The satellite at the center of the discovery is the Surface Water and Ocean Topography mission, known as SWOT, a joint effort between NASA and international partners that has been in orbit since December 2022. SWOT was built to measure the water level of oceans, lakes, rivers and other large bodies of water at least once every three weeks. It does so using interferometric radar, a technique that compares multiple radar scans over time to detect subtle elevation changes on the water surface. Oceans and big lakes are relatively straightforward targets for such an instrument. Irrigation canals, however, are frequently narrower than 20 meters, placing them at the extreme low end of the satellite’s observational power. The mission’s architects assumed that water-level fluctuations inside such small channels would be invisible to the spacecraft.

Faisal Hossain, a professor of civil and environmental engineering at the University of Washington, was not convinced that the canals were beyond reach. In 2025, he and his collaborators published the Global Registry of Agricultural Irrigation Networks, or GRAIN, a global dataset that used open-source mapping data and machine learning to chart 3.8 million kilometers of canal networks worldwide. That registry gave researchers, for the first time, a comprehensive map of where the world’s agricultural canals actually are. What it could not show was what was happening inside them, which is precisely the kind of information farmers and irrigation authorities need to manage water deliveries.

Lead author Mridul Sharma, a graduate research assistant in civil and environmental engineering at the University of Washington, took the logical next step. He overlaid SWOT’s radar data on top of the GRAIN canal map to see whether meaningful elevation changes could be detected where the mapped canals ran. The result surprised even the team. Roughly 800,000 kilometers of canals in Asia showed water levels that the satellite could measure with moderate to high confidence at more than 85 percent of locations. “It was quite the accidental and pleasant discovery to see that SWOT is able to track flow direction and water levels in most of the canals skillfully,” Sharma said. “GRAIN mapped where canals are. SWOT revealed what was happening inside them. They complemented each other beautifully.”

As a proof of concept, the researchers concentrated on canals in 22 countries across Asia, a region where irrigation plays a critical role in feeding roughly 3 billion people. They examined the satellite’s data along 800,000 kilometers of canals within that region and assigned a confidence score to each kilometer. The scoring was based on two criteria: how closely the satellite’s view of the canal water matched the known contours of the surrounding land, and how strong the radar signal was relative to the noise in the data. Where the observed water surface tracked the terrain smoothly and the signal stood out clearly from background noise, confidence was high. Where the two diverged or the signal was weak, confidence dropped.

The team also validated the approach against ground truth. They compared the satellite’s data to real canal measurements in the United States and found that the confidence levels produced by their scoring system matched the system’s actual abilities. This cross-continental check matters because it suggests the confidence scores are not merely statistical artifacts but reliable indicators of where SWOT’s canal observations can be trusted. Of all the kilometers studied, the team designated 37.5 percent as highly observable, 46.9 percent as moderately observable and 15.6 percent as poorly observable. In other words, more than eight in every ten kilometers of canal in the study region could be monitored with at least moderate confidence by a satellite that was never designed to see them.

The patterns behind those numbers are instructive. The highest-confidence areas corresponded to well-organized, wider canals with smooth slopes and open surroundings, conditions that give the radar a clean view of the water surface and a stable signal to track. Dense vegetation around canals proved to be the satellite’s biggest obstacle, since foliage scatters and absorbs radar energy and obscures the narrow ribbon of water beneath. That limitation is likely to matter most in tropical and subtropical regions where canal banks are heavily vegetated. Encouragingly, the researchers expect performance to improve over time as Hossain and other scientists working with SWOT data build better algorithms and analysis methods tailored to small water bodies.

The study, published September 30 in Geophysical Research Letters, points toward a fundamentally new way of managing the conveyance systems that sustain modern agriculture. “What we are seeing is not simply a new satellite capability,” Hossain said. “It may represent a fundamentally new way of managing the water conveyance systems that sustain modern agriculture.” The next step for the research team is to turn the discovery into practical tools. Hossain and collaborators at the University of Washington are already building systems that use SWOT data to monitor and improve water delivery in South Asia and to aid canal management in the western United States, where aging irrigation infrastructure faces growing pressure from drought and competing demands.

The practical implications for farmers could be far-reaching. In time, growers around the world could use SWOT-powered tools to monitor which canals are carrying sufficient water, see where water levels drop unexpectedly, identify stretches where canal flow might be stagnant, and understand how water delivery evolves across an entire growing season. The researchers offer a concrete example: a farmer preparing to plant rice, one of the most water-intensive staple crops, might see through SWOT-based monitoring that there will not be enough water arriving to the field to support the crop, and switch instead to a less water-intensive option such as corn or wheat. Such decisions, made with timely and objective information rather than guesswork, could reduce crop losses and stretch scarce water supplies further.

Beyond individual farms, the new view of agriculture’s circulatory system could improve drought preparedness, strengthen food security and help researchers map humanity’s transformation of the global freshwater cycle. Irrigation is one of the largest human uses of freshwater on the planet, and canal networks are the arteries through which most of that water moves. Measuring them systematically from space adds a missing piece to the global water balance. “Some of the most important scientific discoveries happen when a tool designed for one purpose unexpectedly reveals something else,” Hossain said. “SWOT may be offering a similar surprise. A mission built to study oceans and rivers has begun revealing the hidden dynamics of the canals that sustain agricultural production around the globe. What was once invisible is becoming measurable.” Co-authors on the study include Sanchit Minocha and Shahzaib Khan, graduate research assistants at the University of Washington; Sarath Suresh, a postdoctoral researcher at Virginia Tech who completed the research as a UW doctoral student; and Tamlin Pavelsky of the University of North Carolina at Chapel Hill. The research was funded by NASA.

Subject of Research: Satellite-based monitoring of irrigation canal water levels using the NASA SWOT mission

Article Title: NASA satellite can monitor most of world’s irrigation canals, study finds

Article References: NASA satellite can monitor most of world’s irrigation canals, study finds. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: SWOT satellite, irrigation canals, water monitoring, NASA, University of Washington, remote sensing, interferometric radar, food security, drought preparedness, agriculture, freshwater, Geophysical Research Letters