北京市测绘设计研究院Yanyan Zeng等，在基于垂直重力梯度异常的测深预测及各种影响因素分析中取得新进展。这一研究成果于2024年1月30日发表在国际顶尖学术期刊《大地测量与地球动力学》上。

在这项研究中，团队基于矩形棱柱的垂直重力梯度(VGG)表达式，确定了用于反演水深的海洋深度的控制方程。通过迭代过程对控制方程进行线性化求解，数值仿真验证了其算法和稳定性。团队研究了不同干涉误差的处理方法，利用正则化方法提高了反演过程对误差的稳定性。

用分段双线性插值函数粗略地取代了低频误差，数值模拟表明，经过此处理后，精度可提高41.2%。对于可变的洋壳密度条件下，模拟仿真证实，在海洋水深为6km时，将密度选为平均值，预测的均方根(RMS)误差约为5m。最后，研究对南海两个试验区进行预测，并与船舶测深数据进行对比，预测的均方根误差分别为71.1m和91.4m。

据了解，随着卫星测高技术的发展，测深预报得到了长足的进展。然而，其大部分数据来自海洋重力异常。

附：英文原文

Title: Predicting bathymetry based on vertical gravity gradient anomaly and analyses for various influential factors

Author:Huan Xu, Jinhai Yu, Yanyan Zeng, Qiuyu Wang, Yuwei Tian, Zhongmiao Sun

Issue&Volume: 2024/01/30

Abstract: The prediction of bathymetry has advanced significantly with the development of satellite altimetry. However, the majority of its data originate from marine gravity anomaly. In this study, based on the expression of vertical gravity gradient (VGG) of a rectangular prism, the governing equations for determining sea depths to invert bathymetry. The governing equation is solved by linearization through an iterative process, and numerical simulations verify its algorithm and its stability. We also study the processing methods of different interference errors. The regularization method improves the stability of the inversion process for errors. A piecewise bilinear interpolation function roughly replaces the low-frequency error, and numerical simulations show that the accuracy can be improved by 41.2 % after this treatment. For variable ocean crust density, simulation simulations verify that the root-mean-square (RMS) error of prediction is approximately 5 m for the sea depth of 6 km if density is chosen as the average one. Finally, two test regions in the South China Sea are predicted and compared with ship soundings data, RMS errors of predictions are 71.1 m and 91.4 m, respectively.

DOI: 10.1016/j.geog.2023.12.006

Source: https://www.sciencedirect.com/science/article/pii/S1674984724000041