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Regionalization of a Distributed Hydrology Model Using Random Forest
Siavash Pouryousefi Markhali
, Marie Amélie Boucher
,
Annie Poulin
, Mehrad Rahimpour Asenjan
, Frédéric Talbot
,
Richard Arsenault
École de technologie supérieure
Université de Sherbrooke
Research output
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Contribution to journal
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Journal Article
›
peer-review
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Keyphrases
Catchment Descriptors
100%
Conceptual Hydrological Model
50%
Daily Steps
50%
Distributed Hydrological Model
100%
Distributed Parameter Systems
50%
Efficiency Improvement
50%
Fine Temporal Resolution
50%
Flow Regionalization
50%
Model Efficiency
50%
Model Evaluation
50%
Nonlinear Relationship
50%
Parameter Calibration
50%
Random Forest
100%
Random Forest Machine Learning
50%
Random Forest Model
100%
Regionalization Methods
100%
Resolution Increase
50%
Spatial Refinement
50%
Spatially Distributed
50%
Spatiotemporal Resolution
50%
Sub-daily
50%
Sub-daily Simulation
50%
Temporal Resolution
50%
Earth and Planetary Sciences
Hydrology Models
100%
Machine Learning Model
16%
Regionalization
100%
Streamflow
16%