Flow-dividing structures in combined sewer systems serve to mitigate hydraulic overloads during storm events by providing retention capacity. Their operational performance can be enhanced by adjusting the continuation flows regulated by their flow control devices. To optimise system efficiency to reduce emissions, it is essential to use existing volumetric capacities more efficiently, e.g. by adjusting continuation flows. To assess this potential, statistical analyses are conducted on water level measurements from combined sewer overflow (CSO) structures (e.g. frequency analyses) to derive meta information used to assess the baseline functioning. Meta information, such as weir heights, basin base areas and continuation flows, with higher accuracy than would be feasible through manual measurements in the structures or extraction from construction plans, are derived solely from measured water levels. Derived meta information is employed to isolate events to determine reliably CSO occurrence and duration. The continuation flows are optimised using an emulator coupled with a genetic algorithm, with the objective of achieving enhanced operational performance. The case study, which involved eight CSO structures, revealed improvements in efficiency. Overall system efficiency increased from the baseline functioning to the optimized operational setup through the static adjustment of the continuation flows within a range of +/- 50%.
Sedki et al. (Fri,) studied this question.