The National Water Center (NWC) started using the National Water Model (NWM) in 2016. The NWM delivers state-of-the-science hydrologic forecasts in the nation. The NWM aims at operationally forecasting streamflow in more than 2,000,000 river reaches while currently river forecasts are issued for 4,000. The NWM is a specific configuration of the community WRF-Hydro Land Surface Model (LSM) which has recently been introduced to the hydrologic community. The WRF-Hydro model, itself, uses another newly-developed LSM called Noah-MP as the core hydrologic model. In WRF-Hydro, Noah-MP results (such as soil moisture and runoff) are passed to routing modules. Riverine water level and discharge, among other variables, are outputted by WRF-Hydro. The NWM, WRF-Hydro, and Noah-MP have recently been developed and more research for operational accuracy is required on these models. The overarching goal in this dissertation is improving the ability of these three models in simulating and forecasting hydrological variables such as streamflow and soil moisture. Therefore, data assimilation (DA) is implemented on these models throughout this dissertation. State-of-the art DA is a procedure to integrate observations obtained from in situ gages or remotely sensed products with model output in order to improve the model forecast. In the first chapter, remotely sensed satellite soil moisture data are assimilated into the Noah-MP model in order to improve the model simulations. The performances of two DA techniques are evaluated and compared in this chapter. To tackle the computational burden of DA, Massage Passing Interface protocols are used to augment the computational power. Successful implementation of this algorithm is demonstrated to simulate soil moisture during the Colorado flood of 2013. In the second chapter, the focus is on the WRF-Hydro model. Similarly, the ability of DA techniques in improving the performance of WRF-Hydro in simulating soil moisture and streamflow is investigated. The results of chapter 2 show that the assimilation of soil moisture can significantly improve the performance of WRF-Hydro. The improvement can reach 58% depending on the study location. Also, assimilation of USGS streamflow observations can improve the performance up to 25%. It was also observed that soil moisture assimilation does not affect streamflow. Similarly, streamflow assimilation does not improve soil moisture. Therefore, joint assimilation of soil moisture and streamflow using multivariate DA is suggested. Finally, in chapter 3, the uncertainties associated with flood forecasting are studied. Currently, the only uncertainty source that is taken into account is the meteorological forcings uncertainty. However, the results of the third chapter show that the initial condition uncertainty associated with the land state at the time of forecast is an important factor that has been overlooked in practice. The initial condition uncertainty is quantified using the DA. USGS streamflow observations are assimilated into the WRF-Hydro model for the past ten days before the forecasting date. The results show that short-range forecasts are significantly sensitive to the initial condition and its associated uncertainty. It is shown that quantification of this uncertainty can improve the forecasts by approximately 80%. The findings of this dissertation highlight the importance of DA to extract the information content from the observations and then incorporate this information into the land surface models. The findings could be beneficial for flood forecasting in research and operation.

Government Island, located in the Columbia River approximately 16 km (10 mi) upstream of the confluence with the Willamette River, is a wetland mitigation site prompted by expansion of the southwest quadrant of Portland International Airport. The purpose of the study is to predict water levels in two enclosed lowland areas, Jewit Lake and Southeast Pond, based on levels of the Columbia River, precipitation, and evapotranspiration. Mitigation is intended to convert 1.13 km2 (237 acres) of seasonally flooded wetland to 1.27 km2 (267 acres) of semi-permanently flooded wetland and seasonally flooded wetland. Flooding of the wetland is most likely to occur December through January and May through early June when Columbia River water levels at Government Island exceed 3.6 m (12 ft) m.s.l. Flooding of Jewit Lake occurs through a channel connecting the wetland to the Columbia River. A groundwater model (MODFLOW) was parameterized to simulate the hydrology of the wetland. Observations of the subsurface stratigraphy in 25 soil pits, bucket auger cores, and during installation of water monitoring devices were used to estimate thickness and lateral extent of a confining unit that overlies an aquifer. Climatological data for 1994 and water levels were entered into MODFLOW to calibrate rates of water movement through the subsurface. Periods of drying for Jewit Lake and Southeast Pond were predicted based on precipitation and actual evapotranspiration rates expected to be present in the study area between June and December. Results of groundwater modeling show that Jewit Lake will maintain surface water above 3.6 m (12 ft) in most years. Southeast Pond is expected to dry annually as mitigation is unlikely to change the hydrology of Southeast Pond. Groundwater modeling predicted the types of wetlands present at different elevations by evaluating periods of drying within the wetland using the U.S. Fish and Wildlife Service classification of wetlands method. Results suggest that Jewit Lake will be converted to semipermanently flooded wetland below 3.6 m (12 ft) in elevation. Southeast Pond will remain a seasonally flooded wetland as a result of mitigation.

Water is crucial for domestic, agricultural, industrial, environmental, and hydropower uses. Once precipitation occurs, it eventually partitions into streamflow, evapotranspiration (ET), and groundwater recharge. Distribution of precipitation into these partitions is called a hydrologic budget. The hydrologic budget of any geographic area or watershed under different climate change conditions help water managers to make appropriate water management plans. Computer based hydrologic modeling software has been used extensively to solve many water resources problems including hydrologic budgets. Hydrologic modeling requires high quality weather parameter data. This study projected surface and groundwater flows from the portion of RBC watershed that lies above Red Butte Reservoir (RBR) to Salt Lake Valley (SLV) for water years (WYs) 2051-2060 in two climatic Representative Concentration Pathways (RCPs) scenarios, RCP 4.5 and RCP 8.5. RCP 8.5 corresponds to the pathways with higher greenhouse gas emission than RCP 4.5. To project flows, we first used Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) 4.3 model to calibrate and validate the observed streamflow for WYs 2016 and 2017 respectively. However, within RBC study area weather stations, all three weather parameters (Precipitation (P), Temperature (T), and Net Radiation (NR)) required for HEC-HMS model were missing on the same day for some periods of WYs 2016-2017. This necessitated to fill the missing parameters prior to the model calibration and validation. We hypothesized that systematically using ANN and SMs would enable making accurate estimates, even when multiple parameter values are missing on the same day. The hypothesis-estimated the missing weather parameters (P, T, and NR) values are useful for hydrologic modeling in a watershed. We ran the HEC-HMS validated model for WY 2051-2060 once for each RCP scenario, and quantified the flows to SLV. The model results showed that average stream and groundwater flows of WYs 2016 and 2017 were 14.1% and 55.7% of total study area precipitation, respectively. In the future 2051- 2060, compared with average annual surface and groundwater flows of WYs 2016-2017, percent changes in flows, respectively, were i) decreases of 29.6% and 24.2% for RCP 4.5 and ii) decreases of 26% and 23.9 % for RCP 8.5.

The purpose of this paper is to develop a general hydrologic model for use on a digital computer and prove it s validity by applying it to a management study of the Provo River Basin. Hydrologic equations have been proposed for each major hydrologic occurrence within a river basin. By linking these equations through restrictions on continuity of mass, a general hydrologic model can be obtained. Such a model becomes the basic tool for studying the management of the river basin hydrology. The paper describes the model components, parameter identification program, and the river basin management program.

In order to understand the atmospheric branch of the earth's hydrologic cycle on the global scale, an atmospheric moisture balance is diagnostically analyzed from the January and July data of the OSU atmospheric general circulation model, which has been integrated for thirty-nine months of simulation with seasonally-varying sea-surface temperature and solar insolation. The model hydrologic processes analyzed for the balance include the surface evaporation, the precipitation by large-scale and cumulus condensation, the vertical transport by large-scale and cumulus mass fluxes, and the horizontal transport of water vapor. The large-scale transports include the contributions from the standing and transient components of motion. Also analyzed are the potential and stream functions of horizontal transport, and the statistics of seasonal and interannual variabilities of the global and hemispheric effects of the hydrologic processes. As a result of these analyses, the hydrologic cycle is constructed and understood for both January and July of the model. Large-scale vertical transport moistens the upper layer; the standing and transient motions contribute mostly in the tropics and higher latitudes, respectively. Large-scale horizontal transport moistens the continental atmosphere except for the relatively small transport from the continents to the oceans by the standing motion in the upper layer; the runoff occurs in the model to balance the marine transport but seasonal trends exist such that snow assumulates during January and melts during July on the global average. Cumulus convection drys not only the lower layer but also the upper layer of the model, and the penetrating cumuli are a major mechanism of maritime precipitation, whereas the large-scale condensation and penetrating cumuli have the dominating effect on the continental precipitation during January and July, respectively. The seasonal precipitation over the Northern Hemisphere continents concurs with strong surface evaporation in summer and also with strong cyclonic activity in winter. Comparison with other models and observational data indicates that the model reproduced some basic features of the atmospheric branch of the hydrologic cycle and its seasonal variation. The intense evaporation (≥ 5 mm day⁻¹) over the Pacific and Atlantic oceans and the rain belts in the tropics are well simulated for both January and July. The poleward transport in the northern middle and high latitudes is in good agreement with observations. The maximum toward-thermal-equator transport in the tropics occurs, however, at the geographic equator for both January and July, indicating that these maxima are about 5 degrees of latitude closer to the seasonal thermal equator than the observed maxima. Nevertheless the global statistics of the model atmosphere are not significantly different from that of the real atmosphere. Among others, we mention the following common features of the January and July moisture balances in the present model. Most precipitation of penetrating convection occurs in regions of strong surface evaporation even though some occurs in the moisture convergence zones where most of heavy mid-level convection is located. In the regions of intense penetrating convection, however, the standing part of surface evaporation is much larger in magnitude than the negative transient part which is essentially due to the positive correlation between the turbulence intensity and surface humidity over wet surfaces. Moreover, the horizontal structure of the standing part conforms to that of the standing vapor pressure difference between the air and the underlying surface. A strategy for further studies is recommended on the basis of our understanding of these features. / Graduation date: 1982

This project presents the development and design of a comprehensive interface coupled with a geodatabase (ArcGISwat 2003), for the Soil and Water Assessment Tool (SWAT). SWAT is a hydrologically distributed, lumped parameter model that runs on a continuous time step. The quantity and extensive detail of the spatial and hydrologic data, involved in the input and output, both make SWAT highly complex. A new interface, that will manage the input/output (I/O) process, is being developed using the Geodatabase object model and concepts from hydrological data models such as ArcHydro. It also incorporates uncertainty analysis on the process of modeling. This interface aims to further direct communication and integration with other hydrologic models, consequently increasing efficiency and diminishing modeling time. A case study is presented in order to demonstrate a common watershed-modeling task, which utilizes SWAT and ArcGIS-SWAT2003.

The purpose of this study was to evaluate variations of the Natural Resources Conservation Service (NRCS) curve number (CN) method for estimating near real-time runoff for naturalized flow, using high resolution radar rainfall data for watersheds in various agro-climatic regions of Texas. The CN method is an empirical method for calculating surface runoff which has been tested on various systems over a period of several years. Many of the findings of previous studies indicate the need to develop variations of this method to account for regional and seasonal changes in weather patterns and land cover that might affect runoff. This study seeks to address these issues, as well as the inherent spatial variability of rainfall, in order to develop a means of predicting runoff in near real-time for water resource management. In the past, raingauge networks have provided data for hydrologic models. However, these networks are generally unable to provide data in real-time or capture the spatial variability associated with rainfall. Radar networks, such as the Next Generation Weather Radar (NEXRAD) of the National Weather Service (NWS), which are widely available and continue to improve in quality and resolution, can accomplish these tasks. In general, a statistical comparison of the raingauge and NEXRAD data, where both were available, shows that the radar data is as representative of observed rainfall as raingauge data. In this study, watersheds of mostly homogenous land cover and naturalized flow were used as study areas. Findings indicate that the use of a dry antecedent moisture condition CN value and an initial abstraction (Ia) coefficient of 0.1 produced statistically significant results for eight out of the ten watersheds tested. The urban watershed used in this study produced more significant results with the use of the traditional 0.2 Ia coefficient. The predicted results before and during the growing season, in general, more closely agreed with the observed runoff than those after the growing season. The overall results can be further improved by altering the CN values to account for seasonal vegetation changes, conducting field verification of land cover condition, and using bias-corrected NEXRAD rainfall data.

<p>Prior studies of groundwater systems have associated increasing salinity and anoxic conditions with increasing radium (Ra) activities in water due to the decreasing effectiveness of Ra removal processes. However, the components of salinity (e.g. Ca vs. Na and SO₄^2- vs. Cl^--dominated waters), and the relative importance of salinity-sensitive vs. redox-sensitive processes for Ra mobilization, are less well understood. In this research, the response of Ra to hydrochemical change was examined using a multiple tracer approach to obtain detailed information on divalent cation and Ra mobility. A range of salinity and redox conditions was examined in five field-based studies in the United States and Morocco: (1) fresh waters in fractured crystalline rocks in the Piedmont region of North Carolina; (2) the Willcox Basin, an oxic alluvial basin-fill aquifer in southeastern Arizona; (3) the Jordan sandstone aquifer, a carbonate-cemented quartz sandstone in southeastern Minnesota; (4) an unconfined coastal aquifer undergoing salinization in the city of Agadir, Morocco; and (5) the confined, fresh to saline Cretaceous and Pliocene aquifers of the Atlantic Coastal Plain in North Carolina.</p><p> </p><p>In addition to analysis of major element concentrations, trace metal concentrations, and ²²⁴Ra, ²²⁶Ra, and ²²⁸Ra activities, complementary isotope systems were applied to gain insights on the relative stability of chemical processes that remove radium and other alkaline earth metals: (1) strontium isotope ratios (⁸⁷Sr/⁸⁶Sr) trace divalent cation release from sources such as clay and carbonate minerals in the aquifer solids and also indicate conditions in which divalent cation release (rather than uptake) is dominant; (2) boron concentrations and isotopes (&delta;¹¹B) coincide with the opposite condition in freshening conditions of the Atlantic Coastal Plain, in which divalent cations are removed in exchange for Na; and (3) sulfur and oxygen isotopes (&delta;³⁴S, &delta;¹⁸O) of sulfate trace sulfate sources and provide information on sulfate-reducing conditions, which can inhibit barite (BaSO₄) from removing Ra by coprecipitation. In addition, other isotopic and ion measurements trace salinity sources and groundwater residence time, including &delta;²H, &delta;¹⁸O, ³H, Br^-/Cl^-, Na/Cl^-, and Ca/Na.</p><p>This dissertation documents correlations between salinity and radium in the brackish to saline North Carolina coastal plain aquifer with total dissolved solids (TDS) up to ~18,000 mg L^-1 and to some degree in the Moroccan coastal aquifer, but even the lower-salinity waters (TDS <3000 mg L^-1) exhibit a range of Ra activities spanning approximately 3 orders of magnitude. Among these low-TDS waters, the highest Ra activities were observed in the anoxic Jordan sandstone aquifer and the lowest were observed in the oxic Willcox Basin aquifer. Although the main control on radium activities in fresh groundwater is the U- and Th-series radionuclide content of the aquifer solids, important secondary controls include the stability of redox-sensitive radium adsorption sites (Mn and Fe oxides), the relative dominance of divalent vs. monovalent cations (e.g. the Ca/Na ratio), formation of the uncharged RaSO₄⁰ complex, and/or the saturation state with respect to barite. These processes interact in varied ways in the field-based studies. Increasing radium activities and decreasing ²²²Rn/²²⁶Ra ratios in the North Carolina fractured crystalline rock groundwater system are correlated with increasing Ba, Mn, and Fe concentrations and decreasing dissolved oxygen concentrations, related to weathering and/or organic carbon oxidation. Radium activities in the oxic, neutral to slightly basic Willcox Basin are very low (median ²²⁶Ra activity 2 mBq L^-1), probably due to a combination of effective Ra removal processes including adsorption to Mn and/or Fe oxides and the overall removal of divalent cations during groundwater evolution in this system. These are the same surface charge conditions that release arsenic, of regional water concern, in this pH range. Radium in Jordan aquifer groundwater is dependent on local variations in solid-phase radionuclide levels, probably hosted in the carbonate cement phase. Also, Ra is inefficiently adsorbed to the aquifer solids in the aquifer's anoxic conditions, resulting in the highest radium levels reported in this dissertation (²²⁶Ra up to 420 mBq L^-1) despite apparent barite precipitation that partially removes Ra. Radium-224 activity in the Moroccan coastal aquifer is associated with salinity, but Ra overall is apparently controlled by barite, indicated by conditions near BaSO₄ saturation. Radium activity in the saline waters of the Atlantic Coastal Plain aquifers is associated with TDS concentrations, but the cation exchange properties of the aquifer may provide a major mechanism of Ra removal in the Na-HCO₃^- and Na-Cl^- waters. Overall, the complex interaction between groundwater chemistry and Ra-removing processes implies that in waters with TDS below approximately 3,000 mg L^-1, dissolved solids concentration alone does not fully describe radium's response to hydrochemical conditions, but rather that aquifer-specific examination of Ra removal mechanisms is needed.</p> / Dissertation

This thesis presents a new approach to calibration of hydrologic models using distributed computing framework. Distributed hydrologic models are known to be very computationally intensive and difficult to calibrate. To cope with the high computational cost of the process a Surrogate Model Optimization (SMO) technique that is built for distributed computing facilities is proposed. The proposed method along with two analogous SMO methods are employed to calibrate WATCLASS hydrologic model. This model has been developed in University of Waterloo and is now a part of Environment Canada MESH (Environment Canada community environmental modeling system called Modèlisation Environmentale Communautaire (MEC) for Surface Hydrology (SH)) systems. SMO has the advantage of being less sensitive to "curse of dimensionality" and very efficient for large scale and computationally expensive models. In this technique, a mathematical model is constructed based on a small set of simulated data from the original expensive model. SMO technique follows an iterative strategy which in each iteration the surrogate model map the region of optimum more precisely. A new comprehensive method based on a smooth regression model is proposed for calibration of WATCLASS. This method has at least two advantages over the previously proposed methods: a)it does not require a large number of training data, b) it does not have many model parameters and therefore its construction and validation process is not demanding. To evaluate the performance of the proposed SMO method, it has been applied to five well-known test functions and the results are compared to two other analogous SMO methods. Since the performance of all SMOs are promising, two instances of WATCLASS modeling Smoky River watershed are calibrated using these three adopted SMOs and the resultant Nash-Sutcliffe numbers are reported.

This thesis presents a new approach to calibration of hydrologic models using distributed computing framework. Distributed hydrologic models are known to be very computationally intensive and difficult to calibrate. To cope with the high computational cost of the process a Surrogate Model Optimization (SMO) technique that is built for distributed computing facilities is proposed. The proposed method along with two analogous SMO methods are employed to calibrate WATCLASS hydrologic model. This model has been developed in University of Waterloo and is now a part of Environment Canada MESH (Environment Canada community environmental modeling system called Modèlisation Environmentale Communautaire (MEC) for Surface Hydrology (SH)) systems. SMO has the advantage of being less sensitive to "curse of dimensionality" and very efficient for large scale and computationally expensive models. In this technique, a mathematical model is constructed based on a small set of simulated data from the original expensive model. SMO technique follows an iterative strategy which in each iteration the surrogate model map the region of optimum more precisely. A new comprehensive method based on a smooth regression model is proposed for calibration of WATCLASS. This method has at least two advantages over the previously proposed methods: a)it does not require a large number of training data, b) it does not have many model parameters and therefore its construction and validation process is not demanding. To evaluate the performance of the proposed SMO method, it has been applied to five well-known test functions and the results are compared to two other analogous SMO methods. Since the performance of all SMOs are promising, two instances of WATCLASS modeling Smoky River watershed are calibrated using these three adopted SMOs and the resultant Nash-Sutcliffe numbers are reported.