1D-2D HYBRID RIVER-FLOW MODEL WITH EVALUATION OF ROUGHNESS COEFFICIENT

Abstract

 It is necessary to develop a river flow model with low numerical-parameter dependency for the evaluation of river flow variation due to climate change impact. In this study, we developed a river flow model with high accuracy and low computational load by coupling a 1D-2D hybrid numerical method and data-assimilation approach to evaluate the roughness coefficient. This model can keep low computational loads such as a 1D calculation model and high accuracy like a horizontal 2D flow model. The present model was applied to the flood flow in the Arakawa River under Typhoon Hagibis in 2019. The results indicate that the calculated roughness coefficient with the present model was reasonable compared to that with an existing 1D model. It is also noted that the CPU time in the present model was appreciably reduced to that in a general 2D calculation, demonstrating the fundamental validity of the present model.