地震研究

为研究山西地区重力场变化特征,利用贝叶斯平差和经典平差法,分析2015—2020年山西地震重力监测网的流动重力观测数据,得到山西断陷带内不同时间尺度的重力场动态变化,并对2种方法的计算结果进行误差和精度分析。结果表明:①2种平差方法在点值精度上整体相当,但贝叶斯平差法的段差序列具备更好的随机分布特征,可以更好地消除由仪器的非线性漂移对结果带来的影响; ②2种方法得到的重力场变化形态一致,但变化量有所差异; ③山西断陷带内重力场变化相对稳定,累积重力场变化显示,区内变化趋势具备连续性,但不同部位重力场变化特征有所差异,位于中部和中南部的太原盆地、临汾盆地重力场变化量小,南北两端的变化量较大,且变化态势相反。

To study the characteristics of gravity field changes in Shanxi region,we use the Bayesian adjustment method and the classical adjustment method to calculate the data obtained in the period 2015-2020 through mobile gravity measurement of the Shanxi Gravimetric Network.Thus,we obtain the dynamical gravity changes on different time scales in the Shanxi Fault Subsidence Zone.Then we compare the error and the accuracy of the calculated data through the classical method with the error and the accuracy of the calculated data through the Bayesian method.The results indicate that the accuracy of the observed values at the observing points is equivalent in general.The sequence of the gravitational segment differences obtained through the Bayesian method has better random distribution,which can better eliminate the influence of the gravimeter's nonlinear drift on the data.The changes in the gravity field obtained by the two methods are consistent,but different in variation quantity.In the Shanxi Fault Subsidence Zone,the gravity field is stable.The cumulative gravity field changes expose that the variation tendency in Shanxi is continuous,but the gravity field variation in different parts is different.The gravity field variation in the Taiyuan Basin of the central part and in the Linfen Basin of the south-central part of the Shanxi region is small,while the variation in the north and the south of the Shanxi region is relatively large,but the variation in these two parts shows opposite tendency.

引言
1 研究区概况及数据处理
2 精度对比
3 重力场变化
4 讨论
5 结论

图1 优化前(a)、后(b)的山西地震重力监测网<br/>Fig.1 The Shanxi Gravimetric Network before(a)and after(b)optimization

图1 优化前(a)、后(b)的山西地震重力监测网
Fig.1 The Shanxi Gravimetric Network before(a)and after(b)optimization

图2 2016-01期、2019-01期使用经典平差法(a)与贝叶斯平差法(b)得到的各测点点值精度<br/>Fig.2 Accuracy of the observed values at the monitoring points in 2016-01 termand 2019-01 term obtained through the classical adjustmentmethod(a)and the Bayesian adjustment method(b)

图2 2016-01期、2019-01期使用经典平差法(a)与贝叶斯平差法(b)得到的各测点点值精度
Fig.2 Accuracy of the observed values at the monitoring points in 2016-01 termand 2019-01 term obtained through the classical adjustmentmethod(a)and the Bayesian adjustment method(b)

表1 各测期2种计算方法的平均点值精度<br/>Tab.1 Average accuracy of the observed values at the monitoring points in 6 measurement periods obtained through two adjustment methods

表1 各测期2种计算方法的平均点值精度
Tab.1 Average accuracy of the observed values at the monitoring points in 6 measurement periods obtained through two adjustment methods

图3 2016-01期、2019-01期经典平差法(a)与贝叶斯平差法(b)的点值精度统计<br/>[JZ]Fig.3 Statistics of the accuracy of the observed values at the monitoring points in 2016-01 term and 2019-01term obtained through the classical adjustment method (a)and the Bayesian adjustment method(b)

图3 2016-01期、2019-01期经典平差法(a)与贝叶斯平差法(b)的点值精度统计
[JZ]Fig.3 Statistics of the accuracy of the observed values at the monitoring points in 2016-01 term and 2019-01term obtained through the classical adjustment method (a)and the Bayesian adjustment method(b)

图4 各测期经典平差法与贝叶斯平差法段差残差对比<br/>Fig.4 Comparison of the segment residuals obtained through the classical adjustment method and thesegment residuals obtained through the Bayesian adjustment method in 6 measurement periods

图4 各测期经典平差法与贝叶斯平差法段差残差对比
Fig.4 Comparison of the segment residuals obtained through the classical adjustment method and thesegment residuals obtained through the Bayesian adjustment method in 6 measurement periods

图5 经典平差法(a)和贝叶斯平差法(b)得到的不同时间尺度重力场动态变化<br/>Fig.5 Dynamic gravity changes on different time scales obtained through the classicaladjustment method(a)and the Bayesian adjustment method(b)

图5 经典平差法(a)和贝叶斯平差法(b)得到的不同时间尺度重力场动态变化
Fig.5 Dynamic gravity changes on different time scales obtained through the classicaladjustment method(a)and the Bayesian adjustment method(b)

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备注

引言

1 研究区概况及数据处理

2 精度对比

3 重力场变化

4 讨论

5 结论

期刊信息