thesis or dissertation chair
- Henderson, Heidi Belle
The Oak Ridge National Laboratory, Tennessee, was the site for a number of US Government projects during the 1940s and 1950s including the development of thermonuclear weapons. Chemical processes conducted at the site as part of these projects resulted in contamination of certain building areas at the ORNL. The purpose of this study is to develop a hydraulic-hydrologic computer model via XPSWMM to determine surface water flow rates and water stages within the drainage system during rainfall events and introduce a conservative contaminant into the system to trace peak concentrations of contaminants.
The model was calibrated by simulating actual rainfall events over the area of interest. The model results were compared to that of Outfall 211’s monitored data. Trial 1 was most successful, where the cumulative flow rates produced by the model and the monitored data varied only by 0.5 cfs. A sensitivity analysis was completed by varying Manning’s coefficient and infiltration parameters within the area of interest. The sensitivity analysis concluded that the model was responsive to the variations presented; however, only minor differences were determined for the selected range of parameters, indicating robustness of model predictions.
A hypothetical conservative contaminant was entered into the system as constant and varied timeseries. The resulting pollutographs produced by XPSWMM aid in the assessment for potential mobilization of contaminants and provide insight to where peak concentrations and loads occur under present conditions.
Probability exceedance and probability distribution methods were used to analyze the timeseries of flow and pollutant concentrations collected during this study. Probability exceedance curves determined the percentage of time flooding occurred within the system under various conditions. The flow rates and concentrations produced by the transport analysis were best described by the Generalized Extreme Value, while the loading rates were best described by Log-logistic distribution.
- November 14, 2013
- surface water