Masters Theses

Date of Award

5-2014

Degree Type

Thesis

Degree Name

Master of Science

Major

Environmental Engineering

Major Professor

John S. Schwartz

Committee Members

Kelsey Ellis, Jon M. Hathaway

Abstract

Understanding variability in precipitation both spatially and temporally is critical when planning water resources projects. Furthermore, in mountainous regions, such as the Upper Tennessee Valley, orographic precipitation plays a major role in both water supply and potential hazards due to flooding. The temporal and spatial variability of precipitation was investigated by utilizing a dataset aggregated by the Tennessee Valley Authority (TVA). These data consist of 56 rain gauges that were extracted from the larger TVA rain gauge network as well as mean areal precipitation values for 78 subbasins located in the Upper Tennessee Valley that were retrieved from the National Weather Service (NWS) .The Mann-Kendall trend test, Mann-Kendall-Sneyers test, Yamamoto Method, Morlet’s wavelet, Moran’s I, and the local Moran’s I were used to determine trends both spatially and temporally. Results indicate that a.) Only 11 percent of subbasins in the study area are experiencing significant increasing or decreasing trends while no rain gauges are experiencing significant trends. b.) Seasonal precipitation trends varied with the summer and autumn series showing the largest amount of significant increasing trends for the 78 subbasins in the study area. c.) Abrupt changes in precipitation were detected throughout the area for the 1950-2009 period of record with many subbasins having change points corresponding to strong El Niño events. d.) Throughout the study area several subbasins displayed significant periodicities of 1, 6, 18, and 22 years. e.) Annual mean precipitation in addition to annual and seasonal precipitation trends displayed a high degree of positive spatial autocorrelation. f.) Spatial outliers are concentrated in areas that exhibit topographical breaks, which suggest that the Appalachian Mountains have a significant effect on the spatial dependence of rainfall. These discoveries can aide with decision-support in regulatory and managerial policies in water resources by allowing water managers to understand historical water availability at the temporal and spatial level.

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