Water Quality Control Under Uncertainty.
Water quality of the effluent from a treatment plant has random variations. In addition, the computed quality of receiving waters is affected by random noises due to uncertainty in initial conditions, nonpoint source loading, parameters that define decay, reaeration, and source terms such as photosynthesis activities, among others. The measurement noise is another random factor. It is safe to assume the underlying random characteristics of all but the effluents to be uncontrollable when considering the design of a treatment plant. The proposed work presents a new design procedure that relates the means and coefficients of variation of effluent to the probability of meeting the water quality standards of the receiving waters. The proposed procedure is an alternative method to the Monte-Carlo method which normally requires thousands of simulations, thus making the method unattractive to large problems. The new method is more accurate than the first-order analysis which cannot consider the dynamic randomness in parameters. Numerical examples are presented to illustrate the proposed methodology.
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