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Tidal-current-asymmetry (TCA) influences sediment transport and geomorphologic changes. It is of paramount importance to understand the current asymmetry in this area in context of a long-term scale with consideration of development and protection of the coastal resources. The radial sand ridges (RSR) in the South Yellow Sea is patterned with strong tidal forcing and complex hydrodynamic environment. This paper simulated tidal current field in the RSR based on the Delft3D model and used combined harmonic analysis and skewness theory to analyze the spatial distribution of the TCA under varied shoreline conditions. The results show that peak-current-asymmetry (PCA) in the RSR is mostly flood-dominant and slack-water-asymmetry (SWA) also shows positive, meaning the flooding duration is shorter than the ebbing duration. Both the positively-dominant PCA and negatively-dominant SWA are mainly affected by the nonlinear interactions between the semidiurnal diurnal tides (M2, S2) and shallow water tides (M4, MS4). As the shoreline gradually moves towards sea during 1984 to 2014, although the nature of $ {\gamma }_{\mathrm{P}\mathrm{C}\mathrm{A}} $ remains, the magnitude of which increases by up to 25%. Meanwhile,$ {\gamma }_{\mathrm{S}\mathrm{W}\mathrm{A}} $ decreases by up to 20%, which intensifies its shorter-flooding-duration pattern in the core area of the RSR.

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近岸地区的潮流不对称影响着沉积物输运和地貌改变。南黄海辐射沙洲海域潮动力强且水动力环境复杂,分析研究该海域潮流不对称性对海岸带资源的开发与保护有长远意义。本文基于Delft3D模型模拟1984年、2014年不同岸线条件下辐射沙洲海域的潮汐潮流运动,结合调和分析与偏度理论,分析刻画了不同岸线条件下潮流不对称性的空间分布特征。研究表明:辐射沙洲海域地形主导的涨落潮流速不对称性(PCA)以涨潮占优为主导;涨落憩历时不对称性(SWA)则以涨憩历时短为主导。二者皆主要受半日分潮(M2、S2)和浅水分潮(M4、MS4)的非线形作用影响。1984–2014年岸线变动后PCA正负性不变,但强度进一步增大,最大变幅可达25%;而$ {\gamma }_{\mathrm{S}\mathrm{W}\mathrm{A}} $减小,最大减幅可达20%,SWA在辐射沙洲海域涨憩历时短的趋势增加。

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冯曦(1987-),女,江苏省南京市人,博士研究生,主要从事海岸水动力和海岸带灾害研究。E-mail:

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冯曦(1987-),女,江苏省南京市人,博士研究生,主要从事海岸水动力和海岸带灾害研究。E-mail:

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The red point is the skewness value at each positlon of the model output globally. The horizonal and vertical values of each point on the blue une are equal

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红点为模型输出全局各位置处偏态值,落在蓝线上各点的横纵坐标值相等

, figureFileSmall=2Siz4MTXVkslWMAvsR3H9A==, figureFileBig=Ex9QHhjRRdqwu3usObgMvw==, tableContent=null), ArticleFig(id=1225368171486556912, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1224796863778410944, language=EN, label=Fig. 4, caption=Distribution of flow field at flood and ebb in 1984 (a, b), and changes of flow field at flood and ebb in 2014 as compared to 1984 (c, d), figureFileSmall=CIRR2EmgiSb6H4xSqoOD4g==, figureFileBig=xwsyZeNXa5ayNAxbmB4fzA==, tableContent=null), ArticleFig(id=1225368171616580347, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1224796863778410944, language=CN, label=图4, caption=1984年涨急、落急流场分布(a,b)和2014年相较1984年的涨急、落急流速变化(c,d), figureFileSmall=CIRR2EmgiSb6H4xSqoOD4g==, figureFileBig=xwsyZeNXa5ayNAxbmB4fzA==, tableContent=null), ArticleFig(id=1225368171750798082, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1224796863778410944, language=EN, label=Fig. 5, caption=Distribution of PCA in 2014 (a), distribution of PCA-changes in 2014 compared to 1984 (b), spatial distribution of the largest contributors to PCA in 2014 (c), and spatial distribution of the largest contributors to PCA in 1984 (d), figureFileSmall=kNTOxKamTRI7SzZ87wcMHw==, figureFileBig=5GjqGlFu+d8lFSRwJ6sSdg==, tableContent=null), ArticleFig(id=1225368171855655692, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1224796863778410944, language=CN, label=图5, caption=2014年PCA分布(a),2014年较1984年PCA变化分布(b),2014年PCA最大贡献项空间分布(c)及1984年PCA最大贡献项(d)空间分布, figureFileSmall=kNTOxKamTRI7SzZ87wcMHw==, figureFileBig=5GjqGlFu+d8lFSRwJ6sSdg==, tableContent=null), ArticleFig(id=1225368171981484817, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1224796863778410944, language=EN, label=Fig. 6, caption=Distribution of SWA in 2014 (a), distribution of SWA-changes in 2014 compared to 1984 (b), spatial distribution of the largest contributor to SWA in 2014 (c), and spatial distribution of 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南黄海辐射沙洲潮流不对称性对岸线变动的响应
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冯曦 1 , 丁志伟 1 , 冯辉 1 , 张蔚 1 , 储鏖 1 , 张驰 1
海洋学报 | 论文 2022,44(6): 1-9
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海洋学报 | 论文 2022, 44(6): 1-9
南黄海辐射沙洲潮流不对称性对岸线变动的响应
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冯曦1 , 丁志伟1, 冯辉1, 张蔚1, 储鏖1, 张驰1
作者信息
  • 1.河海大学 港口海岸与近海工程学院,江苏 南京 210098
  • 冯曦(1987-),女,江苏省南京市人,博士研究生,主要从事海岸水动力和海岸带灾害研究。E-mail:

Responses of tidal-current-asymmetry to shoreline variation in radial sand ridges in the South Yellow Sea
Xi Feng1 , Zhiwei Ding1, Hui Feng1, Wei Zhang1, Ao Chu1, Chi Zhang1
Affiliations
  • 1. College of Harbor, Coastal and Offshore Engineering, Hohai University, Nanjing 210098, China
出版时间: 2022-05-25 doi: 10.12284/hyxb2022049
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近岸地区的潮流不对称影响着沉积物输运和地貌改变。南黄海辐射沙洲海域潮动力强且水动力环境复杂,分析研究该海域潮流不对称性对海岸带资源的开发与保护有长远意义。本文基于Delft3D模型模拟1984年、2014年不同岸线条件下辐射沙洲海域的潮汐潮流运动,结合调和分析与偏度理论,分析刻画了不同岸线条件下潮流不对称性的空间分布特征。研究表明:辐射沙洲海域地形主导的涨落潮流速不对称性(PCA)以涨潮占优为主导;涨落憩历时不对称性(SWA)则以涨憩历时短为主导。二者皆主要受半日分潮(M2、S2)和浅水分潮(M4、MS4)的非线形作用影响。1984–2014年岸线变动后PCA正负性不变,但强度进一步增大,最大变幅可达25%;而$ {\gamma }_{\mathrm{S}\mathrm{W}\mathrm{A}} $减小,最大减幅可达20%,SWA在辐射沙洲海域涨憩历时短的趋势增加。

潮流不对称  /  峰值电流不对称  /  松弛水不对称  /  辐射沙洲  /  岸线变迁

Tidal-current-asymmetry (TCA) influences sediment transport and geomorphologic changes. It is of paramount importance to understand the current asymmetry in this area in context of a long-term scale with consideration of development and protection of the coastal resources. The radial sand ridges (RSR) in the South Yellow Sea is patterned with strong tidal forcing and complex hydrodynamic environment. This paper simulated tidal current field in the RSR based on the Delft3D model and used combined harmonic analysis and skewness theory to analyze the spatial distribution of the TCA under varied shoreline conditions. The results show that peak-current-asymmetry (PCA) in the RSR is mostly flood-dominant and slack-water-asymmetry (SWA) also shows positive, meaning the flooding duration is shorter than the ebbing duration. Both the positively-dominant PCA and negatively-dominant SWA are mainly affected by the nonlinear interactions between the semidiurnal diurnal tides (M2, S2) and shallow water tides (M4, MS4). As the shoreline gradually moves towards sea during 1984 to 2014, although the nature of $ {\gamma }_{\mathrm{P}\mathrm{C}\mathrm{A}} $ remains, the magnitude of which increases by up to 25%. Meanwhile,$ {\gamma }_{\mathrm{S}\mathrm{W}\mathrm{A}} $ decreases by up to 20%, which intensifies its shorter-flooding-duration pattern in the core area of the RSR.

tidal-current-asymmetry  /  peak-current-asymmetry  /  slack-water-asymmetry  /  radial sand ridges  /  shoreline-change
冯曦, 丁志伟, 冯辉, 张蔚, 储鏖, 张驰. 南黄海辐射沙洲潮流不对称性对岸线变动的响应. 海洋学报, 2022 , 44 (6) : 1 -9 . DOI: 10.12284/hyxb2022049
Xi Feng, Zhiwei Ding, Hui Feng, Wei Zhang, Ao Chu, Chi Zhang. Responses of tidal-current-asymmetry to shoreline variation in radial sand ridges in the South Yellow Sea[J]. Haiyang Xuebao, 2022 , 44 (6) : 1 -9 . DOI: 10.12284/hyxb2022049
潮流不对称是一种描述河口、近岸水动力特征的现象,并且对沉积物输送具有重大影响[1]。因为地形和水深的变化潮波形态由外海到近岸发生改变,导致涨落潮流速以及憩流历时不对等,我们把这种现象称作潮流不对称。对于潮流不对称的研究,Friedrichs和Aubrey [2]首先用M2、M4分潮的振幅比(M4/M2)和相位差($2{\phi }_{\mathrm{M}_2}-{\phi }_{\mathrm{M}_4}$)来描述不对称的程度以及方向。振幅比越大代表潮波的变形程度越高,相位差在0°~180°为涨潮占优,在180°~360°为落潮占优。Nidzieko[3]及Nidzieko和Ralston[4]利用统计学中的偏态理论研究了美国西海岸的潮汐不对称和潮流不对称,研究主要是对潮波主要分潮流K1、O1、M2、M4进行偏度计算,未能系统地对潮不对称性各贡献来源进行探究。Song等[5]基于此理论进一步推导了涨落潮历时不对称性的各项贡献公式,指出分潮流组合只要频率满足$ {\omega }_{i}={2\omega }_{j} $或$ {\omega }_{i}+{\omega }_{j}={\omega }_{k} $即可对潮汐不对称性产生贡献,分别揭示了全日潮、半日潮以及超潮和倍潮对于潮汐不对称性的贡献。李谊纯[6]从三阶原点矩出发推导涨落潮流速不对称性(Peak-Current-Asymmetry,PCA)的计算方法,并将此方法应用于北仑河口的研究。Gong等[7]提出把涨落潮历时不对称性计算公式中水位替换成流速加速度即可用来计算涨落憩历时不对称性(Slack-Water-Asymmetry,SWA)。Guo等[8]利用Delft3D模型模拟分析了涨落潮流速不对称和涨落憩历时不对称对于地形变化以及海平面上升的响应。陈婷等[9]利用二维水动力模型,结合非稳态调和分析方法和偏度方法,分析研究了长江口潮流不对称性的时空分布规律。
江苏辐射沙洲处于南黄海旋转潮波与东海前进潮波的交汇处,潮波动力强且水动力环境复杂,形成独特的水下沙洲地形[10]。辐射沙洲的存在使得潮波发生形变,涨潮历时小于落潮历时,由海向岸历时差逐渐增大且非线性效应十分显著[11]。近年来,辐射沙洲海域的大规模围垦导致了该海域的岸线向海推进。岸线变动使得潮波在南黄海近岸涨潮占优的空间占比增加,且在主要潮流通道内涨潮占优愈发明显[12]。Feng和Feng[13]研究了南黄海潮汐不对称性的内在机制并得出M2/M4、M2/S2/MS4和K1/O1/M2之间的非线性相互作用是其主要贡献因子。然而,前人对于该地区潮流不对称性随岸线向海推进而改变的时空分布特征鲜有探索。本文拟通过分析、刻画1984年及2014年辐射沙洲海域PCA与SWA的空间分布特征,推求该海域潮流不对称性对于岸线向海推进的响应。
本文利用课题组前期基于Delft3D建立的辐射沙洲海区二维水动力模型[12]开展分析研究,模型覆盖整个南黄海海域,东部有一段两端接岸的弧形海洋开边界,北、西和南边界都为陆地边界。模型采用曲线正交网格(图1a),共有45 539个网格节点,网格分辨率由外海向近岸增高,外海边界处分辨率最低为4 500 m,近岸最高分辨率达500 m。时间步长为60 s,模型曼尼系数在全局设置为0.015,不考虑风场压迫的影响,同时假设恒定的温盐场。水深地形(图1a)数据来源于Feng等[14]
模型采用冷启动,预留2个月冷启动加速时间,每隔1 h输出一个数据。开边界处由日本潮汐预报系统NAOTIDE预报水位进行驱动。该潮汐预报软件同化了T/P卫星高度计和东亚沿岸验潮站观测资料,精度较高。陆边界处分别采用1984年及2014年两种岸线条件(图1c),模型采用临界水深0.1 m作为判断干湿的标准,即当水深大于0.1 m时为淹滩,反之为露滩。在前期工作中[12]该模型已经完成了率定工作(水位及流速)且验证效果良好,故此处不再赘述。
本文通过涨落潮流速不对称(PCA)以及涨落憩历时不对称(SWA)两个潮流不对称性指标来量化分析潮流不对称性的趋势。如图2流速过程线所示,涨落潮流速不对称表示涨落潮峰值流速大小的不对等(如图2a图2b绿色标记所示);涨落憩历时不对称表示涨落憩历时的不对等,其中憩流是当涨落潮流交替时,出现短时间近乎停止流动的状态(如图2c图2d阴影部分所示)。为了计算量化不对称性,Nidzieko和Ralston [4]采用了偏度理论。
$ \gamma \left(x\right)=\frac{\displaystyle\frac{1}{N-1}\sum\limits _{i=1}^{N}{\left({x}_{i}-\bar{x}\right)}^{3}}{{\left[\displaystyle\frac{1}{N-1}\sum\limits _{i=1}^{N}{\left({x}_{i}-\bar{x}\right)}^{2}\right]}^{\frac{3}{2}}}, $
式中,$ \gamma $是偏度,$ {x}_{i} $是等距(每小时)时间序列中的离散值,$ \stackrel{-}{x} $是某时间段内样本的平均值,$ N $表示样本总数。公式(1)中,当$ {x}_{i} $表示流速,则$ \gamma \left(x\right) $可用以计算该时间序列的平均PCA;而当$ {x}_{i} $表示流速加速度,则$ \gamma \left(x\right) $可用以计算对应的SWA。基于该数学推算,Song等[5]首先推导了潮汐历时不对称性可由不同分潮组合来表达。李谊纯[6]进一步推导出潮流流速不对称偏度$ {\gamma }_{\mathrm{P}\mathrm{C}\mathrm{A}} $可由分潮组合以及余流项的叠加来刻画;Gong等[7]在前二者基础上又导出涨落憩历时不对称偏度$ {\gamma }_{\mathrm{S}\mathrm{W}\mathrm{A}} $的近似表达式:
$\begin{split} {\gamma }_{\mathrm{PCA}}=&\frac{\displaystyle\sum\limits _{{\omega }_{i}+{\omega }_{j}={\omega }_{k}}\frac{3}{2}{a}_{i}{a}_{j}{a}_{k}{{\rm{cos}}}({\phi }_{i}+{\phi }_{j}-{\phi }_{k})}{\displaystyle\left({{a}_{0}}^{2}+\frac{1}{2}\sum \limits_{i=1}^{N}{{a}_{i}}^{2}{{\omega }_{i}}^{2}\right)^{\frac{3}{2}}}+\\&\frac{\displaystyle\sum\limits _{2{\omega }_{i}={\omega }_{j}}\frac{3}{4}{{a}_{i}}^{2}{a}_{j}{{\rm{cos}}}(2{\phi }_{i}-{\phi }_{j})}{\left(\displaystyle{{a}_{0}}^{2}+\frac{1}{2}\sum\limits _{i=1}^{N}{{a}_{i}}^{2}{{\omega }_{i}}^{2}\right)^{\frac{3}{2}}}+ \frac{\displaystyle\sum\limits _{i=1}^{N}\frac{3}{2}{{a}_{i}}^{2}{a}_{0}{{\rm{cos}}\phi }_{0}}{\left(\displaystyle{{a}_{0}}^{2}+\frac{1}{2}\sum\limits _{i=1}^{N}{{a}_{i}}^{2}{{\omega }_{i}}^{2}\right)^{\frac{3}{2}}}+\\& \frac{{{a}_{0}}^{3}{{\rm{cos}}\phi }_{0}}{\left(\displaystyle{{a}_{0}}^{2}+\frac{1}{2}\sum\limits _{i=1}^{N}{{a}_{i}}^{2}{{\omega }_{i}}^{2}\right)^{\frac{3}{2}}} \text{,}\\[-20pt] \end{split}$
$ \begin{split}{\gamma }_{\mathrm{S}\mathrm{W}\mathrm{A}}=&\frac{\displaystyle\sum\limits _{{\omega }_{i}+{\omega }_{j}={\omega }_{k}}\frac{3}{2}{a}_{i}{\omega }_{i}{a}_{j}{\omega }_{j}{a}_{k}{\omega }_{k}{{\rm{sin}}}({\phi }_{i}+{\phi }_{j}-{\phi }_{k})}{\left(\displaystyle\frac{1}{2}\sum\limits _{i=1}^{N}{{a}_{i}}^{2}{{\omega }_{i}}^{2}\right)^{\frac{3}{2}}}+\\&\frac{\displaystyle\sum\limits _{2{\omega }_{i}={\omega }_{j}}\frac{3}{4}{{a}_{i}}^{2}{{\omega }_{i}}^{2}{a}_{j}{\omega }_{j}{{\rm{sin}}}(2{\phi }_{i}-{\phi }_{j})}{\left(\displaystyle\frac{1}{2}\sum\limits _{i=1}^{N}{{a}_{i}}^{2}{{\omega }_{i}}^{2}\right)^{\frac{3}{2}}} \text{,}\end{split} $
式中,$ {a}_{i,j,k} $、$ {\omega }_{i,j,k} $、$ {\phi }_{i,j,k} $分别为潮流流速中分潮的振幅、频率和相位;$ {a}_{0} $、$ {\phi }_{0} $分别为余流的振幅和相位,当余流为正向时$ {\phi }_{0} $取0°,反之取180°[7]。取由外海至近岸方向为正向,$ {\gamma }_{\mathrm{P}\mathrm{C}\mathrm{A}} $>0时,涨潮最大流速大于落潮最大流速,涨潮占优(图2a);反之落潮占优(图2b)。$ {\gamma }_{\mathrm{S}\mathrm{W}\mathrm{A}} $>0代表涨憩历时较长(图2c);反之为落憩历时较长(图2d)。式(2)和式(3)也量化了PCA和SWA各成分的贡献度,即由于分潮组合的非线性作用造成的潮流偏态。本文过程性实验的主要目标函数为岸线−水下三角洲地形−外海天文潮共同作用所产生的PCA或SWA,为了明确和量化岸线、地形对PCA的影响,斜压的贡献、气象的强迫、径流的影响忽略不计,因此$ {a}_{0} $设为0。
计算所需的分潮振幅和相位通过T-TIDE调和分析获得[15]。本文选取振幅大于0.1 m/s的分潮进行计算包括:K1、O1、K2、M2、S2、N2、M4、M6、MS4、MN4共10个分潮。式(2)等式右侧的第三、四项分别表达了余流与分潮的相互作用及余流本身对PCA的作用。其中,余流是指海流中除去周期性潮流的剩余部分,一般用潮周期内流速的平均值计算。由图3可得式(1)与式(2)、式(3)不同方法计算所得所有网格点潮流不对称性指标高度吻合,可由式(2)和式(3)计算分析各分潮对潮流不对称性的贡献值。
本文取一个涨急、落急时刻的水位和流速来观测岸线变化对辐射沙洲水位和流速分布的影响(图4),用弶港处水位来衡量高低潮。当弶港水位处于最低时辐射沙洲海域为低潮,北部响水处于涨潮阶段,并且潮流以高于1 m/s的速度自北向南传播到弶港;当弶港水位处于最高时辐射沙洲海域为高潮,水位以弶港为圆心呈扇形向外海扩散,潮流整体向北传播。而当辐射沙洲海域处于涨急、落急时刻时,潮流场以弶港为圆心分别呈辐聚、辐散,并且北部流速小于南部流速,潮流通道流速大于沙脊流速。涨潮时因为辐射沙洲水道口的收缩以及相对水深的增加,流速最大可增长至2.54 m/s;落潮时,流速由弶港向外逐渐增加,在潮流通道中最高可达2.01 m/s,进入外海后开始减小。岸线变动之后,涨急、落急时刻流速均有不同程度减小,涨急时刻流速最大减小0.85 m/s,外海受影响较小,减幅小于0.1 m/s;近岸受影响较大,辐射沙洲海域减小幅度在0.3~0.85 m/s之间。落急时刻流速最大减小0.66 m/s,减小幅度自近岸向外海由0.66 m/s减小至0 m/s。
图5a显示了2014年岸线下辐射沙洲PCA的空间分布。该海域东北部外海呈落潮占优,$ {\gamma }_{\mathrm{P}\mathrm{C}\mathrm{A}} $在−0.5~0之间;北部大丰港区与南部吕四港区呈涨潮占优,$ {\gamma }_{\mathrm{P}\mathrm{C}\mathrm{A}} $在0~0.5之间。沙洲海域整体呈涨潮占优且潮流通道正不对称性强于沙脊,不对称性由外向内逐渐增加;但其中部分沙脊及沙洲中心区域呈落潮占优。潮流通道正不对称性自外海向近岸增长,$ {\gamma }_{\mathrm{P}\mathrm{C}\mathrm{A}} $最高可达1.27;而沙洲中心呈强烈负不对称,$ {\gamma }_{\mathrm{P}\mathrm{C}\mathrm{A}} $最小可达−1.33。由图5b可见,1984年至2014年由于岸线向海推进,东北部外海$ {\gamma }_{\mathrm{P}\mathrm{C}\mathrm{A}} $减小,而北部沿岸及南部近岸海域$ {\gamma }_{\mathrm{P}\mathrm{C}\mathrm{A}} $增加,变幅在±0.1以内。在辐射沙洲顶端$ {\gamma }_{\mathrm{P}\mathrm{C}\mathrm{A}} $变幅相对明显,最大可至±0.5。岸线变动导致涨潮占优海域$ {\gamma }_{\mathrm{P}\mathrm{C}\mathrm{A}} $增加,而落潮占优海域$ {\gamma }_{\mathrm{P}\mathrm{C}\mathrm{A}} $减小。因此,岸线变动并不改变辐射沙洲海域PCA的性质,仅增大了不对称性的强度。由图5c可见,该海域PCA西北部主要由M2/M4控制,东南部近外海M2/S2/MS4分潮组合的非线性贡献突出。图5c图5d对比可得,岸线变动后PCA主要贡献项分布受影响较小。
图6a显示了2014年岸线下辐射沙洲SWA的空间分布。SWA在辐射沙洲中部(以东沙为例)呈明显的涨憩历时较短态势,且沙脊比潮流通道负不对称更为显著。$ {\gamma }_{\mathrm{S}\mathrm{W}\mathrm{A}} $自外海向内减小,最小可达−0.8。此外,北部沿岸呈涨憩历时也较短,$ {\gamma }_{\mathrm{S}\mathrm{W}\mathrm{A}} $最小可至−0.6;在辐射沙洲顶端和南部部分岸段SWA涨憩历时较长,$ {\gamma }_{\mathrm{S}\mathrm{W}\mathrm{A}} $最大可达0.6。由图6b可得,岸线变动后,$ {\gamma }_{\mathrm{S}\mathrm{W}\mathrm{A}} $在大部分海域减小,在靠近岸线处变化剧烈,增减幅可至±0.2。岸线变动使得辐射沙洲海域落憩历时增长趋势愈发显著。由2014年SWA最大贡献项分布图(图6c图6d)可得,辐射沙洲北部SWA主要由M2/M4控制,而在南部海域M2/S2/MS4贡献突出。同时,SWA主要贡献项(即M2/M4分潮组合)所控制的海域面积在2014年岸线条件下(图6c)较1984年岸线条件下(图6d)有所增大。
辐射沙洲海域PCA的最主要贡献项为分潮非线性作用项M2/S2/MS4以及M2/M4。M2/S2/MS4组合在东北外海贡献负不对称性,$ {\gamma }_{\mathrm{M}_2/\mathrm{S}_2/\mathrm{M}\mathrm{S}_4} $最小可达−0.2;近岸区域主要贡献正不对称性,$ {\gamma }_{\mathrm{M}_2/\mathrm{S}_2/\mathrm{M}\mathrm{S}_4} $最大可达0.4;在沙洲中心贡献负不对称性,$ {\gamma }_{\mathrm{M}_2/\mathrm{S}_2/\mathrm{M}\mathrm{S}_4} $最小可达−0.49(图7a)。M2/M4组合贡献主要为正,沿西北与东南近岸两条潮流通道自外向内逐渐增加,$ {\gamma }_{\mathrm{M}_2/\mathrm{M}_4} $最大可达0.56;在沙洲中心部分地区贡献呈负,$ {\gamma }_{\mathrm{M}_2/\mathrm{M}_4} $最小可达−0.6(图7b)。而岸线自1984年至2014年向海推移后M2/S2/MS4与M2/M4的贡献变化趋势较为类似,不对称性均在东北部外海呈减小趋势,在南部和沿岸呈增加趋势,变动最大可达±0.2。因此,岸线的变化并不改变各项贡献的性质,但增加了外海和近岸PCA的强度。经调查,上述贡献项的变化主要源于岸线变动对M2分潮流速的影响。其中,M2分潮流速最大振幅由1.6 m/s减小到1.5 m/s,而S2分潮流速基本不变。
辐射沙洲海域SWA的最主要贡献项为分潮非线性作用项M2/S2/MS4以及M2/M4。M2/S2/MS4以及M2/M4在沙洲北部海域的贡献度均为负($ {\gamma }_{\mathrm{M}_2/\mathrm{S}_2/\mathrm{M}\mathrm{S}_4} $<0,$ {\gamma }_{\mathrm{M}_2/\mathrm{M}_4} $<0),最小分别可达−0.36以及−0.60(图8a图8b)。而在沙洲南部$ {\gamma }_{\mathrm{M}_2/\mathrm{S}_2/\mathrm{M}\mathrm{S}_4} $>0,且绝对值大于M2/M4所贡献的负不对称性,使得辐射沙洲南部整体落憩历时较短($ {\gamma }_{\mathrm{S}\mathrm{W}\mathrm{A}} $>0)。岸线自1984年至2014年变动后$ {\gamma }_{\mathrm{M}_2/\mathrm{S}_2/\mathrm{M}\mathrm{S}_4} $在大部分辐射沙洲海域减小(图8c)。与此同时,$ {\gamma }_{\mathrm{M}_2/\mathrm{M}_4} $在辐射沙洲南翼(以烂沙洋为主)以及北部西洋水道也呈减小趋势(图8d),这使得该海域SWA落憩历时增长的趋势愈发显著,这与岸线变动所致M2分潮流速减小相关。
本文通过建立南黄海水动力模型,模拟了1984年、2014年辐射沙洲逐时流速场。通过结合调和分析及偏度计算方法,本文分析了由于天文潮和辐射沙洲特殊地形所致的潮流流速不对称和涨落憩不对称的空间分布特征,得到以下结论。
(1)PCA在辐射沙洲海域主要呈涨潮占优($ {\gamma }_{\mathrm{P}\mathrm{C}\mathrm{A}} $>0),在中部核心区域和两岸涨潮占优较突出,但在辐射沙洲顶端仍有落潮占优($ {\gamma }_{\mathrm{P}\mathrm{C}\mathrm{A}} $<0)区域存在;自1984年至2014年,岸线向海推进并不改变该海域PCA的整体态势;但增强了近岸涨潮占优、远岸落潮占优的趋势。
(2)SWA在辐射沙洲海域主要呈涨憩历时较短($ {\gamma }_{\mathrm{S}\mathrm{W}\mathrm{A}} $<0),在以沙脊为主的浅水海域(如东沙)尤为突出;自1984年至2014年,因岸线向海推进使得辐射沙洲中部SWA涨憩历时较短趋势愈发显著。
(3)该海域由地形主导的PCA及SWA生成及演变的主要贡献项均为M2/M4,在辐射沙洲南部则由M2/S2/MS4主导。
  • 国家自然科学基金(519056611)
  • 国家自然科学基金长江水科学联合基金项目(U2040203)
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2022年第44卷第6期
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doi: 10.12284/hyxb2022049
  • 接收时间:2021-06-02
  • 首发时间:2026-02-01
  • 出版时间:2022-05-25
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  • 收稿日期:2021-06-02
  • 修回日期:2021-08-12
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国家自然科学基金(519056611)
国家自然科学基金长江水科学联合基金项目(U2040203)
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    1.河海大学 港口海岸与近海工程学院,江苏 南京 210098
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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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