Identifying Wet-Weather Sanitary System Problems by Combining Field Investigations with Computer Modeling
The combination of field investigation and hydraulic modeling is an effective tool to identify the causes of basement flooding. Field investigation (closed conduit televising) provides detailed information on conditions of the sanitary sewer system, while computer modeling assists in developing a better understanding of overall system performance by allowing an investigation of system response under a range of scenarios that may not be witnessed in the field. During the Livingston/James Sewer System Inflow and Infiltration (I/I) Project (City of Columbus, Ohio), over 700,000 linear feet or 130 mi (213,000 m or 213 km) of sanitary sewer was cleaned and televised, 273 homes were tested to identify the sources of I/I contribution. The information gathered from the field investigation was used as a resource for model calibration and quality assurance/quality control (QA/QC). Meanwhile, a hydraulic model (including sanitary sewers with diameter 8 in. (200 mm) and larger) was applied to quantify the impacts of operation and maintenance and system capacity deficiency.
By comparing the locations of deficient sewer carrying capacity with the patterns of historical water-in-basement (WIB) complaints, the authors summarized the causes of the complaints into two categories: system capacity deficiencies and localized insufficient operations and maintenance(e.g. roots, deposits, etc.). Based on the causes, the recommended solutions include both system capacity improvements (replacement pipes, parallel relief pipes, etc.) and local solutions (back flow prevention devices, roottreatment, cleaning, etc.).
This chapter discusses what the potential improvements would have been without routine sewer maintenance, and demonstrates that either field investigation or a modeling approach alone is insufficient to fully understand and identify wet-weather sanitary system problems. It is the combination of these two activities that may prove to be the best approach in understanding the collection system performance.
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