HR: 0800h
AN: H21A-1325    [Abstracts]
TI: Assessing the Impacts of Nutrient Load Uncertainties on Predicted Truckee River Water Quality
AU: * Bartlett, J A
EM: justinb@dri.edu
AF: Desert Research Institute, 2215 Raggio Parkway, Reno, NV 89512 United States
AU: Warwick, J J
EM: John.Warwick@dri.edu
AF: Desert Research Institute, 2215 Raggio Parkway, Reno, NV 89512 United States
AB: This study examines the effects of model boundary condition uncertainty on dissolved oxygen (DO) predictions for the Truckee River, Nevada, using an augmented version of the USEPA's Water Quality Analysis Simulation Program, Version 5 (WASP5). DO values are the focal point because observed data indicate that the minimum DO standard of 5 mg/L during the low-flow season is sometimes exceeded. The Truckee River is Lake Tahoe's sole surficial outlet and flows 195 km northeast to its terminus, Pyramid Lake. The river passes through the Reno-Sparks metropolitan area, located in Nevada's Truckee Meadows. East of the Truckee Meadows, fourteen ditches remove water for irrigation. The most significant diversion is Derby Dam, where at least 32% of the river's water is diverted annually. The model's spatial domain is the lower Truckee River, herein defined as the stretch between Derby Dam and Marble Bluff Dam, located 6.4 km upstream of Pyramid Lake. The lower Truckee River is nitrogen limited during a typical loading regime, and organic nitrogen (ON) accounts for most of the nitrogen load to the model reach. This study builds upon a previously calibrated and verified model built with the augmented version of WASP5. This augmented version includes a number of modifications, the most significant of which is the addition of periphyton, or attached algae, to eutrophication kinetics. Because of the important of organic nitrogen, uncertainty analysis is performed on selected ON boundary conditions: the upstream boundary concentrations and agricultural ditch-return concentrations. Using Monte Carlo techniques, boundary concentrations are assigned values from user-defined probability distributions. This stochastic approach yields a range of simulated DO concentrations at each time step for each segment in the model reach. Ranges of simulated values are then used to construct confidence intervals for simulated DO values. The magnitudes of these confidence intervals indicate the uncertainty associated with model DO predictions. Small confidence intervals may indicate that existing water quality monitoring is sufficient, while large confidence intervals may suggest that additional sampling is necessary in order to accurately predict Truckee River water quality.
DE: 1847 Modeling
DE: 1871 Surface water quality
DE: 1873 Uncertainty assessment (3275)
SC: Hydrology [H]
MN: Fall Meeting 2005