Modeling stochastic load variations in sewer systems.

In wastewater treatment and environmental risk assessments increasing attention is paid to the fate of micropollutants. These are time-consuming, expensive and difficult to detect and quantify. If a substance's load or concentration is subject to high dynamic fluctuations, it is demanding to take representative samples, especially when the "variation" is unknown. Therefore, we developed a concept to model stochastic load variations in sewer systems. We gathered readily available information from existing databases (population and consumption data) and combined it with the characteristics of household activities and appliances. We succeeded in predicting realistic short-term variations of benzotriazole (contained in dishwasher detergents) and validated them with a high-frequency measuring campaign. Benzotriazole stands as an example for other household chemicals, which cannot be measured so easily. All required information used within this case study is also available for other substances and catchments. This allows the forecast of stochastic load variations for many chemical compounds of interest. It helps to plan measuring campaigns, to estimate discharged loads from combined sewer overflows and to have a characteristic input for modeling purposes.