Thesis (M.A.)--Brigham Young University Graduate Dept. of Art. / Electronic thesis. Also available in print ed.

Thesis (M.A.)--Brigham Young University. Dept. of History. / Includes index. Electronic thesis. Bibliography: leaves 189-192. Also available in print ed.

Project (D. Min.)--Trinity Evangelical Divinity School, 1985. / Includes bibliographical references (leaves 132-137).

Thesis (M.A.)--Brigham Young University. Dept. of English, 2005. / Includes bibliographical references (p. 78-83).

Thesis (M.S.)--Brigham Young University. Dept. of Physics and Astronomy, 2005. / Includes bibliographical references (p. 115-120).

I designed a suite of studies in coordination with Utah Division of Wildlife Resources (UDWR) to evaluate waterfowl use of the GSL in winter and ecological aspects associated with GSL use. These studies provided insight into key information gaps previously identified by UDWR regarding management of GSL resources. Population surveys indicated total duck abundance was low when GSL surface elevations were low and wetland resources diminished because of persistent drought in the system. Also, ducks appear to use hypersaline parts of GSL more when freshwater habitats are limited from either drought or ice conditions. Common goldeneye, northern shoveler, and green-winged teal exhibited the most use of hypersaline areas. Dietary evaluations indicated all three species feed on hypersaline invertebrates from GSL to meet energetic and nutritional needs in winter. Brine shrimp cysts were important foods for northern shoveler and green-winged teal. Fat levels of ducks are important determinants of survival and fitness. Fat reserves of goldeneye were generally lower in the winter when both GSL and wetland habitat resources were lower. Results suggest brine fly larvae productivity, freshwater habitat availability, and temperature and wind speed likely play a more prominent role in goldeneye fat reserves than osmoregulation. Also, common goldeneye and northern shoveler using the GSL apparently accumulated biologically concerning amounts of mercury and selenium during winter. However, further research is needed to evaluate the effect of these elements on GSL ducks.

A two-dimensional, finite-element, porous-media flow model is developed to simulate stratified bi-directional flow of brine through the earth embankment carrying the Southern Pacific Railroad across Great Salt Lake. The model is part of a two-year research program whose objective is to develop a computer model of circulation in Great Salt Lake. This overall model is to be used as a predictive device for salinity distributions and circulation patterns in the lake. The porous media flow model is designed to establish flow rates through the Southern Pacific Railroad causeway embankment which traverses the north central part of he lake and divides it into two bodies of water. The study first develops the mathematical equations which describe two-dimensional stratified bi-directional flow of a fluid through porous media. Next , the problem is numerically posed as a boundary value problem in terms of pressure. This formulation is then solved by an iterative finite element scheme which employs quadratic, isoparametric, quadrilateral elements. The study also investigates two possible means of performing an analysis of stratified bi-directional flow with a pressure formulation by either posing the problem as a single boundary value problem with two densities of fluid within, or as two single-density boundary value problems coupled at the density interface. The single boundary formulation did not converge with the techniques attempted due to numerical instability at the density interface. The numerical model developed enables one to calculate fluid flow rates as well as the locations of the free surface and density-interface. The model simulation investigates many lake variables which affect brine flows through the embankment. Realistic model parameters are used which cover the range of actual values observed on the lake for the years 1968 through 1972. The numerical results presented in the study are given in terms of generalized dimensionless variables. The numerical results appeared to be in agreement with previously performed stratified bi-directional Hele-Shaw model studies. The major lake parameters affecting flow rates through the causeway were the free surface head difference, the southside lake surface elevation and the difference in fluid densities between the upper and lower layers of the embankment . The southward density flow was found to be completely cut off for certain combinations of lake parameters. Lack of adequate field data collected on the embankment has left both the geometry and the coefficient of permeability of the fill in question, preventing a rigorous verification of the model' s ability to predict actual flows. More field data are also necessary to establish whether there is stratification on the north side of the embankment which can greatly affect flow calculations. A high Reynold's number was found for flow through the embankment, raising a question as to the validity of the Darcian flow assumption used in the analysis. However, the establishment of the true Reynold's number can only be verified through the collection of more empirical data.

It is well-known that, when it comes to crime, some neighborhoods are safer than others. Researchers who make maps of crime have observed that some areas of cities have more crime than others. These areas of high crime are often called hot spots. Crime pattern theory explained why some neighborhoods have more crime than others by looking at criminal events as a meeting between a motivated criminal and a target. Social scientists, geographers, and city planners have shown that criminals generally choose targets from places they see every day, for example on their ride to work or the grocery store. This means that when the daily routine of a criminal changes, the location of that person's criminal behavior could change too. When trends in the daily routine of a whole city change, the location of crimes in that city could change because criminals, in general, will choose targets from different places in the city. In fact, some researchers have suggested that crimes will become clustered around transportation nodes, such as street car stations, after new lines are opened. But so far only a few studies have tried to demonstrate the pattern hot spots follow in the years following major transportation changes. The answer to this question is important to urban designers and police because it would allow them to respond to changes in the location of hot spots when new public transportation projects occur.

To meet the surging water demand due to rapid population growth and changing climatic conditions around the world, and to reduce the impact of floods and droughts, comprehensive water management and planning is necessary. Climatic variability, hydrologic uncertainty and variability of hydrologic quantities in time and space are inherent to hydrological modeling. Hydrologic modeling using a physically-based model can be very complex and typically requires detailed knowledge of physical processes. The availability of data is an important issue to justify the use of these models. Data-driven models are an alternative choice. This is a relatively new and efficient approach to modeling. Data-drive models bridge the gap between the classical regression and physically-based models. By using a data-driven model that relies on the machine learning approach, it is possible to produce reasonable predictions from a limited data set and limited knowledge of underlying physical processes of the system by just relating input and output. This dissertation uses the Multivariate Relevance Vector Machine (MVRVM) and Support Vector Machine (SVM) for predicting a variety of hydrological quantities. These models are used in this dissertation for identifying influential climate indicators, and are used for long-term streamflow prediction for multiple lead times at different locations in Utah. They are also used for prediction of Great Salt Lake (GSL) elevation series. They provide reasonable predictions of hydrological quantities from the available data. The predictions from these models are robust and parsimonious. This research presents the first attempt to identify influential climate indicators and predict long lead-time streamflow in Utah, and to predict lake elevation using machine learning models. The approach presented herein has potential value for water resources planning and management especially for irrigation and flood management.

This research focuses on the ways in which homelessness is discussed in two newspapers in a major city in the intermountain United States. I analyzed newspaper articles with the goal of understanding public discourse in two ideologically distinct newspaper venues. I examined the news media portrayal of the homeless in 752 articles in these two newspapers during two distinct six­-month time periods, one during which the city was nationally recognized as a major advocate for “Housing First,” or “solving homelessness,” and a more recent period during which urban gentrification has challenged the location of homeless services. Specifically, I addressed the he primary informants drawn upon by the newspapers, and the potential “missing voices” in the media discussion. My research looks at homelessness in these papers both over time and across papers.