Using Geofluvial Principles to Inform Sewer Stream Crossing Identification

Ryan O'Banion, Senior Associate, Hazen and Sawyer

Junaid Malik, PE, Engineer IV, Fairfax County

Magdalena Springer, Engineer III, Fairfax County

Paul Le Bel, PE, Senior Principal Engineer, Hazen and Sawyer

The Fairfax County Department of Public Works and Environmental Services (DPWES) provides wastewater collection and treatment services to over 250,000 county residents in the Northern Virginia area. DPWES owns and operates over 3,250 miles of sewer collection system, 63 pump stations, and the Noman M. Cole, Jr. Pollution Control Plant with an available treatment capacity of 67 MGD.

DPWES’s Wastewater Collection Division (WCD), responsible for the operation and maintenance of the collection system and pump stations, recently implemented a sewer system-wide risk model in InfoAsset Planner. When assessing risk throughout their system, WCD recognized the need to build upon their existing efforts related to sewer assets within the steam corridor.  Therefore, WCD developed a specialized risk framework and model within InfoAsset Planner to assess the likelihood and consequence of failure specific to sewer assets within the stream corridor.

This presentation will describe WCD’s innovative approach to developing and implementing their new risk-based Creek Crossing Program. WCD first worked to enhance their understanding of stream location by using a high-resolution digital elevation model derived from LiDAR. This led to the identification of over 10,000 sewer assets within the stream corridor, more than double previous estimates. WCD then developed a specialized risk framework and model in InfoAsset Planner to assess both the likelihood and consequence of failure (LOF and COF) specific to sewer assets within the stream corridor. The LOF criteria were based upon geospatial indicators tied to stream instability to predict the risk of asset exposure through geofluvial processes. The indicators were developed using repeatable GIS analyses, built in Python, to allow for the continuous update of the criteria as more refined data become available. Indicators developed include: lateral bank migration, streambed erosion, mass wasting, and physical attributes of the sewer asset such as age and material.

Using a programmatic approach to identification of assets at risk also provides the potential for cost sharing between County organizations. For example, WCD is currently coordinating with Stormwater Planning on where TMDL credits can be obtained while protecting assets. This shared approach provides more bang for the buck in a cost constrained environment.


Author Bio

Ryan O’Banion is an experienced project manager at Hazen and Sawyer with expertise in the use of GIS, statistics, and field assessments to help clients manage stormwater and water resources. Based in Fairfax, Virginia he actively works to incorporate new technologies into workflows that provide more informative and useful work products.