黄浦江感潮河段潮位预报精度提升研究-海洋预报

黄浦江感潮河段潮位预报精度提升研究

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。

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.

参考文献：

[1] MOFTAKHARI H, SCHUBERT J E, AGHAKOUCHAK A, et al.Linking statistical and hydrodynamic modeling for compound flood hazard assessment in tidal channels and estuaries[J].Advances in Water Resources, 2019, 128:28-38.
[2] PAWLOWICZ R, BEARDSLEY B, LENTZ S. Classical tidal harmonic analysis including error estimates in MATLAB using T_TIDE[J]. Computers&Geosciences, 2002, 28(8):929-937.
[3] LU S, TONG C F, LEE D Y, et al. Propagation of tidal waves up in Yangtze estuary during the dry season[J]. Journal of Geophysical Research:Oceans, 2015, 120(9):6445-6473.
[4] 陈金泉,蔡文炬,林克,等.有潮河段洪水过程水位的动力数值预报方法及其应用[J].厦门大学学报(自然科学版), 1985, 24(2):243-249.CHEN J Q, CAI W J, LIN K, et al. A dynamic numerical method for the prediction of flooding process height in tidal rivers and its applications[J]. Journal of Xiamen University (Natural Science),1985, 24(2):243-249.
[5] 王浩.感潮河段水位预报模型研究[D].南京:河海大学, 2006.WANG H. Research on stage forecasting in tidal reach[D].Nanjing:Hohai University, 2006.
[6] 胡琳.钱塘江河口段水位实时预报[D].南京:河海大学, 2007.HU L. The real-time stage forecasting in the estuarine area of Qiantang River[D]. Nanjing:Hohai University, 2007.
[7] SYED Z, CHOI G, BYEON S. A numerical approach to predict water levels in ungauged regions-case study of the Meghna River estuary, Bangladesh[J]. Water, 2018, 10(2):110.
[8] PAN Z H, LIU H. Extreme storm surge induced coastal inundation in Yangtze estuary regions[J]. Journal of Hydrodynamics, 2019, 31(6):1127-1138.
[9] THOMAS A, DIETRICH J C, LOVELAND M, et al. Improving coastal flooding predictions by switching meshes during a simulation[J]. Ocean Modelling, 2021, 164:101820.
[10] MUÑOZ D F, ABBASZADEH P, MOFTAKHARI H, et al.Accounting for uncertainties in compound flood hazard assessment:the value of data assimilation[J]. Coastal Engineering, 2022, 171:104057.
[11] JAY D A. Green's law revisited:tidal long-wave propagation in channels with strong topography[J]. Journal of Geophysical Research:Oceans, 1991, 96(C11):20585-20598.
[12] KUKULKA T, JAY D A. Impacts of Columbia River discharge on salmonid habitat:1. A nonstationary fluvial tide model[J]. Journal of Geophysical Research:Oceans, 2003, 108(C9):3293.
[13] KUKULKA T, JAY D A. Impacts of Columbia River discharge on salmonid habitat:2. Changes in shallow-water habitat[J]. Journal of Geophysical Research:Oceans, 2003, 108(C9):3294.
[14] FERNANDES E H L, MARIÑO-TAPIA I, DYER K R, et al. The attenuation of tidal and subtidal oscillations in the Patos Lagoon estuary[J]. Ocean Dynamics, 2004, 54(3):348-359.
[15] 蔡华阳,杨昊,郭晓娟,等.珠江磨刀门河口径潮动力耦合条件下余水位的多时空尺度分析[J].海洋学报, 2018, 40(7):55-65.CAI H Y, YANG H, GUO X J, et al. Investigation of temporalspatial distribution patterns of residual water level under the influence of tide-river interaction in the Modaomen estuary,Zhujiang River[J]. Haiyang Xuebao, 2018, 40(7):55-65.
[16] MATTE P, JAY D A, ZARON E D. Adaptation of classical tidal harmonic analysis to nonstationary tides, with application to river tides[J]. Journal of Atmospheric and Oceanic Technology, 2013,30(3):569-589.
[17] GAN M, PAN H D, CHEN Y P, et al. Application of the variational mode decomposition (VMD) method to river tides[J].Estuarine, Coastal and Shelf Science, 2021, 261:107570.
[18] GAN M, PAN S Q, CHEN Y P, et al. Application of the machine learning LightGBM model to the prediction of the water levels of the Lower Columbia River[J]. Journal of Marine Science and Engineering, 2021, 9(5):496.
[19] CAI H Y, YANG Q S, ZHANG Z H, et al. Impact of river-tide dynamics on the temporal-spatial distribution of residual water level in the Pearl River channel networks[J]. Estuaries and Coasts,2018, 41(7):1885-1903.
[20] PAN H D, GUO Z, WANG Y Y, et al. Application of the EMD method to river tides[J]. Journal of Atmospheric and Oceanic Technology, 2018, 35(4):809-819.
[21] 丁峰,胡凤彬,周建林,等.径流的河口潮位预报方法研究[J].现代交通技术, 2005, 2(3):74-77.DING F, HU F B, ZHOU J L, et al. Improved prediction of tidal level at estuary considering runoffs[J]. Modern Transportation Technology, 2005, 2(3):74-77.
[22] 李国芳,谭亚,张秀菊.感潮河段上游流量对潮位预报的影响[J].河海大学学报(自然科学版), 2006, 34(2):144-147.LI G F, TAN Y, ZHANG X J. Influence of upstream discharge in tidal level prediction for tidal reaches[J]. Journal of Hohai University (Natural Sciences), 2006, 34(2):144-147.
[23] LI G F, XIANG X Y, GUO C X. Analysis of nonstationary change of annual maximum level records in the Yangtze River estuary[J].Advances in Meteorology, 2016, 2016:7205723.
[24] LEE T L, JENG D S. Application of artificial neural networks in tide-forecasting[J]. Ocean Engineering, 2002, 29(9):1003-1022.
[25] LEE T L. Back-propagation neural network for long-term tidal predictions[J]. Ocean Engineering, 2004, 31(2):225-238.
[26] LEE T L, MAKARYNSKYY O, SHAO C C. A combined harmonic analysis-artificial neural network methodology for tidal predictions[J]. Journal of Coastal Research, 2007, 23(3):764-770.
[27] CHANG H K, LIN L C. Multi-point tidal prediction using artificial neural network with tide-generating forces[J]. Coastal Engineering, 2006, 53(10):857-864.
[28] CHEN W B, LIU W C, HSU M H. Comparison of ANN approach with 2D and 3D hydrodynamic models for simulating estuary water stage[J]. Advances in Engineering Software, 2012, 45(1):69-79.
[29] 甘敏.长江河口潮汐非稳态特征与预报方法研究[D].南京:河海大学, 2023.GAN M. Study on the nonstationarity of the Yangtze estuarine tides and its prediction approaches[D]. Nanjing:Hohai University, 2023.
[30] 吴玲莉,张玮.遗传门限自回归模型在感潮河段水位预测中的应用[J].水利水电科技进展, 2005, 25(5):24-27.WU L L, ZHANG W. Application of genetic threshold autoregressive model to water stage forecasting for tidal river section[J]. Advances in Science and Technology of Water Resources,2005, 25(5):24-27.
[31] 都宏博.感潮河段水位统计预报方法研究[D].南京:河海大学,2007.DU H B. The study of the static forecast means of the water level in tidal reach[J]. Nanjing:Hohai University, 2007.
[32] CHEN Y P, GAN M, PAN S Q, et al. Application of autoregressive (AR) analysis to improve short-term prediction of water levels in the Yangtze estuary[J]. Journal of Hydrology,2020, 590:125386.
[33] 徐晓武,陈永平,甘敏,等.基于非稳态调和分析和长短时记忆神经网络的河口潮位短期预报混合模型[J].海洋通报, 2022, 41(4):401-410.XU X W, CHEN Y P, GAN M, et al. Hybrid model for short-term prediction of tide level in estuary based on LSTM and nonstationary harmonic analysis[J]. Marine Science Bulletin,2022, 41(4):401-410.
[34] 欧素英,杨清书,杨昊,等.河口三角洲径流和潮汐相互作用模型及应用[J].热带海洋学报, 2017, 36(5):1-8.OU S Y, YANG Q S, YANG H, et al. The development and application of river-tide harmonic model[J]. Journal of Tropical Oceanography, 2017, 36(5):1-8.
[35] 欧素英,田枫,郭晓娟,等.珠江三角洲径潮相互作用下潮能的传播和衰减[J].海洋学报, 2016, 38(12):1-10.OU S Y, TIAN F, GUO X J, et al. Propagation and damping of tidal energy in the Pearl River Delta[J]. Haiyang Xuebao, 2016,38(12):1-10.
[36] MATTE P, SECRETAN Y, MORIN J. Temporal and spatial variability of tidal-fluvial dynamics in the St. Lawrence fluvial estuary:an application of nonstationary tidal harmonic analysis[J]. Journal of Geophysical Research:Oceans, 2014, 119(9):5724-5744.
[37] 赵有皓,王祥玲,张君伦.天文潮分析及预报实用系统[J].河海大学学报, 1999, 27(4):73-77.ZHAO Y H, WANG X L, ZHANG J L. A practical system of astronomical tidal analysis and prediction[J]. Journal of Hohai University, 1999, 27(4):73-77.
[38] 姜晓晖,董海军.潮汐调和分析的分潮自动优化及预报应用[J].水道港口, 2006, 27(S1):43-44.JIANG X H, DONG H J. Application of tide components auto optimization and prediction in tidal harmonic analysis[J]. Journal of Waterway and Harbor, 2006, 27(S1):43-44.
[39] LI M, WANG Q J, BENNETT J C, et al. A strategy to overcome adverse effects of autoregressive updating of streamflow forecasts[J]. Hydrology and Earth System Sciences, 2015, 19(1):1-15.
[40] 宗虎城,章卫胜,张金善.海平面上升对黄浦江风暴潮水位影响研究[J].人民长江, 2014, 45(9):1-3.ZONG H C, ZHANG W S, ZHANG J S. Study on influence of sea level rise on storm tidal levels of Huangpu River[J]. Yangtze River, 2014, 45(9):1-3.
[41] HASHEMI M R, SPAULDING M L, SHAW A, et al. An efficient artificial intelligence model for prediction of tropical storm surge[J]. Natural Hazards, 2016, 82(1):471-491.
[42] HIEN N T, TRAN C T, NGUYEN X H, et al. Genetic programming for storm surge forecasting[J]. Ocean Engineering,2020, 215:107812.
[43] TADESSE M, WAHL T, CID A. Data-driven modeling of global storm surges[J]. Frontiers in Marine Science, 2020, 7:260.
[44] RAJASEKARAN S, GAYATHRI S, LEE T L. Support vector regression methodology for storm surge predictions[J]. Ocean Engineering, 2008, 35(16):1578-1587.

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