Science Inventory

Framework for Modeling Lead in Premise Plumbing Systems Using EPANET

Citation:

Burkhardt, J., H. Woo, J. Mason, F. Shang, S. Triantafyllidou, M. Schock, D. Lytle, AND R. Murray. Framework for Modeling Lead in Premise Plumbing Systems Using EPANET. JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT. American Society of Civil Engineers (ASCE), Reston, VA, 146(12):04020094, (2020). https://doi.org/10.1061/(ASCE)WR.1943-5452.0001304

Impact/Purpose:

This work discusses the use of EPANET with dispersion for predicting lead concentrations in premise plumbing systems. This work presents the preliminary work associated with modeling lead in homes, which will be extended in future publications to include a probabilistic approach for determining usage patterns. Individuals interested in modeling distribution systems or premise plumbing systems will find this work interesting. This work will also be of value to those interested in potential exposure pathways for lead in drinking water.

Description:

Lead contamination of drinking water in homes and buildings remains an important public health concern. In order to assess strategies to measure and reduce exposure to lead from drinking water, models are needed that incorporate the multiple factors affecting lead concentrations in premise plumbing systems (PPS). In this study, the use of EPANET, a commonly used hydraulic and water quality model for water distribution systems, was assessed for its ability to predict lead concentrations in PPS. The model was calibrated and validated against data collected from multiple experiments in EPA’s Home Plumbing Simulator that contained a lead service line and multiple lead sources. EPANET’s first-order saturation kinetics model was used to model the dissolution of lead in the lead service line. An improved version of EPANET allowed for modeling of dispersion (using an advection-dispersion-reaction (ADR) method using the EPANET toolkit for hydraulics) and small lead sources through the PPS. Modeling results were compared to experimental data, and recommendations were made to improve the EPANET based modeling framework for predicting lead concentrations in PPS.

Record Details:

Record Type:DOCUMENT( JOURNAL/ PEER REVIEWED JOURNAL)
Product Published Date:12/01/2020
Record Last Revised:02/22/2021
OMB Category:Other
Record ID: 350524