jump position associated with each dissipator configuration. Dissipation basin outlet depths predicted with a simple weir equation, some general assumptions about the flow upstream of the weir, and the energy equation with no head losses were reasonably close to measured outlet depths for the tallest full weirs (weirs with heights of 3D/8 and 4D/8). For the shorter weirs (weirs with heights of D/8 and 2D/8), the flow appeared to skim the weir and the weir equation was invalid, especially for high discharges. Within the range of testing conditions, the optimal weir heights for full weir and staggered weir are 4D/8 and 3D/8. Once the optimal dissipation is achieved for full weir, increasing the height of the weir will only reduce the total energy dissipation of the weir/expansion/culvert system; the same is not necessarily true for the staggered weir, for which some flow does not pass over the weir. The geometry of the staggered weir can be altered to optimize its design. Forcing the toe of the jump to approach the culvert break for all tested discharges required the outlet of the culvert to be submerged to about 1.1D by the tailwater. This result was independent of the weirs that were tested because at this submergence the weirs had little influence on energy dissipation. The result was not independent of discharge, and higher discharges than those tested may require greater submergence. However, raising the weir to achieve full submergence is not advisable based on the present observations since taller weirs will lead to higher basin outlet velocities. Forcing a jump to form within the runout section does not appear to be optimal for energy dissipation purposes. Testing taller weirs would help corroborate this observation. Advisor: David M. Admiraal

Forecasts have emerged as a key strategy to support the dynamic management of water resources. Effective dynamic management is expected to only increase in importance as water systems experience increased stress under climate variability and climate change. Despite advancements in short-range weather and long-range climate forecasts, there persists a gap between the theoretical value of forecasts to inform water resources management decisions and the actual utilization of forecast information by water managers. This dissertation focuses on the real-world application of forecast information in water resources, specifically in flood risk management and many- objective water reservoir management, to explore the relationship between forecast value and a variety of technological, operational, and social barriers that complicate the utility of forecast information. This work is highly motivated and guided by regional stakeholder needs. Each project is developed with end-user needs in mind, and findings and deliverables are designed to be utilized by water managers in their decision-making processes.

Over 26% of the world's land area and ~8% of its population depend on snowmelt as the primary water source. A typical example is the western U.S. (WUS), where snowmelt has been the center of streamflow research for the past two decades. Under climate warming, snow's contribution to streamflow will decrease, increasing the uncertainty of streamflow fluctuations and challenging streamflow forecasting and management that are based on traditional snow-based methods. Addressing these challenges requires a deep understanding of the linkages among warming, snowmelt, and other runoff-generating processes and how they affect future streamflow. In my dissertation, I take the WUS as an example, using hydrologic modeling and in-situ data to explore the following questions: 1. How does seasonal warming affect annual streamflow in different watersheds, and why? 2. What composes runoff during water-scarce seasons, and how does the composition change under warming? 3. What mechanism dominates annual runoff decline under warming in snow-affected areas, and how do its dynamics affect the evolution of runoff? In 1, I found and explained an asymmetrical pattern that controls annual streamflow response to seasonal warming, which indicates the cooler, inland region streamflow is more sensitive to warm season warming, whereas warmer, coastal region streamflow is more sensitive to cool season warming. I found this asymmetry is explained by the bell-shape variation of evapotranspiration-temperature sensitivity as a function of increasing temperature, filling a long-lasting gap in the sub-annual linkages between water and climate in WUS. In 2, I developed a custom-period water source partition algorithm that uses a handful of output variables from land surface models to quantify the fractional contribution of custom-period rainfall to custom-period streamflow. Using this algorithm, I detected an increasing contribution of seasonal rainfall to summer streamflow under warming, which shed light on the evolution of a new dynamic for summer streamflow generation in the water-short WUS. In 3, I explored the ongoing runoff decline under warming across major WUS snow-covered regions and explored the linkage between the evolving trend dynamics with changing snow. In three major snow-covered basins, I discovered a smaller warming-sensitivity of runoff under a warmer climate with fixed precipitation, which could break the long-lasting static mechanism paradigm that governs hydrologic dynamics and a more rigorous assessment of future streamflow. In summary, the dissertation provides important contributions to understanding ongoing and future runoff evolution in WUS snow-affected regions under a warmer future.

Abstract: Water resources in the Edmonton region are expected to be increasingly threatened by climate change and/or contamination in the coming decades. Currently, the sole source of water for the city of Edmonton is the North Saskatchewan River (NSR). This makes Edmonton vulnerable to changes in water supply from drought or contamination. A potential temporary secondary water source is groundwater. The groundwater resource in the Edmonton region with the most favourable prospects for large scale water withdrawal is buried valleys (channels). A steady state groundwater model is used to understand regional groundwater flow and the role of buried valleys in groundwater flow in the region. It includes dipping bedrock geology and surficial geology together with recently mapped buried valley extents. Findings help to characterize groundwater flow in the area, highlighting flow system features such as discharge areas, groundwater-surface water interactions and buried valley’s role in a regional flow context. The steady state model also provides a starting point for transient simulations. Transient simulations focus on the Onoway, Beverly and Stony channels. Results indicate the Beverly channel is the most favourable for large scale water extraction followed by the Onoway and the Stony channels respectively. The Beverly channel was able to supply 190 ML/day for 365 days, followed by the Onoway channel at 190 ML/day for 30 days, with the smallest extraction rate sustained by the Stony channel at 10 ML/day for 365 days.

Seasonal hypoxia in the Gulf of Mexico and harmful algal blooms experienced in many inland freshwater bodies is partially driven due to excessive nitrogen loading seen from agricultural watersheds. Within the Mississippi/Atchafalaya River Basin, many areas are underlain with karst features, and efforts to reduce nitrogen contributions from these areas have had varying success, due to lacking a complete understanding of nutrient dynamics in karst agricultural systems. To improve the understanding of nitrogen cycling in these systems, 35 months of high resolution in situ water quality and atmospheric data were collected and fed into a two-hidden layer extreme learning machine (TELM) to predict discharge and nitrate exports from a karst agroecosystem in the Inner Bluegrass region, to improve the understanding of nitrate dynamics in karst and determine the variables of influence driving nitrate loading in karst systems. Including atmospheric and soil moisture and temperature records to 100 cm in modeling resulted in the TELM providing accurate estimates of both nitrate concentration and flowrate (NSE=0.9328 and NSE=0.9363 respectively) and represented short term storm event hysteresis and diurnal signals in model predictions. The TELM also showed the variables most influential in training were the soil moisture and temperature parameters levels, pointing to the importance of focusing future work on understanding how temperature influences matrix-macropore interactions in the temperate karst environment. Finally, the ELM showed the fertilizer application data was not influential in model training, indicating that, at this study site, the fertilizer application has little control over nitrate loading. This should be studied further in other landscapes with higher rates of fertilizer application where alternative hysteretic patterns have been observed.

This dissertation explores the influence of extreme precipitation and the potential impacts of climate change on the vulnerable water resources of the southwestern United States. Specifically, it focuses on 1) the characteristics, origins, and impacts of historical extreme warm-season precipitation in the Lake Mead watershed, 2) improving existing bias correction techniques for projected future streamflows, and 3) investigating the vulnerability of California’s largest reservoir, Lake Shasta, to climate change under existing and adaptive operating protocols. Although the North American Monsoon (NAM) is the main driver of summertime climate variability in the American southwest, considerable knowledge gaps exist regarding its impact at the northern extent of the core region (northwestern Mexico, southern Arizona, and New Mexico). The first part of this dissertation catalogues historical extreme precipitation events in the Lake Mead watershed (located at the NAM’s northern boundary) and identifies unique synoptic drivers of extreme precipitation between the canonical NAM region and watersheds to the north. From here, the dissertation shifts its focus from the historical period to future climate projections. Motivated by a desire to connect bias correction techniques to the underlying dynamics within earth systems models, a novel statistical method is developed for projected streamflow wherein data are windowed based on hydrograph-relative time, rather than Julian day. This method yields improved preservation of original climate model data for both extreme and non-extreme events. Utilizing these bias corrected streamflow projections, and a simplified model of operations at California’s largest reservoir, Lake Shasta, developed by the author, coming threats to water supply and flood risk under existing operations and several forms of adaptive responses to climate change are analyzed. Compared to the historical period, we simulate 27% declines in carryover storage (storage on September 30th) at the end of the 21st century under a severe warming scenario if operations are left unchanged. Despite many simulated interventions favoring water supply over flood risk, historical levels of carryover storage were irretrievable at the end of the century under the warmer of the two warming scenarios examined in this study.

The Northern Rocky Mountains, home to the highest concentration of glaciers in the American West, are undergoing increased rates of climate warming, resulting in previously unseen ecological and hydrological outcomes. Globally, many glacier basins have experienced glacial recession to the threshold point of surpassing peak basin runoff, resulting in substantial decreases in local hydrological yield. Such findings call for models that do not alone examine glacial runoff but a complete examination of changes in the water budget. Alpine catchments are increasingly vulnerable to evapotranspirative losses due to climatic warming, and the rates of vegetation succession are often unable to keep up with the rate of warming. Basin scale analyses of glacial recession on streamflow are then confounded by ecohydrologic dynamics created by primary succession and the associated increase in evapotranspiration. In this study, I present a conceptual framework for modelling basin runoff in landscapes responding to paraglacial adjustment. The study goal was achieved by calibrating and running the Hydrologiska Byråns Vattenbalansavdelning (HBV) model in Swiftcurrent basin and investigating change across the basin water balance through baseflow analysis. The research findings indicate catchment scale changes in the timing and magnitude of the flow regime in the deglaciating Swiftcurrent basin, by employing HBV and empirical baseflow analysis. While most components of the water balance appear consistent across the study period, late summer baseflow values suggest the basin hydrology is undergoing changes, possibly a result of melt occurring earlier in the season. Ultimately, I advocate for an adaptable and accessible approach to understanding paraglacial basins by constructing an estimation of basin-scale water budgets.

Abstract: Northern rivers are affected by river ice processes for a significant portion of the year. This poses many challenges and opportunities to river ice engineers and geoscientists. Since 2009, several researchers have conducted a variety of river ice studies on the North Saskatchewan River through Edmonton, Alberta. This has resulted in a relatively comprehensive dataset which includes meteorological, hydrometric and river ice data. Analyses of these data have produced interesting results which are evidence of a highly complex ice regime. The conditions preceding and during freeze-up and break-up are highly variable. The University of Alberta’s River1D Ice Process model is used to investigate these phenomena by simulating the 2009-10 and 2010-11 winter seasons. The 29 km long study reach includes multiple bridging locations and the discharge from the Gold Bar Wastewater Treatment Plant (GBWTP). Simulation results are compared to the observed water surface elevation, ice front progression, surface pan concentration, border ice fraction, ice thickness, suspended frazil concentration, and water temperature data measured at several locations along the reach. Strong agreement between the observed and simulated data was achieved for an unprecedented number of river ice variables. The model can be sued as the foundation for future river ice studies in Edmonton and to help address specific problems or challenges that have been observed within the study reach.

Hydraulic models can provide efficient and cost-effective ways for water utilities to respond to changes in operating conditions (e.g., population dynamics, disasters), thereby increasing system resiliency during crises. Unfortunately, model development remains out of reach for many utilities due to high software costs, data needs, and/or personnel requirements. This study seeks to classify hydraulic modeling data needs, identify success factors and challenges associated with model development, and demonstrate the relevance of hydraulic modeling in a crisis, specifically, the COVID-19 pandemic. At the pandemic onset, development began on a hydraulic model, with the goal of understanding how shifts in spatiotemporal water demands impacted a water distribution system’s performance. Results indicate that the completed model can offer useful insight by identifying system vulnerabilities (e.g., stagnation). However, the data collection and processing challenges encountered (e.g., siloed collection efforts, lack of standardization, lengthy processing) reflect barriers to model adoption. The amount of time required to gather and process the necessary data (upwards of eight months in a best-case scenario) shows that model development cannot occur during a time-sensitive crisis, likely rendering any insight too late for use. Here, recommendations are made to address data-related challenges and support utilities in incorporating hydraulic modeling into emergency planning

Ground and surface waters are essential for human communities and ecosystems. They are complex interconnected systems and are largely controlled by climate and regional geology. The Lawn Hill region, northwest Queensland, Australia is subject to a semi-arid monsoonal climate and is situated on predominantly either carbonate tablelands or plains formed over siliciclastic units. This study analysed rock and water geochemistry, including major and minor elements and stable- and radio-isotopes (3H, 14CDIC¸14CDOC, δ13CDIC, δ13CDOC) and found the following trends of water-rock interaction and flow systems in the region. (1) Groundwater is vital for perennial surface waters. (2) When using chemical tracers to quantify groundwater discharge to surface waters, the volumes could be commonly underestimated if input concentrations are obtained from regional groundwater values, as found for Louie Creek. (3) Host geology is an important control on groundwater flow and chemistry. (4) Groundwaters from carbonate aquifers typically have a chemical composition controlled by dolomite dissolution, they exhibit minimal evapotranspirative enrichment, and have relatively fast recharge (mean residence times were generally

Chapter One examines how firms respond to changes in environmental regulations that rely on self-reporting. Routine natural gas flaring at oil wells in the U.S. has soared in the last decade as advances in hydraulic fracturing enabled oil production in previously unprofitable regions, leading to concerns over climate and health damages. What is the effect of environmental policy aimed at reducing gas flaring? How do responses in self-reported versus remotely detected flaring data compare? I employ a difference-in-differences approach comparing North Dakota to Montana wells before and after the policy implementation to estimate the effect of the policy on reported and remotely-detected flaring. I construct a novel monthly well level remotely detected flared volume dataset, that is comparable to administrative well level flared volume data between 2012-2019 in the Bakken Shale. I document both an unprecedented uptick in natural gas flaring and an increasing gap between self-reported and remotely detected flaring. During the first two years of the policy, wells reduced flaring in compliance with the policy and reported truthfully; however, in the last three years, compliance fell, and half the gains in reported flaring reduction are from misreporting. This paper fits into a growing body of literature utilizing newly available satellite data to evaluate the effectiveness of environmental policy and measure the activity of the oil and gas industry. This paper fits into a growing body of literature utilizing newly available satellite data to evaluate the effectiveness of environmental policy and measure the activity of the oil and gas industry. Chapter Two presents a novel hydrological approach to identifying and addressing nonpoint source pollution from agricultural runoff in national-scale river networks.Freshwater and coastal ecosystems worldwide increasingly suffer from eutrophication caused by nonpoint source agricultural runoff, resulting in detrimental environmental, social, and economic outcomes. The main challenge for policymakers in regulating and reducing nonpoint source water pollution is the difficulty in identifying the source of nutrient runoff and measuring whether policy changes effectively reduce pollution.Our paper addresses this problem through modeling pollutant flux in national-scale river networks and identifying which catchments exhibit higher nutrient loss at a spatially and temporally granular level.Our spatial approach combines publicly available water data and hydrographic methods to localize annual nitrogen and phosphorus based pollutant loads at the sub-watershed level in the United States Mississippi River Basin (USMRB) and the country of New Zealand between 1981 -- 2018.We found that the distribution of nitrogen and phosphorus pollutant loads are spatially heterogeneous even within the same region in the two watersheds that we evaluated. We found that average total nitrogen and total phosphorus runoff was consistently highest in the Southland and Gisborne Regional Councils in New Zealand. In the USMRB, average total nitrogen and total phosphorus runoff was highest in the central region of the watershed.Our results are useful for evaluating historical water pollution and establishing baseline pollutant loads, measuring changes in agricultural runoff over time, and monitoring the effects of changes in water quality regulations and land use activities at annual and sub-annual time steps.The use of our spatial model can be used to shed light on the effect of water pollution on human health, how water pollution differentially impacts disadvantaged populations and communities of color, and the distribution of water pollution under varying climate change scenarios. Chapter Three investigates whether there is evidence of multinational oil producers engaging in base erosion and profit shifting practices. I do this through estimating the responsiveness of reported profits of oil companies with respect to corporate tax rate differences. The elasticity of reported profits with respect to changes in corporate tax rates helps to elucidate whether companies employ artificial profit shifting techniques. My identification strategy exploits exogenous changes in corporate tax rate differentials for multinational corporations whose foreign subsidiaries pay taxes in the country where they are located. Identifying a significant and substantive corporate tax differential elasticity to reported profits will provide evidence that firms extralegally choose where to report their profits based on the locations of their subsidiaries, thereby artificially shifting their profits from high to low tax jurisdictions.

This dissertation makes new advances in multi-criteria decision analysis (MCDA) and MCDA-based multi-objective optimization (MOO) and applies these methods to new areas of sustainable sediment and water resources management. Chapter 1 briefly introduces some central themes of this dissertation. Chapter 2 presents a new method for identifying preference weights in MCDA decision models. Chapter 3 applies existing tools for MCDA to the new topic area of sustainable marine sand resource use. Chapter 4 presents a new version of the Dredged Material Management Decisions (D2M2) software and applies it to optimize dredged sediment placement for multiple objectives.In the new approach for preference weight identification presented in Chapter 2, a stakeholder or decision maker is observed playing a game (e.g., a serious video game) with a similar context to a real-world decision problem of interest. As the player make choices within the game, a record is kept of each chosen and non-chosen alternative and its performance data. After gameplay is finished, analysis is performed on the choice data from the gameplay log. Two approaches are demonstrated to best fit weight sets to the observed decisions. A brute force, enumeration approach evaluates all possible weight sets in a discretized weight space and an evolutionary optimization approach, with parameters tuned for a more explorative search, generates, evaluates, and evolves random weight sets within the continuous weight space. In an illustrative case study with a simple water management game, both approaches produce similar results showing a weight space of best fit. Tradeoffs between shorter and longer gameplay and analysis time affect the accuracy and completeness of the results. While further work is needed to validate the decision models inferred from gameplay against the decision models used in real life, this approach has promise for avoiding some cognitive biases and increasing the scalability of weight identification in MCDA applications.Chapter 3 applies MCDA to sustainably manage sand deposits (borrow areas) on the ocean floor that are dredged for fill material for coastal engineering projects such as beach nourishment. Borrow area users and managers have expressed concern that existing approaches are not sufficiently sustainable, e.g., do not adequately promote the long-term viability of borrow areas and balance environmental, social, and economic concerns. To remedy this, an MCDA workshop was held with stakeholders and subject matter experts from state and federal government, industry, and academia. Workshop participants were asked to develop an MCDA criteria hierarchy for evaluating the sustainable use of marine sand borrow areas, suggest metrics and scoring considerations for those criteria, list best management practices for sustainable borrow area use, and provide additional observations about existing challenges and future recommendations. Each of these products fills a gap in the literature for marine sand resource use.The D2M2 software advanced and applied in Chapter 4 creates MCDA-based MOO models of dredged material placement scenarios. This new version incorporates several features to better specify costs, benefits, and impacts and to support the modeler in developing useful solutions. It is applied in a case study using realistic site and management data for dredging and sediment placement along the Gulf Intracoastal Waterway (GIWW) near Galveston, TX. The site data are optimized in nine scenarios that vary the site network and weighting scheme for seven objectives that include financial cost, environmental impacts, and beneficial uses and effects. Results show tradeoffs between impacts and benefits, identify proposed sites most likely to be useful for system management, and highlight the need for additional placement capacity in the system over the 20-year timeframe, a need that can largely be filled through the creation of proposed beneficial use sites included in the model.

Nitrate and phosphate present in agricultural subsurface drainage water can impact surface water quality thus impacting the environment and human health by causing eutrophication and Methemoglobinemia in young infant. Biological denitrification and phosphate adsorption filters are treatments options that can help reduce nitrate and phosphate concentration from agricultural subsurface drainage before it can be discharged in surface water. The first objective of this dissertation was to determine the Michaelis-Menten kinetics model parameters for nitrate removal in bioreactors using the fresh, aged, and composted woodchips. The composted woodchips achieved a denitrification rate 2.4 times higher than the fresh woodchips which was in term achieved 2.9 times higher denitrification rate than the aged woodchips. Denitrification rates decreased at 5ºC compared to 22ºC for composted woodchips and fresh woodchips. The composted still performed better at low temperatures compared to fresh woodchips. The second objective was to determine the impact of different pairing configurations of woodchips and steel chips on nitrate and phosphate removal capacity and how the pairing configurations affect the DOC and iron leaching from the reactors. Three different reactors pairing configurations were evaluated in this project including woodchips followed by steel chips, steel chips followed by woodchips, and mixed woodchips/steel chips. The effect of low temperature (5℃) on phosphate removal capacity was studied. There was no statistical difference in nitrate and phosphate removed between all three reactors configurations. Three different reactors pairing configurations were evaluated in this project including woodchips followed by steel chips, steel chips followed by woodchips, and mixed woodchips/steel chips. The effect of low temperature (5℃) on phosphate removal capacity was studied. There was no statistical difference in nitrate and phosphate removed between all three reactors configurations.

Ecologically conscious watershed management is not a new concept. It presents numerous benefits but also incurs economic costs. This study posits that NYC presents an exemplary case for which other metropolitan areas can adopt in establishing a symbiotic relationship with its hinterlands. Both creating efficient allocation of scare resources and reducing overall anthropogenic impact on the biota. In comparing the effectiveness of capital investments in Green and Grey water infrastructure in seven upstate New York (NY) watersheds from 1962-1998, this paper uses a quasi-experimental regional approach to explore the benefits and trade-offs of water infrastructure capital investments and policy decisions. Thereby allowing for a more mutually beneficial and sustainable urban-rural relationship to develop.

Cambodia’s Tonle Sap Lake is the largest permanent freshwater body not just in Cambodia, but in Southeast Asia, and is also one of the world’s richest lacustrine-wetland ecosystems. Agriculture and fisheries provide the primary livelihoods of people living in the area. Despite a high abundance of natural resources, the area around Tonle Sap Lake is known to be one of the poorest areas in Cambodia, where most people derive their livelihoods directly from the resources provided by the lake. This study aims to assess the impacts caused by climate change on water resources and agricultural production in the basin by looking into future changes of streamflow of the tributary rivers, flood pulse and the paddy rice areas supported by the Mekong River’s flood pulse. For this study, six climate change scenarios were employed to assess future change in rainfall and river flow. They are the result of the combinations between three global circulation models (GFDL-CM3, GISS-E2-R-CC and IPSL-CM5A-MR) and two representative concentration pathways (RCP4.5 and RCP8.5). HEC-HMS was used for simulating rainfall and runoff for 11 sub-basins that feed the Tonle Sap Lake. HEC-RAS was used for computing inundation areas around the lake. Both models were calibrated and validated using data for the year 2000–2005 and 2006–2007, respectively. The results from HEC-RAS were exported in a format that enabled further analysis in GIS to examine changes to paddy rice areas at both the basin- and sub-basin scales. Both HEC-HMS and HEC-RAS model performances were evaluated using statistical indices NSE and R2. The indices indicated satisfactory performance for both simulation models with NSE > 0.40 and R2 > 0.60 for HEC-HMS and NSE > 0.60 and R2 ≥ 0.90 for HEC-RAS. The main findings in the study were the reduction of annual streamflow that is projected to occur in almost every sub-basin under all climate change scenarios up to the year 2030. The Dauntri sub-basin is projected to experience the highest streamflow decrease, up to 62.53%, while streamflow in the Sen and Boribor sub-basins showed a slight increase. The results from HEC-RAS suggest a decrease of flood pulse extent under all climate change scenarios. The magnitudes of decrease are almost the same for each scenario with an average decrease of around 10%. The Sen sub-basin showed the greatest reduction of flooded areas (13.82%) while Sangker was projected to decrease the least (2.00%). Though the Sen and Boribor catchments show an increase in streamflow, the increase is offset by the reduced flows in the remaining catchments, thus contributing less flow to the lake overall, leading to its reduced area. The results also suggest a decrease in paddy rice areas supported by the flood pulse. Stuang is the sub-basin with the highest reduction of paddy rice areas of up to 28.36%, while Sangker remains the sub-basin with the least reduction (2.67%). Some noteworthy implications arise from the main findings. The decrease of flows in the tributary rivers suggests an increase in drought risk and consequences for household water supply and surface irrigation that divert or extract water from those rivers. The change of the extent of flood pulse suggests that there will be lower nutrients and sediment loads and this would substantially impact the ecosystems in the lake and other connected parts. The reduction of paddy rice areas underscores the potential implications for social and economic development such as food insecurity, unemployment and economic impacts.

The effective management of water resources faces unprecedented pressures from growing demand and shifting climate among other stressors. Widespread issues of both water quantity and water quality affect many regions. One common problem facing many areas is the excess supply of nitrate (NO3) to receiving bodies such as aquifers, rivers, streams, and estuaries. Excess nitrate is linked to human activity and can have detrimental effects of human and ecosystem health. Addressing these issues and ensuring that humans and ecosystems have sufficient supplies of clean water requires a more complete understanding of the complex linkages between water quantity and quality across space and time. In this dissertation, I present four original studies across a range of scales investigating the flow of water across and through landscapes that have been altered by human activity. In each study I ask the fundamental question how does the magnitude, timing, and/or rate of water flow affect key water quality parameters? Chapters One, Two, and Three focus on investigating water quality improvements during managed aquifer recharge (MAR), a technique for improving groundwater supply and quality through targeted infiltration. In Chapter One, measurements of water quality parameters during controlled percolation experiments revealed that soil amendments could enhance nitrate removal during infiltration. In Chapter Two, column studies conducted on soil cores collected from MAR sites demonstrated that the rate of infiltration and the presence of a soil amendment were key factors controlling nitrate removal and affecting microbial community composition during MAR. In Chapter 3, we synthesized data from various scales to develop a novel, spatial model of nitrate removal during MAR based on soil and fluid properties. Finally, in Chapter Four, similar concepts are applied to the analysis of nitrate mobilization in streams and rivers of agricultural watersheds to analyze the patterns and timing of delivery of nitrate. Taken together, the studies serve to elucidate fundamental linkages between the hydrologic cycle and key biogeochemical cycles that have profound impacts on our understanding of water resource management for the health and well-being of humans and ecosystems.

Online continuous monitoring of water quality variables is a crucial aspect to ensure the correct performance in Water Resource Recovery Facilities. In the last few decades, with the advent of water reclamation and the use of new technologies to lower the energy consumption of processes, real-time measurements have gained a larger role in both process monitoring and control. In order to obtain on-line data, sensors and analyzers are essential, which technology in time have been improved to obtain reliable high-frequency measurements, and to optimize maintenance and costs of operation. Despite the improvements and the development of new technologies for measuring different water quality, sensors are often expensive and usually present problems of fouling, poor calibration, and lack of reliability. A common perception is that sensors represent the bottleneck for implementing online process control of wastewater treatment, especially in consideration of the harsh environment they are deployed and the number of water professionals sufficiently confident to rely entirely on them.In this dissertation we focused on ammonium sensors, typically based on Ion-Selective-Electrode technology, which are often found to incur into faulty behavior compared to other water quality sensors, but they have a large potential application for different monitoring and control systems. In this study we analyzed the field limitations of ISE-NH4+ sensors installed in different sections of the activated sludge tank at a full-scale treatment plant. Among the different field influencing factors, a special focus was given to the development of fouling on the sensor’s membrane, both in terms of composition of the film layer and effect on the functional behavior of the sensor when subject to fouling. The results show that the sensors presented a reduced accuracy when working in the lower ammonium range, due to the larger interference of cations like K+ and Na+, which exposes a limit to the possible deployment of these sensors for effluent monitoring. The fouling development was found to be increasing as a negative exponential against time, with a high content of Iron in the inert fraction. The sensor was affected by the fouling development, showing a negative drift in time, therefore leading to an underestimation of the ammonium reading. In consideration of the demonstrated low reliability of such sensors, especially in effluent installations and concurrently the high request for the use of ammonium sensors for effluent measurement, this study aimed at improving the sensor’s accuracy and reliability for low range installations. A machine learning methodology, based on the use of Artificial Neural Networks and Principal Component Analysis, was employed to develop a fault detection chart to promptly detect the occurrence drifts, biases and in general sensor faults. In detail, the fault detection methodology shows promising results, requiring only few hours to detect an incorrect calibration procedure and one day to detect a fouling drift of the sensor.

Accurate tracking of open-water evaporative losses, one of the largest consumptive uses of water in the Southwestern USA, is increasingly important with anticipated climate shifts toward longer and more severe droughts. A new open-water evaporation technique, the Collison Floating Evaporation Pan, (CFEP), was tested on Cochiti Lake, New Mexico, USA for one year with objectives being: identify the limitations and potential solutions to evaporation techniques; deploy, test the reliability, and validity of the CFEP and evaluate uncertainties in standard evaporation techniques; and improvements over prior evaporation techniques. The CFEP provided reliable evaporation measurements during sustained winds greater than 20 m/s. The accuracy of the CFEP was validated with an averaged percent difference of 1.72 of actual. The CFEP provided more accurate evaporation measurements than the five methods it was compared to with the Class A Pan underestimating evaporation by 910 acre-feet from May 13 through November 30, 2018.

Data science is a powerful tool that supports decision-making in sectors as diverse as healthcare, education, and finance. As the costs of natural disasters continue to rise against the backdrop of a changing climate, data science can play an important role in helping to identify climate-adaptive management pathways for natural resources systems. This dissertation will introduce specific data-driven approaches to identify robust pathways to reduce the impact of climate extremes in agricultural and water resources systems. Several pitfalls of statistical modeling for prediction in the era of climate change are introduced. Specifically, local surface meteorological variables are thermodynamically coupled in a way that impedes our ability to diagnose causality among a suite of meteorological variables in observational analysis of climate stress. Climate change will impact both large-scale dynamical and thermodynamical atmospheric processes, and will lead to non-linear shifts in local climate. A diagnostic-predictive framework is forwarded as a way to build statistical models that are in line with process-based understanding of environmental systems, and provide tailored information to support climate-adaptive management.

We use a bivariate sample selection model to address peer network effects on participation in and/or intensity of use of land being irrigated by alternative irrigation practices in the state of Arkansas. As groundwater in the state becomes more limited, the use of scientific scheduling, flowmeters, and more efficient row crop water application systems will allow producers to better manage water resources. We find relatively large, positive relationships between belonging to a peer network of the same irrigation practice and participation in that practice. Intensity of use of alternative irrigation techniques is mostly influenced by which crop type the practice is associated with and income.

Groundwater in the Kentucky Appalachian region is constrained by physiography and lithology. Lithostratigraphy, groundwater flow, and chemistry were delineated in the alluvial aquifer along the Cumberland River at H.L. Disney Training Center. To assess groundwater-river interactions and water quality, 11 monitoring wells were installed and sampled quarterly, plus the river and an existing bedrock well. Analytical results were evaluated for temporal and spatial trends. Collected soil cores were analyzed for bulk chemistry and grain size. Solute speciation and saturation indices were calculated and hydraulic conductivity estimated from grain-size analyses. Pumping and slug tests were performed to estimate hydraulic conductivity and hydraulic head was monitored using logging transducers for river stage comparison. Site lithology consists of loamy soils underlain by silty clay, transitioning downward to clayey-fine sands on friable sandstone/shale. Alluvium becomes finer-grained and has lower hydraulic conductivities with proximity to the river (10-9–10-2 cm/s). Meteoric recharge drives local groundwater flow from ridges toward rivers. Hydraulic head fluctuates with stage and temporary gradient reversals occur. Groundwater does not appear to be impacted by current land use. Wells have elevated iron and manganese concentrations; post-treatment, the alluvial aquifer may provide sufficient quality and rates of water to support onsite military activities.

In California, predicted climate warming increases the likelihood of extreme droughts. As irrigated agriculture accounts for roughly 80% of the state’s managed water supply, agriculture simultaneously shows high vulnerability to a warming climate while also offering the greatest opportunity to mitigate the impact of future droughts through adaptation strategies. This dissertation took advantage of hyperspectral Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and thermal MODIS/ASTER Airborne Simulator (MASTER) imagery collected by the HyspIRI Airborne Campaign over three years of a multi-year drought to measure agricultural response to changes in water availability and highlight the potential of remote sensing to aid in future agricultural management during water-limited times. In Chapter 2, I used the Random Forest classifier to classify crops into categories of similar water usages, assess the accuracy at which hyperspectral imaging could be of use for agricultural mapping, and evaluate changes in crop plantings with drought. The results showed overall field-level accuracies of 94.4% with AVIRIS, as opposed to 90.4% with Landsat OLI and 91.7% with Sentinel, indicating that hyperspectral imagery has the potential to identify crops by water-use group at a single time step at higher accuracies than multispectral sensors. With these classifications, I quantified shifts in crop plantings over drought and found a prioritization of high-value, perennial crops over lower-valued annual plantings. In Chapter 3, I used paired AVIRIS and MASTER imagery to assess crop stress in fruit and nut orchards using an approach that accounted for thermal complexity within the landscape, without the need for ancillary environmental measurements. I used surface characteristics obtained by AVIRIS data to model expected pixel temperatures. These temperatures were compared to measured temperatures as a way of assessing crop stress. Crop species showed significantly different temperature distributions independent of fractional cover (F(10, 33135) = 735, p < 0.001 for 2013, with similar results in 2014 and 2015). Crop residuals were found to increase as the drought progressed with average residuals of 0.14°C in 2013, 0.97°C in 2014, and 1.1°C in 2015. In addition, crops with the highest LST residuals had the largest reductions in yield during the study period. In Chapter 4, I analyzed spatiotemporal patterns of water vapor as they varied across a diverse and dynamic agricultural scene. I tested a set of hypotheses to better understand surface-atmosphere interactions and their ability to be evaluated through AVIRIS-derived column water vapor estimates. Results showed a positive correlation between crop water use and the frequency with which that crop showed directional alignment between wind and water vapor (r=0.42). We also found patterns of water vapor across the region that support advection of moisture across the scene. Results conclude that accumulation of water vapor above fields in these scenes is observable with water vapor imagery while advection at the field level is obscured by variable winds, differences in field structure and composition, and smaller-scale patterns of vapor. Overall, this dissertation enhances scientific and social ability to monitor and assist in food and water resource management with remote sensing during drought.

Financial incentives are traditionally relied upon by economists to influence behavior, however there is increasing evidence that non-market-based solutions may be preferable. This outcome particularly emerges when dealing with inattentive individuals or in situations where financial approaches face prohibitive legislation, budgetary restrictions, or political pushback. Understanding the impact of using non-market-based behavioral instruments, and how they compare to the use of market-based financial incentives, is crucial for governments to design effective public policy, as well as for private institutions to maximize profit. In this dissertation, I consider the setting of drought-prone California and its water consumers. The first two chapters contribute to the behavioral and environmental economics literature by exploring the impact of using non-market-based techniques – namely the use of information provision and moral suasion – in encouraging water conservation. The last chapter highlights the importance of finding effective approaches to water conservation by quantifying the impact of drought on economic outcomes.In the first chapter, I use a novel natural experiment and a randomized field experiment to investigate how information and financial incentives compare in influencing the behavior of inattentive customers. Specifically, I study how these two tools compare in encouraging water customers to fix in-home leaks. I find that information is a powerful, low-cost tool in swaying behavior, and can be even more effective than financial incentives. Importantly, the impact of a financial incentive depends on a customer’s typical bill-to-bill charge variance, such that high-variance customers are less likely to react to a financial incentive and respond more to a clear informational signal. Financial incentives under one standard deviation of customer bill-to-bill variation likely go unnoticed. In the observed setting of customers with in-home leaks, the average customer has a 30% relative standard deviation of the month-to-month bill and only responds to a bill increase of 50% or more. Further, the impact of financial incentives vary by customer income and are considerably less effective on customers with automatic bill payment. I also find that while sending information by mail is effective, delivery through email or text may be preferable in time sensitive situations and for encouraging the use of online resources.In the second chapter, I assess the impacts of using moral suasion via public appeals to encourage behavior change. As a case study, I analyze the effect of Governor Jerry Brown’s public pleas for water conservation in the face of California’s record-breaking drought. Using high frequency hourly consumption data at the household-level for the years 2012-2015, I conduct an event study to understand the level of short-term water conservation associated with these appeals. I find statistically and economically significant decreases in water consumption in the single-family residential sector of San Francisco in the two weeks following a well-publicized public appeals announcement. These short-term decreases range from 1.9 - 4.6% of total single-family residential water demand.In the third chapter, co-authored with David Sunding and Maximilian Auffhammer, we evaluate the effect of the drought on economic outcomes. In this study we use ex post impact assessment methods to measure the effect of drought on farm employment and harvested acreage for the fifth largest economy in the world – California. We find evidence of a statistically and economically significant relationship between surface water imports and both employment and harvested area. We also present evidence that the effects of drought are smaller in areas with better access to local water supplies, especially groundwater, and have declined over time. The latter observation is consistent with observed shifts in land allocation toward perennial crops and with increased reliance on groundwater extraction, particularly in dry years. These trends may not be sustainable in light of the State’s recent efforts to curb groundwater overdraft. Our results suggest that absent other interventions, the future effects of drought on economic outcomes in California agriculture could be even larger than those observed in the recent past.

The simulation and optimization of reservoir systems has attracted a great deal of attention in the field of hydrology and water resources management. Although many advances have been made, the gap between theoretical and real-world operation of reservoir systems still exists. Here, multiple tools and algorithms are proposed to bridge the existing gap to some extent. These tools are developed to aid decision makers, engineers, and scientists to understand, simulate, and improve the operational rules of reservoir systems.In this dissertation, I propose an optimization framework, titled shuffled complex-self adaptive hybrid evolution (SC-SAHEL), to optimize the controlled discharge from reservoirs. This new optimization tool can solve a wide range of optimization problems, using a self-adaptive search mechanism. The algorithm employs multiple search methods from different optimization tools and selects the most suitable method for the problem space. This process reveals the potential of each search mechanism during the course of the search and enhances the efficiency and effectiveness of the search. The SC-SAHEL framework is tested on multiple benchmark problems and showed superior performance in comparison to single search methods. The framework is applied to the Folsom reservoir to maximize hydropower generation by tuning the controlled discharge. The results showed that the SC-SAHEL algorithm is superior to other single search method algorithms for finding near optimum solutions. The results also demonstrated the robustness of the SC-SAHEL framework for solving a wide range of reservoir optimization problems.In addition to the optimization framework, a new data-mining algorithm, title generalized model tree (GMT), is proposed for simulating rule-based hydrologic systems. The new framework is developed based on the decision tree models and employs linear regression for prediction and model induction. The newly developed framework is tested on several benchmark datasets to compare its performance with other popular decision tree models. The framework can generate simple models to replicate different rule-based hydrologic systems. The simple structure of the inducted models makes them easy to implement and use in any programming languages and modeling framework. The framework is employed to simulate controlled discharge from multiple reservoirs across the Contiguous United States (CONUS). The results revealed the potential of the GMT framework for generating reservoir routing models. The models inducted by the GMT framework can be employed as a reservoir module within the hydrologic models, especially in large scale hydrologic modelling. In addition, the GMT framework model structure can reveal useful information about the underlying structure of the system. Hence, it can reveal information about importance of decision variables in the real operation of the reservoir systems.The proposed tools benefit stakeholders to understand and improve their management practices of reservoir systems. The simulation method reveals the hydrologic response of natural systems to historical reservoir operation through reservoir routing, while shed light on the importance of decision variable in real operation of the system. The optimization algorithm finds the optimum operational rules for the reservoir systems for the specified goal and objective. The outcome of these two algorithms can be used for evaluating reservoir management practices, while considering the hydrologic behavior of the watersheds.

My dissertation research investigates the spatial and temporal variability of water sources in the Arun watershed, a river basin in the eastern Himalaya, using a combination of geochemical and isotopic tools to assess the hydrologic and climatic processes that control water resources in the region. Broadly, I aim to answer the questions: (1) what are the spatiotemporal patterns of the Indian Summer Monson versus Winter Westerly Disturbance storm systems as they contribute to water supply, and (2) how do contributions of snowmelt, glacial melt, groundwater, and rain vary from local-to-regional scales in the eastern Himalaya? I address these questions by exploiting the natural variability in the geochemical and isotopic composition of meteoric water, which is controlled by distinct hydrologic and climatic processes. I explore these data across spatial scales that include the Tibetan Plateau headwaters of the Arun River, a high-elevation glacierized tributary, a low-elevation tributary, and the downstream outlet of the Arun River. In Chapter Two, I find that deuterium excess emerges as valuable tracer to partition regional precipitation systems while high sulfate levels are correlated to glacial melt source waters. I use these two tracers to qualitatively describe broad patterns in regional water supply for the Arun watershed and its tributaries, and highlight differences that arise from the varying hydroclimatic characteristics throughout the basin. In Chapter Three, I explore the variability in δ 18O and δD stable isotope values along a 6000-m elevation gradient and identify non-linear δ 18O and δD lapse rates in river water controlled by regional precipitation patterns and local mixing with glacial melt. In Chapter Four, I use a combination of dissolved ion concentrations and δ 18O and δD stable isotope values in a mixing model approach to partition streamflow during low-flow periods before and after the monsoon, and I identify the tracers that offer the highest utility to identify water sources in these Himalayan catchments. The dissertation provides evidence that seasonality and elevation act as strong controls on Himalayan water supply with low-elevation catchments dependent on monsoon rainfall and high-elevation catchments relying more heavily on glacial melt. Contributions of snowmelt to river discharge are seasonally discrete in the pre-monsoon season and spatially constrained to high-altitude regions or headwaters. I elucidate the potential applications of isotopic and geochemical tracers to differentiate snowmelt from glacial melt and to identify seasonal precipitation cycles. This work advances an emerging body of literature focused on Himalayan water resources and provides a practical framework to assess water budgets across local and regional scales. Critically, the dissertation provides insights and direction for future research to accurately quantify water resources in the Himalaya and, ideally, inform water management decisions.

The valuation of small fishing lakes is a vital component in understanding the importance of fishing and of recreational resources, in general. Knowing the values associated with such lakes is essential when prioritizing management activities. The overall value of a lake as a resource for human benefit is estimated as the summation of both instrumental and non-instrumental values. Instrumental values consist of economic and utilitarian values, as well as the values that a lake provides from ecosystem services. Non-instrumental values consider what the lake is worth as a good of its own, such as aesthetic, moral, and spiritual values gained by people because of the lake’s existence. In South Dakota, limited information of the economic and social values associated with small fishing and recreational lakes across the state has been collected. Many economic and social value studies have taken place on relatively larger lakes and reservoirs in the state; however, there is an abundance of small lakes that have yet to receive such research attention. With over 400 small lakes under state management, over time, many of these lakes will require costly renovation projects, such as dam repair, dredging, maintenance and replacement of docks and boat ramps, creation of fishing access, and general fisheries population management. Angler usage and economic information of the contributions of fishing and other water-related recreation at particular lakes of interest can help prioritize these expensive renovation projects. Moreover, the non-market values that local residents place on these lakes can be just as valuable to decision-making processes as the associated economic information. When combined, the information gathered from these lakes will contribute to better economic and social value estimates of similar lakes across South Dakota, and even across the United States. The economic evaluation of small recreational lakes also provides more precise measurements of recreational value when conjoined with already existing valuation data from relatively larger and higher use lakes. While currently published economic information has been useful in influencing management and policy decisions, the process in which data have been collected has not provided an accurate representation of the economic activity resulting from small fisheries within a region. Several other studies in South Dakota have targeted larger, more impactful fisheries resources for economic analyses; however, the economic value of the fishing industry becomes even more substantial with the addition of over 400 small lakes across the state. With few nearby opportunities for anglers to fish at larger lakes and reservoirs, the importance of quality fishing opportunities at nearby small fisheries could be sizeable, meaning that the collective economic value of these fisheries may be quite considerable. Recognizing the lack of information on this topic, I initiated this study to better understand the share that small fisheries have in the overall economic activity related to the fishing industry in South Dakota. For my first goal, the economic activity of seven small, South Dakota fishing lakes was estimated by using the expenditures during angling trips to these individual lakes in 2016. In particular, I wanted to: (1) estimate angler use, (2) estimate the extent of the total economic activity (TEA) associated with small fisheries, and (3) provide economic and use information that may be important to managers in determining future management priorities. The economic activity associated with angling visits to seven small fisheries in South Dakota was estimated using IMPLAN software. The average economic activity associated with fishing individual lakes in 2016 was $35,369/lake, supporting an average of 0.48 jobs and creating $5,572 in tax revenue. I observed that lakes with the highest proportion of ice fishing pressure also had the greatest associated economic activity, even though several of these had the lowest overall fishing pressure throughout the year. In addition to economic activity, zone of influence for each lake was estimated and compared with the proximity to urban centers. The inclusion of economic information from small fisheries may play an important role in influencing key strategic planning efforts by management agencies and in estimating the overall economic importance of angling on broader scales. Further, this study provides evidence of the importance of community events, such as fishing tournaments, in increasing the TEA of a small fishery and that these small fishing lakes are important assets to local communities. This study also indicated that special management strategies, such as the stocking of a catchable-size popular sportfish, can generate excitement around a fishery that may increase its use and economic activity. While collecting the monetary value on a resource seems to be the most popular method for determining how important a resource is to a region, perhaps the value of inland fisheries transcends economic statistics. Inland fisheries can also serve a crucial non-monetary role in contributing to the overall well-being of individuals by providing opportunities to form connections between humans and nature. Freshwater fisheries provide a wide array of ecosystem services that are important to individuals, society, and the environment, which include: food security, economic security, empowerment, cultural services, recreational services, human health and well-being, knowledge transfer and capacity building, ecosystem function and biodiversity, aquatic “canaries,” and “green” food opportunities. The ability to understand these non-market values, and the extent to which they contribute to the overall value provided by a small lake is a critical component in any decision-making process pertaining to management activities and priorities, as well as when deciding additional stakeholders that are necessary to include in these processes. For my second goal, I determined the importance of small fishing lakes to the overall quality of life of residents living in nearby communities in South Dakota. My objectives were to (1) measure the recreational activities and other uses provided to residents by lakes near their local communities, (2) measure the attitudes and values of residents towards the lakes that are near their communities, and (3) determine the uses, respondent characteristics, and attitudes towards these lakes that are best at predicting the importance of the lakes to local residents’ overall quality of life living in their communities. I used multiple linear regression analysis to identify that the most important predictors to lakes’ importance to local residents’ quality of life were: “lake is an important community resource,” “lake is a place I enjoy visiting,” “the number of different activities participated in at lake,” and “the lake is important to local businesses.” These 4 predictors were positively related to the contribution of lakes to residents’ quality of life. My findings provide empirical evidence for the desire to incorporate community participation and economic growth objectives into management plans for local lake resources. Realizing the diversity of recreation and leisure opportunities that lakes and adjacent lands can provide may be a simple, but critical, step in increasing economic opportunity for local regions and for providing a place for communities to hold events and ceremonies. Managers of these resources may find that agency-community collaboration, and careful co-management, can provide positive outcomes in the form of increased satisfaction among users and local communities, as well as increased overall use of the resources. Not only do these lakes contribute to economic value through angling opportunities, they also contribute in the form of non-market social values, such as increased community involvement, expanded recreational opportunities, and a greater overall quality of life. Managers of small recreational lakes must select appropriate survey methodologies in order to collect precise, accurate, and unbiased information from their constituents regarding the lakes’ economic and social valuations. Traditional survey approaches for gathering information from stakeholders have relied on on-site, mail, or telephone surveys. However, the ability to administer surveys quickly and with relatively low cost using the internet has become a popular method among managers and researchers. The rapid onset of internet surveys as a method for collecting angler information has provided limited time to assess the quality of the data being produced. For my third goal, I compared the quality of data collected using on-site, mail, and internet survey data from the 2016 fishing year. More specifically, my objective was to determine the ability of internet surveys to estimate fishing pressure at small South Dakota lakes (evaluated with data estimated using on-site surveys of fishing pressure). A secondary objective was to compare three metrics (age, gender ratios, and satisfaction of anglers’ fishing experiences) across survey methods to demonstrate how these metrics can vary across survey methods and sampling frames. Results indicate that angling pressure estimated from internet surveys were found to be 2.2 times greater than estimates from on-site surveys across all seven lakes; however, the proportion of angler days relative to the other lakes within the study were not significantly different between on-site and internet survey methods (p = 0.91). Internet surveys may have been subjected to recall error and nonresponse bias, which would likely cause a large multiplier effect during extrapolation. I also found that angler satisfaction on a scale from -3 to 3 was significantly different among on-site surveys (1.46 ± 0.07) and internet surveys (-0.04 ± 0.08). This is likely due to the interpretation of two different metrics based on the recency of the fishing experience that the anglers are being asked to rate. The mean age of internet survey respondents was significantly different (p < 0.001) than the age of mail survey respondents (49.6 ± 0.2 and 55.6 ± 0.7, respectively). Internet respondents may have been younger than mail survey respondents as a result of internet illiteracy, and lack of internet usage by older participants. The proportion of male respondents (vs. female) for each survey method were 94.1% (on-site), 65.0% (mail), and 88.3% (internet), which were all significantly different from each other (p < 0.001). The gender proportions also all differed from the distribution of anglers who had purchased a South Dakota fishing license in 2016 at 78.4% males and 21.6% females. Differences in gender ratios may have been caused by the topic of the survey being administered. As internet surveys become more prevalent, researchers and managers must use caution when considering these tools. Internet surveys are a relatively cheap and efficient method of collecting angler data when used properly. However, methods such as on-site and mail surveys should be considered in specific situations that evoke the biases and errors that are common with internet surveys, as described by this study.

This dissertation contains three distinct empirical chapters in applied energy and environmental economics. Each chapter focuses on a unique set of research questions, methods, and data. The unifying motivation therein concerns the development of renewable or alternative low-carbon energy sources as a policy response to the challenges of climate change mitigation, local and regional environmental quality issues, and energy security concerns. Economic and environmental evaluation of the energy policies coupled with understanding energy use patterns is of paramount importance. Together, the empirical chapters focus on demand, supply, and policy aspects of energy markets in the United States (US). First, Chapter 2 evaluates the impacts of the Renewable Portfolio Standard (RPS) on renewable electricity capacity. RPS is a state-level policy that requires electricity suppliers to include a certain proportion (or quantity) of renewable electricity in their total electricity sales over a specified time period. The chapter employs a fixed-effects panel regression model and a spatial econometric methodology using panel data spanning 47 states between 1990 and 2014. Thus, and importantly, the analyses incorporate salient spatial and temporal heterogeneities of RPS (i.e., varying RPS features across states and years). The results illustrate that the RPS has driven a 194 MW increase in overall renewable capacity (representing more than one third of the average electricity capacity developed between 1990 and 2014 in 47 states). The results also suggest that the impacts of RPS, while exhibiting spatial dependencies, vary depending on the renewable energy source. RPS positively impacts renewable electricity capacity, the share of renewable electricity capacity in total electricity capacity, as well as the shares of solar and wind capacity in total electricity capacity (the impacts become 1.3 times larger for solar and about two thirds fold larger for wind with reference to their average counterparts). However, the impacts of RPS are not statistically significant for biomass or geothermal resources. With the consistent patterns of the impacts of RPS across modeling scenarios, RPS adoption or lack thereof in different states, policy age, provision of renewable energy certificates (REC), and annually mandated obligations for renewable electricity in the overall electricity mix are among the critical factors which determine the efficacy of RPS. The positive impacts of RPS on solar and wind capacity are consistent with the relatively emphasized focus of RPS legislation across states which serves to prioritize these two renewable energy sources. Notwithstanding limitations in the available data (and the possibility that improvements in this respect over time would enable a more nuanced and higher-resolution investigation), the current findings provide guidance on how RPS is performing. The significantly positive impact of flexible REC provisions (allowing REC to be generated in any state), coupled with spatial spillover effects indicate the interstate marketing possibilities of renewable energy (and energy credits). The results (with respect to the significant contribution of different RPS attributes) suggest that the critical role the state level policies can make to meet national level goals about climate change and energy mix. More specifically, the results imply that scaling up RPS proliferation across the states (guided by policy treatment effects, coupled with spatial dependencies of both the RPS and renewable electricity) and specifying RPS mandates by renewable energy sources (guided by significantly positive impacts for solar and wind), at least up to the point where renewable energy sector obtains efficiency gains (economies of scales and allocative efficiency) or to the situation where better alternative to the RPS becomes available (e.g., market based carbon pricing policy, which can be least-cost carbon mitigation mechanism), can play an important role in generating transformative advances in renewable electricity sector. Next, Chapter 3 reports on an economic and environmental assessment to determine the optimal manure management strategy for large dairies. More specifically, a cost-benefit analysis and a life cycle assessment are carried out based on publicly available secondary data, motivated by the fact that improper management of dairy manure can result in adverse environmental and public health impacts. The results illustrate the comparatively high economic and environmental benefits associated with an integrated framework of bioenergy production as an alternative approach to manure management. Analyses are conducted under several scenarios (exploring the potential market for nutrients and greenhouse gases), all of which confirm that co-producing bioenergy in this context is more profitable than traditional on-site management approaches. The results imply that the livestock sector can maximize economic and environmental gains by integrating nutrient recovery and bioenergy production in alternative manure management considerations (rather than simply considering dairy manure as a waste disposal problem). The final empirical investigation, Chapter 4, explores the temporal and spatial variation of sectoral natural gas demand in the US. A fixed-effects panel regression model is configured to analyze monthly data between 2001 and 2015. The results demonstrate the inelastic price responses at state, regional, and national levels across natural gas consumption sectors in the US, reflecting the importance of natural gas in contemporary energy systems. The implication is that price based policies, such as energy efficiency standards or energy saving targets in building codes, in the natural gas sector may not be effective (but, since the magnitudes of price elasticity vary across economic sectors, states and regions, efficacy of such price based policies will vary across these different dimensions). On the other hand, the inelastic price responses may reveal resiliency (i.e., stable market) of natural gas market to the changes in natural gas prices that may be driven by policy changes in other segment of the energy market (e.g., renewable energy supporting policies may increase natural gas prices). The resulting implication can be that natural gas that holds critical significance in the contemporary energy system from both environmental and economic perspectives can also serve as a transition fuel. The statistically significant weather impacts in terms of heating degree days (HDD) and cooling degree days (CDD) revealed in this analysis are consistent with the extant energy demand literature, where higher HDD stimulates greater consumption of natural gas in the residential sector while CDD appears to increase natural gas consumption for electricity production. The impacts with regard to weather attributes (HDD and CDD) also help to design informed policies to achieve various energy management goals (e.g., attaining energy efficiency or promoting alternative clean energy by quantifying the repercussions of changes in consumers’ responses to natural gas demand across climatic seasons in the energy market stability). Collectively, these empirical chapters offer novel and important implications concerning energy market structures (supply and demand aspects), the environmental and economic assessment for renewable energy production potentials, and the policy responses, which have been or should be designed, to ensure the multi-dimensional sustainability of complex energy systems.

This dissertation contributes to the assessment of new scientific developments for multi-objective decision support to improve multi-purpose river basin management. The main insights of this work highlight opportunities to improve modeling of complex multi-purpose water reservoir systems and opportunities to flexibly incorporate emerging demands and hydro-climatic uncertainty. Additionally, algorithm diagnostics contributed in this work enable the water resources field to better capitalize on the rapid growth in computational power. This opens new opportunities to increase the scope of the problems that can be solved and contribute to the robustness and sustainability of water systems management worldwide. This dissertation focuses on a multi-purpose reservoir system that captures the contextual and mathematical difficulties confronted in a broad range of global multi-purpose systems challenged by multiple competing demands and uncertainty. The first study demonstrates that advances in state of the art multiobjective evolutionary optimization enables to reliably and effectively find control policies that balance conflicting tradeoffs for multi-purpose reservoir control. Multiobjective evolutionary optimization techniques coupled with direct policy search can reliably and flexibly find suitable control policies that adapt to multi-sectorial water needs and to hydro-climatic uncertainty. The second study demonstrates the benefits of cooperative parallel MOEA architectures to reliably and effectively find many objective control policies when the system is subject to uncertainty and computational constraints. The more advanced cooperative, co-evolutionary parallel search expands the scope of problem difficulty that can be reliably addressed while facilitating the discovery of high quality approximations for optimal river basin tradeoffs. The insights from this chapter should enable water resources analysts to devote computational efforts towards representing reservoir systems more accurately by capturing uncertainty and multiple demands when properly using parallel coordinated search. The third study extended multi- purpose reservoir control to better capture flood protection. A risk-averse formulation contributed to the discovery of control policies that improve operations during hydrologic extremes. Overall this dissertation has carefully evaluated and advanced the Evolutionary Multiobjective Direct Policy Search (EMODPS) framework to support multi-objective and robust management of conflicting demands in complex reservoir systems.

The Yaqui River Basin (YRB) is located in the semi-arid state of Sonora in northwest Mexico. This watershed flow is controlled by three reservoirs: Angostura, Novillo, and Oviachic. In order to assess and improve the management of the Yaqui reservoir system, a daily reservoir operation model was developed. This model is composed of a semi-distributed daily watershed simulation combined with an optimization model. The hydrologic simulation was developed using the Hydrologic Modeling System (HEC-HMS) developed by the US Army Corps of Engineers (USACE) Hydrologic Engineering Center. This simulation framework can estimate the water availability in different regions of the watershed. The HEC-HMS model was integrated to a nonlinear optimization model that estimates the water allocation in order to satisfy the competing water demands from different users according to water rights established in Mexico's National Water Law. The optimization model is developed using the General Algebraic Modeling System (GAMS). The communication between HEC-HMS and GAMS was completely automated via Python scripts for time efficiency reasons.Different hydrological forcing (precipitation, temperature, and solar radiation) scenarios were applied to the HEC-HMS simulation: (1) a network of daily ground observations from Mexican water agencies during the historical period of 1990-2010, (2) gridded fields from the North America Land Data Assimilation System (NLDAS) at 12 km resolution during the same simulation period, and (3) bias corrected NLDAS fields. The NLDAS forcing and bias corrected NLDAS performed better for Angostura and Novillo whereas ground observation datasets provided the best simulation for Oviachic. The simulated reservoir releases were compared to ideal releases at the three reservoirs to generate confidence in the simulation tools. It was concluded that authorized water allocation is unable to satisfy all users’ demands. The simulated water allocation satisfied these demands; therefore the model could be used to assist local reservoir operators make decisions.

This research compares Gravity Recovery and Climate Experiment (GRACE) groundwater storage (GWS) and root zone soil moisture (RZSM) percentiles to measured data, other drought indicators (DIs) and indices, and stakeholder observations for the purpose of assessing the feasibility and usefulness of these products to detect drought conditions. GRACE percentiles were directly compared to historic groundwater percentiles at 89 Nebraska well locations. Spatial time-series correlations over CONUS were performed between GRACE GWS and RZSM and the U.S. Drought Monitor (USDM), Standardized Precipitation Index (SPI), and soil moisture parameters from several North American Land Data Assimilation System (NLDAS) models. A survey of stakeholder observations during a 2016 flash drought event centered on Montana, Wyoming, South Dakota, and Nebraska was also compared to GRACE percentile data to analyze drought onset timing, geographic coverage, and severity. Overall the results show GRACE GWS has similar spatial and temporal agreement over the well period of record, and generally has the expected negative correlation relationship with observed groundwater, but it does not accurately reflect historic percentiles in Nebraska. GRACE GWS and RZSM have moderate correlation with USDM, and high correlation with SPI, and NLDAS models over the entire U.S. with notable regional and seasonal patterns. SPI accumulation period also plays an important role in correlation strength for both RZSM and GWS with the best agreement seen at 3-month and 12-month accumulation periods, respectively. GRACE RZSM time-series data closely matches stakeholder observations of decreasing soil moisture availability, while observations of decreasing water levels were not as closely matched by GWS. When analyzed as an average over all responding zip codes, RZSM showed an early warning trend up to six weeks prior to observed reports. These results indicate GRACE percentiles are promising drought indicators that can be used as a monitoring and early warning system by decision makers. Advisor: Tsegaye Tadesse

Snowmelt contribution to streamflow in the western United States is a critical supply of fresh water. The most widely applied operational model for estimating snowmelt utilizes the temperature index model which is based on empiricism and ground data. This work aims to advance our capability for estimating snowmelt for both clear and cloudy weather conditions using a ground calibrated physically based modified radiation balance that utilizes satellite data. The robustness of a modified radiation balance for computing snowmelt depends on reliable estimates of both long and short-wave radiation. I tested my model estimations of snowmelt against daily measurements of snow water equivalent (SWE) reduction at snow pillows from 129 locations over a 14-year period in the snowmelt dominated region of the Sierra Nevada. For clear-sky conditions (n ~ 25,000), I found that the temperature index model achieved an R2 = 0.52 (RMSE =9.7 mm/day;) with remotely sensed LST as an input and R2=0.48 (RMSE = 10.1 mm/day) using measured air temperature (Ta) from weather stations. The modified radiation balance model achieved an R2 = 0.72 (RMSE = 7.4 mm/day) with a fixed atmospheric emissivity, while a further refinement of an emissivity calculated from satellite-derived precipitable water resulted in R2 =0.75 (RMSE = 7.0 mm/day).In order to estimate shortwave radiation during cloudy days, I first constructed a simple binary cloud index based on inference of clouds from ‘missing’ MODIS LST data, which when regressed against daily shortwave ratio, yielded a regression equation with a correlation coefficient of R2 = 0.40 and an RMSE = 0.21. For an improved method, I used cloud optical depth (COT) and cloud mask (MOD35) data from MODIS 06C6 and found that with an exponential decay equation the regression with shortwave ratio led to a correlation coefficient R2 = 0.72 and a lower RMSE=0.14 making this method the more robust the two. For estimating the long-wave radiation, a closer examination of data on directly measured longwave radiation at one individual station revealed that measured air temperature is a better predictor of long wave compared to the satellite based LST. I found that the relation between daytime Ta and MODIS LST, as well as the diurnal LST swing, was influenced by surface characteristics such as canopy cover. I used the findings to introduce an LST “swing factor” into a linear equation for modeling daytime Ta based om LST. Utilizing Ta modeled from LST the long-wave radiation model performance improved significantly compared to a model based directly on LST. I extended my snowmelt model to include cloudy-days based on temporal extrapolation of LST data and an emissivity cloud-adjustment based on remote sensed cloud properties. With the cloud adjustments for both short- and long-wave incorporated in the snowmelt model, I added several physical factors over the course of 11 model runs. These included the effect of canopy in the local environment and a simple albedo model, that can cause spatial and temporal variations in the radiation load. The addition of cloudy days increased the data sample size significantly (n=58,077), with the final model run achieving an R2 = 0.68 with an RMSE= 7.0 mm/day. I achieved my goal of increasing the physical basis of the model for estimating snowmelt in both clear- and cloudy sky conditions, and for modeling the radiative effect of clouds without compromising model capability for estimating snowmelt at the snow sensor scale. In the course of my research, I was also able to identify several promising paths for future work for improving the physical basis and accuracy of the model.

During the modern era, the urbanization of water has been facilitated by various privileged discourses, which valorize major engineering interventions for the sake of continued urban growth. This research examines discourse surrounding the 2-th Century proposal and construction of a reservoir near the then-tiny farming community of Grapevine, Texas, for the benefit of urban interests. I argue that urban interests produced Grapevine space as nothing more than a container for city water, by rendering meaningless any conception of space that was not directly articulated with urban economic networks. Modern discourse collapsed Denton Creek space from a watershed and landscape into a dimensionless node in the urban space of flows. In return, rural inhabitants were encouraged to progress and to modernize their own spaces: to become urban. Whereas urban discourse entails an implicit spatial imaginary of networks, I deploy the conceptual framework of settler colonialism to show that a core-periphery relationship remains relevant, and is not reducible to a network spatial ontology.