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A finite difference model for predicting sediment oxygen demand in streams
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Sediment oxygen demand (SOD) is a significant part of the dissolved oxygen budget in waterways, comprising up to 50% in some systems. It, therefore, has the potential of having a significant impact on the environment. As such, an accurate and reliable determination of SOD is needed when applying it to water quality studies. Current measurement techniques are often difficult to implement and produce widely variable and inconsistent results between different methods. There is also currently no standardized approach. This study has aimed to develop an alternative to current measurement techniques that places less reliance on SOD chambers, allowing for easier multiplicity of measurements in order to more accurately quantify the system, especially its variability over space and time. The objectives of this study are: 1) to develop a model for predicting SOD based on parameters developed for the system under study; 2) to validate the model by comparing model results to SOD measurements made in the representative river system using benthic chambers. A finite difference model was developed based on Fick's Law of Diffusion. Mass transfer principles are used to perform a mass balance on the oxygen concentrations in the sediment in order to determine SOD. The developed model was used to predict SOD in the Arroyo Colorado River in South Texas. The model generated results were compared against measurements obtained using benthic chambers in the Arroyo Colorado at three sites. Results show good agreement between model predicted and measured SOD. Average SOD values at each site display percent differences from model predictions of 0.87%, 8.88% and 12.4%. Finally, a sensitivity analysis was performed on the parameter inputs to the model. Results show that the model is most sensitive to the mass convection coefficient. The sensitivity analysis was also performed on all base parameters used to develop the model input parameters. Model predicted SOD was most sensitive to temperature and free-stream oxygen concentration, with relative sensitivities greater than 90%. This model shows potential for future use in a variety of water systems and even as a possible standard method. However, further study is necessary to validate its usefulness in these applications.
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Includes bibliographical references (leaves 81-84).
Issued also on microfiche from Lange Micrographics.
Charbonnet, Danielle Andrea (2003). A finite difference model for predicting sediment oxygen demand in streams. Master's thesis, Texas A&M University. Available electronically from
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