利用局域欧拉矢量法建立CGCS2000速度场模型

现有研究中，中国大陆速度场模型容易出现数据量小、连续性不佳、现势性不强等问题。基于近7年的中国地壳运动观测网络工程连续运行基准站GNSS(global navigation satellite system)观测数据，解算得到高精度陆态网基准站点的点位坐标和速度场，并利用提出的局部无缝Delaunay三角网反距离加权模型构建中国大陆格网速度场。相较现有的NNR-NUVEL1A(no net rotation Nubia velocity 1A)欧拉矢量模型与常用的速度场数值拟合模型，局部无缝Delaunay三角网反距离加权模型的精度最高，其水平速度场拟合精度优于1.5 mm/a; 采用陆态网约1 800个区域站进行外部检核，结果表明，东、北方向速度差值的绝对值平均值分别为1.11 mm/a、0.90 mm/a，中误差分别为1.50 mm/a、1.35 mm/a。相较于整体三角网而言，局域三角网在大陆边缘地区的拟合精度更优，水平速度场的插值精度更高，平均可以提高约0.3 mm/a，且不易产生粗差。局部无缝Delaunay三角网反距离加权模型不仅考虑了邻近点的距离和方位信息，还可以刻画出更为精细的局部特征，同时克服了边缘地区整体三角网跨度过大以及二级块体边缘处三角网不连续的缺点。

No-Net-Rotation Model of Current Plate Velocities Incorporating Plate Motion Model NUVEL-1

  Objectives  With the development of modern millimeter level geodetic technology, velocity field is one of the indispensable basic elements in Geodetic work. Under the background that current velocity models have limitations such as small data, poor continuity and timeliness update, a method based on local seamless Delaunay triangulation with inverse distance weighting is presented to establish the velocity field model in Chinese mainland.  Methods  Aiming at the limitations of the current velocity models, we obtain the high-precision coordinates and velocities of each CMONOC (crustal movement observational network of China) station, through processing the long-term CMONOC GNSS (global navigation satellite system) observation data of recent seven years by the GAMIT/GLOBK software. And we construct the velocity field of Chinese mainland grid with the inverse distance weighted model of locally seamless Delaunay triangulation. Compared with that calculated by NNR-NUVEL1A (no net rotation Nubia velocity 1A) Euler vector model and some other numerical fitting models, the velocity obtained by the new method in this research has the highest precision.  Results  The fitting precision of horizontal velocity field constructed by this new model is better than 1.5 mm/a. By using more than 1 800 regional stations for external checking, it shows that the average of absolute value of velocity differences in East and North directions are 1.11 mm/a and 0.90 mm/a, respectively, and the corresponding mean square errors are 1.50 mm/a and 1.35 mm/a. In continental margin areas, the fitting precision of horizontal velocity filed by the method of local triangulation net is much higher than that from the whole triangulation net model. Furthermore, based on the method of local triangulation net, interpolation precision of horizontal velocity filed is higher, an improvement of about 0.3 mm/a on average, and the gross errors could be largely reduced.  Conclusions  The new model, which is based on the method of local seamless Delaunay triangulation with inverse distance weighting, can effectively utilize both distance and orientation information of the adjacent points, depict subtler local features with high precision. And it overcomes the shortcomings of the large span of the whole triangulation network in the edge area and the discontinuity of the triangulation network at the edge of the secondary block.