Every day, the United States’ extensive water supply system faces pressure to deliver safe water. Now, University of Vermont (UVM) scientists have invented a new tool using AI to help communities better predict threats to their supply. New research published today by Vermont scientists shows how an already-existing computer system—the federal government’s National Water Model—can be modified, with AI and real-time data from sensors, to go beyond simply forecasting stream flow—to predicting water quality too.
To test the tool in real-world conditions, the researchers focused on New York City’s water supply, an ideal testing ground due to the city’s extensive network of sensors that monitor water flow and sediment—and the episodic nature of the problem that the NYC water supply faces.
A key concern for reservoir water quality is turbidity, a measure of water clarity affected by sediment and other material in the water column. When certain levels are exceeded, the NYC DEP must limit the supply from that reservoir, impacting the management and operations of the entire downstream network. The capacity to forecast high turbidity threats is critical for streamlining water supply operations. Across the United States, this tool can have widespread applications, allowing locations that typically face various water quality issues to better predict threats.
Source: Phys.org
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