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PROBABILISTIC METHODS IN STREAM QUALITY MANAGEMENT 1
Author(s) -
Burges Stephen J.,
Lettenmaier Dennis P.
Publication year - 1975
Publication title -
jawra journal of the american water resources association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.957
H-Index - 105
eISSN - 1752-1688
pISSN - 1093-474X
DOI - 10.1111/j.1752-1688.1975.tb00664.x
Subject(s) - probabilistic logic , monte carlo method , uncertainty analysis , quality (philosophy) , water quality , environmental science , econometrics , statistics , hydrology (agriculture) , computer science , mathematics , engineering , physics , geotechnical engineering , ecology , biology , quantum mechanics
. Recent advances in water quality modelling have pointed out the need for stochastic models to simulate the probabilistic nature of water quality. However, often all that is needed is an estimate of the uncertainty in predicting water quality variables. First order analysis is a simple method of providing an estimate in the uncertainty in a deterministic model due to uncertain parameters. The method is applied to the simplified Streeter‐Phelps equations for DO and BOD; a more complete Monte Carlo simulation is used to check the accuracy of the results. The first order analysis is found to give accurate estimates of means and variances of DO and BOD up to travel times exceeding the critical time. Uncertainty in travel time and the BOD decay constant are found to be most important for small travel times; uncertainty in the reaeration coefficient dominates near the critical time. Uncertainty in temperature was found to be a negligible source of uncertainty in DO for all travel times.