Developing Best Estimates for CSO Control Volumes to Meet NPDES Requirements

Abstract
The City of Seattle owns and operates a combined sewer system (CSS) that overflows during heavy rain events into surrounding water bodies, potentially impacting their quality and uses. Hydraulic and hydrologic models of the city’s uncontrolled combined sewer overflow (CSO) basins were developed to identify projects and programs that will limit untreated overflows at each CSO outfall to an average of no more than one annually, a performance standard established in the City’s CSO national pollutant discharge elimination system (NPDES) permit.
After manual calibration, each model underwent an automated calibration process, the automated calibration and uncertainty analysis for storm water management model (ACU-SWMM). ACU-SWMM is a software package created by MGS Engineering Consultants, Inc. (MGS) for use with the U.S. Environmental Protection Agency (USEPA) Storm Water Management Model (SWMM5). It was designed primarily for use with CSSs where uncertainties from multiple sources can make model calibration difficult and severely impact the reliability of sewer flow predictions.
This chapter also describes the process established to identify the overflow control levels using a continuous long term simulation (LTS), taking into account the effect of the several uncertainties due to precipitation time series, collected flow data, climate changes, and model hydrology and hydraulics uncertainties.
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