Date
Monday, September 9, 2024
Time
1:30 PM - 2:00 PM
Location Name
M103
Name
Behind the Curtain of Predictive Modeling for Service Line Inventories
Track
Distribution
Description

The EPA finalized the Lead and Copper Rule Revisions (LCRR) and released the proposed Lead and Copper Rule Improvements (LCRI) on November 30, 2023. These regulatory changes are impacting water treatment systems in many ways, including: the development of service line material inventories and lead service line replacement plans, evaluations of corrosion control treatments, changes to compliance sampling locations and methods, sampling for lead at schools and childcare facilities, and public education requirements. This presentation will focus on the development of service line inventories and describe how our predictive models are created to assist utilities across the country to meet the compliance requirements. Black & Veatch’s work with more than 470 water systems and numerous state regulators across the country have provided us valuable insight on how to develop service line inventories and predictive models for identifying service line materials. Our LCRR programs for utilities followed a similar critical path: 1) identify the known information regarding service line materials, 2) complete a gap analysis of unknown service line materials, 3) develop a predictive model and identify the number and location of sites for field verifications, 4) conduct field verifications with developed SOPs and public outreach materials, 5) calibrate the predictive model and determine the accuracy of the model, 6) complete the service line inventory for compliance and public display, 7) prioritize service line replacements with social equity and planned infrastructure projects. Our projects utilize predictive modeling to estimate the likelihood that an unknown service line material could be lead. Several locations are then verified with potholing field investigations to validate the model. This information is tracked with GIS maps and business intelligence dashboards to ensure that all levels of customer notification, scheduling, pitcher filter delivery, potholing, lead sampling, etc. are tracked and completed. These dashboards are equipped with logic to categorize the service line material type and help the utility understand what actions could need to be taken at each service connection in their system. Tracking dashboards allow utilities to stay informed of the program’s progress and helps plan for upcoming costs. This presentation will focus on the predictive modeling aspects of these projects including development of a predictive model, statistics used in the selection of required field investigation sites, calibration of a predictive model to minimize bias, evaluation of model accuracy with a subset of the field verifications, and the interactive dashboards developed to assist with visualization and prioritization of service line replacements. This is a peak behind the curtain to understand the methods employed and why predictive modeling was our recommendation to complete service line inventories.