Thesis (Ph. D.)--University of Wisconsin--Madison, 1980. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 179-187).

Theses (M.S.)--Marshall University, 2006. / Title from document title page. Includes abstract. Document formatted into pages: contains xii, 117 p. including illustrations and map. Bibliography: p. 36-42.

Thesis (Ph. D.)--University of Tennessee, Knoxville, 2003. / Title from title page screen (viewed Sept. 23, 2003). Thesis advisor: R. Bruce Robinson. Document formatted into pages (xxi, 268 p. : ill. (some col.)). Vita. Includes bibliographical references (p. 196-206).

Thesis (M.S.)--Ohio University, March, 1992. / Title from PDF t.p.

M.Sc. / The Vaal Dam (South Africa) and its tributaries have been extensively affected by domestic, mining, agricultural and industrial activities, as well as the release of effluents. These practices have contributed to large-scale algal blooms that have caused serious ecological, aesthetic, water purification and water distribution problems. This study addresses the need to develop a system that enables forecasts to be made regarding potential changes in the water quality ofthe Vaal Dam, especially with regards to predicting algal blooms. The primary aim was to develop a simple spreadsheet based model to predict the occurrence of algal blooms and other water quality changes in the Vaal Dam, making use of environmental parameters recorded at several sites located upstream of the Rand Water intake point at the Vaal Dam wall. Accurately forecasting sudden changes in water quality would enable proactive resource management, ensuring that Rand Water maintains a high standard of potable water delivered to its customers. Statistical model equations, to predict the concentrations of various water quality constituents, were obtained by step-wise regression analysis. These equations were then entered into MS-Excel spreadsheets. This allowed the input of environmental data and the subsequent calculation of the predicted value. This also allowed for the manipulation of various parameters to forecast the effects any changing values will have on the water quality. These "if-then'' scenarios would be of considerable use in implementing management measures to achieve the desired water quality. The performance of the model was statistically tested to determine if it adequately represents the study system. The models to determine chlorophyll-a concentration and several other water quality constituents proved to be fairly accurate in representing the study system. However, the model to predict nitrate concentrations did not perform satisfactorily. The limitations in model performance were attributed to the low frequency of water quality sampling and the effects of undetermined variables not represented by the water quality parameters selected for model development. The model is compact, does not require specialised software, and is applicable in practice. The predictive and scenario forecasting abilities make this model useful for the identification, monitoring and prediction of changes or trends in water quality over time. The benefits arising from this model will thus contribute to more cost efficient water treatment, improved response times to algal blooms, improved decision-making and proactive water resource management.

by Liu Ah-chuen. / Bibliography: leaves 122-125 / Thesis (M.Phil.)--Chinese University of Hong Kong, 1982

Thesis (M.S.)--University of Wisconsin--Stevens Point, 2009. / Submitted in partial fulfillment of the requirements for the degree Master of Science in Natural Resources (Water Resources), College of Natural Resources. Includes bibliographical references (leaves 28-29).

Thesis (Ph. D.)--Auburn University. / Abstract. Includes bibliographical references (p. 64-67).

A statistical analysis of water quality data collected on paired agricultural watersheds was undertaken. The objective of the study was to evaluate trends in water quality. The data sets that were used to determine the changes in water quality were taken from the project "Gestion de leau dans le bassin versant de la partie superieure du ruisseau St. Esprit". For the period from 1994 to 1996, the analysed water quality parameter were nitrate, phosphate, ammonium, potassium, total Kjeldahl nitrogen, total phosphorus and suspended sediment. / The data sets were analysed using descriptive statistics, graphical techniques and non-parametric methods to detect trends in the measured water quality parameters. The statistical analyses were undertaken to determine the effects of soil conservation practices and fertiliser management and to compare different sampling strategies. / The analyses showed that there were no detectable changes in water quality over the 3-year period related to the conservation practices. The lack of improvement in water quality might be due to the slow rate of adoption of conservation practices and to climatic variations. / For the non-parametric methods applied, it was possible to show that climatic variations on small watershed affect the results over a short time period (<5 years). The phosphate concentration on the control showed a significant upward trend. The nitrate concentration on St. Esprit showed an upward trend over the 3-year period and then downward trend after a 4-year period of water quality data. This was likely due to the implementation of best management practices. / The statistical analyses showed that weekly sampling on fixed schedule produce the same results as automated sampling based upon flow rate related to a defined discharge. This shows that the more complex and expensive flow weighted sampling scheme is not required to detect trends in water quality.

Thesis (M.S.)--University of Wisconsin--Stevens Point, 2007. / Includes bibliographical references (p. 47-49).