projects/3d-stratigraphic-data-mgmt-systemprojects/SEPATF-NG911-phase-1
  • Sewer Consent Decree Program Heat Map

In 2005, the Environmental Protection Agency (EPA) and Maryland Department of the Environment (MDE) brought forth a Consent Decree against Baltimore County to investigate and improve the County’s vast sewage collection system’s operations over a 14-year timeframe to comply with the Clean Water Act.

The county and its consultant team (led by prime contractor Louis Berger) have implemented GIS technology in important ways to achieve the goals set forth by the Consent Decree and eliminate sewage overflows through inspection and preventative maintenance. geographIT, a division of EBA Engineering, Inc., has been instrumental in identifying the best GIS tools and analytical methods to improve the project’s workflow and analyses.

geographIT has been applying GIS analysis and backend geo-processing automation with Python and SQL scripts to support work order creation and updates, summarize work order activities, provide status updates for management, produce activity summary reports for the County and EPA/MDE, and provide easy access to non-GIS users in the field through web-enabled GIS data.

All system overflows are reported to the County, including the address and, if available, the ID of the backed-up pipe segment. The overflow events are then mapped in GIS using the overflow address or by matching the pipe ID to the sewer segment. Even if only an address is available, spatial analysis can be used to select the closest sewer segment to the mapped GIS point and identify the clogged segment.

If roots have caused the overflow, the pipe segments are put on a special cleaning schedule to remove the future root growth and prevent additional clogging in the pipe. Inspections also determine if the pipe segment needs to be repaired or replaced. If fats, oils, and grease (FOG) have caused the overflow, GIS is used to trace the sewer network upstream of the overflow and identify the source of the FOGs entering the system.

Since multiple years of overflow data are now available, the team can perform spatial analysis on all the mapped overflow data to identify areas of frequent overflow events.

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