Water Quality, Exposure and Health

, Volume 5, Issue 4, pp 163–172 | Cite as

A Dynamic Model to Quantify Pathogen Loadings from Combined Sewer Overflows Suitable for River Basin Scale Exposure Assessments

  • Rishab Mahajan
  • James G. Uber
  • Joseph N. S. EisenbergEmail author
Original Paper


Raw sewage discharges from Combined Sewer Overflows (CSOs) during rainfall can severely impact microbial drinking water quality. These pathogen loading events are episodic and short lasting. Traditional risk assessment that uses mean exposure values will therefore average out these short term duration high risk events, and result in underestimates of risk. A more accurate approach requires a characterization of the exposure dynamics that result from multiple upstream CSO communities, creating a challenge for more computational and data intensive urban watershed models. To this end, we developed a simple dynamic model of CSOs to estimate overflow discharges from combined sewer networks for river basin scale exposure assessments. The impervious subcatchment and sewer system are modeled as linear reservoirs in series. The overflow volume estimates of this CSO model were found to be in good agreement with a sophisticated hydrodynamic model (SWMM), and with real overflow data with R 2 values of 0.96 and 0.91, respectively. Pathogen loadings from CSO’s were estimated by superimposing simulation of overflow discharges on raw sewage enteric pathogen concentration. We apply this simplistic approach to estimate pathogen concentration due to multiple upstream CSO’s in a hypothetical river basin, demonstrating that this simplified model is suitable for representing the dynamics of CSO induced pathogen loadings into receiving waters. The model serves a framework to estimate the dynamics of pathogen loadings that are central to river basin microbial risk assessments.


Combined sewer overflows Enteric pathogens River basin scale 



This work was funded by USEPA Star Grant RD8317270. We thank Joseph Koran, Frank Brown and Ann Bealer at MSD-GC for making the overflow data available.


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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Rishab Mahajan
    • 1
  • James G. Uber
    • 1
  • Joseph N. S. Eisenberg
    • 2
    Email author
  1. 1.Department of Civil and Environmental EngineeringUniversity of CincinnatiCincinnatiUSA
  2. 2.Department of EpidemiologyUniversity of MichiganAnn ArborUSA

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