Owners of combined sewer systems must make decisions concerning the control of overflows that have significant cost considerations. Computer models, both of the collection system and of receiving waters, can be beneficial in making informed decisions. However, water quality models that include combined sewer overflows (CSOs) as point sources face challenges in characterizing the pollutant loads from these highly variable sources. The pollutant strength of CSOs varies not only from location to location, but also temporally at a given location. Differences in both population density and the hydraulic configuration of an overflow structure can affect the fraction of sanitary sewage present in each overflow event. The situation is often simplified by the use of event mean concentrations (EMCs) that are applied to all CSO locations, which has the effect of characterizing pollutant loads entirely on the basis of volume. The EMC approach suggests that the incremental benefit of increased storage volume remains the same no matter how large the capture volume, which can lead to chasing down increasingly dilute overflows that have minimal impact on water quality.
In this work we make use of available information to develop measures of the severity of individual CSOs (Source Loading). Collection system models, which have been calibrated on a volume basis, have a tracer added to them that represents the base sanitary sewage load. The loads come from estimates of sewage flows derived as a GIS exercise, using a combination of housing counts, winter water billing records and population data. The resulting tracer concentrations in the overflows are used to determine the relative contribution of sanitary sewage to the total volume of each overflow event, thereby revealing differences among events at a given location as well as among multiple locations. Curves are developed to show the total annual (typical year) volumes of both CSO and its sanitary sewage component captured, at each overflow location, for a range of storage facility volumes. The curves can be used to assess where a storage facility of a given volume could capture the greatest volume of sanitary sewage.
The paper will provide details of the methods used to derive the sanitary loads, including a discussion of the uncertainties. Storage curves from various locations will be presented to illustrate the range of CSO strengths that the methodology captures. An emphasis will be placed on how the use of tracers in collection system models can provide additional information beyond what is typically expected in terms of volume and flow rate, and how this information can be beneficial in making more effective use of resources for CSO control.