Outperforms national models & industry competitors, even in ungauged locations
Designed with resource planning in mind — confidence bounds on the forecasts enable planners to assess and mitigate risk
Rapidly reacts to basin and climatic changes without lengthy recalibration
Redundant inputs and industry-leading cyber security standards ensure reliable delivery
Unlock a new level of safe and efficient operations with state-of-the-art, highly accurate streamflow forecasts. Read about HydroForecast’s accurate short-term streamflow predictions in Idaho’s South Payette river.
Design policies to restore and maintain environmental flows, even where there are no gauges. HydroForecast reconstructs continuous historic records to help understand how a watershed has changed over time. Streamflow forecasts inform proactive management of watersheds.
Read about how we leveraged HydroForecast to simulate potential restoration mitigation of increasing streamflow temperatures in New Jersey.
HydroForecast learns to represent hydrologic processes by identifying relationships between satellite observations, basin characteristics, meteorological forecasts, and streamflow measurements.
Our approach is distinct from purely data-driven machine learning models in that we use physical science to guide and constrain the relationships between inputs and streamflow predictions. We believe that the best model is one grounded in scientific principles and enhanced by finding deep connections in the relationships between data.
HydroForecast’s Core Model has been trained on a wide range of hydrologic conditions and landscapes, and can be tuned for specific locations anywhere on Earth.