Evaluation of Combined Sewer System Operation Strategies Based on Highly Resolved Online Data

Operational and structural interventions in the field of stormwater management are usually planned based on long-term simulations using rainfall-runoff models. The simulation results are often highly uncertain due to imperfections of the model structure and inevitable uncertainties of input data. The trend towards monitoring of combined sewer overflows (CSO) structures produces more and more data which can be used to replace parts of the models and reduce uncertainty. In this study we use highly resolved online flow and quality monitoring data to optimize static outflow settings of CSO tanks. In a second step, the additional benefit of real time control (RTC) strategies is assessed. In both cases the aim is the reduction of CSO emissions. The methodology is developed on a conceptual drainage system with two CSO tanks and then applied to a case study area in Southern Germany with six tanks. A measured time series of six months is sufficient for reliable optimization results in the conceptual catchment as well as in the case study area system. In the investigated system the choice of the optimization objective (minimum overflow volume or total suspended solids (TSS) load) had no significant influence on the result. The presented method is particularly suitable for areas in which reliable monitoring data are available, but hydrological parameters of the catchment areas are uncertain. One strength of the proposed approach lies in the accurate representation of the distribution of emissions between the individual CSO structures over an entire system. This way emissions can be fitted to the sensitivity of the receiving water body at the specific outlets.

Automated summary

Operational and structural interventions in stormwater management are often based on long-term simulations using rainfall-runoff models, leading to uncertainties due to model imperfections and input data variability. Monitoring of CSO structures can provide valuable data to optimize outflow settings and assess real time control strategies for reducing CSO emissions. The method developed in this study is suitable for areas with reliable monitoring data but uncertain hydrological parameters, accurately distributing emissions between CSO structures to match the sensitivity of receiving water bodies.