Central Arkansas Water employees honored with AWWA Heroism Award

Stephen Shirley, Central Arkansas Water foreman (middle) receives the Heroism Award at ACE23 in Toronto from AWWA President Joe Jacangelo (left) and Executive Director David LaFrance (right). Photo courtesy of AWWA.

The American Water Works Association (AWWA) has recognized two Central Arkansas Water employees with its 2023 Heroism Award. The Regional Municipality of York was the recipient of the AWWA Innovation Award. Both were presented during AWWA’s 2023 Annual Conference & Exposition (ACE23) this month in Toronto.

The Heroism Award recognizes an act of heroism performed by a water utility professional who puts themself in personal danger while doing so. Stephen Shirley, a Central Arkansas Water (CAW) foreman, and Chris Duncan, a water distribution specialist II, helped two injured gunshot victims who were involved in a three-vehicle car accident at an intersection in front of their crew truck. 

At the scene, the two CAW employees provided life-saving measures until emergency responders arrived. They approached one vehicle and applied a tourniquet to a victim who was bleeding profusely from a gunshot wound to the leg. They also helped a woman in another vehicle who was bleeding and in shock.

Ranin Nseir, M.Eng., P.Eng., project manager, inflow and infiltration strategy and analysis, York Region (right) accepts the AWWA Innovation Award from T.J. Stroebl (middle), chair of AWWA’s Manufacturers/Associates Council. Photo courtesy of AWWA.

AWWA’s Innovation Award recognizes a member who has inspired or implemented an innovative idea, best practice, or solution to benefit the water sector. This year it was awarded to the Regional Municipality of York (York Region) for developing a machine learning project for managing inflow and infiltration.

York Region designed a machine learning model as part of its Inflow and Infiltration Reduction Strategy. Inflow and infiltration occur when water, groundwater and stormwater enter the wastewater system through pipe misconnections and deteriorated infrastructure. This takes up sewer system capacity and may backup into the environment.

The model uses machine learning to process raw data into actionable information to help make proactive and better-informed decisions to manage infrastructure. Real-time and historical data are integrated to create a priority map that informs future operations and maintenance work. It can predict the way the system would respond to hypothetical precipitation events.

To date, the model has achieved over 90 percent confidence in the analysis based on pilots completed from 2018 through 2022. The York Region has also realized a 78 percent reduction in analysis time when compared to the two weeks it took to do the analysis manually. This amounts to approximately $40,000 in labor costs per analysis of all nine of the municipalities that make up the York Region.

The tool helps ensure money is spent with the greatest impact, and the savings of staff time and resources allows the York Region to focus more on additional planning and finding efficiencies elsewhere in its system.

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