A Faster Fix for Lead Water Lines

BlueConduit’s software uses existing data to predict the location of lead lines and expedite removal.

A Faster Fix for Lead Water Lines

Matthew Call

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The city of Toledo’s residents are getting safer water thanks to an ongoing underground makeover.

In 2014, the Ohio city had a drinking water advisory due to an algae bloom in western Lake Erie. That brought water quality to the forefront and initiated an effort to provide the best drinking water possible. To do that, the city put lead service line removal at the top of their to-do list. 

“We knew we had to prioritize lead exposure,” says Mark Riley, administrator for the city of Toledo’s Department of Public Utilities. “We researched Flint, Michigan, because of the issues they had, to see what sort of partnerships they were using, and they introduced us to BlueConduit.”  

BlueConduit is a water analytics company that developed machine learning software to locate lead service lines. Not only did Flint’s contamination issues pave the road for Toledo’s lead removal plan, but it is also the reason BlueConduit developed a specific software in the first place. 

Eric Schwartz, co-founder of BlueConduit, says the Flint crisis raised the question of how many people have lead contamination, to which he says no one had a good answer. 

“As a data scientist, I realized this was an opportunity to really help cities like Flint figure out how many lead pipes existed and which homes have lead pipes, and guide the resource allocation so the process can be efficient and equitable,” Schwartz says. 

And that’s exactly what BlueConduit did. They helped the city of Flint locate lead pipes and create public-facing maps to help inform the community about replacement. 

BlueConduit’s software takes existing data about lead pipes, formulates an inspection plan to verify what is known and unknown and from that, makes predictions of where lead lines may be. It provides real-time maps so water utility managers and consumers can see progress on lead pipe replacements in their community.

Getting started

The software was an obvious choice for Riley and the city of Toledo, and they have now been working with BlueConduit for over two years.

The beginning stages were all about building a base of information. “They began by collecting data on all of our service lines, especially documentation on lead lines,” Riley says. “They wanted to see what type of pipe material we had from the city side as well as the pipes going into the customer’s home.”

Cities are urged to upload any data they have about their service lines and parcels so from the very beginning, the software can build from what is known, like how many homes, and which homes have actually had eyes on material in recent years.  

Gathering as much preexisting data as possible is crucial to the process. The more data city officials could provide from the start, the more accurate predictive models would become. 

“BlueConduit helped our staff understand what sort of information was needed and how to transfer it,” Riley says. “They were very straightforward and thorough, asking a lot of questions to make sure they understood how we keep our city data.”

Using the data

After collecting available data, BlueConduit created early models that predicted areas with the highest probability of lead service lines. 

From those early predictive models, city officials were able to do curbside inspections of homes to see firsthand and confirm what type of material was being used. “We could then plan our lead service line replacement program to first target the neighborhoods with the greatest concentration of lead,” Riley says. 

The models are constantly being updated with new data as officials replace pipes and visit more areas of the city for inspections, making them more and more accurate over time. 

Data collected, as well as the corresponding maps and models, are not only available to city officials but to anyone interested. Riley welcomes and encourages the public to stay engaged, so maps are available in a public online portal.

“We worked with Toledo to put together a map of the entire city with predictions, address by address online, so anyone can access the information at any time,” Schwartz says. 

And according to Riley, the portal is getting a lot of attention thanks to media blasts and a YouTube video highlighting the research while helping customers identify pipes in their home. It’s important to Riley that the public is involved, knowledgeable and feels comfortable asking questions when crews are working near their homes. 

Keeping citizens feeling comfortable throughout the process of replacing lines is also a priority. “One of the key things we’re doing during the pipe replacement is providing residents a water pitcher with filter at no charge,” Riley says. “That way they know that while we are doing the work, they have safe water.” 

The accuracy of the predictive models has also been a significant factor for securing funding. “We have been able to leverage the BlueConduit work to mobilize more than $10 million in funding to replace lead pipes,” Riley says. 

So not only is the software helping locate lead pipes, but it’s also allowing the city to act in a much faster way than originally anticipated.

Changing the game

Before working with BlueConduit’s software, the city of Toledo predicted it would take around 30 years to replace all the lead service lines in Toledo, but now with the predictive model, they are hoping to achieve that goal in about seven years. 

“Because we’ve been able to leverage the BlueConduit work to rally significant funding, our timeline for replacement has significantly advanced,” Riley says. “Without BlueConduit, we would have had to rely on historical records and inefficient ways of checking pipe. This would have cost the city more money and likely placed a bigger burden on our ratepayers.”

Riley and the city of Toledo will continue to use the software until the goal of complete lead service line removal is achieved.


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