Stochastic Determination of Combined Sewer Overflow Loads for Decision-Making Purposes and Operational Follow-Up

Characterizing the emissions and impact of combined sewer overflows (CSOs) remains one of the key challenges in the field of urban wastewater. Considering the large number of existing CSOs, decision-makers need a pragmatic approach that allows fairly easy, hands-on determination of emissions (particularly loads) without compromising accuracy. This philosophy is incorporated in the Cockle tool presented here, which uses stochastically processed input from a vast amount of pre-registered water quality data (pollutant concentrations) in combination with spill flow time series either generated from hydrodynamic models or converted from monitored overflow water levels. Uncertainty is intrinsically covered by the statistical output range of the reported results. As a fully automated tool, Cockle allows to readily assess emissions within a chosen time frame, facilitating more accurate guidance for further remediation actions and/or mapping of the current state for operational follow-up.

Automated summary

This article presents a tool called Cockle that allows for the assessment and monitoring of emissions from combined sewer overflows (CSOs) in urban areas. The tool uses a large amount of water quality data and spill flow time series, processed statistically to determine emissions. It provides a means for easily assessing emissions within a chosen time frame.