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台湾浅滩多尺度沙波地貌的地形傅里叶分解

朱超 吴自银 周洁琼 阳凡林 赵荻能 刘洋 鲁号号

朱超,吴自银,周洁琼,等. 台湾浅滩多尺度沙波地貌的地形傅里叶分解[J]. 海洋学报,2019,41(9):136–144,doi:10.3969/j.issn.0253−4193.2019.09.013
引用本文: 朱超,吴自银,周洁琼,等. 台湾浅滩多尺度沙波地貌的地形傅里叶分解[J]. 海洋学报,2019,41(9):136–144,doi:10.3969/j.issn.0253−4193. 2019.09.013
Zhu Chao,Wu Ziyin,Zhou Jieqiong, et al. Fourier decomposition of multi-scale sand wave fields on the Taiwan Banks[J]. Haiyang Xuebao,2019, 41(9):136–144,doi:10.3969/j.issn.0253−4193.2019.09.013
Citation: Zhu Chao,Wu Ziyin,Zhou Jieqiong, et al. Fourier decomposition of multi-scale sand wave fields on the Taiwan Banks[J]. Haiyang Xuebao,2019, 41(9):136–144,doi:10.3969/j.issn.0253−4193. 2019.09.013

台湾浅滩多尺度沙波地貌的地形傅里叶分解

doi: 10.3969/j.issn.0253-4193.2019.09.013
基金项目: 国家自然科学基金(41830540,41476049);公益性科研院所基本科研业务费专项资金重点项目(JZ1902);卫星海洋环境动力学国家重点实验室自主项目(SOEDZZ1802);科技基础性工作专项(2013FY112900);全球变化与海气相互作用专项(GASI-EOGE-01)。
详细信息
    作者简介:

    朱超(1991—),男,山东省济南市人,主要从事多波束海底地形地貌及海洋地球物理勘测研究。E-mail:chaozhu1114@163.com

    通讯作者:

    吴自银(1972—),男,河南省光山县人,研究员,研究方向为多波束海底地形地貌探测与研究。E-mail:zywu@vip.163.com

  • 中图分类号: P737.2

Fourier decomposition of multi-scale sand wave fields on the Taiwan Banks

  • 摘要: 海底沙波在全球广泛分布、成因复杂,但往往多种尺度的沙波叠加在一起形成复杂的沙波地貌体系,导致难以进行量化研究。针对该问题,本文提出一种实用的傅里叶分析方法,设计了巴特沃斯滤波器,将水深数据变换到频率域,进而将复杂沙波地貌分解成不同频率的单一类型沙波。并以台湾浅滩复杂的沙波地貌体系为例进行了分析研究,分解量化出3种空间尺度的沙波:巨型沙波(波长>100 m,波高>5 m)、中型沙波(波长5~100 m,波高0.4~5 m)和沙波纹(波长<5 m,波高<0.4 m)。本文提出的海底沙波地貌量化分析方法,有助于研究不同尺度海底沙波的成因与机理,对沙波区海洋工程的安全评估也具有实用价值。
  • 图  1  实验区平面地形图(a)和A–B水深剖面(b)

    Fig.  1  Bathymetric map of the experimental area (a), and water depth of Profile A–B (b)

    图  2  研究区沙波几何参数定义

    水深的极大值点C表示波峰点,极小值点T代表波谷点,CT之间的垂向高差H表示波高,相邻两个T之间的水平距离L为波长

    Fig.  2  Characterized parameters of sand waves

    Point C represents crest, T represents crest trough, H is wave height and L is wave length

    图  3  方法流程图

    Fig.  3  Workflow of the Fourier decomposition method

    图  4  傅里叶变换的频谱图

    红色部分代表低频,蓝色部分代表中频,黑色部分代表高频

    Fig.  4  Spectral plot by Fourier transform

    The red part represents the low frequency, blue part represents the medium frequency, and black part represents the high frequency

    图  5  傅里叶变换各个频率累加效果图

    图中展示了复合沙波地貌的3种主要组成:巨型沙波、中型沙波 和沙波纹,图6是3种沙波分离的结果

    Fig.  5  Cumulative constituents of the Fourier analysis

    The figure showing three groups of constituents that each represent a bedform type: giant sand waves, small sand waves, and megaripples, Fig. 6 is the separation results of sand waves

    图  6  一维傅里叶变换分离结果

    a.低频沙波信号;b.中频沙波信号;c.高频沙波信号

    Fig.  6  1-D separation results of the Fourier analysis

    a. The separated low frequency sand wave signals;b. the intermediate frequency sand wave signals; c. the residual high frequency sand wave signals

    图  7  二维傅里叶变换分离结果

    a.低频沙波信号;b.中频沙波信号;c.高频沙波信号

    Fig.  7  2-D separation results of the Fourier analysis

    a. The low frequency sand wave signals;b. the medium frequency sand wave signals; c. the high frequency sand wave signals

    图  8  分离的3个尺度与原始水深的对比

    Fig.  8  Separation results of the three scales of sand waves compared with the original water depth

    图  9  提取的沙波峰线散点图

    红点为提取的巨型沙波波峰点,蓝点为中型沙波波峰点

    Fig.  9  Plots of the extracted sand wave crests

    Red points represent the crests of the giant sand waves, and blue points are the crests of the small sand waves

    表  1  3种尺度沙波主要几何参量的统计结果

    Tab.  1  Statistical results of the main characteristics of the separated three scales of sand waves

    沙波类型波长/m波高/m走向/(°)
    巨型沙波最大值366.898.0382.80
    最小值192.475.1373.80
    平均值280.686.7677.30
    中型沙波最大值91.083.93106.20
    最小值42.961.2781.10
    平均值65.592.9777.30
    沙波纹最大值5.160.91
    最小值1.250.06
    平均值3.930.23
    下载: 导出CSV
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  • 收稿日期:  2018-10-29
  • 修回日期:  2019-03-18
  • 网络出版日期:  2021-04-21
  • 刊出日期:  2019-09-25

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