Communications Project

Document Type:Master's Thesis
Name:Daniel S Dorsel
Title:Spring Hollow Reservoir: Application of a two-dimensional water quality model
Degree:Master of Science
Department:Civil and Environmental Engineering
Committee Chair: John C Little
Committee Members:Dan Gallagher
Robert Hoehn
Keywords:modeling, water treatment, reservoir
Date of defense:June 12, 1998
Availability:Release the entire work for Virginia Tech access only.
After one year release worldwide only with written permission of the student and the advisory committee chair.


The BETTER water quality model, created by TVA, was used to model the temperature and dissolved oxygen (DO) in Spring Hollow Reservoir. The water balance consisted of pump discharge from the Roanoke River, runoff, releases at the dam, leakage, and storage. The geometry of the reservoir was represented by four columns and a variable number of five-foot layers. Through a sensitivity analysis, the parameters that influenced temperature and DO the most were determined. Temperature was then calibrated to a subset of the 19-month simulation period by systematically varying the most sensitive parameters. DO was calibrated to the entire simulation period due to the young age of the reservoir and the inconsistent inflow rates and timing. The verification process showed that the model reasonably reproduced the seasonal temperature patterns. By varying the sediment oxygen demand temporally and spatially, the model depicted the gradual hypolimnetic oxygen depletion in the reservoir. The model results suggest that the inflow organics and subsequent settling and accumulation are key factors in the DO depletion rate. Therefore, to enhance water quality conditions in the reservoir, a monitoring system in the Roanoke River should be installed with filling carried out when water quality in the river is optimal. For future modeling purposes, this research indicated that the model was very sensitivity to meteorological data, especially in determining temperature. Thus, a weather station located at the reservoir would permit collection of more accurate meteorological data, leading to greater confidence in the interpretation of the model predictions.

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