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Uncertainty Analysis and Risk Assessment of DO Concentrations in the Buffalo River Using the Perturbance Moments Method
A three-point approximation method, the perturbance moments method (PMM), is applied to quantify the uncertainty of predicted dissolved oxygen (DO) concentrations in the Buffalo River that arise from data variability and parameter uncertainty. A risk assessment is then conducted to systematically compute the probability of exceeding a predetermined water quality standard. Numerical investigations reveal that the overall uncertainty of the output DO concentrations does not necessarily equal the sum of the uncertainties of all individual variables or parameters of interest. Therefore, different sources of uncertainty can have compensative or additive effects on the overall uncertainty of output DO concentrations. In a particular case study of the Buffalo River, the variability of measured concentrations was demonstrated to have the largest influence on the overall uncertainty of predicted DO concentrations. Notably, data with a higher collection frequency should have a smaller uncertainty, and therefore a smaller variability in the expected values, and so contribute less to the magnitude of the standard deviation of the output DO concentrations. The effective risk that DO concentrations exceed the selected standard over time is evaluated. The effective risk that the DO concentration drops below the selected standard is relatively high in a higher-temperature season.
Uncertainty Analysis and Risk Assessment of DO Concentrations in the Buffalo River Using the Perturbance Moments Method
A three-point approximation method, the perturbance moments method (PMM), is applied to quantify the uncertainty of predicted dissolved oxygen (DO) concentrations in the Buffalo River that arise from data variability and parameter uncertainty. A risk assessment is then conducted to systematically compute the probability of exceeding a predetermined water quality standard. Numerical investigations reveal that the overall uncertainty of the output DO concentrations does not necessarily equal the sum of the uncertainties of all individual variables or parameters of interest. Therefore, different sources of uncertainty can have compensative or additive effects on the overall uncertainty of output DO concentrations. In a particular case study of the Buffalo River, the variability of measured concentrations was demonstrated to have the largest influence on the overall uncertainty of predicted DO concentrations. Notably, data with a higher collection frequency should have a smaller uncertainty, and therefore a smaller variability in the expected values, and so contribute less to the magnitude of the standard deviation of the output DO concentrations. The effective risk that DO concentrations exceed the selected standard over time is evaluated. The effective risk that the DO concentration drops below the selected standard is relatively high in a higher-temperature season.
Uncertainty Analysis and Risk Assessment of DO Concentrations in the Buffalo River Using the Perturbance Moments Method
Tsai, Christina W. (Autor:in) / Li, Mao (Autor:in)
18.02.2014
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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