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    吴滨滨, 于汪洋, 马奉泉, 喻海军, 穆杰, 柴福鑫, 李敏, 宋文龙. 海河“23·7”流域性特大洪水东淀蓄滞洪区洪水演进模拟与预报[J]. 中国防汛抗旱, 2023, 33(10): 37-42,57. DOI: 10.16867/j.issn.1673-9264.2023408
    引用本文: 吴滨滨, 于汪洋, 马奉泉, 喻海军, 穆杰, 柴福鑫, 李敏, 宋文龙. 海河“23·7”流域性特大洪水东淀蓄滞洪区洪水演进模拟与预报[J]. 中国防汛抗旱, 2023, 33(10): 37-42,57. DOI: 10.16867/j.issn.1673-9264.2023408
    WU Binbin, YU Wangyang, MA Fengquan, YU Haijun, MU Jie, CHAI Fuxin, LI Min, SONG Wenlong. Simulation and forecasting of flood evolution in Dongdian storage-detention area during Haihe “23·7” basin-wide extreme flood[J]. China Flood & Drought Management, 2023, 33(10): 37-42,57. DOI: 10.16867/j.issn.1673-9264.2023408
    Citation: WU Binbin, YU Wangyang, MA Fengquan, YU Haijun, MU Jie, CHAI Fuxin, LI Min, SONG Wenlong. Simulation and forecasting of flood evolution in Dongdian storage-detention area during Haihe “23·7” basin-wide extreme flood[J]. China Flood & Drought Management, 2023, 33(10): 37-42,57. DOI: 10.16867/j.issn.1673-9264.2023408

    海河“23·7”流域性特大洪水东淀蓄滞洪区洪水演进模拟与预报

    Simulation and forecasting of flood evolution in Dongdian storage-detention area during Haihe “23·7” basin-wide extreme flood

    • 摘要: 为全面支撑海河“23·7”流域性特大洪水中东淀蓄滞洪区的运用决策及预报预警,基于中国水利水电科学研究院自主研发的高性能洪水分析软件IFMS/Urban,构建了蓄滞洪区一维、二维耦合水动力学模型,利用实时监测和预报的水情数据,持续开展了东淀蓄滞洪区洪水演进模拟和滚动预报工作。实践证明,本次构建的洪水演进模型模拟预报精度较高,模拟结果跟遥感监测淹没范围和前方现场实时反馈信息吻合较好,可反映蓄滞洪区洪水演进实际过程,并能准确预测未来动态变化,及时为下游关键区域提供洪水预警,有效支撑了本次洪水防御工作。

       

      Abstract: To fully support the decision-making and forecasting efforts of Dongdian storage-detention area operation during the "23·7" extreme flood in the Haihe River Basin, a 1D-2D coupled hydrodynamic model was constructed based on the highperformance flood analysis software IFMS/Urban developed independently by China Institute of Water Resources and Hydropower Research. This model utilized real-time monitoring and water regime forecasting data to continuously simulate and provide rolling predictions of flood evolution in Dongdian storage-detention area. It has been proven through practical applications that the flood evolution model constructed in this paper has high accuracy in simulation and prediction, with simulation results closely matching the flooded area detected by remote sensing and the real-time feedback from the front line. This model can thus reflect the actual flood evolution process in the storage-detention area, accurately predict future dynamic changes, and provide timely flood warnings for the key downstream areas, effectively supporting the flood prevention work.

       

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