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Researchers from the University of New Hampshire, in partnership with the U.S. Geological Survey, unveiled a new snow‑pack model on Tuesday that predicts winter thaws and runoff in the Northeast with far greater accuracy than existing tools, the Phys.org report said. The model, dubbed SnowModel‑NE, integrates local humidity, temperature swings and forest cover to track how snow melts and feeds rivers across the region. Initial tests show it reduces forecast errors by roughly 30 percent compared with the western‑focused models that agencies have used for decades.

The improvement matters because the Northeast’s mountainous terrain behaves differently from the dry, high‑altitude slopes of the West. Milder winters, higher humidity and frequent rain‑on‑snow events create a patchwork of snow conditions that are hard to capture with a one‑size‑fits‑all approach. As climate change pushes more precipitation into rain and forces earlier melts, water managers face growing uncertainty about flood risk and spring water supplies. Accurate runoff forecasts are essential for municipalities that rely on snowmelt for drinking water, for hydroelectric plants that schedule generation, and for emergency services that need early warnings of flash floods.

In validation studies using ten years of stream‑flow data from the Hudson, Connecticut and Merrimack basins, SnowModel‑NE predicted peak runoff within five percent of observed values, a marked gain over the ten‑to‑15‑percent deviations typical of older models. State water officials praised the advance, saying it will sharpen seasonal planning and improve flood‑alert systems. The research team plans to hand the model to NOAA’s National Weather Service later this year, where it could be folded into daily forecasts and long‑range climate projections. If adopted broadly, the tool could help the Northeast manage water resources more resiliently as winter weather grows increasingly erratic.