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卫星遥感技术在山东黄河凌情监测中的应用
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1.济南黄河河务局,山东济南 250000 ;2.济南市章丘区城乡水务局,山东济南 250200 ;3.济南黄河河务局槐荫黄河河务局,山东济南 250000

作者简介:

宋兆谦(1988—),男,工程师

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TV875

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Application of Satellite Remote Sensing Technology in Ice Jam Flood Monitoring of the Yellow River in Shandong
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1.Yellow River Administration Bureau of Jinan Municipality, Jinan, Shandong 250000 , China ;2.Urban and Rural Water Affairs Bureau of Zhangqiu District, Jinan Municipality, Jinan, Shandong 250200 , China ;3.Yellow River Administration Bureau of Huaiyin District, Jinan Municipality, Jinan, Shandong 250000 , China

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    摘要:

    黃河凌汛作为季节性水文现象,是热力学与流体动力学的复杂耦合过程。本文以山东黄河段为研究对象, 探讨卫星遥感技术在凌情监测中的应用。通过整合高分系列、环境减灾卫星及哨兵2号等多源遥感数据,构建“数据获取-预处理-信息解译-分析-成果汇编”的技术流程,结合辐射校正、大气校正及几何精校正等预处理方法,提升冰水边界识别精度,动态监测 2022-2023年黄河山东段凌情演变过程。研究结果显示,该年度山东段经历“两封两开” 特殊凌情,封河总历时37 d,最大封河长度达37.7 km。研究表明,卫星遥感技术可为黄河凌情实时监测、预警及防灾决策提供高效技术支撑。

    Abstract:

    As a seasonal hydrological phenomenon, the Yellow River ice jam flood is a complex coupling process of thermodynamics and fluid dynamics. This paper takes the Shandong section of the Yellow River as the research object to explore the application of satellite remote sensing technology in ice jam flood monitoring. By integrating multi-source remote sensing data such as Gaofen series, Environment Disaster Reduction Satellites and Shaobing-2, a technical process of "data acquisition-preprocessing-information interpretation-analysis-result compilation" is constructed. Combined with preprocessing methods such as radiometric correction, atmospheric correction and geometric precision correction, the accuracy of ice-water boundary recognition is improved, and the evolution process of ice jam flood in the Shandong section of the Yellow River from 2022 to 2023 is dynamically monitored. The research results show that the Shandong section experienced a special ice condition of "two freeze-ups and two break-ups" in that year, with a total freeze-up duration of 37 days and a maximum freeze-up length of 37.7 km. The study indicates that satellite remote sensing technology can provide efficient technical support for real-time monitoring, early warning and disaster prevention decision-making of the Yellow River ice jam flood.

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  • 收稿日期:2025-03-31
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  • 在线发布日期: 2025-08-27
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