Technical Papers
Sep 20, 2023

Tracking the Cost of Maintaining Stormwater Best-Management Practice Facilities: The Role of Database Design and Data Entry Best Practices

Publication: Journal of Sustainable Water in the Built Environment
Volume 10, Issue 1

Abstract

Best-management practices (BMPs) are widely used to mitigate non-point source pollution from stormwater discharges. However, long-term operation and maintenance of stormwater BMPs have been an afterthought before the compliance requirement detailed in the Municipal Separate Storm Sewer Systems (MS4) permit. As a result, there is limited information available on the actual cost of maintaining BMPs. The objective of this research is to analyze the stormwater maintenance tracking database created by the Virginia Department of Transportation (VDOT) to (1) complete a preliminary cost analysis of routine and non-routine maintenance with respect to VDOT district or practice type and to (2) identify challenges encountered when processing the data for analysis and provide potential solutions relevant to other entities tracking BMP maintenance costs. The cost analyses presented in this study are preliminary based on the currently available data; however, they show insightful trends among the data collected by VDOT from 2018 to 2020. Namely, preventative maintenance actions appeared to greatly lower the need for non-routine or major repairs within the Virginia districts. Routine and non-routine maintenance costs were, on average, $375 per task and $812 per task, respectively. The cost of major repairs was approximately $63,000 per case. The most expensive routine maintenance tasks were basin BMPs (constructed wetlands, wet ponds, and extended detention ponds), averaging $400 per task. The most expensive non-routine maintenance tasks were infiltration BMPs (permeable pavement, infiltration practices, and bioretention), averaging $1,123 per task. Basin BMPs had the largest annual upkeep at $1,100 per year. Approaches for extending the current database design used by VDOT are discussed to address challenges identified through the analysis including data incompleteness, overloaded work orders, and the lack of controlled vocabulary. These lessons learned regarding database design can be useful to other agencies seeking to track and analyze stormwater maintenance activities and associated costs.

Practical Applications

The tracking of stormwater best-management practice (BMP) operation and maintenance (O&M) practices can help reduce the costs associated with stormwater permit compliance. A key factor in the O&M tracking process is the database design, which governs the collection, storage, accessibility, and analysis of the O&M data. However, the database design for BMP O&M tracking is not well documented. An analysis of the Virginia Department of Transportation’s (VDOT’s) O&M collection process and database design indicates that a many-to-many relationship exists between work orders and BMP assets, hindering the cost analysis of the maintenance work. Other challenges observed were a lack of controlled vocabulary when reporting the maintenance activities, assigning maintenance tasks associated with multiple BMPs to a single BMP, and the presence of incomplete work orders. Access to detailed BMP maintenance information can be used to calculate the approximate costs of routine and non-routine maintenance with respect to district or practice type, to determine estimates for BMP inspection frequencies, and to assess the level of effort needed to maintain certain BMPs. A design extension of the VDOT stormwater O&M tracking database is proposed that can inform the design for other states’ and communities’ stormwater BMP O&M tracking databases.

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Data Availability Statement

Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request. The following data, models, or code are available:
VDOT stormwater work order data created from October 2018 to September 2020.
VDOT stormwater BMP inventory data as of December 2020.
String-searching algorithm Python script.

Acknowledgments

This study was supported by funding from the Virginia Department of Transportation (VDOT). The authors would like to extend their gratitude to VDOT for providing the data for this study and Scott Crafton, John Olenik, Alex Foraste, and Hyung Jun Ahn of VDOT for their valuable insights, guidance, and feedback.

References

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Go to Journal of Sustainable Water in the Built Environment
Journal of Sustainable Water in the Built Environment
Volume 10Issue 1February 2024

History

Received: Nov 15, 2022
Accepted: Aug 21, 2023
Published online: Sep 20, 2023
Published in print: Feb 1, 2024
Discussion open until: Feb 20, 2024

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Graduate Research Assistant, Dept. of Civil and Environmental Engineering, Univ. of Virginia, 351 McCormick Rd., P.O. Box 400742, Charlottesville, VA 22904. ORCID: https://orcid.org/0000-0001-5651-6995
Jacob D. Nelson
Ph.D. Candidate, Dept. of Civil and Environmental Engineering, Univ. of Virginia, 351 McCormick Rd., P.O. Box 400742, Charlottesville, VA 22904.
Savannah L. Cummins
Graduate Research Assistant, Dept. of Civil and Environmental Engineering, Univ. of Virginia, 351 McCormick Rd., P.O. Box 400742, Charlottesville, VA 22904.
P.E.
Professor, Dept. of Civil and Environmental Engineering, Univ. of Virginia, 351 McCormick Rd., P.O. Box 400742, Charlottesville, VA 22904 (corresponding author). ORCID: https://orcid.org/0000-0002-1112-4522. Email: [email protected]

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