For surface-water resource management studies, it is important to quantify all of the mechanisms that contribute to water quantity and influence water quality. In this regard, various methods have been used to ground-water fluxes in lake systems. These have included physical measurements (e.g., seepage meters), flow-net analyses, water budgets, chemical tracers, ground-water flow models, and statistical analyses. The method developed for this study for calculating ground-water inflow uses a simplified, 1-layer (surficial aquifer) ground-water flow model. The test area was on a set of lakes known as the Winter Haven Chain of Lakes in Polk County, Florida. The technique combines the use of a numerical model (MODFLOW) with an inverse prediction technique (PEST) to determine net surficial recharge rates. Within the model, the lakes were represented as constant-head boundaries. A general, surficial ground water no-flow boundary was delineated around the entire lake system based on the topographic boundaries. The model used annual average lake elevations to create a constant-head boundary for each lake for each year. Annual average elevations of surficial well heads were used as target well data. Model results generally support previous studies in the region, concluding that the lake chain receives significant inflow from the surficial aquifer and leaks to the Floridan aquifer. As a consequence, ground-water quality constituency was found to be of critical importance. One of the most important observations from this study is the need for accurate ground-water concentrations for ridge lake water quality management. The initial measured values used in this study were highly variable, uncertain, and likely underestimated the effect that ground water has on nutrient loading to the Winter Haven Chain of Lakes.

The global continental carbon and water cycles are intimately linked through stomatal regulation during vegetation photosynthesis and biosphere-atmosphere interactions. Therefore, to have a complete understanding of both present and future climate, these cycles must be studied as an interconnected system. This thesis presents three studies that aim to better explain these interactions and provide a direction forward for improved model projections of climate. The first study shows that biosphere-atmosphere feedbacks can contribute up to 30% of climate and weather variability in certain regions that help determine the net CO2 balance of the biosphere. It demonstrates that Earth System Models are under-estimating these contributions, mainly due to the underestimation of the biosphere response to radiation and water availability. It emphasizes the importance of correctly capturing these feedbacks in models for accurate subseasonal to seasonal climate predictions. The second demonstrates that changes in soil moisture (both short-term variability and long-term trends) strongly limit the ability of the continents to act as a carbon sink, with overall effects on the same order of magnitude as the land sink itself. Photosynthesis rates tend to be reduced when soil moisture is depleted, leading to decreased carbon uptake. Additionally, respiration rates increase due to increased temperature through land-atmosphere feedbacks. These carbon losses are not compensated for during wet anomalies due to the nonlinear response of vegetation activity (both respiration and photosynthesis) to soil moisture. This suggests that the increasing trend in carbon uptake rate may not be sustained past the middle of the century and could result in accelerated atmospheric CO2 growth. The third decouples the effects of atmospheric dryness (vapor pressure deficit) and soil dryness on vegetation activity in the largest terrestrial carbon sink: the tropics. Understanding vegetation response to environmental drivers and stressors in the tropics is essential to accurately modeling these ecosystems and predicting whether they will remain carbon sinks in the future. The study finds that in regions that are water limited, vegetation is driven by precipitation and radiation while being limited by high vapor pressure deficit. Conversely, in the wettest regions that are light limited, increases in vapor pressure deficit accompany increasing rates of photosynthesis. These three studies contribute to our understanding of land-atmosphere and biosphere-atmosphere feedbacks and the coupling of the continental carbon and water cycles. They identify model process representations, such as soil moisture and vegetation water-stress, that are hindering our ability to make accurate forecasts. By improving our knowledge of these mechanisms and evaluating the ability of models to reproduce them, we pave the way forward for improved climate and weather projections. Better predictions can be used not only to protect society in the present, but also to appropriately shape climate policy to protect society in the future.

For this dissertation I studied groundwater and surface water interactions in the Kenai Lowlands, Alaska. In particular, I examine two important aspects of groundwater and surface water interactions: 1) Groundwater's influence on surface-water temperature; and 2) Groundwater's role in forming hydrologic flow paths that can connect uplands to streamside wetlands and streams. Chapter 2 investigates the controls on stream temperature in salmon-bearing headwater streams in two common hydrogeologic settings: 1) drainage-ways, which are low-gradient streams that flow through broad valleys; and 2) discharge-slopes, which are high gradient streams that flow through narrow valleys. The results from chapter 2 showed significant differences in stream temperatures between the two hydrogeologic settings. Observed stream temperatures were higher in drainage-way sites than in discharge-slope sites, and showed strong correlations as a continuous function with the calculated topographic metric flow-weighted slope. Additionally, modeling results indicated that the potential for groundwater discharge to moderate stream temperature is not equal between the two hydrogeologic settings, with groundwater having a greater moderating effect on stream temperature at the low gradient drainage-way sites. Chapter 3 examines the influence of groundwater on juvenile coho salmon winter habitat along the Anchor River. Two backwater habitats were selected from the larger set of 25 coho overwintering sites from a previous study for an in-depth hydrologic analysis. The results from chapter 3 showed that the type of groundwater discharge (i.e., focused versus diffuse groundwater discharge) can play an important role in determining habitat suitability in these backwater sites. During winter, focused discharge from a local groundwater seep maintained higher surface-water temperatures and higher concentrations of dissolved oxygen compared to the site with more diffuse groundwater discharge. Chapter 4 investigates the linkages along hydrologic flow paths among alder (Alnus spp.) stands, streamside wetlands, and headwater streams. Chapter 4 tested four related hypotheses: 1) groundwater nitrate concentrations are greater along flow paths with alder compared to flow paths without alder; 2) on hillslopes with alder, groundwater nitrate concentrations are highest when alder stands are located near the streamside wetlands at the base of the hillslope; 3) primary production of streamside wetland vegetation is N limited and wetlands are less N limited when alder stands are located nearby along flow paths; and 4) stream reaches at the base of flow paths with alder have higher nitrate concentrations than reaches at the base of flow paths without alder. The results from chapter 4 showed that groundwater nitrate concentrations were highest along flow paths with alder, however no difference was observed between flow paths with alder located near versus alder located further from streamside wetlands. Vegetation had a greater response to N fertilization in streamside wetlands that were connected to flow paths without alder and less when alder stands were near. Finally, higher nitrate concentrations were measured in streams at the base of flow paths with alder. The combined results of this dissertation showed that, in the Kenai Lowlands, groundwater and surface water interactions have a direct influence on the local ecology and that a fundamental understanding of the hydrology can aid in the successful management and protection of this unique and important ecosystem.

Appropriately constructed pollutant export models can help set management priorities for catchments, identify critical pollutant source areas, and are important tools for developing and evaluating economically viable ways of minimising surface water pollution.¶ This thesis presents a comparison, an evaluation and an integration of models for predicting the export of environmental pollutants, in particular sediment, through river systems. A review of the capabilities and limitations of current water quality modelling approaches is made. Several water quality and quantity modelling approaches are applied and evaluated in the catchment of the upper Murrumbidgee River.¶ The IHACRES rainfall-runoff model and a simple hydrologic routing model are applied with the aim of developing a capacity to predict streamflow at various catchment scales and to enable integration with other pollutant load estimation techniques. Methods for calculating pollutant loads from observed pollutant concentration and modelled streamflow data are also investigated. Sediment export is estimated using these methods over a 10-year period for two case study subcatchments. Approaches for water quality sampling are discussed and a novel monitoring program using rising stage siphon samplers is presented. Results from a refinement of the Sediment River Network model in the upper Murrumbidgee catchment (SedNet-UM) are presented. The model provides a capacity to quantify sediment source, transport and to simulate the effects of management change in the catchment. The investigation of the model includes rigorous examination of the behaviour of the model through sensitivity assessment and comparison with other sediment modelling studies. The major conclusion reached through sensitivity assessment was that the outputs of the model are most sensitive to perturbation of the hydrologic parameters of the model.¶ The SedNet-UM application demonstrates that it is possible to construct stream pollutant models that assist in prioritising management across catchment scales. It can be concluded that SedNet and similar variants have much potential to address common resource management issues requiring the identification of the source, propagation and fate of environmental pollutants. In addition, incorporating the strengths of a conceptual rainfall-runoff model and the semi-distributed SedNet model has been identified as very useful for the future prediction of environmental pollutant export.

Hydrological observations are characterised by wet and dry cycles, a characteristic that is termed hydrological persistence. Interactions between global climate phenomena and the hydrological cycle result in rainfall and streamflow data clustering into wetter and drier states. These states have implications for the management and planning of water resources. Statistical tests constructed from the theory of wet and dry spells indicate that evidence for persistence in monthly observations is more compelling than at an annual scale. This thesis demonstrates that examination of monthly data yields spatially - consistent patterns of persistence across a range of hydrological variables. It is imperative that time series models for rainfall and streamflow replicate the observed fluctuations between the climate regimes. Monthly time series are generally represented with linear models such as ARMA variants ; however simulations from such models may underestimate the magnitude and frequency of persistence. A different approach to modelling these data is to incorporate shifting levels in the broader climate with a tendency to persist within these regimes. Hidden Markov models ( HMMs ) provide a strong conceptual basis for describing hydrological persistence, and are shown to provide accurate descriptions of fluctuating climate states. These models are calibrated here with a full Bayesian approach to quantify parameter uncertainty. A range of novel variations to standard HMMs are introduced, in particular Autoregressive HMMs and hidden semi - Markov models which have rarely been used to model monthly rainfall totals. The former model combines temporal persistence within observations with fluctuations between persistent climate states, and is particularly appropriate for modelling streamflow time series. The latter model extends the modelling capability of HMMs by fitting explicit probability distributions for state durations. These models have received little attention for modelling persistence at monthly scale. A non - parametric ( NP ) HMM, which overcomes the major shortcomings of standard parametric HMMs, is also described. Through removing the requirement to assume parametric forms of conditional distributions prior to model calibration, the innovative NP HMM framework provides an improved estimation of persistence in discrete and continuous data that remains unaffected by incorrect parametric assumptions about the state distributions. Spatially - consistent persistence is identified across Australia with the NP HMM, showing a tendency toward stronger persistence in low-rainfall regions. Coherent signatures of persistence are also identified across time series of total monthly rainfall, numbers of rain - days each month, and the intensities of the most extreme rain events recorded each month over various short durations, illustrating that persistent climate states modulate both the numbers of rain events and the amount of moisture contained within these events. These results provide a new interpretation of the climatic interactions that underlie hydrological persistence. The value of HMMs to water resource management is illustrated with the accurate simulation of a range of hydrologic data, which in each case preserves statistics and spell properties over a range of aggregations. Catchment - scale rainfall for the Warragamba Reservoir is simulated accurately with HMMs, and rainfall - runoff transformations from these simulations provide reservoir inflows of lower drought risk than provided from ARMA models. / Thesis (Ph.D.)--School of Civil and Environmental Engineering, 2006.

The effect of landuse change on the hydrologic, biogeochemical and ecological response of watersheds is a concern throughout the world. To help characterize the potential magnitude of such changes, and of the potential to remediate or avoid undesirable features, studies focused on the cumulative watershed effects of site level change are necessary. The current state of the art model for water quality in agricultural lands, Soil Water Assessment Tool (SWAT), was used to estimate the effects of a set of future landscape scenarios on water quality in the Corn Belt region of the United States. These results indicated that changes to the current water quality management strategies will be necessary to significantly improve water quality in the Corn Belt region. In addition, the experience of implementing SWAT suggested a variety of changes to the model structure and study design with potential to improve the quality of the results. These changes include improved treatment of hydrologic process, full integration of input data and model code, different methods of distributing data across space, the use of fewer parameters, more sophisticated numerical techniques, and improved methods for generating potential landscape scenarios. A new model structure (WET_Hydro) was developed to address these issues. The hydrologic components of the model focus on a conceptual physically based characterization of the movement of water in soils, as overland flow, and in channels. Tests using a variety of input data sets, including both synthetic inflows and real watershed data were developed to verify the hydrologic components of the model. Additional model analyses evaluate how model scale interacts with parameters and with measurements. These analyses point toward additional criteria that may prove useful to the determination of correct model scales and to the utility of the flexible model structure which provides automatic changes to model scale. In addition to the scale analysis, a method of estimating the average new water contribution to storm discharge was developed.. This additional model criterion was shown to provide further understanding of model utility under different hydrologic regimes. The hydrologic model was extended to produce estimates of erosion and sediment export. Sensitivity to various restoration options were developed focusing on simple descriptions of remediation potential, and a minimum of parameters. In addition, the water quality model was coupled with a Decision Support System (DSS). Example applications demonstrate the potential of the combination to improve the process of restoration planning at the watershed scale. / Graduation date: 2003 / Best scan available. Figures in original are very light.

Based on the determination of the zero-flux plane, a water balance procedure for large-scale experimental databases was automated to estimate the soil water balance based on soil water content distribution with depth through time. The automated procedure was verified using data from the BOREAS project obtained in three Intensive Field Campaigns during the spring and summer of 1994. The data used correspond to four tower sites measuring atmospheric fluxes above the forest canopy from the Northern and Southern Study Areas and are designated according to the predominant vegetation in the area as Old Jack Pine and Young Jack Pine. The total hydraulic head through time at these sites is determined to identify the position of the zero-flux plane, which separates that part of the soil profile in which water flow is upward from the region in which the water flow is downward. In conjunction with precipitation and soil water content data, the procedure allows estimation of the actual soil water balance, the water used from the region above the zero-flux plane being evapotranspiration, and the change in soil water content below the mean zero-flux plane being drainage. Prior to this study, no published attempt had been made to automate a water balance procedure for large-scale experimental databases based on the position of the zero-flux plane and soil water content distribution through time. / Graduation date: 1997

Thesis (Ph. D.)--University of Washington, 2006. / Vita. Includes bibliographical references (leaves 113-121).

Farming communities in the United States and around the world lose billions of dollars every year due to drought. Drought Indices such as the Palmer Drought Severity Index (PDSI) and Standardized Precipitation Index (SPI) are widely used by the government agencies to assess and respond to drought. These drought indices are currently monitored at a large spatial resolution (several thousand km2). Further, these drought indices are primarily based on precipitation deficits and are thus good indicators for monitoring large scale meteorological drought. However, agricultural drought depends on soil moisture and evapotranspiration deficits. Hence, two drought indices, the Evapotranspiration Deficit Index (ETDI) and Soil Moisture Deficit Index (SMDI), were developed in this study based on evapotranspiration and soil moisture deficits, respectively. A Geographical Information System (GIS) based approach was used to simulate the hydrology using soil and land use properties at a much finer spatial resolution (16km2) than the existing drought indices. The Soil and Water Assessment Tool (SWAT) was used to simulate the long-term hydrology of six watersheds located in various climatic zones of Texas. The simulated soil water was well-correlated with the Normalized Difference Vegetation Index NDVI (r ~ 0.6) for agriculture and pasture land use types, indicating that the model performed well in simulating the soil water. Using historical weather data from 1901-2002, long-term weekly normal soil moisture and evapotranspiration were estimated. This long-term weekly normal soil moisture and evapotranspiration data was used to calculate ETDI and SMDI at a spatial resolution of 4km ?? 4km. Analysis of the data showed that ETDI and SMDI compared well with wheat and sorghum yields (r > 0.75) suggesting that they are good indicators of agricultural drought. Rainfall is a highly variable input both spatially and temporally. Hence, the use of NEXRAD rainfall data was studied for simulating soil moisture and drought. Analysis of the data showed that raingages often miss small rainfall events that introduce considerable spatial variability among soil moisture simulated using raingage and NEXRAD rainfall data, especially during drought conditions. The study showed that the use of NEXRAD data could improve drought monitoring at a much better spatial resolution.

<p>The research was driven by a need to increase the knowledge base concerning wetland ecological responses, as well as to identify and evaluate the factors driving the functioning of the Franschhoek Trust Wetland. An ecohydrological study was undertaken in which vegetation cover, depth to groundwater, water and soil chemistry were monitored at 14 sites along three transects for a 12 month period. The parameters used include temperature, pH, electrical conductivity (EC), sodium, potassium, magnesium, calcium, iron, chloride, bicarbonate, sulphate, total nitrogen, ammonia, nitrate, nitrite and phosphorus. T-tests and Principal Component Analysis (PCA) were used to analyze trends and to express the relationship between abiotic factors and vegetation.</p>