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Monitoring and numerical prediction of ground stability changes using CORS network

Authors

Wang,  Wei
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Zhang,  Chuanyin
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Dang,  Yamin
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Shi,  Ke
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Yang,  Qiang
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

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Citation

Wang, W., Zhang, C., Dang, Y., Shi, K., Yang, Q. (2023): Monitoring and numerical prediction of ground stability changes using CORS network, XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG) (Berlin 2023).
https://doi.org/10.57757/IUGG23-1327


Cite as: https://gfzpublic.gfz.de/pubman/item/item_5017281
Abstract
In view of the monitoring of the spatial distribution, linkage and temporal evolution of geophysical hazard risk areas, we proposed to use ground stability change monitoring and numerical prediction methods to carry out relevant research. We took CORS network as the control, integrates multi-source data such as hydrometeorology, obtained the regional geometric and physical deformation field model by inversion, and further constructed the law criterion of ground stability criterion, so as to realize the monitoring and numerical prediction of ground stability changes. By interpreting the occurrence place and time, spatial distribution and temporal evolution of the phenomenon of reduced ground stability, the spatial distribution, linkage and temporal evolution law of geological disaster risk areas were revealed, and an application pilot was carried out in western Yunnan province. It was found that the monitoring and numerical prediction methods of ground stability changes using CORS network could effectively grasp the distribution dynamics, linkage relationship and time evolution law of hazard areas, and could provide scientific basis for geological hazard risk assessment, control of hidden danger points and risk areas, disaster preparation process and disaster formation law cognition.