Articles | Volume 28, issue 14
https://doi.org/10.5194/hess-28-3367-2024
https://doi.org/10.5194/hess-28-3367-2024
Research article
 | 
29 Jul 2024
Research article |  | 29 Jul 2024

Regionalization of GR4J model parameters for river flow prediction in Paraná, Brazil

Louise Akemi Kuana, Arlan Scortegagna Almeida, Emílio Graciliano Ferreira Mercuri, and Steffen Manfred Noe

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Short summary
The authors compared regionalization methods for river flow prediction in 126 catchments from the south of Brazil, a region with humid subtropical and hot temperate climate. The regionalization method based on physiographic–climatic similarity had the best performance for predicting daily and Q95 reference flow. We showed that basins without flow monitoring can have a good approximation of streamflow using machine learning and physiographic–climatic information as inputs.