Channel types predictions for the Sacramento River basin

Hydrologic and geomorphic classifications have gained traction in response
to the increasing need for basin-wide water resources management.
Regardless of the selected classification scheme, an open scientific
challenge is how to extend information from limited field sites to
classify tens of thousands to millions of channel reaches across a basin.
To address this spatial scaling challenge, we leveraged machine learning
to predict reach-scale geomorphic channel types using publicly available
geospatial data.