Abstract

The full understanding of flow dynamics and pollutant concentrations in combined sewer systems is an important issue in the management and design of these systems.

While detailed data of water levels and discharges is often available and is used in model calibration, water quality data in sufficient quality and detail is often lacking. Conventionally obtained samples (for example from automated samplers and lab analysis) cannot account for the full dynamics of pollutant concentrations encountered in sewer systems, such as the first flush occurrence in wet weather conditions. Moreover, the lack of field data is a critical aspect in modeling, with serious consequences for model calibration (Bertrand-Krajewski, 2007).

In Graz, Austria a sewer online monitoring station has been operated at a combined sewer overflow (CSO) at the outlet of an urban catchment area since 2002. Flow meters are installed in the inflow and the overflow channel of the CSO. A submersible ultraviolet-visible spectrometer probe measures continuously chemical oxygen demand (CODeq), total organic carbon (TOCeq) and total suspended solids (TSSeq) concentrations, with intervals of 3 min during dry weather conditions and 1 min during wet weather conditions, directly in the overflow chamber (Gruber et al., 2005).

Two models of the catchment were set up in previous studies: an aggregated hydrological model in the SMUSI software and a detailed hydrodynamic model in SWMM 5.0. Both models have been coupled with an optimization algorithm based on evolutionary strategies, allowing automated model calibration (Muschalla, 2008). The SMUSI model was calibrated against discharge and pollutant concentrations (CODeq). The SWMM model, set up in late 2009, was calibrated against discharge so far.

This chapter describes the setup of the measurement station, the experiences obtained from its long term operation and the results obtained from the simulation models. The challenges in maintenance, operation and probe calibration are addressed and the limits of in situ sewer monitoring discussed. In addition the results of the discharge simulations from both models are compared, and the quality of the SMUSI model in CODeq prediction is briefly discussed.

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