Medium and long-term runoff forecast based on ensemble Kalman filter/

被引:0
|
作者
Yuan, L.I.U. [1 ]
Changming, J.I. [1 ]
Haoyu, M.A. [2 ]
Wang, Yi [1 ]
Zhang, Yanke [1 ]
Ma, Qiumei [1 ]
Yang, Han [3 ]
机构
[1] School of Water Resources and Hydropower Engineering, North China Electric Power University, Beijing,102206, China
[2] China Yangtze Power Co. , Ltd., Yichang,443002, China
[3] Water Resources Comprehensive Utilization Institute, Changjiang River Scientific Research Institute, Wuhan,430010, China
关键词
Data fusion;
D O I
10.3880/j.issn.10046933.2024.01.012
中图分类号
学科分类号
摘要
To reduce the uncertainty of medium and long-tenn runoff forecast and increase the power generation efficiency of hydropower reservoirs, a deterministic inflow runoff forecast method based on ensemble Kalman filtering is proposed to address the issue of existing methods focusing on improving the accuracy of deterministic forecast results of a single forecasting model to reduce the uncertainty of runoff forecast. Taking the Jinxi Reservoir as the research object and ten days as the foresight period, conduct a case stud)'. The results show that compared with traditional single forecast models and traditional inionnation iusion forecast models, the medium-and long-tenn runoff forecast based on ensemble Kalman filtering reduces RMSE by 4. 78 mVs and improves qualification rate by 0. 56%. And it effectively reduces the uncertainty of flood season forecasting, obtaining more accurate and reliable deterministic runoff forecasting results, which can provide technical support for the optimization and scheduling of cascade hydropower stations in the basin. © 2024 Water Resources Protection. All rights reserved.
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页码:93 / 99
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