Yang, Mochen, Edward McFowland III, Gordon Burtch, and Gediminas Adomavicius. "Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach ...

There is an increasing need for skillful streamflow forecasts that extend beyond a 12-month lead time (“year-2 forecasts”), particularly in basins with highly variable interannual streamflow, large ...

We developed a modeling approach for seasonal streamflow forecasts using a machine learning technique, random forest (RF), for runoff season flows (April 1–July 31 total) at the important gauge of ...