《海洋预报》| 黄浦江感潮河段潮位预报精度提升研究|东海|海洋预报|潮位预报|潮河|黄浦江|黄海

黄浦江感潮河段潮位预报精度提升研究

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作者：潘崇伦

单位：上海市水旱灾害防御技术中心, 上海 200050

分类号：P731.34

出版年·卷·期（页码）：2024·41·第二期（24-33）

摘要：黄浦江感潮河段水位波动以天文潮影响为主,同时也受上游径流、区间降雨和风暴潮等因素的影响,传统的调和分析方法难以考虑径流等非天文潮因素,在对黄浦江感潮河段进行潮位预报时总体精度偏低。本文在对传统调和分析方法预报误差频谱分析的基础上,提出了将传统调和分析模型和自回归模型相结合的预报方法,并将该方法应用于黄浦江感潮河段3个代表性站点(吴淞口、黄浦公园、米市渡)的潮位逐时预报中。结果表明:24 h潮位预报的均方根误差由原来的0.20 m左右降至0.10~0.14 m,预报精度显著提升。

关键词：黄浦江经典调和分析自动分潮优化模型潮位自回归模型

Abstract：The water level fluctuation of Huangpu River is dominated by tides, and affected by the upstream river discharge, rainfall and typhoon storm surge. The traditional harmonic analysis model cannot consider the nontidal factors, thus its prediction accuracy on the water level of Huangpu River can still be improved. Based on the spectral analysis of the prediction errors of the traditional harmonic analysis method, i. e. the automatic optimization of tidal harmonic analysis(ACOTHA) model, this study found that the ACOTHA model's errors mainly exist in the low-frequency band. Therefore, this study introduced an auto-regressive method to correct the short-term prediction of the ACOTHA model. Validation of the 24-h water level prediction at three representative stations suggested that the auto-regressive model can reduce the root mean square errors of the ACOTHA sea level prediction from about 0.20 m to 0.10~0.14 m.

Key words：Huangpu River; traditional harmonic analysis; automatic optimization of tidal harmonic analysis; tidal levels; Auto-regressive