As part of a five-year project funded by the United States Bureau of Reclamation, a team of researchers has compiled and analyzed data from more than 500 U.S. water utilities and 100 federal facilities to provide a fuller picture of the health of the country’s pipeline infrastructure systems.
The image that’s surfaced is one of 985,000 miles of transmission and distribution of water pipes in the U.S., and of installed water pipeline infrastructure in need of replacements worth an estimated $3.6 trillion over the next 25 years. These findings are among dozens of key insights distilled into reports on pipeline performance, risk, and economics, designed by the team for more detailed, drill-down reading by the country’s water utility managers.
The release of the reports coincides with national policy considerations for how to address aging infrastructure. In early April, the Biden administration released a $2 trillion infrastructure plan that lays out intentions to modernize aging drinking water, wastewater, and stormwater systems and support clean water infrastructure in rural America through $56 billion in grants and loans to states and communities. With the national spotlight on infrastructure, the project’s principal investigator, Sunil Sinha, believes the reports will provide timely insights.
Sinha, a professor of civil and environmental engineering at Virginia Tech, said the reports will also lay the foundation for a longer-term effort to bring the data and its analysis online. The team is building the Pipeline Infrastructure Database, or PIPEiD, to create a secured, standardized, and easily accessible online database that can help water utility managers better monitor pipeline infrastructure systems.
“It is critical for society that we transform our siloed water management and infrastructure systems into smart, connected, sustainable, and resilient systems,” said Sinha, who leads the Sustainable Water Infrastructure Management Center. “This transformation will allow us to ameliorate the effects of increasing extreme climate events, ecosystem demands, rapid global urbanization, and infrastructure deterioration from age and neglect.”
Just as national health databases allow users to glean information from emerging patterns and trends among large, anonymous swaths of the U.S. population, Sinha hopes PIPEiD can enable water utilities to learn from the local, regional, and national patterns it presents through modeling and visualization, using tools like artificial intelligence and GIS mapping. PIPEiD will allow users to run queries that provide helpful analysis for decision-making, like estimating pipeline useful life.
Collecting data at national scale and tapping into the information age to present it could transform the industry, Sinha believes, enabling water utilities to become more proactive in tracking and acting on pipeline performance.
“Now, I have a national database, so I can easily go in and make a query,” Sinha said. “If I have corrosive soil and unlined cast iron pipes, and I can find two, three, four different locations in the U.S. with similar conditions, I can bring in that data and enhance my confidence. I can say with more confidence how long the pipes will last.”
Today’s water utilities work much differently, according to Sinha — each operating on its own, without a set of standards to follow for the data the water utility collects or how to format it. As the team worked within this reality, their data collection effort became an exhaustive one, Sinha said. They received data in many different forms from water utilities around the country: as water quality reports and main break orders, and as CAD design files and geospatial databases.
The team collected field performance data for potable, raw, and reuse water pipelines made from materials reflecting the wide range of pipes currently in the ground throughout the U.S., including cast and ductile iron, prestressed concrete cement pipe, reinforced concrete, steel, and thermoplastic.
The researchers worked to collect data distributed across different ecological areas, or cohorts, organized based on the climatic conditions of the 500 water utilities’ locations, including coastal, arid, arctic, and mountainous regions. The cohorts factored in environmental conditions affecting pipelines as well, such as soil corrosivity, traffic loading, and frost action.
The team fleshed the data set out further with the help of external sources like the United States Geological Survey and the Soil Survey Geographic Database from the United States Department of Agriculture, as well as additional field data collected by a group of 25 water utilities they selected to fill more gaps.
This push for ample usable data reflects Sinha’s broader objective of giving an accurate national picture of water pipeline infrastructure systems. To do so, one of his team’s main objectives was to collect data across the entire life cycle of pipelines, from design to development, to construction, to operation and maintenance, to renewal. It’s a way to get ahead of costly failures, Sinha said.
Sinha compares the effect to getting regular checkups to maintain our own health. “If you go to see a doctor, there is protocol,” Sinha said. “They take your X-ray or they take your blood sample. In our water industry, especially for these pipes, everyone collects data in a different way. And they don’t collect data unless there is a problem, yet they need to predict when the pipe is going to fail. That’s not going to happen. You have to make regular visits to the doctor.”
Bringing data-driven insights online
As the researchers moved on from data collection to analysis, they worked from 150 pipe performance parameters. Their descriptive analyses covered a wide range of factors affecting pipeline management. Analyses included studying how factors influencing deterioration of pipes — like frost action or soil metallic corrosivity — stack up for different pipe materials; where and how pipes fail over space and time; common failure modes; overall spending on operation and maintenance; and service life estimates for various pipe materials and diameter categories.
The team conducted risk analysis to examine the criticality of water pipelines in different risk scenarios, and produced renewal recommendations for pipes falling in different risk zones.
They also conducted lifecycle economic analysis, which provided cost comparisons for managing different pipeline materials and diameters throughout the entire lifecycle. The intent with the findings detailed in the team’s recent reports is to help inform decision-making, as managers try to estimate remaining pipeline useful life, determine how well materials perform in specific environmental conditions, or decide on pipe material to replace based on lifecycle costs.
The researchers will work next to bring PIPEiD to life, giving managers a platform for interacting with the national data and its in-depth descriptive, performance, and lifecycle economic analyses through modeling and visualization.
For such a platform to work well for users in the future, Sinha and his team laid out recommendations in their reports for changes in practice among water utilities. They suggested measures like upping periodic collection of time-dependent data during pipeline condition assessment and maintenance activities, for more accurate models and a better understanding of performance over 50 and 100-year time scales.
With PIPEiD, Sinha sees potential for information-sharing beneficial to water utilities of all sizes. Small water utilities, for instance, could extract insights from a database that brings in data from larger, bigger-budget utilities with comparable pipeline materials and environmental conditions.
“PIPEiD’s artificial intelligence platform for water pipeline management is cloud-based and will give access to decision-making capabilities to even the most resource-limited water providers,” Sinha said. “The PIPEiD platform will enable a paradigm shift on how resilience and sustainability can be operationalized in water systems through development of a ‘system of systems’ approach, and could effectively catalyze a data revolution in the water industry.”
Story by Suzanne Irby