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。
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 non tidal 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.
作者
潘崇伦
PAN Chongun(Shanghai Flood and Drought Disaster Prevention Technology Center,Shanghai 200050,China)
出处
《海洋预报》
CSCD
北大核心
2024年第2期24-33,共10页
Marine Forecasts
基金
上海市市级财政事前绩效评估项目(2024年度)——上海沿海风暴潮模型研究。
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
Huangpu River
traditional harmonic analysis
automatic optimization of tidal harmonic analysis
tidal levels
Auto-regressive
作者简介
潘崇伦(1982-),男,高级工程师,硕士,主要从事水情预报和水利信息化研究工作。E-mail:13817146568@139.com。
