热带气象学报2026，Vol.42Issue(2)：204-212,9.DOI:10.16032/j.issn.1004-4965.2026.017
基于WRF-Hydro模式的不同汇流方法对清江流域径流模拟的影响
The Impact of Different Confluence Methods on Runoff Simulation in Qingjiang River Basin Based on WRF-Hydro Model
摘要
Abstract
Hydrological models are the core technology for flood forecasting,and the selection of channel routing algorithms has a significant impact on the effectiveness of runoff simulation.The Muskingum method ignores the effect of backflow,which may cause bias in the application of hydrological models in complex terrain areas.The comparative study of different channel routing algorithms in WRF Hydro mode is still insufficient.The basin above Shuibuya Hydrological Station in the Qingjiang River Basin is the research area.Simulate using 7 runoff processes from 2016 to 2017.Three experimental schemes were designed for simulation.The diffusion wave method which parameterized based on the default CHANPARM.TBL parameter table(WW),the Muskingum method which parameterized based on the Routenlink.nc file(MM),and the diffusion wave method which parameterized based on the modified CHANPARM.TBL parameter table(WM).Compare the differences in the application effects of diffusion wave and Muskingum river confluence calculation methods in the WRF Hydro model,and analyze their influencing factors.The results indicate that both WRF Hydro models using two river confluence methods have good performance.Compared with WW/WM,the average NSE of Muskingum method increased by 0.017 and 0.037,and the average KGE decreased by 0.012 and 0.021.In the case of consistent parameters,the diffusion wave method simulates slower runoff velocity,smaller peak flow rate,and delayed peak appearance time due to considering the backflow effect,indicating that the backflow effect is a key factor affecting channel routing.关键词
WRF-Hydro模式/径流模拟/扩散波/Muskingum方法Key words
WRF-Hydro model/runoff simulation/diffusion wave/Muskingum method分类
天文与地球科学引用本文复制引用
高玉芳,张晨昊,彭涛,高勇..基于WRF-Hydro模式的不同汇流方法对清江流域径流模拟的影响[J].热带气象学报,2026,42(2):204-212,9.基金项目
国家自然科学基金(U2442601) （U2442601）
国家重点研发计划项目(2024YFC3013002)共同资助 （2024YFC3013002）
