EGM2008模型与地表观测重力数据的融合及其在川西地区的应用

发布时间：2018-02-14 09:35

本文关键词： EGM重力场模型数据融合最小二乘配置自由空气重力异常川西地区　出处：《地球物理学进展》2017年03期 　论文类型：期刊论文

【摘要】：依据四川盆地和其西部高原地区1549个地面重力实测点数据,利用基于‘消去-恢复’思想的最小二乘配置方法,将EGM2008地球重力场模型给出的自由空气重力异常与地面实测自由空气重力异常两种数据进行融合,并对其适用性加以验证分析.计算结果表明,在四川高原地形起伏剧烈的山地,利用采样间隔4 km的地面测点,通过该数据融合方法能将模型值与实测值的标准差从41.9 mGal(10~(-5)ms~(-2))提高到11.6 mGal,平均差异从-105.4 mGal提高到-0.5 mGal;在龙泉山以东较为平坦的盆地区域,间隔8 km的地面测点密度就可以将模型标准差从5.2 mGal提高到1.9 m Gal,平均差异从-16.8 mGal提高到-0.1 mGal.上述不同地面测点分布密度对数据融合结果影响的分析表明,在地形起伏的山地,要将模型标准差控制在10 mGal左右,必须将地面测点密度控制在2 km以内;在平坦的盆地或平原地区,地面测点60 km间隔采样就可以将EGM2008模型值标准差校正到5 mGal左右.
[Abstract]:Based on the data of 1549 ground gravity measured points in Sichuan Basin and its western plateau, the least-square collocation method based on the idea of "erasure and restoration" is used. The free air gravity anomaly derived from the EGM2008 gravity field model is fused with the ground measured free air gravity anomaly, and its applicability is verified and analyzed. By using the method of data fusion, the standard deviation between the model value and the measured value can be raised from 41.9 mGala 10 ~ (-5) to 11.6 MGala, and the average difference from -105.4 mGal to -0.5 mGal. by using the data fusion method, the mean difference can be increased from -105.4 mGal to -0.5 mGala in the flat basin area east of Longquan Mountain. The standard deviation of the model can be increased from 5.2 mGal to 1.9 mGal and the average difference from -16.8 mGal to -0.1 mg 路L ~ (-1). The analysis of the effect of the distribution density of the above different ground points on the data fusion results shows that in the mountainous areas with undulating terrain, the model standard deviation can be increased from -16.8 mGal to -0.1 m Gal1. In order to control the standard deviation of the model to about 10 mGal, the density of the ground measurement point must be controlled within 2 km, and in the flat basin or plain area, the standard deviation of the EGM2008 model value can be corrected to about 5 mGal if the sampling interval is 60 km.
【作者单位】：中国地震局地震预测重点实验室(地震预测研究所);
【基金】：国家自然科学基金(41574071) 东北亚地震、海啸、火山合作研究计划项目(ZRH2014-01-02) 地震行业专项(201108004)联合资助
【分类号】：P223

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