For a long time Marais's model has been the main tool for disinfection prediction in waste stabilization ponds (WSPs), although various authors have developed other disinfection models. Some ten other empirical models have been listed over the past fifteen years. Unfortunately, their predictions of disinfection in a given pond are very different. The existing models are too empirical to give reliable predictions: often their explanatory variables were chosen arbitrarily. In this work, we try to demonstrate that if influent variables have daily variations, the use of their average values in simulations may overestimate the disinfection effect. New methods are thus needed to provide better fittings of the models. Better knowledge of the mechanisms involved is needed to improve disinfection models.

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