河海大学学报（自然科学版）2026，Vol.54Issue(2)：18-27,10.DOI:10.3876/j.issn.1000-1980.2026.02.003
协同MIKE11-KF的遥感河道流量数据同化
Remote sensing river discharge data assimilation with MIKE11-KF
摘要
Abstract
To improve the simulation accuracy of flow in ungauged small and medium rivers,river surface widths were inverted,and preliminary discharges were estimated using satellite imagery(Sentinel series and high-resolution images).These estimated values were then used as observed flow data and assimilated with the flow data simulated by the MIKE11 model using the Kalman filter algorithm.The assimilated flow results were fed back as updated inputs to the MIKE11 model,forming a closed-loop iteration that continuously corrected model errors and enhanced simulation accuracy.Validation results from the Huangkou Gate section in Quzhou County show that after data assimilation with the Kalman filter algorithm,the MIKE11 model achieves an R2 of 0.820,an NSE of 0.813,and an RRMSE of 0.260 for simulated flow.Compared to pre-assimilation results,R2 increases by 28.1%,NSE improves by 27.0%,and RRMSE decreases by 43.5%,demonstrating effective improvement in river discharge simulation accuracy.关键词
卡尔曼滤波/MIKE11模型/遥感数据/河道流量/多源数据同化Key words
Kalman filter/MIKE11 model/remote sensing data/river discharge/multi-source data assimilation引用本文复制引用
李宾,栾清华,李涛,赵长森,李毛毛..协同MIKE11-KF的遥感河道流量数据同化[J].河海大学学报（自然科学版）,2026,54(2):18-27,10.基金项目
国家自然科学基金面上项目(52279004,52379008) （52279004,52379008）
