长江下游潮汐河段高精度潮位预报方法比较研究
作者:
作者单位:

(1.南京水利科学研究院水利部水旱灾害防御重点实验室,江苏 南京 210029;2.江苏省水利勘测设计研究院有限公司,江苏 扬州 225127 )

作者简介:

夏明嫣(1996—),女,助理工程师,硕士,主要从事河口水动力研究。E-mail:myxia@nhri.cn

通讯作者:

中图分类号:

基金项目:

国家重点研发计划项目(2021YFC30001000);国家自然科学基金项目(52201332) ;江苏省水利科技项目(2023046,2023021)


Comparative study on high-precision tidal level forecast methods in tidal reach of the lower Yangtze River
Author:
Affiliation:

(1.Key Laboratory of Flood & Drought Disaster Defense, the Ministry of Water Resources, Nanjing Hydraulic Research Institute, Nanjing 210029, China;2.Jiangsu Surveying and Design Institute Co., Ltd., Yangzhou 225127, China)

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 文章评论
    摘要:

    针对长江下游高水位主控因素的沿程变化,采用非稳态潮汐调和分析(NS_TIDE)模型、非稳态潮汐调和分析与自回归模型修正(NS_TIDE-AR)组合方法、Transformer深度学习模型、水动力学模型、水动力学模型结合集合卡尔曼滤波(HM-EnKF)同化方法预报长江下游潮位,并对比了各种方法对长江下游沿线站点潮位预报的精度和在不同条件下的适用性。结果表明:相同条件下Transformer深度学习模型的潮位预报精度最高且最稳定,NS_TIDE-AR组合方法与HM-EnKF同化方法的精度较为接近,NS_TIDE模型和水动力学模型误差相对较大;NS_TIDE-AR组合方法、Transformer深度学习模型、HM-EnKF同化方法均能较好地预报洪水期长江下游潮位,NS_TIDE-AR组合方法不适用于风暴潮期间的潮位预报。

    Abstract:

    To understand the evolution of low flow and enhance the ability to cope with drought in the Yangtze River Basin, typical dry years on an annual scale and monthly scale during dry seasons were extracted, and spatiotemporal evolution characteristics of runoff in typical dry years were analyzed based on the hydrological data of the main hydrological stations in the Yangtze River Basin from 1956 to 2022. The results show that the typical dry years identified at the annual scale are concentrated in 2006, 2011, and 2022, while the typical dry years identified at the monthly scale during dry seasons are concentrated in 1978 and 2022. The common characteristic of typical dry years in 2006, 2011, and 2022 is that the runoff during flood seasons is low. In 2006, the runoff gradually decreased before August compared with the historical average of the same period, and the dry situation became more obvious after August. However, in 2022, the runoff was relatively abundant compared with the historical average of the same period before August, and there was a sharp transition from wet to dry after August. In 2006, the severity of drought gradually accumulated along the upper reaches above Yichang Station, and it gradually decreased from upstream to downstream below Yichang Station. In 2011, the severity of drought in the XiangjiabaCuntan, CuntanLuoshan, and LuoshanDatong sections showed a fluctuating trend of decreasing, increasing, and decreasing. In 2022, upstream, midstream, and downstream experienced simultaneous drought in the Yangtze River Basin.

    参考文献
    相似文献
    引证文献
引用本文

夏明嫣,张帆一,闻云呈,等.长江下游潮汐河段高精度潮位预报方法比较研究[J].水资源保护,2025,41(4):159-168.(XIA Mingyan, ZHANG Fanyi, WEN Yuncheng, et al. Comparative study on high-precision tidal level forecast methods in tidal reach of the lower Yangtze River[J]. Water Resources Protection,2025,41(4):159-168.(in Chinese))

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:
  • 最后修改日期:
  • 录用日期:
  • 在线发布日期: 2025-08-11
  • 出版日期: