Chapter
Apr 26, 2012

Predicting CSOs for Real Time Decision Support

Publication: World Environmental and Water Resources Congress 2009: Great Rivers

Abstract

This paper presents a novel data-driven method for modeling combined sewer overflows (CSOs) in real-time. This method treats CSO event generation as a threshold process that is triggered by increasingly intense rainfall events, and predicts the likelihood of a CSO given input conditions using a Bayesian network. The fusion of relevant data from multiple agencies into a unified data stream in real time is described, and a hierarchical modeling strategy is proposed that will facilitate the exploration of the causes of CSOs and direct research into the adaptive management of combined sewer systems using the Chicago wastewater system as a case study.

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Go to World Environmental and Water Resources Congress 2009
World Environmental and Water Resources Congress 2009: Great Rivers
Pages: 1 - 10

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Published online: Apr 26, 2012

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National Center for Supercomputing Applications, University of Illinois, Urbana, IL, USA 61820. E-mail: [email protected]
Department of Civil and Environmental Engineering, University of Illinois, Urbana, IL, USA 61820. E-mail: [email protected]
Department of Civil and Environmental Engineering, University of Illinois, Urbana, IL, USA 61820. E-mail: [email protected]

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