Case studies

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In the world of hydrology, a basin’s streamflow response from rain-on-snow events can be particularly difficult to predict. These can be critical events for water managers, hydropower generators and other water system operators because they can cause unexpected runoff events and indicate the start or end of the snowmelt season, both of which need to be closely managed.  

HydroForecast’s unique combination of physical and statistical modeling approaches in a neural network framework has created a model that is better able to handle the uncertainty of rain-on-snow events and provide more accurate forecasts to customers to help de-risk their operational decision-making.

To learn more, check out the case study.