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Assessing the Impacts of Nutrient Load Uncertainties on Predicted Truckee River Water Quality
Authors:Justin Bartlett  John J Warwick
Affiliation:1Associate Geoscientist, Tetra Tech EC, Inc., Santa Ana, CA 92705.
2Executive Director, Division of Hydrologic Sciences, Desert Research Institute, Reno, NV 89512.
Abstract:This study examined the effects of uncertain model boundary conditions on dissolved oxygen (DO) predictions for the lower Truckee River, Nevada using an augmented version of the EPA’s Water Quality Analysis Simulation Program Version 5 (WASP5) that included periphyton, or attached algae, in eutrophication kinetics. Uncertainty analyses were performed on selected organic nitrogen (ON) and carbonaceous biochemical oxygen demand boundary conditions using Monte Carlo techniques. The stochastic model was run using boundary concentrations assigned from observed probability distributions. Ranges of simulated values were used to construct confidence intervals, the magnitudes of which indicated the uncertainty associated with model predictions. Uncertainty in agricultural ditch return concentrations had minimal effects on in-stream model predictions, as predicted values of daily minimum and maximum DOs, daily average ON, and periphyton biomass all failed to show significant variability as a result of ditch concentration uncertainty. This result indicates that while ditch return nutrient loads are not trivial, their exact concentrations are not needed to make relatively accurate predictions of in-stream DO. However, uncertainty in the upstream ON boundary did result in significant uncertainty during summer months with regard to in-stream model predictions of ON, periphyton biomass, and DO. The model is clearly more sensitive to changes in this boundary than to changes in agricultural ditch concentrations.
Keywords:Monte Carlo method  Nevada  Numerical models  Nutrient load  Stochastic models  Surface water  Uncertainty principles  Water quality  Rivers  
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