Abstract
Urban water quality forecast models for use in real-time integrated control of combined sewer systems are developed and applied to a small combined sewer system in Hamilton, Ontario. Water quality forecasts for lead times ranging from 5 to 60 min are provided for both suspended solids and chemical oxygen demand. Two modelling approaches are examined: (a) a statistical approach based on the formulation of autoregressive moving-average models with exogenous inputs and (b) a two-stage deterministic/stochastic model based on the first-order surface pollutant washoff model. While both groups of model yield comparable forecasts in terms of the mean absolute percent error in water quality forecasts, statistically based models were found to provide definite operational advantages. Key words: adaptative modelling, real-time forecasting, statistical model, stochastic system, urban hydrology, water quality modelling.
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