Modeling Every Sanitary Pipe in the City: Unique Aspects and Benefits
As part of an effort to better manage SSOs and basement backups, the City of Ann Arbor developed a citywide model that includes all of the approximately 11,000 sanitary sewer pipes in their collection system. The model developed was based on the US EPA SWMM 4.4h engine and uses the Rainfall Dependent Inflow and Infiltration (RDII) parameters. This chapter addresses the following key issues associated with this work.
To accommodate the size of the model input, certain parameter arrays were increased from that currently available in 4.4h versions. It was found that optimizing model settings and the computers used to run the model allowed for entire citywide simulations to be run in three to five hours, eliminating the need for multiple area models.
Use of high quality geographic information system (GIS) and global positioning system (GPS) information allowed for quick and efficient model development.
The model uses over 2,600 sub-basins to provide the resolution needed to support the footing drain disconnection program effectively. Further, this resolution reduced dependence on hydrologic parameters to account for routing i.e., the hydraulic model was better utilized to simulate routing than if fewer and larger subbasins were used.
Field data collection included over 80 flow and peak level recorders coupled with radar rainfall distributed data.
A distinct difference in system response was identified between the dormant (winter and early spring) and growth (summer and early fall) seasons.
To facilitate the use of the high number of sub-basins, GIS information, including soil types, percent impervious, surface water features, age of construction, and ground slopes were used to allocate wet weather parameters.
The water use records were linked to the parcel layer to compare dry weather flows (DWF) to flow meter data and to allocate dry weather I/I distinct from sanitary usage.
During calibration, one of the key findings was that shape parameters could be grouped by footing drain and non-footing drain areas and the average size of the sub-basin so that ultimately, only 6 different shape parameter groupings were required to match modeled peak and volume to observed data.
Overall, the city has found the investment into this size of a model to be beneficial as the model is being used to facilitate prioritization of the footing drain disconnection program to maximize removal of footing drain flows and gain the most benefit for relieving system deficiencies and basement flooding. The model is also being used to evaluate newly proposed development projects. This includes analysis of available capacity, best locations for footing drain mitigation to offset new development, and reviewing alternatives for system upgrades to allow for development where footing drain disconnection cannot mitigate system problems
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