Article(id=1224796773219189037, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1224796769733726966, articleNumber=null, orderNo=null, doi=10.12284/hyxb2022198, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1649779200000, receivedDateStr=2022-04-13, revisedDate=1656259200000, revisedDateStr=2022-06-27, acceptedDate=null, acceptedDateStr=null, onlineDate=1769943906359, onlineDateStr=2026-02-01, pubDate=1664553600000, pubDateStr=2022-10-01, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1769943906359, onlineIssueDateStr=2026-02-01, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1769943906359, creator=13701087609, updateTime=1769943906359, updator=13701087609, issue=Issue{id=1224796769733726966, tenantId=1146029695717560320, journalId=1149651085930835976, year='2022', volume='44', issue='10', pageStart='1', pageEnd='192', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1769943905528, creator=13701087609, updateTime=1769996085810, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1225015629757956162, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1224796769733726966, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1225015629757956163, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1224796769733726966, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1, endPage=9, ext={EN=ArticleExt(id=1224796773537956146, articleId=1224796773219189037, tenantId=1146029695717560320, journalId=1149651085930835976, language=EN, title=Flow structure decomposition and baroclinic M4 constituent current exploration in estuarine zone, columnId=1194652705852465724, journalTitle=Haiyang Xuebao, columnName=Article, runingTitle=null, highlight=null, articleAbstract=

Estuarine flow is the fundamental driving of physical processes such as estuarine ecological environment, river evolution and material transport. Due to the runoff, tide, topography and meteorology, the estuarine flow presents a complex three-dimensional structure, including not only the residual flow induced by fresh water injection, but also the periodical tidal current, wind-driven flow, baroclinic flow and the residual flow caused by estuarine nonlinearity. In order to explore the composition and intra-tidal variation of estuarine flow, based on the field data in the Oujiang River Estuary, the estuarine flow is decomposed by principal component analysis (PCA) method, and the decomposition performance of PCA method for estuarine flow and high-frequency characteristics of baroclinic overtide are deeply discussed. The results show that PCA method can operate original data or standardized data in the study of estuarine flow structure. PCA method can decompose baroclinic components (estuarine gravitational circulation structure), but cannot separate barotropic components (runoff and tidal current). The coupled effect of runoff and tidal current is reflected in the score of principal components. The filter of principal components should employ conjoint judgment of flow structure and cumulative interpretation variance, rather than only cumulative interpretation variance. The estuarine baroclinic flow has clearly high-frequency characteristics, which approximates quarter-diurnal.

, correspAuthors=Jingui Liu, Tianyu Zhang, authorNote=null, correspAuthorsNote=null, copyrightStatement=Copyright © 2022 Pratacultural Science. All rights reserved., copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Yichun Li, Jingui Liu, Tianyu Zhang, Shasha Lu), CN=ArticleExt(id=1224796775018545500, articleId=1224796773219189037, tenantId=1146029695717560320, journalId=1149651085930835976, language=CN, title=河口水流结构分解及斜压M4分潮流探讨, columnId=1149698756456657529, journalTitle=海洋学报, columnName=论文, runingTitle=null, highlight=null, articleAbstract=

河口水流是河口生态环境、河道演变、物质输运等物理过程的根本动力。由于径流、潮波、地形以及气象等因素的影响,河口水流呈现复杂的三维结构。其中既包括淡水注入形成的余流,也包括周期性的潮流、风生流、斜压流及河口非线性作用导致的流动等。为探究河口水流的组成及其潮内变化,基于瓯江口实测资料,利用主成分分析(Principal Component Analysis, PCA)法对河口水流进行分解,探讨了PCA法对河口水流的分解性能及斜压分潮流的高频特征。研究认为,PCA法在河口水流结构研究中既可采用原始数据操作亦可用标准化的数据进行计算。PCA法可分解出斜压成分(河口重力环流型结构),但不能将正压成分(径流和潮流)分开,径流和潮流二者综合作用的结果体现在主成分的得分之中。主成分的取舍应根据水流结构和累计解释方差综合判断,不宜仅依据累计解释方差。河口斜压流动具有明显的高频特征,近似呈1/4日分潮的周期。

, correspAuthors=刘金贵, 仉天宇, authorNote=null, correspAuthorsNote=
刘金贵,副教授,主要从事河口海岸动力学、泥沙运动和近海生态动力学模型研究。E-mail:
仉天宇,教授,主要从事风暴潮过程等海洋灾害防灾减灾研究。E-mail:
, copyrightStatement=版权所有©《海洋学报》编辑部 2022, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=200KzsGLPQU6BTaDBRmiEA==, magXml=ObKPss7i5T5rrOHlTGNE+Q==, pdfUrl=null, pdf=ffTy1/BL2oJkMKRqsEA4+g==, pdfFileSize=1273405, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=yI0/TihuQLjIPZNhl+IqGw==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=zikHCUOtTtGOSklndKkd9w==, mapNumber=null, authorCompany=null, fund=null, authors=

李谊纯(1977-),男,河北省乐亭县人,从事河口海岸动力学、物质输运过程研究。E-mail:

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李谊纯(1977-),男,河北省乐亭县人,从事河口海岸动力学、物质输运过程研究。E-mail:

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李谊纯(1977-),男,河北省乐亭县人,从事河口海岸动力学、物质输运过程研究。E-mail:

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Red and blue lines mark the first and second principal component, respectively

, figureFileSmall=q2uwdvdHHj7dW7LQE1BCiA==, figureFileBig=5b+htQZRvwPRaq/11F/1sg==, tableContent=null), ArticleFig(id=1225368254579913244, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1224796773219189037, language=CN, label=图3, caption=瓯江口流速测点的余流成分

红色、蓝色分别表示第一、二主成分

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PCA cumulative variance (%) of velocity measurement sites in the Oujiang River Estuary

, figureFileSmall=null, figureFileBig=null, tableContent=
L1L2L3L4L5L6L7L8L9
PC199.5399.6999.0599.6599.7099.5799.6999.7198.66
PC20.400.180.720.230.240.260.240.220.66
PC30.040.090.140.090.040.130.040.050.38
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瓯江口流速测点PCA的主成分累计解释方差(%)

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河口水流结构分解及斜压M4分潮流探讨
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李谊纯 1, 2 , 刘金贵 1, 3, 4, * , 仉天宇 1, 3, 4, * , 陆莎莎 5
海洋学报 | 论文 2022,44(10): 1-9
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海洋学报 | 论文 2022, 44(10): 1-9
河口水流结构分解及斜压M4分潮流探讨
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李谊纯1, 2 , 刘金贵1, 3, 4, * , 仉天宇1, 3, 4, * , 陆莎莎5
作者信息
  • 1.广东海洋大学 海洋与气象学院 广东省近海海洋变化与灾害预警实验室,广东 湛江 524088
  • 2.北部湾大学 建筑工程学院,广西 钦州 535011
  • 3.自然资源部空间海洋遥感与应用重点实验室,北京100081
  • 4.广东海洋大学 广东省高等学校陆架及深远海气候、资源与环境重点实验室,广东 湛江 524088
  • 5.自然资源部第二海洋研究所,浙江 杭州 310012
  • 李谊纯(1977-),男,河北省乐亭县人,从事河口海岸动力学、物质输运过程研究。E-mail:

通讯作者:

刘金贵,副教授,主要从事河口海岸动力学、泥沙运动和近海生态动力学模型研究。E-mail:
仉天宇,教授,主要从事风暴潮过程等海洋灾害防灾减灾研究。E-mail:
Flow structure decomposition and baroclinic M4 constituent current exploration in estuarine zone
Yichun Li1, 2 , Jingui Liu1, 3, 4, * , Tianyu Zhang1, 3, 4, * , Shasha Lu5
Affiliations
  • 1. Guangdong Key Laboratory for Coastal Ocean Variation and Disaster Prediction, College of Ocean and Meteorology, Guangdong Ocean University, Zhanjiang 524088, China
  • 2. College of Civil Engineering and Architecture, Beibu Gulf University, Qinzhou 535011, China
  • 3. Key Laboratory of Space Ocean Remote Sensing and Application, Ministry of Natural Resources, Beijing 100081, China
  • 4. Key Laboratory of Climate, Resources and Environment in Continental Shelf Sea and Deep Sea of Department of Education of Guangdong Province, Guangdong Ocean University, Zhanjiang 524088, China
  • 5. Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China
出版时间: 2022-10-01 doi: 10.12284/hyxb2022198
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河口水流是河口生态环境、河道演变、物质输运等物理过程的根本动力。由于径流、潮波、地形以及气象等因素的影响,河口水流呈现复杂的三维结构。其中既包括淡水注入形成的余流,也包括周期性的潮流、风生流、斜压流及河口非线性作用导致的流动等。为探究河口水流的组成及其潮内变化,基于瓯江口实测资料,利用主成分分析(Principal Component Analysis, PCA)法对河口水流进行分解,探讨了PCA法对河口水流的分解性能及斜压分潮流的高频特征。研究认为,PCA法在河口水流结构研究中既可采用原始数据操作亦可用标准化的数据进行计算。PCA法可分解出斜压成分(河口重力环流型结构),但不能将正压成分(径流和潮流)分开,径流和潮流二者综合作用的结果体现在主成分的得分之中。主成分的取舍应根据水流结构和累计解释方差综合判断,不宜仅依据累计解释方差。河口斜压流动具有明显的高频特征,近似呈1/4日分潮的周期。

斜压  /  PCA  /  M4分潮  /  瓯江口  /  河口重力环流

Estuarine flow is the fundamental driving of physical processes such as estuarine ecological environment, river evolution and material transport. Due to the runoff, tide, topography and meteorology, the estuarine flow presents a complex three-dimensional structure, including not only the residual flow induced by fresh water injection, but also the periodical tidal current, wind-driven flow, baroclinic flow and the residual flow caused by estuarine nonlinearity. In order to explore the composition and intra-tidal variation of estuarine flow, based on the field data in the Oujiang River Estuary, the estuarine flow is decomposed by principal component analysis (PCA) method, and the decomposition performance of PCA method for estuarine flow and high-frequency characteristics of baroclinic overtide are deeply discussed. The results show that PCA method can operate original data or standardized data in the study of estuarine flow structure. PCA method can decompose baroclinic components (estuarine gravitational circulation structure), but cannot separate barotropic components (runoff and tidal current). The coupled effect of runoff and tidal current is reflected in the score of principal components. The filter of principal components should employ conjoint judgment of flow structure and cumulative interpretation variance, rather than only cumulative interpretation variance. The estuarine baroclinic flow has clearly high-frequency characteristics, which approximates quarter-diurnal.

baroclinic  /  PCA  /  M4 constituent  /  Oujiang River Estuary  /  estuarine gravitational circulation
李谊纯, 刘金贵, 仉天宇, 陆莎莎. 河口水流结构分解及斜压M4分潮流探讨. 海洋学报, 2022 , 44 (10) : 1 -9 . DOI: 10.12284/hyxb2022198
Yichun Li, Jingui Liu, Tianyu Zhang, Shasha Lu. Flow structure decomposition and baroclinic M4 constituent current exploration in estuarine zone[J]. Haiyang Xuebao, 2022 , 44 (10) : 1 -9 . DOI: 10.12284/hyxb2022198
河口作为河流与海洋的联结点,环境、动力以及生态过程均极为复杂。不论是生态环境问题还是泥沙起动与输运、河床演变问题,水流均是其根本动力。影响河口水动力过程的因素有很多,如:径流、潮波、风、地形以及水体密度变化等。各种因素导致的水流成分共同构成河口水流过程,其中既有周期性的潮流,也包含相对稳定的余流;既有单向的水流也有双向的水流(如潮流、河口重力环流);既有高频成分也有低频或零频成分。各成分的产生机制有根本差异。因此,将各水流成分分离开考虑是深入研究河口水动力过程的重要工作之一。以往的研究中,河口水流的分解主要有两种方法。一是求余流成分的解析解。在此方面,Hansen和Rattray[1]做出了开创性的工作,他们给出了河口重力环流的解析解;Cheng等[2-3]给出了斜压、非线性等余流成分的解析表达式;Wei等[4]重新定义了“潮汐混合”机制,研究了这种混合不对称导致的河口环流的结构与量值;Li等[5]给出了适用于具有明显大−小潮变化的河口区域的正压余流和斜压余流的分解方法。二是通过在数学模型中逐一孤立某种动力机制进行敏感性试验得到不同机制对水流的影响。这两种方法中前者多基于摄动法,因此可以适用于弱非线性问题。而后者存在的问题主要是:河口水流是非线性作用显著的过程,将不同机制孤立出来,虽然在某种程度上或某些问题中是一种可接受的近似,但本质上仍是忽略了该机制与其他不同动力机制之间的非线性相互作用,而各动力之间并非是线性叠加的。主成分分析(Principal Component Analysis, PCA)法利用实测资料或数值模拟的结果进行主成分分析,可探求原始数据中不同产生机制的水流特征且避免了在数据处理中的信息损失。PCA法是一个进行场模态分析的方法,在气象领域应用比较广泛,但在河口水动力学研究中却应用较少。其中的原因可能是:PCA法本质上是一种数据统计方法,其得到的模态与动力机制之间不易建立直接联系;其次,PCA的结果对采用的数据是否经过标准化可能比较敏感;再次,河口及近海区域的流速资料一般仅在少数测点有同步测量,实测数据的缺少也限制了PCA在河口的应用。魏登云和张文俊[6]曾对原始数据是否须标准化处理进行讨论,认为若研究目标需保留变量变异信息,则宜采用原始数据进行分析而不可将其标准化,但可做无量纲化;若研究只需变量之间的关系信息,则原始数据需要标准化。Stacey等[7]采用标准化的数据将PCA法应用于旧金山湾的余流分析中,取得了一定的效果。瓯江是浙江南部一条非常重要的入海河流,瓯江口区域人口密集、经济发达,各种河口海岸工程也密集建设,然而尚未见有对瓯江口水流结构的专门报道。此外,以往河口水动力研究多关注余流特征及其机制,比如重力环流的研究、混合不对称导致的余流特征、正压/斜压河口水体输运的空间分布特征—即低频成分或零频成分。事实上,河口过程中除了低频成分以外,更主要的过程为高频的周期性运动:既包括日潮周期、半日潮周期的成分,也包括1/4日分潮周期甚至1/6日分潮周期的成分。例如:河口重力环流的驱动力为斜压力,湍混合则起反作用,显然,此二机制均存在周期性变化。河口中的水体随潮汐做周期性运动,产生的斜压力必然是周期性的。因此,可以预见斜压力导致的斜压流动除包含重力环流以外,也应含有周期性的成分。虽然此海洋过程存在重要的潜在意义,但相关的研究极为少见。Jay和Musiak[8]曾认为可能存在偶次的高频分潮流,但是其结论是基于大量假设的理论解析解。实际上,河口中的斜压力一般是指向上游的,并不随潮汐涨落而改变方向,因此可能会导致偶次的高频成分产生。由于在河口中M6分潮、M8分潮及更高频率的分潮一般很弱,因此我们将PCA法应用于瓯江口的实测水流资料,对河口M4分潮流进行研究,并对PCA法在河口水流分析中的应用条件、分离性能进行探讨,以期对河口环境水动力过程的研究提供参考。
主成分分析属于经验正交函数分解方法,对于河口研究中的速度场和标量场(盐度、温度等),主成分分析可以将场中的时间模态和空间模态分离开。空间模态不随时间变化,表达场的空间分布特征;时间函数由空间点的线性组合构成,称为主分量。假设场中$ p $个空间点,样本容量为$ n $。记$ p $个空间点上的要素为$ {x}_{1},{x}_{2},{x}_{3}, \cdots,{x}_{p} $,其观测值为$ {x}_{ki} $($k=\mathrm{1,2},3,\cdots,p$;$i=\mathrm{1,2}, 3,\cdots,n$)。在河口海洋的应用中,$ {x}_{ki} $可代表某测点流速,此时$ p\mathrm{、}n $可分别设定为该测点的测量层数和测量的采样时长。若这$ p $个变量的线性组合组成新变量,公式为
$ y=\sum _{i=1}^{p}{v}_{i}{x}_{i}\text{,} $
式中,$ {v}_{i} $为系数,可由$ {x}_{i} $的协方差矩阵求得。如果$ y $满足方差极大的要求,则称$ y $为原$ p $个变量的主分量[9]。对于非奇异的协方差矩阵:
$ {{\boldsymbol{S}}}=\frac{1}{n}\sum _{i=1}^{n}\left({x}_{i}-\bar{x}\right){\left({x}_{i}-\bar{x}\right)}^{{'}} \text{,} $
将其$ p $个特征值由大至小排列,对应的特征向量则称为第$ i $个主成分($ i=\mathrm{1,2},3,\cdots,p $)。其解释能力(或累计方差贡献)为累计特征值与特征值总和的比。
PCA法是一种线性统计方法,可以把随时间变化的要素场分解为空间函数部分和时间函数部分。其结果反映了某些现象,但是现象与机制之间并未建立起对应的关系。所谓模态分离,最终能够分离出哪些有效空间模态亦未曾有明确结论。总之,PCA法在河口水流中的应用极少且不成熟。因此,在将PCA法应用于瓯江口实测水流之前,先对其性能进行检验。首先,构造理想的水流结构。斜压分潮流和正压分潮流的垂向结构是完全不同的。为了能够使理想流速的组成机制清晰,只选择了河口区域内的径流、单一频率规则潮流和重力环流。水流流速设定为
$ {V}={V}_{{\rm{f}}}+{V}_{{\rm{t}}}+{V}_{{\rm{g}}}\text{,} $
式中,${V}_{{\rm{f}}}$为径流流速(0.02 m/s);$ {V}_{{\rm{t}}} $为潮流流速;${V}_{{\rm{g}}}$为河口斜压流速,其时间平均在数值上等于河口重力环流,三者均存在垂向上的变化。径流与斜压流速参考Hansen与Rattray[1]的结果,令:
$ \overline{{V}_{{\rm{f}}}+{V}_{{\rm{g}}}}={V}_{0}\left[\frac{3}{2}\left(1-{\eta }^{2}\right)+\frac{\nu {R}{a}}{48}\left(1-9{\eta }^{2}+8{\eta }^{3}\right)\right]\text{,} $
式中,$\overline{{V}_{{\rm{f}}}+{V}_{{\rm{g}}}} $中横杠表示时间平均;$ {V}_{0} $为径流导致的断面平均流速;$ \eta $为无量纲水深,$\eta=\dfrac{\textit{z}}{h}$,其中$\textit{z} $为水深坐标,h为总水深;$\nu$为系数;$ {R}{a} $为河口Rayleigh数,$ \nu {R}{a}=250 $。为表达各流速在时间上的变化,令瞬时流速表达式为
$ {V}_{{\rm{f}}}={\overline{{V}}_{{\rm{f}}}} \text{,} $
$ {V}_{{\rm{g}}}=\overline{{V}_{{\rm{g}}}}\left[{\rm{cos}}\left(\omega t-\phi \right)+1\right] \text{,} $
$ {V}_{{\rm{t}}}=A{\rm{cos}}\left(\omega t\right)g\left(\textit{z}\right) \text{,} $
式中,$ \phi $为相位差$\left(\phi=\dfrac{\text{π} }{4}\right)$;$\omega $为频率;$ A $为流速的振幅,设为1 m/s;$ g\left(\textit{z}\right) $为潮流的垂向分布函数,采用1/7律指数分布[10],相关公式为
$ g\left(\textit{z}\right)=\left\{\begin{array}{cc}{\left(\dfrac{\textit{z}}{0.32h}\right)}^{{1}/{7}},& 0 < \dfrac{\textit{z}}{h}\leqslant 0.5\text{,}\\ 1.07,& 0.5 < \dfrac{\textit{z}}{h} < 1\text{,}\end{array}\right. $
在式(5)中,径流设定为恒定值,这是考虑到一般的径流资料常以日平均的形式给出。式(6)的构造是为了既体现斜压流动的周期性变化又能使其均值为重力环流流速。该理想水流中仅为检验PCA法的分离性能,因此暂不考虑其准确的周期值。
在PCA法中,时不变的径流不能分离出来,从空间模态的意义上来讲,它的作用将与同为正压流的潮流混合在一起,其量值体现在主成分的得分(S1,S2)上。然而,斜压流则明显表现出来(图1a,PC2),且斜压流的曲线与式(4)所预设的河口重力环流形式基本一致。在图1a中,正压流的垂向分布曲线(PC1)偏离式(4)所设的1/7律指数分布,这应为径流与潮流共同作用所致。径流设置为时不变,所以未能将其分离出。事实上,在下一节的实测流速处理中,也未能将径流的水流结构分离出。除了因为该成分随时间变化缓慢以外,其量值很小也是一个原因。图1b为PC1和PC2两个主成分(或主分量)的得分(S1和S2)随时间的变化。可以看出,S1和S2均呈现出周期性变化,这反映了原始数据中流速的周期性设定,同时二者也表现出明显的相位差,与式(6)和式(7)中所预设的一致。
因此,基本可以认为,PCA可以对水流进行分解,正压流成分和斜压流成分可以清晰分离开,但对同为正压流动的径流和潮流似乎没有效果。此外,需要指出的是,在一般的PCA数据处理中,主成分对原始数据的解释能力一般通过特征值来确定。如果累计解释方差达到某一临界值,则认为完成了对原始数据的降维处理。但在河口水流的处理中,此种准则不适用。因为在河口水流中,潮流(半日潮和全日潮)是水流的重要特征,因此用原始数据做处理时,第一主成分(一般代表周期性潮流)的解释方差往往达到90%以上。而PCA在河口水流的应用中,重点常为考量水流的结构,因此须增加有无显著的水流结构作为判断准则,即利用主成分(结构)及其得分(量值)二者综合判断。关于是否采用标准化的数据,在此研究中,二者并无差别。
瓯江口是浙江省东南部的一个强潮河口,潮差超过6 m。其沿岸经济发达,人口稠密。近些年,伴随着经济的快速发展,人类活动对于瓯江口自然环境的干扰也越来越多,多个大规模沿海、沿岸工程已经或正在实施。瓯江多年平均年径流量分别为470 m3/s。潮汐属正规半日潮类型,潮流属正规浅海半日潮流类型,由于涨落潮流受水域地形限制‚基本呈往复流运动。
在前节中讨论了PCA法的应用方法、分离性能及主成分的取舍原则。在此将PCA法应用于瓯江口的实测流速数据之中,对瓯江口的水流结构进行研究。流速资料为2014年10月25日16:00至2014年10月26日17:00大潮期间的实测数据。同期的径流约为130 m3/s。流速测量垂向采用六点法(表层、0.2h、0.4h、0.6h、0.8h、底层),测量时长为26 h,测点分布见图2。在每一个测点形成一个6×26的数据表,即2.1节中的$ {x}_{ki} $。用PCA法处理流速数据时,可以将流速以矢量形式直接处理[9]。但在河口区域,流速一般为往复流。因此,为简便起见,下面的研究中仅针对主流向(纵向)流速进行。主流向采用“变差最大法”确定:即采用垂向平均流速变差最大的方向作为主流向,并将这一方向的流速分量作为纵向流速。
表1为各测点前3个主成分的累计解释方差。图3给出了瓯江口L1−L9测点第一、第二主成分的结构,第三主成分因其得分明显较小而未列出。可以看出,代表潮流和径流的第一主成分的累积解释方差均达到99%左右,第二主成分呈重力环流型结构,代表了斜压流。第二主成分的累积解释方差大多为0.2%~0.3%,最大可达0.72%。尽管第二主成分的累积解释方差比较小,但它代表了河口水流中的一个重要成分,所以不能将其忽略。第三主成分的解释方差平均约为第二主成分的1/3甚至更小,这也导致第三主成分代表的流动量值也很小,一般不超过0.01 m/s。因此,一般情况下可暂将第三主成分及其后的主成分略去。
图3可以看出,在瓯江北口水道上游端的L1和L2测点呈现差异很大的流速形式。在L1测点,斜压水流比较显著,流速在表层和底层可达到约0.05 m/s和 −0.05 m/s,但代表正压流动的余流则呈垂向近似均匀分布,流速为0.01~0.02 m/s。在南侧的L2测点,第二主成分代表的余流很小,不超过0.01 m/s,而第一主成分代表的正压余流则达到0.10~0.15 m/s。在此断面流速横向上的差异源于该区域涨落潮流路的分离。该断面所处河段地形极其复杂,上游七都岛将瓯江分为分流比约1∶1的南北两汊,下游瓯江被灵昆岛分为南口和北口两支,中间的过渡段北侧水深很浅而南侧龙湾附近最大水深可达40 m上下。瓯江北口主深槽靠近凹岸,L1测点靠近北侧凹岸,北侧的深槽水深较大,是涨潮的主要通道,并在该断面逐渐形成一定的横向水流。L2测点所在的南岸水深很小,因此水体混合相对充分,不利于河口重力环流的产生。落潮时,上游来水经过位于龙湾断面自北岸伸出的潜丁坝。该丁坝坝顶高程在断面中段较低,坝头接近龙湾深槽(图2),因此有一股水流经丁坝挑流并在南口潜坝的共同作用下经过L2测点附近。水深和地形的共同作用导致了L1测点位置可发育一定的重力环流型态的流动,而在L2测点所处的南侧,则表现有较明显的指向下游的欧拉余流。在北口口门附近的黄华断面包括L3−L6 4个测点。其中L3−L5测点的第一主成分和第二主成分的型式基本一致,仅在量值上略有差异。自靠近北岸的L3测点向南至L5测点,不论是第一主成分还是第二主成分代表的余流流速均逐渐减小,这应是局部水深逐渐变浅所致。3个测点均有流速为0.05 m/s左右的斜压流动。黄华断面位于河口口门处,该区域在低径流量的情况下水平盐度梯度已比较明显,且水深相对较大(水深大于10 m),因此存在较为明显的斜压水流。在靠近南侧的L6测点,依旧存在明显的斜压水流,但正压流动(PC1)产生的余流指向上游,流速约为0.07 m/s。L6测点在口门处的副槽之中,涨落潮流路的不一致或为此流速横向差异的主要原因。L7测点位于口门外北侧的沙头水道之中,该处水深不大,垂向混合充分,因此未见明显的双向斜压流动。但是,统计结果显示,该测点的第一主成分代表的余流指向口门方向,这与一般性的认识不同。由于测流时间较短,其中原因尚不明确。L8测点的第二主成分与L7测点类似,但L8测点的第一主成分的余流指向外海,反映了河口水体向外海的输运。L9测点的第一主成分也呈现了这一态势。L9测点的第二主成分代表的余流虽然很小,但却呈现与斜压流动相反的垂向分布。第二主成分应该代表了另一种水流结构:河口欧拉余流指向下游而Stokes输运则指向上游[11]。该处水深较小,从欧拉意义来讲,由于潮汐变形等因素,会导致此种模式的流速结构出现。若同时斜压成分较弱,则会呈现L9测点的流速形式。事实上,该处第三主成分的解释方差仅0.38%,约为第二主成分的一半。加之该测点靠近灵霓北堤,水深较浅,因此水体垂向混合强,不利于斜压流的发育。
图4为L1−L9测点第一、第二主成分(或主变量)对应得分的时间变化。可以看出,所有测点的第一主成分得分(S1)均呈现典型的半日潮周期的变化。这也表明第一主成分反映的主要是周期性的潮流。对于第二主成分,在L1测点、L3−L6测点均显示存在明显的斜压水流,对应的主成分得分(S2)则呈现比第一主成分更复杂的形式。它们不再是半日潮周期的变化,但也并非毫无规律可循。在L3−L5测点,第二主成分的S2实际上呈现近似1/4日分潮周期,在L1和L6测点也基本如此。对于余流量值不大的L2、L7和L8测点,也隐约呈现类似的高频变化,尤其是L7测点,明显呈现1/4分潮周期。对于L9测点,由于其水流结构并非斜压水流而且量值不大,因此对其S2不做进一步讨论。
综上所述,在河口区,纵向斜压流动在平均意义上表现为河口重力环流,但其自身也存在近似为1/4分潮周期的高频振荡。Jay和Musiak[8]曾通过理论分析得出类似结论。Stacey等[7]则将此现象归因为周期性的水体层化(SIPS)。在瓯江口枯水期,水体层化是基本不存在或很弱的,这种高频的振荡应主要为水平盐度梯度在潮周期内的变化所致。Jay和Musiak[8]认为,这种斜压高频流动的存在可通过M4分潮流的标准化振幅和相位的垂向变化进行判断。标准化振幅定义为M4分潮流的相对振幅与M4分潮的相对振幅之比—$\dfrac{\left({U}_{{\rm{M}}_{4}}/ {U}_{{\rm{M}}_{2}}\right)}{\left({A}_{{\rm{M}}_{4}}/{A}_{{\rm{M}}_{2}}\right)}$,其中,$ U $、A分别为潮流和潮汐的振幅。在斜压M4分潮流不发育的情况下,标准化振幅应为O(1~2)。反之,标准化振幅会显著增大[8],且M4分潮流在垂向上流向相反。图5中给出的是瓯江口实测水流数据经调和分析得到的分潮调和常数进而得到相关参数的情况。调和分析采用T-tide实现[12]图5b图5c中竖线给出的为不同测点处垂向上的最大值、最小值和平均值。可以看出,瓯江口不论在口内还是口外,标准化振幅均很大。按文献[8]的判断准则,此处可能存在斜压M4分潮流。图5c中最后一列为各测点M4分潮流迟角的垂向变化特征。可以看出,迟角在垂向上变化不大。因此,虽然标准化振幅很大但不能断定斜压M4分潮流的存在。然而,在图3图4中,斜压流确实在部分测点明显存在,振幅可达0.05 m/s。二者结论的不一致可能是由于瓯江口正压M4分潮流很大。图5显示M4分潮流的相对振幅达到约0.3。瓯江口M2分潮流的振幅可超过1.5 m/s,所以M4分潮流的振幅近似可达0.3~0.4 m/s。而斜压成分的振幅仅为0.05 m/s,二者相差一个量级。不论如何,PCA法可以对河口水流进行分离,可以得出斜压M4分潮流的结构和量值。相对于文献[8]关于M4斜压分潮流的判别准则更为简便和直接。
基于瓯江口实测流速资料,利用主成分分析方法对水流结构进行了分解,验证了PCA法在河口水流中的分离性能及主成分的选择。在此基础上,讨论了河口斜压流动的高频特征。研究认为:PCA法可以将河口水流分离得到正压部分和斜压部分。第一主成分一般为水流的正压部分,反映周期性的潮流。第二主成分一般为斜压部分,反映河口斜压力的作用。斜压流动呈现明显的1/4分潮周期,印证了文献[8]关于斜压不对称导致的偶次高频分潮流的结论。相对于文献[8]的准则,利用PCA法可更便捷的确定斜压M4分潮流。该发现对进一步研究河口流速不对称导致的物质净输运具有重要意义。
  • 国家自然科学基金(41976200)
  • 广东海洋大学科研启动经费(060302032106)
  • 广东省普通高校创新团队项目(2019KCXTF021)
  • 广东省冲一流专项(080503032101-231420003)
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2022年第44卷第10期
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文章信息
doi: 10.12284/hyxb2022198
  • 接收时间:2022-04-13
  • 首发时间:2026-02-01
  • 出版时间:2022-10-01
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出版历史
  • 收稿日期:2022-04-13
  • 修回日期:2022-06-27
基金
国家自然科学基金(41976200)
广东海洋大学科研启动经费(060302032106)
广东省普通高校创新团队项目(2019KCXTF021)
广东省冲一流专项(080503032101-231420003)
作者信息
    1.广东海洋大学 海洋与气象学院 广东省近海海洋变化与灾害预警实验室,广东 湛江 524088
    2.北部湾大学 建筑工程学院,广西 钦州 535011
    3.自然资源部空间海洋遥感与应用重点实验室,北京100081
    4.广东海洋大学 广东省高等学校陆架及深远海气候、资源与环境重点实验室,广东 湛江 524088
    5.自然资源部第二海洋研究所,浙江 杭州 310012

通讯作者:

刘金贵,副教授,主要从事河口海岸动力学、泥沙运动和近海生态动力学模型研究。E-mail:
仉天宇,教授,主要从事风暴潮过程等海洋灾害防灾减灾研究。E-mail:
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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