This thesis is concerned with the fisheries of Deer Creek Reservoir, Wasatch County, Utah, with special emphasis on the yellow perch. The study period was from May 13 to November 24, 1968. Objectives included the determination of size, age, and food habits of the yellow perch. Parasitic occurrences in the perch population by Ligula intestinalis were also recorded as well as the utilization of the perch by the fishermen. Observations on other species of fish including an analysis of rainbow trout stocking programs were also objectives of this thesis. Data was gathered by means of creel census and fish collection techniques. Collections were made by use of seine, hook and line, shocking and experimental gill nets.

Thesis (D. Min.)--McCormick Theological Seminary, 1997. / Includes bibliographical references.

Thesis (Ph. D.)--Ohio State University, 2004. / Title from first page of PDF file. Document formatted into pages; contains xiii, 253 p.; also includes graphics (some col.). Includes abstract and vita. Advisor: Earl F. Epstein, Dept. of Natural Resources. Includes bibliographical references (p. 228-238).

Thesis (M.S.)--Southern Oregon University, 2008. / Includes bibliographical references (leaves 36-38). Also available via Internet as PDF file through Southern Oregon Digital Archives: http://soda.sou.edu. Search Bioregion Collection.

Deer Creek Reservoir in Utah has a history of high algae concentrations. Despite recent nutrient reduction efforts, seasonal algae continue to present problems. Cost effective, accurate, and comprehensive monitoring is important to understand the reservoir processes driving this problem and characterizing the algae spatial and temporal distributions are an important part of this effort. Current laboratory methods for accurately measuring algae are expensive and time consuming and are based on water samples taken in the field and transported to the laboratory. This approach only provides data for relatively few point samples because of the time and expense of sample collection and analysis. These relatively few samples do not describe the complex spatial and temporal trends in the algal data. Algae exhibit non-uniform distributions, especially in the vertical direction. In situ probes are able to measure chlorophyll-a and provide a less expensive measuring alternative than laboratory methods. These probes provide relatively quick, high resolution vertical profile measurements, which allows for more comprehensive horizontal and temporal sampling. To have confidence in the probe data, good correlations between in situ chlorophyll-a measurements and laboratory algae or chlorophyll measurements are important, but these correlations can be reservoir and time dependant as reservoir conditions change. Therefore, they must be developed for each study site. This study reports on efforts at Deer Creek Reservoir to develop these correlations and provide a general description of the dynamic reservoir algal processes. I found that chlorophyll-a is weakly correlated to most algae species in the reservoir. However, it correlated well with total phytoplankton biovolume and the dominant algal species, which for this study was the diatom. Variations in correlation strength among the several algae species was assumed to most likely be affected by environmental factors, sample methods, algae species diversity, and the accuracy of the optical chlorophyll-a sensor. The data analysis indicate that the field methods used to obtain laboratory samples may have been a significant source of error because of the difficulty of matching the location of a probe measurement to the location of a sample. Field samples were not taken at the same depths as probe measurements and field samples from two locations were either mixed before laboratory analysis or the sample was a composite over a 2-meter range. Based on my observations, I have made several recommendations to improve the accuracy of the correlation between algae and chlorophyll-a.

The accurate prediction of water quality is essential for management of reservoirs used for drinking water supply. Since algae are a major source of taste and odor problems in drinking water, understanding and controlling algal growth and production is an important task. Deer Creek Reservoir supplies drinking water for over one million people in northern Utah and has been highly eutrophic in the past. Despite major reductions in external nutrient loading, including phosphorus, seasonal algal blooms in Deer Creek have not decreased to desired levels. Resuspension of sediment has been suggested as a potential source of internal nutrient loading for water bodies (including reservoirs in the Utah/Wyoming area) and may be responsible for delays in water quality improvement. I investigated sediment deposition and resuspension rates at the upper end of the reservoir and evaluated these sediments as a possible internal source of phosphorus. Sonar and GPS systems were used to make measurements of recently deposited sediment in the submerged Provo River delta of Deer Creek Reservoir during the period of May, June, July, and August 2011. ArcGIS 10 was used to interpolate survey points and calculate sediment volume changes, including areas of deposition and erosion. These data were used to develop approximate sedimentation rates for the soft sediment – which is most susceptible to resuspension during reservoir drawdown. I used previously measured field phosphorous concentrations in the sediment to estimate if these processes could affect reservoir phosphorous concentrations. The study used two survey areas, a small area near the Provo River inlet early in the year, and an extended larger area starting on June 23rd. I found that sediment volume in the smaller study area was increasing at a rate of 27-109 m3/day during the spring season. Data show that rates are slightly correlated with flow and reservoir elevation. Typically by August, Deer Creek reservoir would have been drawn down 2 to 4 m. However, due to a heavy snow pack in 2011, Deer Creek reservoir was not drawn down. When the reservoir is drawn down, the sediments in the upper region of the delta, where the survey was conducted, will be resuspended and deposited lower in the reservoir. These processes will likely result in releasing the phosphates currently bound to the sediment into the water column. Based on previous measurements of readily soluble phosphates bound to the sediment, this resuspension could release between 80 and 230 kg of phosphorus from the study area into the water column during critical times during the warm months–conditions well suited for algal growth. This amount of phosphorus, while an upper bound of what could be expected under actual field conditions, could raise phosphorus concentrations in the survey area by as much as 0.38 mg/L. The potential P (80-230 kg) release could account for 14%-42% of the TMDL. This is a potentially significant amount, especially if released during the critical late-summer period, and warrants more detailed study.

I evaluated twenty-eight years (1980-2007) of spatial-temporal water quality data from Deer Creek Reservoir in Utah. The data came from three sampling points representing the lotic, transitional and lentic zones. The data included measurements of climatological, hydrological and water quality conditions at four depths; Surface, Above Thermocline, Below Thermocline and Bottom. The time frame spanned dates before and after the completion of the Jordanelle Reservoir (1987-1992), approximately fourteen miles upstream of Deer Creek. I compared temporal groupings and found that a traditional month distribution following standard seasons was not effective in characterizing the measured conditions; I developed a more representative seasonal grouping by performing a Tukey-Kramer multiple comparisons adjustment and a Bonferronian correction of the Student's t comparison. Based on these analyses, I determined the best groupings were Cold (December - April), Semi-Cold (May and November), Semi-Warm (June and October), Warm (July and September) and Transition (August). I performed principal component analysis (PCA) and factor analysis (FA) to determine principal parameters associated with the variability of the water quality of the reservoir. These parameters confirmed our seasonal groups showing the Cold, Transition and Warm seasons as distinct groups. The PCA and FA showed that the variables that drive most of the variability in the reservoir are specific conductivity and variables related with temperature. The PCA and FA showed that the reservoir is highly variable. The first 3 principal components and rotated factors explained a cumulative 59% and 47%, respectively of the variability in Deer Creek. Both parametric and nonparametric approaches provided similar correlations but the evaluations that included censored data (nutrients) were considerably different with the nonparametric approach being preferred.

No description available.

Ground subsidence due to underground coal mining is a complex, narrowly-understood phenomenon. Due to the complicated physical processes involved and the lack of a complete knowledge of the characteristics of overlying strata, the reliability of current prediction techniques varies widely. Furthermore, the accuracy of any given prediction technique is largely dependent upon the accuracy of field measurements and surveys which provide input data for the technique. A valuable resource available for predicting and modeling subsidence is aerial survey technology. This technology produces yearly datasets with a high density of survey points. The following study introduces a method wherein these survey points are converted into elevation plots and subsidence plots using GIS. This study also presents a method, titled the Type-Xi Integration method (TXI method), which improves upon a previous subsidence prediction technique. This method differs from the previous technique in that it incorporates accurate surface topography and considers irregular mine geometry, as well as seam thickness and overburden variations in its predictions. The TXI method also involves comparing predicted subsidence directly to measured subsidence from subsidence plots. In summary, this study illustrates a method of combining data from aerial survey points and mine geometry with subsidence models in order to improve the accuracy of the models.

No description available.