Using machine learning methods for supporting GR2M model in runoff estimation in an ungauged basin
Estimating monthly runoff variation, especially in ungauged basins, is inevitable for water
resource planning and management. The present study aimed to evaluate the
regionalization methods for determining regional parameters of the rainfall-runoff model (ie,
GR2M model). Two regionalization methods (ie, regression-based methods and distance-
based methods) were investigated in this study. Three regression-based methods were
selected including Multiple Linear Regression (MLR), Random Forest (RF), and M5 Model …
resource planning and management. The present study aimed to evaluate the
regionalization methods for determining regional parameters of the rainfall-runoff model (ie,
GR2M model). Two regionalization methods (ie, regression-based methods and distance-
based methods) were investigated in this study. Three regression-based methods were
selected including Multiple Linear Regression (MLR), Random Forest (RF), and M5 Model …
[引用][C] Using machine learning methods for supporting GR2M model in runoff estimation in an ungauged basin. Sci Rep 11: 19955
P Ditthakit, S Pinthong, N Salaeh, F Binnui… - 2021