AUTHOR=Li Ting , Hao Shilong , Chai Fuxin , Li Kuang , Tong Haoqiang 

TITLE=Comparative analysis of different hydrological models in flood forecasting for the upper Juma River basin

JOURNAL=Frontiers in Water

VOLUME=Volume 7 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/water/articles/10.3389/frwa.2025.1617212

DOI=10.3389/frwa.2025.1617212

ISSN=2624-9375

ABSTRACT=Accurate flood forecasting is of critical importance for flood control and disaster mitigation. This study focuses on the upper basin of the Juma River and employs the China Flash Flood Hydrological Model (CNFF) to calibrate model parameters using three specific runoff generation models implemented within the CNFF platform: the Xin’anjiang three-source saturation-excess runoff model, the vertical mixed runoff model, and the Dahuofang model. These models, respectively, represent three distinct physical runoff mechanisms—saturation-excess, vertical mixing, and infiltration-excess. The primary scientific objective is to systematically compare the flood forecasting accuracy of these models and to identify the most suitable one for flood forecasting in this basin. The results indicate that the overall forecasting accuracy of the Xin’anjiang model is superior to that of the vertical mixed runoff model and the Dahuofang model. The absolute value of the relative error in peak discharge and the relative error in mean runoff depth simulated by the Xin’anjiang model are 6.8 and 10.7%, respectively. The absolute value of the mean peak arrival time error is 0.47 h, and the average Nash-Sutcliffe efficiency coefficient is 0.69. The Xin’anjiang model demonstrated superior performance, achieving an average Nash-Sutcliffe Efficiency (NSE) approximately 0.21 higher than the other models across the evaluated events. When flood discharge is high and exhibits a single-peak pattern, the simulation performance of all runoff models improves. Overall, the Xin’anjiang model achieves a Class B accuracy level in flood simulation for the upper Juma River basin. These findings provide a reference for hydrological simulation, flood forecasting, and early warning in the upper Juma River basin.