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Wildlife managers, through the use and management of their areas, influence water quality and quantity on and off site. Natural resource managers are coming under increasing pressure to preserve ecosystems and natural processes while producing a "optimum" balance of recreation, wildlife habitat, and natural resource products, and to justify their decisions. Water is a critical component to consider when managing recreation, wildlife, and wildlife habitats, and is itself a valuable resource to be managed. Unfortunately, the knowledge of hydrology is imperfect, effects of each management option are hard to predict, and field studies are time-consuming and expensive. The purpose of this study was to evaluate a simple hydrologic model as a tool for assisting wildlife managers in comparing potential hydrologic effects of different management options and of natural and anthropogenic site disturbances on eastern forested mountain watersheds. A number of existing hydrologic models were considered. AGNPS (Agricultural Non-Point Source pollution model) was chosen for its simplicity, applicable outputs, and successful use around the country. AGNPS was applied to a watershed at the Coweeta Hydrologic Laboratory in North Carolina. After adjustments, a baseline run was made, then the model was manipulated to simulate and compare several hypothetical management scenarios. This study demonstrated the potential utility of hydrologic models in wildlife management or other natural resource management decision-making processes. Model outputs may be useful in evaluating the relative impacts of alternative land-use decisions. Some problems remain in modeling the hydrology of eastern forested mountain watersheds. / Master of Science

This thesis presents the development of a dual-isotope simulation in a hydrological model, and its application to the lower Nelson River basin. The purpose of this study is to find if the simulation of stable water isotopes aids in hydrological simulation, and if a dual-isotope simulation is an improvement over a single-isotope simulation. The isoWATFLOOD model was enhanced to include δ2H and improve physical representativeness. The model was calibrated using various isotope and flow simulation error functions. Internal hydrologic storages and fluxes were verified by comparing simulated isotope values to observed isotope data. Adding isotope error to the calibration resulted in small but consistent improvements to the physical basis of calibrated parameter values. Isotope simulation error was found to be the best predictor of streamflow simulation performance beyond the calibration period. The dual-isotope simulation identified a number of model limitations and potential improvements from the verification of internal hydrologic storages. / October 2016

[Truncated abstract] Generally hydrologic and ecologic models operate on arbitrary time and space scales, selected by the model developer or user based on the availability of field data. In reality rainfall is highly variable not only annually, seasonally and monthly but also the intensities within a rainfall event and infiltration properties on semi-arid hillslopes can also be highly variable as a result of discontinuous vegetation cover that form mosaics of areas with vegetation and areas of bare soil. This thesis is directed at improving our understanding of the impacts of the temporal representation of rainfall and spatial heterogeneity on model predictions of hydrologic thresholds and surface runoff coefficients on semi-arid landscapes at the point and hillslope scales. We firstly quantified within storm rainfall variability across a climate gradient in Western Australia by parameterizing the bounded random cascade rainfall model with one minute rainfall from 15 locations across Western Australia. This study revealed that rainfall activity generated in the tropics had more within storm variability and a larger proportion of the storm events received the majority of rain in the first half of the event. Rainfall generated from fontal activity in the south was less variable and more evenly distributed throughout the event. Parameters from the rainfall analysis were then used as inputs into a conceptual point scale surface runoff model to investigate the sensitivity of point scale surface runoff thresholds to the resolution of rainfall inputs. This study related maximum infiltration capacities to average storm intensities (k*) and showed where model predictions of infiltration excess were most sensitive to rainfall resolution (ln k* = 0.4) and where using time averaged rainfall data can lead to an under prediction of infiltration excess and an over prediction of the amount of water entering the soil (ln k* > 2). For soils susceptible to both infiltration excess and saturation excess, total runoff sensitivity was scaled by relating drainage coefficients to average storm intensities (g*) and parameter ranges where predicted runoff was dominated by infiltration excess or saturation excess depending on the resolution of rainfall data were determined (ln g* <2). The sensitivity of surface runoff predictions and the influence of specific within storm properties were then analysed on the hillslope scale. '...' It was found that using the flow model we still get threshold behaviour in surface runoff. Where conditions produce slow surface runoff velocities, spatial heterogeneity and temporal heterogeneity influences hillslope surface runoff amounts. Where conditions create higher surface runoff velocities, the temporal structure of within storm intensities has a larger influence on runoff amounts than spatial heterogeneity. Our results show that a general understanding of the prevailing rainfall conditions and the soil's infiltration capacity can help in deciding whether high rainfall resolutions (below 1 h) are required for accurate surface runoff predictions. The results of this study can be considered a contribution to understanding the way within storm properties effect the processes on the hillslope under a range of overall storm, slope and infiltration conditions as well as an improved understanding of how different vegetation patterns function to trap runoff at different total vegetation covers and rainfall intensities.

<p>In this dissertation, a Hydrologic Data Assimilation System (HDAS) relying on the Duke Coupled surface-groundwater Hydrology Model (DCHM) and various data assimilation techniques including EnKF (Ensemble Kalman Filter), the fixed-lag EnKS (Ensemble Kalman Smoother) and the Asynchronous EnKF (AEnKF) was developed to 1) investigate the hydrological predictability of precipitation-induced natural hazards (i.e. floods and landslides) in the Southern Appalachians in North Carolina, USA, and 2) to characterize the seasonal (wet/dry) and inter-annual variability of surface-groundwater interactions with implications for water resource management in the Upper Zambezi River Basin (UZRB) in southern Africa. The overarching research objective is to improve hydrologic predictability of precipitation-induced natural hazards and water resources in regions of complex terrain. The underlying research hypothesis is that hydrologic response in mountainous regions is governed by surface-subsurface interaction mechanisms, specifically interflow in soil-mantled slopes, surface-groundwater interactions in recharge areas, and wetland dynamics in alluvial floodplains at low elevations. The research approach is to investigate the modes of uncertainty propagation from atmospheric forcing and hydrologic states on processes at multiple scales using a parsimonious uncalibrated hydrologic model (i.e. the DCHM), and Monte Carlo and Data-Assimilation methods. In order to investigate the coupled surface-groundwater system and assess the predictability of precipitation-induced natural hazards (i.e. floods and landslides) in headwater basins, including the propagation of uncertainty in QPE/QPF (Quantitative Precipitation Estimates/Forecasts) to QFE/QFF (Quantitative Flood Estimates/Forecasts), the DCHM model was implemented first at high spatial resolution (250m) in the Southern Appalachian Mountains (SAM) in North Carolina, USA. The DCHM modeling system was implemented subsequently at coarse resolution (5 km) in the Upper Zambezi River Basin (UZRB) in southern Africa for decadal-scale simulations (i.e. water years from 2002 to 2012). </p><p>The research in the SAM showed that joint QPE-QFF distributions for flood response at the headwater catchment scale are highly non-linear with respect to the space-time structure of rainfall, exhibiting strong dependence on basin physiography, initial soil moisture conditions (transient basin storage capacity), the space-time organization of runoff generation and conveyance mechanisms, and in particular interflow dynamics. The errors associated with QPEs and QPFs were characterized using rainfall observations from a dense raingauge network in the Pigeon River Basin, resulting in a simple linear regression model for adjusting/improving QPEs. Deterministic QFEs simulated by the DCHM agree well with observations, with Nash–Sutcliffe (NS) coefficients of 0.8~0.9. Limitations with state-of-the-science operational QPF and the impact of even limited improvements in rainfall forcing was demonstrated through an experiment consisting of nudging satellite-like observations (i.e. Adjusted QPEs) into operational QPE/QPF that showed significant improvement in QFF performance, especially when the timing of satellite overpass is such that it captures transient episodes of heavy rainfall during the event. The research further showed that the dynamics of subsurface hydrologic processes play an important role as a trigger mechanism of shallow landslides through soil moisture redistribution by interflow. Specifically, transient mass fluxes associated with the temporal-spatial dynamics of interflow govern the timing of shallow landslide initiation, and subsequent debris flow mobilization, independently of storm characteristics such as precipitation intensity and duration. Interflow response was shown to be dominant at high elevations in the presence of deep soils as well as in basins with large alluvial fans or unconsolidated debris flow deposits. In recharge areas and where subsurface flow is an important contribution to streamflow, subsurface-groundwater interactions determine initial hydrologic conditions (e.g. soil moisture states and water table position), which in turn govern the timing and magnitude of flood response at the event scale. More generally, surface-groundwater interactions are essential to capture low flows in the summer season, and generally during persistent dry weather and drought conditions. Future advances in QFF and landslide monitoring remain principally constrained by progress in QPE and QPF at the spatial resolution necessary to resolve rainfall-interflow dynamics in mountainous regions.</p><p>The predictability of QFE/QFF was further scrutinized in a complete operational environment during the Intense Observing Period (IOP) of the Integrated Precipitation and Hydrology Experiment (IPHEx-IOP), in order to investigate the predictability of floods (and flashfloods) in headwater catchments in the Southern Appalachians with various drainage sizes. With the DCHM, a variety of operational QPEs were used to produce hydrological hindcasts for the previous day, from which the final states were used as initial conditions in the hydrological forecast for the current day. Although the IPHEx operational testbed results were promising in terms of not having missed any of the flash flood events during the IOP with large lead times of up to 6 hours, significant errors of overprediction or underprediction were identified that could be traced back to the QPFs and subgrid-scale variability of radar QPEs. Furthermore, the added value of improving QFE/QFF through assimilating discharge observations into the DCHM was investigated for advancing flood forecasting skills in the operational mode. Both the flood hindcast/forecast results were significantly improved by assimilating the discharge observations into the DCHM using the EnKF (Ensemble Kalman Filter), the fixed-lag EnKS (Ensemble Kalman Smoother) and Asynchronous EnKF (AEnKF). The results not only demonstrate the utility of discharge assimilation in operational forecasts, but also reveal the importance of initial water storage in the basin for issuing flood forecasts. Specifically, hindcast NSEs as high as 0.98, 0.71 and 0.99 at 15-min time-scales were attained for three headwater catchments in the inner mountain region, demonstrating that assimilation of discharge observations at the basin’s outlet can reduce the errors and uncertainties in soil moisture. Success in operational flood forecasting at lead times of 6, 9, 12 and 15hrs was also achieved through discharge assimilation, with NSEs of 0.87, 0.78, 0.72 and 0.51, respectively. The discharge assimilation experiments indicate that the optimal assimilating time window not only depends on basin properties but also on the storm-specific space-time-structure of rainfall within the basin, and therefore adaptive, context-aware configurations of the data assimilation system should prove useful to address the challenges of flood prediction in headwater basins.</p><p>A physical parameterization of wetland hydrology was incorporated in the DCHM for water resource assessment studies in the UZRB. The spatial distribution of wetlands was introduced in the model using probability occurrence maps generated by logistic regression models using MODIS reflectance-based indices as predictor variables. Continuous model simulations for the 2002-2012 period show that the DCHM with wetland parameterization was able to reproduce wetland hydrology processes adequately, including surface-groundwater interactions. The modelled regional terrestrial water storage anomaly (TWSA) captured very well the inter- and intra-annual variability of the system water storage changes in good agreement with the NASA’s GRACE (Gravity Recovery and Climate Experiment) TWSA observations. Specifically, the positive trend of TWSA documented by GRACE was simulated independently by the DCHM. Furthermore, it was determined that the TSWA positive trend results from cumulative water storage in the sandy soils of the Cuando-Luana sub-basin when shifts in storm tracks move rainfall to the western sector of the Angolan High Plateau. </p><p>Overall, the dissertation study demonstrates the capability of the DCHM in predicting specific characteristics of hydrological response to extreme events and also the inter- and intra-annual variability of surface-groundwater interactions at a decadal scale. The DCHM, coupled with slope stability module and wetland module featuring surface-groundwater interaction mechanism, not only is of great potential in the context of developing a regional warning system for natural hazards (i.e. flashfloods and landslides), but also is promising in investigating regional water budgets at decadal scale. In addition, the DCHM-HDAS demonstrated the ability to reduce forecasting uncertainty and errors associated with forcing data and the model proper, thus significantly improving the predictability of natural hazards. The HDAS could also be used to investigate the regional water resource assessment especially in poorly-gauged regions (e.g. southern Africa), taking advantage of satellite observations.</p> / Dissertation

Project Completion Report, OWRT Project No. A-051-ARIZ / Agreement No. 14-31-0001-5003 / Project Dates: July 1974 - June 1975 / Acknowledgement: The work upon which this report is based was supported by funds provided by the United States Department of the Interior, Office of Water Research and Technology, as authorized under the Water Resources Research Act of 1978. / Bio-physicochemical measurements were made on treated sewage effluent releases at established locations within the channel of an ephemeral stream, the Santa Cruz River of Southern Arizona. Water samples were taken in chronological sequence as the effluent moved downstream, to trace changes in quality parameters during low and high hydrograph stages. Results indicate that dissolved oxygen (DO) concentrations at low effluent flows were higher than DO concentrations at high effluent flows; while, conversely, biochemical oxygen demand (BOD) concentrations at low effluent flows were generally lower than BOD concentrations at high effluent flows. Biochemical oxygen demand concentrations are affected by waste loadings, flow conditions, phytoplankton growth and nitrification. Mean river deoxygenation rates (k ) in sewage flows after six river miles from the Tucson Sewage Treatment Plant were always negative or increasing, indicative of nitrification, algal growth, and concentration of organic constituents through seepage losses.

Thesis (Ph. D.)--Oregon State University, 2004. / Printout. Includes bibliographical references (leaves 143-154). Also available on the World Wide Web.