Speaking

The City of Tampa Water Department supplies water through over 2,200 miles of watermains, serving more than 725,000 people in Tampa and parts of Hillsborough County. In 2025, the city began advancing its watermain risk management practices as part of a Water Master Plan update project, adopting an AI-powered watermain break prediction and replacement planning tool. The city also advanced its methodology and modeling capabilities for estimating the consequences of failure (COF) of watermain breaks to create monetized, triple bottom line (TBL) risk costs associated with every watermain. The resultant advanced risk-cost values improved both the prioritization of watermain replacements and the determination of budgets for replacements to achieve level-of-service goals for water reliability. The watermain replacement planning process began with an evaluation of AI-driven watermain break prediction and replacement planning software.

After an extensive review, the city shortlisted five software solutions and selected the one that most fit their criteria, amongst which was the desire to be able to update the software on their own following the consultant-led master plan and replacement plan update. The selected software was used to predict breaks over the planning horizon and help provide the city with an understanding of their system under several scenarios ranging from “status quo” to several watermain replacement investment scenarios. In addition, the city worked with a consultant to develop comprehensive TBL COF values for every pipe. This included estimating the financial cost to repair the break based on each pipe’s diameter and proximity to roadways, structures, water bodies and railroads. COF values also included the hydraulic impacts of shutting down mains to perform repairs: TBL costs were developed for hospitals, dialysis centers, nursing homes, schools, prisons and other critical customers and large users.

This presentation will share the methodology and tools utilized and provide advice on how to conduct a similar analysis. The presentation will share how Probability of Failure (POF) values we generated using the AI break model and coupled with COF values to develop a risk profile for every watermain and how risk values were used to right-size the watermain replacement planning budget.