How Real-Time Data Is Changing CSO Control

Cities are using real-time sewer analytics to cut CSOs faster, reduce risk, and rethink billion-dollar infrastructure plans

23 Jan 2026

For decades, American cities with combined sewers have faced an awkward choice. When heavy rain overwhelms pipes, foul water spills into rivers. The usual cure has been brute force: tunnels, tanks and treatment plants that take years to build and cost billions. A quieter alternative is now edging into the mainstream.

The new approach relies less on concrete and more on computation. Using live data, such as rainfall forecasts, flow sensors and hydraulic models, utilities can steer water through existing networks more carefully during storms. The aim is not to eliminate construction, but to squeeze more performance from what is already there.

Richmond, Virginia, is often held up as proof of concept. Planning models there suggest the city could cut combined sewer overflows by about 180m gallons a year, while avoiding some $725m in capital spending, according to a case study by Xylem, a water-technology firm. These are projections rather than audited results. Even so, they help explain why cash-strapped utilities are paying attention.

Regulators are part of the reason. America’s Environmental Protection Agency continues to press cities to curb overflows through consent decrees and long-term control plans. It has also shown some flexibility over how targets are met. That leaves utilities under pressure to show progress quickly, even as borrowing costs rise and ratepayers bristle.

The market is responding. In late 2024 Xylem bought a majority stake in Idrica, a Spanish water-data firm, bolstering the analytics behind its Xylem Vue platform. The pitch is straightforward: most utilities already collect mountains of operational data, but struggle to turn it into timely decisions. Software, advocates say, can help bridge that gap. Few pretend it makes pipes redundant.

There are limits. Real-time control depends on reliable sensors, secure communications and clear rules about who is accountable when algorithms shape choices that affect public health. Some operators remain wary of trusting automated advice during storms.

Yet the direction of travel is clear. As deadlines tighten and budgets strain, digital tools are being treated less as experiments than as stopgaps that buy time and cut risk. America’s sewer problem will not be solved by software alone. But smarter use of data may help cities spill less, sooner, and at lower cost.