An efficient data-driven method for isolating dry-weather flow from total combined sewer flow data

Wastewater treatment plants in combined sewer systems are often required to accommodate the widely fluctuating flow due to the dynamic interactions between multiple water flow sources. A major challenge in wastewater management, and particularly in combined sewer overflow (CSO) mitigation, is decoupling the total sewer flow into its components: dry-weather flow (DWF) and rain-derived inflow and infiltration (RDII). While current approaches have been successful for dry climates, their requirement to filter out rainfall-affected data often leads to inaccurate estimates for flow components in wet and semi-wet climates or seasons. The twice-detrended residual method (TDRM) developed in this study is a data-driven model that seeks to alleviate this drawback while utilizing all available data. We implement TDRM with sewer flow data collected from three locations and time periods within the Greater Cincinnati, Ohio Metropolitan Sewer District, and demonstrate that it can successfully decouple rain-inclusive flow datasets into their weekly DWF and RDII components.