Assessing the Responses of Streamflow to Pollution Release in South Carolina
Abstract
The purpose of this investigation was to examine the effects of various stream flows on the transport of a pollutant downstream and to evaluate the uncertainty associated with using a single stream flow value when the true flow is unknown in the model. The area used for this study was Horse Creek in South Carolina where a chlorine pollutant spill has occurred in the past resulting from a train derailment in Graniteville, SC. In the example scenario used, the chlorine gas pollutant was released into the environment, where it killed plants, infected groundwater, and caused evacuation of the city. Tracking the movement and concentrations at various points downstream in the river system is crucial to understanding how a single accidental pollutant release can affect the surrounding areas. As a result of the lack of real-time data available this emergency response model uses historical monthly averages, however, these monthly averages do not reflect how widely the flow can vary within that month. Therefore, the assumption to use the historical monthly average flow data may not be accurate, and this investigation aims at quantifying the uncertainty associated with using a single stream flow value when the true stream flow may vary greatly. For the purpose of this investigation, the event in Graniteville was used as a case study to evaluate the emergency response model. This investigation was conducted by adjusting the STREAM II V7 program developed by Savannah River National Laboratory (SRNL) to model a confluence at the Horse Creek and the Savannah River system. This adjusted program was utilized to track the progress of the chlorine pollutant release and examine how it was transported downstream. By adjusting this program, the concentrations and time taken to reach various points downstream of the release were obtained and can be used not only to analyze this particular pollutant release in Graniteville, but can continue to be adjusted and used as a technical tool for emergency responders in future accidents. Further, the program was run with monthly maximum, minimum, and average advective flows and an uncertainty analysis was conducted to examine the error associated with the input data. These results underscore to profound influence that streamflow magnitudes (maximum, minimum, and average) have on shaping downstream water quality.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2017
- Bibcode:
- 2017AGUFM.H23C1662M
- Keywords:
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- 0430 Computational methods and data processing;
- BIOGEOSCIENCES;
- 1805 Computational hydrology;
- HYDROLOGY;
- 1846 Model calibration;
- HYDROLOGY;
- 1873 Uncertainty assessment;
- HYDROLOGY