Climate change and human activities alter the hydrologic systems and exerted global scale impacts on our environment with significant implications for water resources. Climate change can be characterized by the change of precipitation and temperature, and both precipitation pattern change and global warming are associated with the increase in frequency of flooding or drought and low flows. With increasing water demand from domestic, agricultural, commercial, and industrial sectors, humans are increasingly becoming a significant component of the hydrologic cycle. Human activities have transformed hydrologic processes at spatial scales ranging from local to global. Human activities affecting watershed hydrology include land use change, dam construction and reservoir operation, groundwater pumping, surface water withdrawal, irrigation, return flow, and others. In this thesis, the hydromorphology (i.e., the change of coupled hydrologic and human systems) of the Econlockhatchee River (Econ River for short) is studied. Due to the growth of the Orlando metropolitan area the Econ basin has been substantially urbanized with drastic change of the land cover. The land use / land cover change from 1940s to 2000s has been quantified by compiling existing land cover data and digitizing aerial photography images. Rainfall data have been analyzed to determine the extent that climate change has affected the river flow compared to land use change. The changes in stream flow at the annual scale and low flows are analyzed. The Econ River has experienced minimal changes in the amount of annual streamflow but significant changes to the amount of low flows. These changes are due to urbanization and other human interferences.

The Environmental Justice (EJ) movement has long highlighted the disproportionate exposure to environmental hazards experienced by Black, Indigenous, People of Color (BIPOC) and low-income communities across the country. Environmental practitioners have recently focused on utilizing EJ screening tools, which combine environmental and social data to visualize vulnerable communities, to begin to address environmental injustice rampant in BIPOC and low-income communities. This project explores EJ theoretical frameworks and the historical context of social oppression and environmental pollution in the Elizabeth River watershed (ERW) of Virginia to: 1) understand the social, political, and economic context behind environmental injustice; and 2) generate goals to address environmental injustice with a particular focus on utilizing EJ screening tools. This project highlights five EJ theoretical frameworks that can be used to explain disproportionate exposure to environmental hazards: 1) Racism and Discrimination; 2) Exploitation, Manipulation, Enticement, and Intimidation; 3) Institutional Practices; 4) Economics; and 5) Physical Characteristics and provides an overview of the history of the ERW to highlight the operation of these frameworks. Further, this project suggests three major goals to address environmental injustice: 1) empowering communities through equitable and just community engagement; 2) mapping distributions of environmental hazards, social factors, and institutional practices using EJ screening tools; and 3) ensuring that environmental amenities, burdens, and practices are equitably distributed and target vulnerable communities using EJ screening tools. This project serves as a framework for exploring the social, political, and economic contexts that give rise to environmental injustice and how EJ screening tools can be used to begin addressing them.

Uncertainty in climate change plays a major role in watershed systems. The increase in variability and intensity in temperature and precipitation affects hydrologic cycle in spatial and temporal dimensions. Predicting uncertainty in climate change impacts on watershed systems can help to understand future climate-induced risk on watershed systems and is essential for designing policies for mitigation and adaptation. Modeling the temporal patterns of uncertainties is assessed in the New England region for temperature and precipitation patterns over a long term. The regional uncertainty is modeled using Python scripting and GIS to analyze spatial patterns of climate change uncertainties over space and time. The results show that the regional uncertainty is significant in variation for changes in location and climatic scenarios. Watershed response to climate change under future scenarios is assessed using hydrologic simulation modeling for the Connecticut River watershed. Changes in water budgets are assessed for each of the subbasins using spatial analysis and process modeling using GIS and Soil and Water Assessment tool (SWAT). The results show that climate change uncertainty in precipitation and temperature can lead to uncertainty in both quantity and quality in the watershed system. A spatiotemporal, dynamic model was applied to subbasins within the Chicopee River Watershed to estimate climate change uncertainty impacts at a micro scale. These changes were assessed relative to changes in land use and climatic change. The results show that there is a significant potential for climate change to increase evaporation, watershed runoff and soil erosion rates and this varied with climate change uncertainty. Finally, water sustainability gradient analysis was applied to the Volga River watershed in Russia to assess potential climate change impacts by combining with downscaled Global Circulation Model estimates and spatial assessment. Results show that runoff and evapotranspiration are projected to increase with potential for more localized floods and drought events effecting both water resources and food supply. Overall results show that climate change uncertainty can impact watershed systems and spatial and temporal assessments is important for developing strategies for adaptation to climatic change conditions at local and regional scales.

Groundwater water resources must be accurately characterized in order to be managed sustainably. Due to the cost to install monitoring wells and challenges in collecting and managing in-situ data, groundwater data is sparse in space and time especially in developing countries. In this study we analyzed long-term groundwater storage changes with limited times-series data where each well had only one groundwater measurement in time. We developed methods to synthetically create times-series groundwater table elevation (WTE) by clustering wells with uniform grid and k-means-constrained clustering and creating pseudo wells. Pseudo wells with the WTE values from the cluster-member wells were temporally and spatially interpolated to analyze groundwater changes. We used the methods for the Beryl-Enterprise aquifer in Utah where other researchers quantified the groundwater storage depletion rate in the past, and the methods yielded a similar storage depletion rate. The method was then applied to the southern region in Niger and the result showed a ground water storage change that partially matched with the trend calculated by the GRACE data. With a limited data set that regressions or machine learning did not work, our method captured the groundwater storage trend correctly and can be used for the area where in-situ data is highly limited in time and space.

High latitude mountain environments are experiencing disproportionately adverse effects in a currently changing climate. The Gulf of Alaska (GoA) region is an exemplar of this. Dramatic shifts are occurring in the region’s freshwater reservoirs as glaciers retreat more with each passing year. Research in the region places much focus on observing and predicting climate driven shifts in glacier mass balance, surface discharge, and associated nutrient fluxes to the ocean. On the other hand, coastal groundwater discharge (CGD) is given very little attention. Global and near-global estimates of CGD indicate variable results spanning an order of magnitude. Focusing on regionally specific processes may provide more reliable estimates of CGD and allow isolation of CGD hotspots. This is of particular importance in the GoA region where complex topography, geology, and climate are coupled with recharge derived from rain, snow, and ice. I estimate CGD to the GoA with a water balance that integrates high temporal and spatial resolution recharge inputs and distinguishes between high conductivity surficial deposit and bedrock catchments. I find that CGD contributes nearly 3% of the total freshwater flux to the GoA, equivalent to a mean annual flux of 20.8 km3, and that CGD has been increasing by 0.5%/year over the past 4 decades. Although freshwater discharge to the GOA is well-constrained, the importance of fresh CGD to the GoA has, thus far, been overlooked.

京都大学 / 新制・課程博士 / 博士(地球環境学) / 甲第24953号 / 地環博第244号 / 新制||地環||48(附属図書館) / 京都大学大学院地球環境学舎地球環境学専攻 / (主査)教授 西前 出, 准教授 淺野 悟史, 教授 小林 広英 / 学位規則第4条第1項該当 / Doctor of Global Environmental Studies / Kyoto University / DGAM

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There are many different controlling factors on the partitioning of rainfall into runoff. However, the influence of each of these controls varies across different temporal scales. Consequently, numerous water balance models have been developed in the literature for application across various time scales. These models are usually developed for a particular time scale so that the controls with the greatest influence on rainfall partitioning are captured. For example, the SCS curve number method was developed to simulate direct runoff at the event scale; the "abcd" model was developed as a monthly water balance model; and the Budyko model was developed for long-term water balance. More recently, the proportionality hypothesis, which traces its origins from the SCS curve number method, has been identified as the commonality between these three hydrologic models, suggesting that this hypothesis may be the unifying principle of hydrologic models across various time scales. The objective of this thesis is to develop a conceptual hydrologic model structure for continuous simulations for multiple time scales. The developed model is applicable to daily, monthly, and annual time scales. Direct runoff is computed by a proportionality relationship in the SCS curve number method. In the "abcd" model, evapotranspiration and storage at the end of each time period are computed by a proportionality relationship, however evapotranspiration is computed based on an exponential relationship of storage and potential evapotranspiration while base flow is computed based on a linear reservoir model. In the Budyko model, runoff and evapotranspiration are computed by a proportionality relationship. The primary difference with the proposed model in this thesis in comparison with the other three water balance models is the application of the proportionality hypothesis to the partitioning of surface runoff and continuing abstraction as well as the partitioning of continuing evapotranspiration and subsurface flow. The proposed model structure is implemented in Matlab. The developed model includes six parameters, which are estimated for 71 case study catchments in the United States using a genetic algorithm. The model performances at the daily, monthly and annual time scales are evaluated during calibration and validation periods, and compared with the "abcd" model and a Budyko-type model developed for multiple time scales. Evaluation of the models shows that the proposed model performs better or comparable to the other models at all time scales.

A fish kill was observed in a historically freshwater region of the Everglades, coinciding with a spike in salinity. Sea level rise and altered hydrology allow freshwater wetland systems to be susceptible to saltwater intrusion. Most wetlands are characterized by highly organic soils with microbial communities starved of oxygen, seeking alternative electron acceptors. Seawater contains sulfate (SO42-), which is one of the alternative electron acceptors. Provided with sufficient quantities, sulfate-reducing bacteria (SRB) outcompete other anaerobes and produce toxic hydrogen sulfide. This study asked, what combination of soil organic matter (SOM) and SO42- are needed to produce sulfide concentrations potentially lethal to freshwater fish? Soil samples were collected from two freshwater wetlands with varying SOM content and incubated in microcosms at four SO42- concentrations (0, 0.75, 4.0, and 12.0 mM Na2SO4). Sulfide concentrations produced were compared to published data on lethal sulfide toxicity levels for aquatic life. This study demonstrated that high SOM soils (89.3 ± 0.2 % moisture) incubated with SO42- concentrations > 0.75 mM, rapidly produced toxic sulfide concentrations (> 5 ppm S2-) within 24 hrs.. While many freshwater species may tolerate a salinity of 1 ppt (0.75 mM SO42-), this SO42-concentration is sufficient to support SRB and lead to toxic sulfide production. ese results support the need to restore freshwater hydrology in wetland systems, such as the Everglades, thereby protecting against the rapid ecological effects of saltwater intrusion.

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