Qiyu Wang
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Qiyu Wang has a total of 8 co-authors. Here are the top co-authors by number of shared publications:
- Chunjian Li
National Institute of Metrology (NIM), Beijing 100029, China
1 shared publication - Dong Wang
National Institute of Metrology (NIM), Beijing 100029, China
1 shared publication - Huijuan Ma
National Key Laboratory of Metrology and Calibration, Beijing Changcheng Institute of Metrology & Measurement, Beijing 100095, China
1 shared publication - Jiamin Yao
National Institute of Metrology, Beijing 100029, China
1 shared publication - Jinyang Feng
National Institute of Metrology, Beijing 100029, China
1 shared publication - Lishuang Mou
National Institute of Metrology (NIM), Beijing 100029, China
1 shared publication
Latest Publications
- Open Access
- 5 June 2026
- Published by MDPI AG in Applied Sciences
- Vol. 16 (11) , 5713
Stability Maintenance of Gravity Comparison Sites (2017–2024): Environmental Factors and Data Processing Strategies
To ensure the sustained stability of absolute gravity benchmark points from 2017 to 2024, observational records from superconducting gravimeters (SGs) and absolute gravimeters were comprehensively examined in this work, and the environmental effects on gravitational acceleration were quantitatively assessed. The annual fluctuation of the SG (iGrav-012k) scale factor reached 0.268 μGal/V, with a weighted average of (–92.8702 ± 0.0265) μGal/V (relative precision of 0.3‰), providing a precise scale factor for long-term SG monitoring. By removing step discontinuities in the SG data using FG5-X249 absolute gravimeter measurements, the residual fitting error decreased to 6.3 μGal. In addition, the SG drift was estimated as 1.0 μGal/year through international comparison datasets and FG5 measurements, substantially improving the consistency of the time series. Further investigation showed that the SG residuals exhibited clear seasonal oscillations, which were mainly attributed to local hydrological processes and ground deformation near the benchmark sites. By integrating groundwater level and deformation monitoring data and applying a neural network model to separate hydrological load components, the peak-to-peak residual amplitude was reduced from 13 μGal to 3.5 μGal. Quantitative analysis indicated that hydrological effects contributed about 9.5 μGal to the seasonal variation, whereas surface deformation had only a minor impact (<2 μGal). The findings confirm that careful data correction and isolation of environmental effects are effective for maintaining the long-term stability of gravity benchmarks. The developed workflow provides a reproducible framework for high-precision gravity site maintenance and supports future dynamic monitoring of regional environmental load responses.
- 5 June 2026
- Published by MDPI AG in Applied Sciences
- Vol. 16 (11) , 5713
Open AccessStability Maintenance of Gravity Comparison Sites (2017–2024): Environmental Factors and Data Processing Strategies
To ensure the sustained stability of absolute gravity benchmark points from 2017 to 2024, observational records from superconducting gravimeters (SGs) and absolute gravimeters were comprehensively examined in this work, and the environmental effects on gravitational acceleration were quantitatively assessed. The annual fluctuation of the SG (iGrav-012k) scale factor reached 0.268 μGal/V, with a weighted average of (–92.8702 ± 0.0265) μGal/V (relative precision of 0.3‰), providing a precise scale factor for long-term SG monitoring. By removing step discontinuities in the SG data using FG5-X249 absolute gravimeter measurements, the residual fitting error decreased to 6.3 μGal. In addition, the SG drift was estimated as 1.0 μGal/year through international comparison datasets and FG5 measurements, substantially improving the consistency of the time series. Further investigation showed that the SG residuals exhibited clear seasonal oscillations, which were mainly attributed to local hydrological processes and ground deformation near the benchmark sites. By integrating groundwater level and deformation monitoring data and applying a neural network model to separate hydrological load components, the peak-to-peak residual amplitude was reduced from 13 μGal to 3.5 μGal. Quantitative analysis indicated that hydrological effects contributed about 9.5 μGal to the seasonal variation, whereas surface deformation had only a minor impact (<2 μGal). The findings confirm that careful data correction and isolation of environmental effects are effective for maintaining the long-term stability of gravity benchmarks. The developed workflow provides a reproducible framework for high-precision gravity site maintenance and supports future dynamic monitoring of regional environmental load responses.