Limiting the Spread of Lead in Water Pipes Using Predictive Modeling

This diagram demonstrates the new model in action: Engineers take into account several factors, including water use patterns and water chemistry, to predict where lead particles will dislodge and end up in the drinking water supply during a partial lead service line replacement. (Image courtesy of Biswas Lab.)

In an attempt to increase the safety and purity of drinking water, a team of engineers at Washington University in St. Louis recently developed a new technique to model and track the movement and buildup of lead particles during the partial lead service line (LSL) replacement of aging water pipes.

The leeching of lead into water supplies due to corrosion is a serious risk associated with lead water pipes. Such contamination is responsible for a variety of health hazards, like detrimental neurological and developmental effects in children. Though the practice of installing harmful lead pipes was banned years ago, they still supply millions of homes with drinking water each day.

One common solution is to dig up old lead pipes and substitute portions of them with another metal, like copper. This type of replacement can, however, dislodge lead particles and release them into the water supply. Additionally, partial LSL replacements (as opposed to replacing the entire pipe network) can be a prohibitively expensive and difficult process.

The delicate and costly nature of the existing obstacles associated with lead pipe replacement is why new research by assistant vice chancellor of international programs Pratim Biswas and research assistant Ahmed A. Abokifa is so promising.

“We all know lead is not safe, it needs to go,” said Biswas. “This is the first comprehensive model that works as a tool to help drinking water utility companies and others to predict the outcome of an action. If they have the necessary information of a potential action, they can run this model, and it can advise them on how best to proceed with a pipe replacement to ensure there are no adverse effects.”

Biswas and Abokifa’s new approach employs water quality modeling that the team had previously developed for the Environmental Protection Agency and predicts how far lead particles and other dissolved matter may travel after they have been disturbed. The model accounts for factors such as pipe age and dimensions, water use patterns, water chemistry and previous pipe disturbances.

Following a number of simulations testing their predictions, Biswas and his team are prepared to make their model available to utility companies and other consumers. The team has also developed a number of other drinking water distribution system models to predict disinfectant concentrations in pipe networks, particularly dead-end systems. These efforts will hopefully lead to an increase in public health and safety and make us all feel a little better when we turn on the tap.

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