STUDY ON THE REGIONAL GRAVITY GRADIENT FIELD MODELING IN IRREGULAR AREA WITH CONSIDERATION OF SURFACE FLUCTUATION: A CASE STUDY OF YUNNAN PROVINCE

doi:10.3969/j.issn.0253-4967.2023.05.006

SEISMOLOGY AND GEOLOGY ›› 2023, Vol. 45 ›› Issue (5): 1129-1146.DOI: 10.3969/j.issn.0253-4967.2023.05.006

STUDY ON THE REGIONAL GRAVITY GRADIENT FIELD MODELING IN IRREGULAR AREA WITH CONSIDERATION OF SURFACE FLUCTUATION: A CASE STUDY OF YUNNAN PROVINCE

LIU Jin-zhao¹^,²⁾(), LIANG Xing-hui²⁾^,^*(), YE Zhou-run³⁾, CHEN Zhao-hui¹⁾, HU Min-zhang⁴⁾, HAN Yu-fei⁵⁾, WANG Qing-hua⁶⁾, LIU Dong⁶⁾, HAO Hong-tao⁴⁾, ZHANG Shuang-xi¹⁾, CHEN Ming¹⁾

¹⁾ The First Monitoring and Application Center, China Earthquake Administration, Tianjin 300180, China
²⁾ State Key Laboratory of Geodesy and Earth's Dynamics, Innovation Academy for Precision Measurement Science and Technology. Chinese Academy of Science, Wuhan 430077, China
³⁾ Hefei University of Technology, Hefei 230009, China
⁴⁾ Key Laboratory of Earthquake Geodesy, Institute of Seismology, China Earthquake Administration, Wuhan 430071, China
⁵⁾ China Earthquake Networks Center, Beijing 100045, China
⁶⁾ Yunnan Earthquake Administration, Kunming 650224, China

Received:2022-12-26 Revised:2023-05-31 Online:2023-10-20 Published:2023-11-23

考虑地表起伏的不规则区域重力梯度场模型构建方法——以云南地区为例

刘金钊¹^,²⁾(), 梁星辉²⁾^,^*(), 叶周润³⁾, 陈兆辉¹⁾, 胡敏章⁴⁾, 韩宇飞⁵⁾, 王青华⁶⁾, 刘东⁶⁾, 郝洪涛⁴⁾, 张双喜¹⁾, 陈铭¹⁾

¹⁾ 中国地震局第一监测中心, 天津 300180
²⁾ 中国科学院精密测量科学与技术创新研究院, 大地测量与地球动力学国家重点实验室, 武汉 430077
³⁾ 合肥工业大学, 合肥 230009
⁴⁾ 中国地震局地震研究所, 地震大地测量重点实验室, 武汉 430071
⁵⁾ 中国地震台网中心, 北京 100045
⁶⁾ 云南省地震局, 昆明 650224

通讯作者: *梁星辉, 男, 1983年生, 博士, 副研究员, 主要从事动态重力测量的理论、方法与应用研究, E-mail: lxh_whigg@asch.whigg.ac.cn。
作者简介:
刘金钊, 男, 1986年生, 2015年于中国科学院测量与物理研究所获大地测量学与测量工程专业博士学位, 副研究员, 主要从事重力测量、建模及应用方面的研究, E-mail: whiggliujinzhao@126.com。
基金资助:
国家自然科学基金(41704084); 国家自然科学基金(41904010); 安徽省基金(2008085MD115)

Abstract

Abstract:

The gravity gradient full tensor can sense the slight changes of the gravity vector in different directions, and because of the large number of components(6 components), it can reflect more information on different sides of the same field source than the gravity vector. On the other hand, the ground gravity survey has accumulated a lot of basic gravity vector data, and using the mathematical relationship between the gravity vector and the full tensor of gravity gradient to build a full tensor gravity gradient field model is helpful to the depth mining of existing gravity data information.

Based on the mathematical relation and covariance function relation of disturbance potential, gravity anomaly, gravity disturbance and gravity gradient disturbance, along with the Least Square Configuration(LSC)algorithm, in this paper, the numerical formulas have been derived in detail for modeling the full tensor of regional gravity gradient disturbance field from gravity disturbance or gravity anomaly which distributed on undulating surface with non-grid pattern. The full tensor of gravity gradient derived from the grid distributed gravity anomaly data in West Arnhem Land, Australia by using the spectral domain(two-dimensional fast Fourier transform)method were taken as the “reference value”, Then, the full tensor of gravity gradient, in the same area with irregular regional gravity data distribution, derived form the LSC algorithm based on derived formulas were taken as the “evaluated value”.

By comparing the differences between the “reference value” and the “evaluated value” of the gravity gradient, we found that: 1)The “evaluated value” obtained by the LSC method is consistent in spatial pattern of variation with the “reference value” derived from the spectral domain method. The vertical component of the gravity gradient disturbance describes the boundary characteristics of the field source more precisely than the vertical component of the gravity anomaly, and other gravity gradient disturbance components provide the information representation of the same field source, which provides inspiration for the in-depth interpretation of the field source. 2)Each difference component ΔδΓxxfft-lsc,ΔδΓxyfft-lsc,ΔδΓxzfft-lsc,ΔδΓyyfft-lsc,ΔδΓyzfft-lsc and ΔΓzzfft-lsc between the “evaluated value” and the “reference value” of the gravity gradient has systematic deviation, which is 5.54E, 5.30E, 1.85E, 6.55E, 2.09E and 9.67E respectively. It is much lower than the difference between measured gravity gradient and that from constructed model in previous studies. The results show that the accuracy of the two methods is within the allowable range, but the accuracy of the modeling method based on the Least Square Configuration needs to be further verified by the measured data.

Finally, based on the measured surface differential gravity anomaly values in regional area of Yunnan province, the annul gravity gradient field variation model for this region, about 20km in half wavelength, is firstly constructed and presented by using the LSC with the derived formulas in this paper. The different gravity gradient component models show more abundant interannual scale signal variation characteristics, and demonstrate more local signal characteristics from different sensitive directions in Yunnan region during this time period. In addition, in the vicinity of Zhaotong city in northeast Yunnan province, because there is no gravity points available, both the annual difference results of gravity value and the annual change model of gravity gradient show uniform signal characteristics, indicating that the modeling method in this paper does not introduce additional false “anomalies”. In southern Yunnan province, where gravity points are relatively sparse, both the annual difference results of gravity values and the annual change models of gravity gradients are dominated by long-band signals, and no additional signals will be added due to the increase of expansion order of the LSC algorithm, which is also consistent with our intuitive cognition. These provide support for further research on the relationship between crustal material migration, hydrological changes and earthquakes in Yunnan region.

The procedure and method proposed in this paper can improve the efficiency of using measured gravity data(mainly gravity anomaly and gravity disturbance). Moreover, it can provide basic data for better understanding and interpretation of gravity data, gravity gradient data and their relationship with different field sources in geophysics and geology.

Key words: Co-variance function, Rugged topography, Non-grid gravity, Construction of regional gravity gradient field, Yunnan province

摘要：

文中推导并给出了基于非格网分布的起伏面扰动重力或重力异常解算区域扰动重力梯度场模型的数值计算公式。基于澳大利亚West Arnhem Land地区的格网重力数据, 以频谱域(二维快速傅里叶变换)解算的扰动重力梯度全张量作为“基准值”, 然后利用基于推导公式的最小二乘配置方法(LSC)对相同区域非规则范围的重力数据进行扰动重力梯度模型解算, 将结果作为“评估值”。对比“基准值”与“评估值”之差, 研究发现: 1)基于推导公式的最小二乘配置方法解算得到的扰动重力梯度值与频谱域方法得到扰动梯度“基准值”各分量在空间形变变化上是一致的; 2)统计扰动重力梯度各分量的差值 $Δ δ Γ x x f f t - l s c 、 Δ δ Γ x y f f t - l s c 、 Δ δ Γ x z f f t - l s c 、 Δ δ Γ y y f f t - l s c 、 Δ δ Γ y z f f t - l s c 和 Δ Γ z z f f t - l s c,$ “基准值”与“评估值”差值的标准差分别为5.54E、 5.30E、 1.85E、 6.55E、 2.09E和9.67E(1E=1×10^-9s^-2), 远低于国际上实测重力梯度与解算模型差值的研究结果。最后, 基于云南地区实测地表差分重力值, 文中首次给出了该区域半波长约20km的重力梯度场年际变化模型。文中的思路和方法提高了广泛分布的重力数据(主要为重力异常和扰动重力)的使用效率, 可为地球物理学、地质学研究更好地理解和解释重力数据、重力梯度数据及其与场源的关系提供数据基础。

关键词: 协方差函数, 起伏地形, 云南地区, 非格网重力值, 区域重力梯度场构建

LIU Jin-zhao, LIANG Xing-hui, YE Zhou-run, CHEN Zhao-hui, HU Min-zhang, HAN Yu-fei, WANG Qing-hua, LIU Dong, HAO Hong-tao, ZHANG Shuang-xi, CHEN Ming. STUDY ON THE REGIONAL GRAVITY GRADIENT FIELD MODELING IN IRREGULAR AREA WITH CONSIDERATION OF SURFACE FLUCTUATION: A CASE STUDY OF YUNNAN PROVINCE[J]. SEISMOLOGY AND GEOLOGY, 2023, 45(5): 1129-1146.

刘金钊, 梁星辉, 叶周润, 陈兆辉, 胡敏章, 韩宇飞, 王青华, 刘东, 郝洪涛, 张双喜, 陈铭. 考虑地表起伏的不规则区域重力梯度场模型构建方法——以云南地区为例[J]. 地震地质, 2023, 45(5): 1129-1146.

Figures/Tables 12

Table 1 Statistics of free air gravity anomaly

起始经度	起始纬度	终止经度	终止纬度	经向点数	纬向点数	最小值	最大值	分辨率
132.96443484°	-12.7732721555°	133.78443484°	-12.2532721555°	42	27	27.59mGal	75.85mGal	0.02°

Fig. 1 Free air gravity anomalies and the FFT-derived full tensor of gravity gradient of western Australia.

Fig. 2 Tailored free air gravity anomalies and the full tensor of gravity gradients tailored of western Australia.

Fig. 3 Comparison of LSC-derived gravity gradient and FFT-derived gravity gradient(component δΓxx, δΓxy, δΓxz).

Fig. 4 Comparison of lsc-derived gravity gradient and FFT-derived gravity gradient(component δΓyy, δΓyz, δΓzz).

Table 2 The statistical difference of calculated gravity gradient between LSC method and FFT method(1E=1×10-9s-2)

差值	最大值/E	最小值/E	平均值/E	标准差/E
δ $Γ x x f f t$ -δ $Γ x x l s c$	31.53	-7.73	4.42	5.54
δ $Γ x y f f t$ -δ $Γ x y l s c$	16.76	-17.12	1.66	5.30
δ $Γ x z f f t$ -δ $Γ x z l s c$	9.23	-8.09	-0.004	1.85
δ $Γ y y f f t$ -δ $Γ y y l s c$	36.76	-10.09	-0.73	6.55
δ $Γ y z f f t$ -δ $Γ y z l s c$	9.77	-5.33	-1.16	2.09
δ $Γ z z f f t$ -δ $Γ z z l s c$	11.32	-68.22	-3.54	9.67

Table 2 The statistical difference of calculated gravity gradient between LSC method and FFT method(1E=1×10-9s-2)

差值	最大值/E	最小值/E	平均值/E	标准差/E
δ $Γ x x f f t$ -δ $Γ x x l s c$	31.53	-7.73	4.42	5.54
δ $Γ x y f f t$ -δ $Γ x y l s c$	16.76	-17.12	1.66	5.30
δ $Γ x z f f t$ -δ $Γ x z l s c$	9.23	-8.09	-0.004	1.85
δ $Γ y y f f t$ -δ $Γ y y l s c$	36.76	-10.09	-0.73	6.55
δ $Γ y z f f t$ -δ $Γ y z l s c$	9.77	-5.33	-1.16	2.09
δ $Γ z z f f t$ -δ $Γ z z l s c$	11.32	-68.22	-3.54	9.67

Fig. 5 The distribution of measured point and survey route of gravity network in Yunnan province.

Table 3 Statistics of the survey points, instrument parameters and gravity data after adjustment of regional survey network(Unit:μGal)

绝对重力测点数	相对重力点数	相对重力测段数	相对重力仪编号及格值参数	点值精度平均值	观测年月
9	249	274	CG5-C169, 1.000089	7.80	2020-03
9	249	274	CG5-C170, 0.999928	7.80	2020-03
9	249	274	CG5-C169, 1.000089	10.30	2021-03
9	249	274	CG5-C170, 0.999928	10.30	2021-03

Table 4 The statistics of elevation distribution of survey points and gravity variation in the study area

数据类型	最大值	最小值	平均值	标准差
测点高程/m	3330.00	0.00	1574.00	584.08
重力变化/μGal	30.69	-48.70	-10.27	14.78

Fig. 6 Regional gravity changes from Mar. 2020 to Mar. 2021 in Yunnan province.

Fig. 7 Annual variation model of surface gravity gradient in Yunnan province by using the least squares configuration method based on the derived data from Mar. 2020 to Mar. 2021.

Table 5 Statistics of the annual variation of surface gravity gradient model in the study area(1E=1×10-9s-2)

重力梯度年度变化	最大值/E	最小值/E	平均值/E	标准差/E
ΔΓ_xx	52.36	-76.26	2.91	15.57
ΔΓ_xy	78.75	-42.00	0.47	11.79
ΔΓ_xz	74.59	-89.26	-2.62	22.09
ΔΓ_yy	49.36	-67.62	2.64	13.61
ΔΓ_yz	82.68	-2.27	-4.92	31.99
ΔΓ_zz	64.65	-49.35	-5.55	17.23

References 34

[1]	韩宇飞, 汪健, 徐如刚, 等. 2020. 陆态网络重力测网的分形特征与地震监测能力分析[J]. 中国地震, 36(4): 879—887.
	HAN Yu-fei, WANG Jian, XU Ru-gang, et al. 2020. Fractal characteristics and earthquake monitoring capability of the CMONOC gravity network[J]. Earthquake Research in China, 36(4): 879—887. (in Chinese)
[2]	胡敏章, 郝洪涛, 韩宇飞, 等. 2021. 2021年青海玛多 M_S7.4 地震的重力挠曲均衡背景与震前重力变化[J]. 地球物理学报, 64(9): 3135—3149.
	HU Min-zhang, HAO Hong-tao, HAN Yu-fei, et al. 2021. Gravity flexural isostasy background of the 2021 Madoi(Qinghai) M_S7.4 earthquake and gravity change before the earthquake[J]. Chinese Journal of Geophysics, 64(9): 3135—3149. (in Chinese)
[3]	刘东, 郝洪涛, 王青华, 等. 2021. 2021年云南漾濞 M_S6.4 地震前重力变化[J]. 地震地质, 43(5): 1157—1170. doi: 10.3969/j.issn.0253-4967.2021.05.008.
	LIU Dong, HAO Hong-tao, WANG Qing-hua, et al. 2021. Gravity field change before the 2021 Yangbi M_S6.4 earthquake, Yunnan[J]. Seismology and Geology, 43(5): 1157—1170. (in Chinese)
[4]	刘繁明, 张迎发, 荆心, 等. 2013. 基于余弦变换的重力梯度Parker正演方法及其应用[J]. 测绘学报, 42(2): 177—183, 190.
	LIU Fan-ming, ZHANG Ying-fa, JING Xin, et al. 2013. Gravity gradient Parker's forward method and application using cosine transform[J]. Acta Geodaetica et Cartographica Sinica, 42(2): 177—183, 190. (in Chinese)
[5]	刘金钊, 梁星辉, 叶周润, 等. 2020. 融合多源数据构建区域航空重力梯度扰动全张量[J]. 地球物理学报, 63(8): 3131—3143.
	LIU Jin-zhao, LIANG Xing-hui, YE Zhou-run, et al. 2020. Combining multi-source data to construct full tensor of regional airborne gravity gradient disturbance[J]. Chinese Journal of Geophysics, 63(8): 3131—3143. (in Chinese)
[6]	刘金钊, 柳林涛, 梁星辉, 等. 2013. 基于实测重力异常和地形数据确定重力梯度的研究[J]. 地球物理学报, 56(7): 2245—2256.
	LIU Jin-zhao, LIU Lin-tao, LIANG Xing-hui, et al. 2013. Based on measured gravity anomaly and terrain data to determine the gravity gradients[J]. Chinese Journal of Geophysics, 56(7): 2245—2256. (in Chinese)
[7]	刘金钊, 柳林涛, 梁星辉, 等. 2015. 利用重力异常数据构建重力梯度场的方法比较[J]. 武汉大学学报(信息科学版), 40(12): 1677—1682.
	LIU Jin-zhao, LIU Lin-tao, LIANG Xing-hui, et al. 2015. Comparison of methods to model gravity gradient field using gravity anomaly data[J]. Geomatics and Information Science of Wuhan University, 40(12): 1677—1682. (in Chinese)
[8]	刘金钊, 王岩, 高春春, 等. 2018. 航空重力梯度数据的模拟退火参数反演[J]. 测绘科学, 43(8): 7—13.
	LIU Jin-zhao, WANG Yan, GAO Chun-chun, et al. 2018. Inversion of airborne gravity gradient by using simulated annealing algorithm[J]. Science of Surveying and Mapping, 43(8): 7—13. (in Chinese)
[9]	马国庆, 黄大年, 于平, 等. 2012. 改进的均衡滤波器在位场数据边界识别中的应用[J]. 地球物理学报, 55(12): 4288—4295.
	MA Guo-qing, HUANG Da-nian, YU ping, et al. 2012. Application of improved balancing filters to edge identification of potential field data[J]. Chinese Journal of Geophysics, 55(12): 4288—4295. (in Chinese)
[10]	宋宏伟. 2017. 基于冷原子干涉仪的重力梯度精密测量研究[D]. 武汉: 华中科技大学.
	SONG Hong-wei. 2017. Precise Measurement of Gravity Gradient Based on the Cold Atom Interferometer[D]. Huazhong University of Science & Technology, Wuhan. (in Chinese)
[11]	王青华, 郝洪涛, 汪健, 等. 2019. 云南地震流动重力监测网建设与映震能力分析[J]. 大地测量与地球动力学, 39(3): 317—324.
	WANG Qing-hua, HAO Hong-tao, WANG Jian, et al. 2019. Construction and analysis of seismic response capability of gravimetric network in Yunnan[J]. Journal of Geodesy and Geodynamics, 39(3): 317—324. (in Chinese)
[12]	周文月, 陈昌昕, 侯振隆, 等. 2018. 不同高度数据联合欧拉反褶积法研究[J]. 地球物理学报, 61(8): 3400—3409.
	ZHOU Wen-yue, CHEN Chang-xin, HOU Zhen-long, et al. 2018. The study on the joint Euler deconvolution method of different heights[J]. Chinese Journal of Geophysics, 61(8): 3400—3409. (in Chinese)
[13]	周文月, 马国庆, 侯振隆, 等. 2017. 重力全张量数据联合欧拉反褶积法研究及应用[J]. 地球物理学报, 60(12): 4855—4865.
	ZHOU Wen-yue, MA Guo-qing, HOU Zhen-long, et al. 2017. The study on the joint Euler deconvolution method of full tensor gravity data[J]. Chinese Journal of Geophysics, 60(12): 4855—4865. (in Chinese)
[14]	Bucha B, Janák J, Papčo J, et al. 2016. High-resolution regional gravity field modelling in a mountainous area from terrestrial gravity data[J]. Geophysical Journal International, 207(2): 949—966. DOI URL
[15]	Cooper G R J, Cowan D R. 2006. Enhancing potential field data using filters based on the local phase[J]. Computers & Geosciences, 32(10): 1585—1591. DOI URL
[16]	Cooper G R J, Cowan D R. 2008. Edge enhancement of potential-field data using normalized statistics[J]. Geophysics, 73(3): H1—H4. DOI URL
[17]	Fedi M, Ferranti L, Florio G, et al. 2005. Understanding the structural setting in the southern Apennines(Italy): Insight from Gravity Gradient Tensor[J]. Tectonophysics, 397(1-2): 21—36. DOI URL
[18]	Jekeli C, Zhu L. 2006. Comparison of methods to model the gravitational gradients from topographic data bases[J]. Geophysical Journal International, 166(3): 999—1014. DOI URL
[19]	Jiang F Y, Huang Y, Yan K. 2012. Full gravity gradient tensor from vertical gravity by cosine transform[J]. Applied Geophysics, 9(3): 247—260. DOI URL
[20]	Liu J Z. 2022. Using gravity gradient component and their combination to interpret the geologic structures in the eastern Tianshan Mountains[J]. Geophysical Journal International, 228(2): 982—998. DOI URL
[21]	Liu J Z, Li H L. 2019. Separation and interpretation of gravity field data based on two dimensional Normal Space-Scale Transform(NSST2D)algorithm: A case study of Kauring airborne gravity test site, western Australia[J]. Pure and Applied Geophysics, 176(6): 2513—2528. DOI
[22]	Liu J Z, Liu L T, Liang X H, et al. 2015. 3D density inversion of gravity gradient data using the extrapolated Tikhonov regularization[J]. Applied Geophysics, 12(2): 137—146. DOI URL
[23]	Maria A, Brian M. 2007. Benefits of a high performance airborne gravity gradiometer(HD-AGG^TM)for resource exploration[C]. Proceedings of Exploration 07, Fifth Decennial International Conference on Mineral Exploration:889—893.
[24]	Mehdi E, Lars S E. 2009. Topographic and atmospheric effects on GOCE gradiometric data in a local north-oriented frame: A case study in Fennoscandia and Iran[J]. Studia Geophysica et Geodaetica, 53(1): 61—80. DOI URL
[25]	Murphy C A. 2010. Recent developments with Air-FTG[C]. Airborne Gravity 2010, Abstracts from the ASEG-PESA Airborne Gravity 2010 Workshop: Australia: 142—151.
[26]	Oruç B. 2011. Edge detection and depth estimation using a tilt angle map from gravity gradient data of the Kozakl1-Central Anatolia Region, Turkey[J]. Pure and Applied Geophysics, 168(10): 1769—1780. DOI URL
[27]	Oruç B, Keskinsezer A. 2008. Structural setting of the northeastern Biga Peninsula(Turkey)from tilt derivatives of gravity gradient tensors and magnitude of horizontal gravity components[J]. Pure and Applied Geophysics, 165(9): 1913—1927. DOI URL
[28]	Rummel R. 1997. Spherical spectral properties of the earth's gravitational potential and its first and second derivatives[M]// SansóF, RummelR. Geodetic Boundary Value Problems in View of the One Centimeter Geoid. Springer, Berlin, Heidelberg: 359—404.
[29]	Tscherning C C. 1976. Covariance expressions for second and lower order derivatives of the anomalous potential[R]. Reports of the Department of Geodetic Science No. 225, The Ohio State University, Columbus, Ohio.
[30]	Yuan Y, Zhang X Y, Zhou W N, et al. 2020. Application of the normalized large eigenvalue of structure tensor in the interpretation of potential field tensor data[J]. Earth Planets and Space, 72(1): 143—155. DOI
[31]	Zhang X, Zhong J, Tang B, et al. 2018. Compact portable laser system for mobile cold atom gravimeters[J]. Applied Optics, 57(22): 6545. DOI URL
[32]	Zhu L, Jekeli C. 2007. Combining gravity and topographic data for local gradient modeling[M]. //Tregoning P, RizosC. Dynamic Planet. Springer, Berlin, Heidelberg: 288—295.
[33]	Zhu L, Jekeli C. 2009. Gravity gradient modeling using gravity and DEM[J]. Journal of Geodesy, 83(6): 557—567. DOI URL
[34]	Zhu L, Jekeli C. 2006. Comparing methods to model the local gravity gradients from gravity anomalies[C]. Proceedings of the Symposium of the International Gravity Field Service, Istanbul, Turkey.

STUDY ON THE REGIONAL GRAVITY GRADIENT FIELD MODELING IN IRREGULAR AREA WITH CONSIDERATION OF SURFACE FLUCTUATION: A CASE STUDY OF YUNNAN PROVINCE

考虑地表起伏的不规则区域重力梯度场模型构建方法——以云南地区为例

RichHTML

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 12

References 34

Related Articles 10

Recommended Articles

Metrics

Comments

[1]	LIU Wei, BAI Xi-min, LÜ Shao-jie, SHI Zhe-ming, QI Zhi-yu, HE Guan-ru. HYDROLOGICAL PROPERTIES ESTIMATION BY WATER LEVEL IN RESPONSE TO BAROMETRIC PRESSURE [J]. SEISMOLOGY AND GEOLOGY, 2023, 45(3): 652-667.
[2]	WANG Bo, ZHOU Yong-sheng, ZHONG Jun, HU Xiao-jing, ZHANG Xiang, ZHOU Qing-yun, LI Xu-mao. GEOCHEMICAL CHARACTERISTICS OF SOIL GAS IN ACTIVE FAULT ZONE IN NORTHWEST YUNNAN AND ITS ENLIGHTENMENT TO FAULT ACTIVITY [J]. SEISMOLOGY AND GEOLOGY, 2022, 44(2): 428-447.
[3]	ZHOU Qing, GUO Shun-min, XIANG Hong-fa. PRINCIPLE AND METHOD OF DELINEATION OF POTENTIAL SEISMIC SOURCES IN NORTHEASTERN YUNNAN PROVINCE [J]. SEISMOLOGY AND GEOLOGY, 2004, 26(4): 761-771.
[4]	Ji Fengju, Zheng Rongzhang, Li Jianping, Yin Jinhui. CHRONOLOGICAL RESEARCH OF GEOMORPHIC SURFACE OF LOWER TERRACES ALONG SEVERAL MAJOR RIVERS IN THE EAST AND WEST OF YUNNAN PROVINCE [J]. SEISMOLOGY AND GEOLOGY, 2000, 22(3): 265-276.
[5]	Xiang Hongfa, Guo Shunmin, Xu Xiwei, Zhang Wanxia, Dong Xingquan. ACTIVE BLOCK DIVISION AND PRESENT-DAY MOTION FEATURES OF THE SOUTH REGION OF SICHUAN-YUNNAN PROVINCE [J]. SEISMOLOGY AND GEOLOGY, 2000, 22(3): 253-264.
[6]	Hu Hongxiang. EXPLOSION INVESTIGATION OF THE SHALLOW FAULTS AND THE VELOCITY DISTRIBUTION ALONG THE TOP BOUNDARY OF THE BASEMENT IN YUNNAN PROVINCE [J]. SEISMOLOGY AND GEOLOGY, 1993, 15(2): 181-185.
[7]	He Honglin, Li Ping, Fang Zhongjing. ANALYSIS OF SEISMOGENIC CONDITIONS IN THE WEDGE TECTONIC REGION OF SOUTHEAST YUNNAN PROVINCE [J]. SEISMOLOGY AND GEOLOGY, 1992, 14(3): 217-226.
[8]	Huangfu Gang, Han Mingwang, Jin-nan. STUDY ON FRACTAL GEOMETRY OF FAULTS IN NORTHWESTERN YUNNAN PROVINCE [J]. SEISMOLOGY AND GEOLOGY, 1991, 13(1): 61-66.
[9]	Wang De-ming, Kong Lin, Yang Mei-e. ON THE SEISMOGEOLOGICAL CONDITIONS FOR YANGZONGHAI THERMAL POWER PLANT, YUNNAN PROVINCE [J]. SEISMOLOGY AND GEOLOGY, 1989, 11(2): 39-45.
[10]	Shang-guan Zhi-guan. GEOCHEMICAL CHARACTERISTICS OF THE MAIN ACTIVE FAULTS IN WESTERN YUNNAN EARTHQUAKE PREDICTION TEST SITE [J]. SEISMOLOGY AND GEOLOGY, 1988, 10(4): 134-142.