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首页> 外文期刊>Coastal engineering >The application of a radar-based depth inversion method to monitor near-shore nourishments on an open sandy coast and an ebb-tidal delta
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The application of a radar-based depth inversion method to monitor near-shore nourishments on an open sandy coast and an ebb-tidal delta

机译：基于雷达的深度反转方法在露天砂岩海岸和潮流潮汐三角洲监测近岸营养

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摘要

Coastal management in the Netherlands has the aim to defend coastal zones by preventing flooding and mitigating erosion. To that end, large-scale nourishments are placed in the nearshore, which are supposed to dynamically preserve the coastal zone over a timescale of years. To assess their effectiveness, these nourishments are monitored over large areas and long durations. As repetitive, in-situ measurements become too expensive, remote sensing offers an attractive alternative, mapping depth and near-surface current fields via depth inversion algorithms (DIA). However, the information that can be derived from remotely-sensed data is subject to improvement. In this study a 3D-FFT based DIA named XMFit (X-Band Matlab Fitting) is introduced, which is robust, accurate and fast enough for operational use. Focusing on depth estimates, the algorithm was validated for two case studies in the Netherlands: (1) the "Sand Engine", a beach mega nourishment at a uniform open coast, and (2) the tidal inlet of the Dutch Wadden Sea island Ameland, characterizing a more complex coast. Considering both sites, the algorithm performance was characterized by a spatially averaged depth bias of -0.9 m at the Sand Engine and a time-varying bias of approximately -2 - 0 m at the Ameland Inlet. When compared to in-situ depth surveys the accuracy was lower, but the time resolution higher. Depth estimates from the Ameland tidal inlet were produced every 50 min by an operational system using a navigational X-Band radar to monitor the placement of a 5 million m(3) ebb-tidal delta nourishment - a pilot measure for coastal management. Volumetric changes in the nourishment area over the year 2018, occurring at 7 km distance from the radar, were estimated with an error of 7%. Depth errors statistically correlated with the direction and magnitude of simultaneous near-surface current estimates. Additional experiments on Sand Engine data demonstrated that depth errors may be significantly reduced using an alternative spectral approach and/or by using a Kalman filter.
机译：荷兰的沿海管理旨在通过防止洪水和缓解侵蚀来防御沿海地区。为此，将大规模的营养置于近岸，这应该在少年的时间内动态保护沿海地区。为了评估其有效性，这些营养发生在大面积和长持续时间内。尽可能重复，原位测量变得太昂贵，遥感通过深度反转算法（DIA）提供有吸引力的替代，映射深度和近表面电流。但是，可以从远程感测数据派生的信息受到改进。在本研究中，引入了一个名为XMFIT（X波段MATLAB配件）的3D-FFT基因DIA，这是坚固，准确，足够快的操作使用。专注于深度估计，该算法在荷兰进行了两种案例研究验证：（1）“砂发动机”，海滩巨型营养，在均匀的开放海岸，（2）荷兰瓦登海岛阿美岛的潮汐入口，表征更复杂的海岸。考虑到两个站点，算法性能的特征在于在砂发动机处的空间平均深度偏差和在Ameland入口处的时变偏差约-2-0米。与原位深度调查相比，精度较低，但时间分辨率更高。通过使用导航X波段雷达每50分钟通过操作系统每50分钟生产Ameland潮汐入口的深度估计，以监测500万米（3）次EBB-TIDAL DELTA营养的放置 - 沿海管理的试验措施。 2018年营养区的容量变化，从雷达距离距离发生在7公里，估计误差为7％。深度误差与同时近表面电流估计的方向和幅度统计相关。砂发动机数据的附加实验表明，使用替代光谱方法和/或使用卡尔曼滤波器可以显着减少深度误差。

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  • 来源
    《Coastal engineering》 |2020年第8期|103716.1-103716.15|共15页
  • 作者

    Gawehn Matthijs; van Dongeren Ap; de Vries Sierd; Swinkels Cilia; Hoekstra Roderik; Aarninkhof Stefan; Friedman Joshua;

  • 作者单位

    Deltares Unit Marine & Coastal Syst Dept Appl Morphodynam Delft Netherlands|Delft Univ Technol Fac Civil Engn & Geosci Delft Netherlands;

    Deltares Unit Marine & Coastal Syst Dept Appl Morphodynam Delft Netherlands;

    Delft Univ Technol Fac Civil Engn & Geosci Delft Netherlands;

    Deltares Unit Hydraul Engn Dept Harbours Coasts & Offshore Delft Netherlands;

    Deltares Unit Hydraul Engn Dept Harbours Coasts & Offshore Delft Netherlands;

    Delft Univ Technol Fac Civil Engn & Geosci Delft Netherlands;

    Deltares Unit Hydraul Engn Dept Harbours Coasts & Offshore Delft Netherlands;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Remote sensing; Depth inversion; X-band radar; Tidal inlet; Coastal zone; Nourishment;

    机译：遥感;深度反转;X波段雷达;潮汐入口;沿海地区;营养;

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