华南理工大学学报(自然科学版)

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洪潮分离-耦合的高潮位自动预报模型研究

陈金浩  王淑英  魏金俐  刘福瑶   

  1. 浙江省水文管理中心,浙江 杭州 310009

  • 发布日期:2026-04-03

Research on Automatic Forecasting Model of High Tide Level Based on Flood-Tide Separation-Coupling

Chen Jinhao  Wang Shuying  Wei Jinli  Liu Fuyao   

  1. Zhejiang Hydrological Management Center, Hangzhou 310009, Zhejiang, China

  • Published:2026-04-03

摘要:

针对冲淤频繁感潮河段因缺乏稳定水下地形资料而导致的高潮位预报难题,创新性地提出了“洪潮分离-耦合”的建模框架,并构建了一种仅需常规水文资料的自动化预报模型。首先,基于双向波叠加原理,将断面总水位分解为代表径流作用的“洪控水位”和代表潮汐作用的“潮控水位”两个分量。其次,利用钱塘江之江站与乍浦站2015-2019年水文资料,分别构建了潮控低潮位演算、潮控涨潮潮差演算、洪控水位演算及潮差传播有效系数等四个子模型。模型核心在于通过流量阈值筛选“纯潮汐”与“纯径流”样本以率定基础关系,并设计了实时率定机制:采用滑动时间窗(30天)动态更新潮控潮差关系,引入偏移系数β动态校准综合线与外包线,以自适应河床冲淤变化。最后,利用2020—2024年资料进行实时率定与预报检验。结果表明,在日均流量大于10000 m³/s的洪水期,模型对之江站高潮位的预报误差均小于0.3 m,最大误差为-0.28 m,预报合格率达到100%,满足《水文情报预报规范》(GB/T 22482—2008)甲级精度标准。该模型成功克服了传统方法对水下地形资料的依赖,通过实时学习近期水文规律提升了冲淤频繁河段的预报稳定性,为同类感潮河段的业务化洪水位预报提供了可靠且实用的技术解决方案。

关键词: 感潮河段, 潮位预报, 高潮位, 洪潮耦合, 钱塘江, 洪水预报, 实时率定

Abstract:

To address the challenge of forecasting high tide levels in tidal river sections with frequent bedload transport, where stable bathymetric data are often lacking, this study developed an automatic forecasting model based on a “flood-tide separation-coupling” framework using only conventional hydrological data. The total water level of a station was first decomposed into “flood-controlled level” dominated by upstream runoff and “tide-controlled level” dominated by downstream tidal action, based on the bidirectional wave superposition principle. Four sub-models were then constructed using data of Zhijiang and Zhapu stations in Qiantang River from 2015 to 2019, including sub-models for the tide-controlled low tide level, the tide-controlled rising tide range, the flood-controlled level, and an empirical model for the effective tidal range propagation coefficient during floods.  The core of the model was to screen the "pure tide" and "pure runoff" samples through the flow threshold to calibrate the fundamental relationship. And a real-time calibration mechanism was designed, including a sliding time window (30 days) to dynamically update the tidal relationship and an offset coefficient (β) to adjust between baseline and envelope curves, enabling the model to adapt to riverbed scour and silting. Validation using data from 2020 to 2024 showed that during flood periods with a daily average flow greater than 10000 m³/s, the forecast error for high tide level of Zhijiang station was less than 0.3 m, with a maximum error of -0.28 m and a 100% qualification rate, meeting the Class A accuracy standard of the code for hydrological information prediction (GB/T 22482-2008). The model successfully eliminates the dependence on underwater topography, enhances forecasting stability in volatile riverbeds through real-time learning, and provides a practical, operational solution for floodwater level forecasting in similar tidal reaches.

Key words: tidal river section, tide level forecasting, high tide level, flood-tide coupling, Qiantang river, flood forecasting, real-time calibration