Analysis of Influencing Factors on Gravity Variations Observed by Quantum Gravimeter at Zhaotong Central Station
PENG Dengjing1,LIU Dong2,MA Da1,LI Wang1
1.Zhaotong Earthquake Monitoring Center Station, Yunnan Earthquake Agency, Zhaotong 657600, China;2.Information Center of Yunnan Earthquake Agency, Kunming 650224, China
To explore the influencing factors of gravity changes at Zhaotong Central Station, this paper utilized continuous observation data from the domestically developed RAI-g type quantum gravimeter from November 2024 to September 2025. After eliminating data jumps and steps and sequentially subtracting interferences like tides, atmospheric pressure, and polar motion, a gravity residual sequence was obtained. Combined with observation data from GNSS, groundwater, and rainfall, the contributions to gravity changes were quantified. Furthermore, integrated with the tectonic setting of Xiaojiang Fault Zone, the possibility of deep material migration was explored. The results indicate that the contribution of underground soil moisture changes to gravity is 4.21 μGal, while the contribution of crustal vertical deformation is 0.427 μGal. Rainfall may indirectly affect gravity changes. After subtracting various interferences, the gravity residual still exhibits fluctuations 1-20 μGal. A comparative analysis between the gravity residual and the water level of Baihetan reservoir shows no significant correlation between the two. Rainfall around the quantum absolute gravimeter may indirectly affect gravity changes. The findings preliminarily verify that domestic quantum gravimeter are capable of monitoring microgravity variations, which can provide reliable data support for the study of regional tectonic activities.
图1 国产量子重力仪安装位置、站点分布、历史5级以上地震情况分布图Fig.1 Installation location of domestic quantum absolute gravimeter, station distribution and distribution of historical earthquakes with M≥5.0
表1 研究数据信息表Table1 Basic information of research data
图2 昭通中心站量子重力仪观测原始数据Fig.2 Raw data of quantum absolute gravimeter at Zhaotong Central Station
式(1)中, g w , i , j (t) 为第t 时刻(日)、第i , j网格的地下水重力效应; θ i , j, k (t) 为第i , j网格第k层土壤的体积含水率(动态值,由时间序列模型获取);∆z i , j, k (t) 为第i , j网格第k层土壤的厚度(动态值,由含水层厚度动态调整模型获取);N为土壤分层数(取100,每层厚度随网格与时间变化)。
计算步骤为:按1 km×1 km网格划分研究区,共生成约800个计算网格;每日读取各网格的θt与∆zt参数;逐网格计算gw, i, j (t) ,并对所有网格的g w , i , j (t) 进行面积加权平均,得到研究区每日的地下水重力效应均值;每周对计算结果进行平滑处理(采用3日滑动平均),消除单日观测噪声。
2.1.4 不确定性分析与结果
不确定性量化:通过蒙特卡罗模拟(1000次抽样),分析含水率(±0.05)、含水层厚度(±0.5 m)的波动对g w (t) 的影响,计算结果的95%置信区间为3.82~4.56 μGal;采用交叉验证法(删除1个观测井数据后重新插值),计算插值误差对g w (t) 的贡献为0.28 μGal,小于0.3 μGal。最终,通过优化后的方法计算得到研究区域2024-11—2025-09平均含水层地下水变化引起的重力效应为g w (t) =4.21 μGal。
图4 扣除气压、倾斜、潮汐、气温、极移等干扰后的剩余重力变化Fig.4 Residual gravity variation after removing interference of air pressure, tilt, earth tide, temperature and polar motion
图5 白鹤滩水电站蓄水与昭通中心站重力变化对比Fig.5 Comparison between water storage of Baihetan Hydropower Station and gravity variations at Zhaotong Central Station