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Unraveling the Deformation and Water Storage Characteristics of Different Aquifer Groups by Integrating PS-InSAR Technology and a Spatial Correlation Model.

Authors :
Zhao, Danni
Chen, Beibei
Gong, Huili
Lei, Kunchao
Zhou, Chaofan
Hu, Jinming
Source :
IEEE Journal of Selected Topics in Applied Earth Observations & Remote Sensing; 2024, Vol. 17, p2501-2515, 15p
Publication Year :
2024

Abstract

Land subsidence is an environmental geological phenomenon mainly caused by groundwater overexploitation. Long-term overexploitation of groundwater not only causes compaction of aquifer thickness and surface deformation but also leads to the loss of aquifer water storage capacity. The skeleton water storage coefficient (Sk) is an important parameter for evaluating the water storage capacity of aquifer groups. This article proposes a new research framework for obtaining the Sk of different aquifer groups: combining permanent scatter for SAR interferometry technology and a multiscale geographic weighted regression model to obtain subsidence information for different aquifer groups, inverting the Sk of different aquifer groups from the spatial scale, and discussing the deformation characteristics of soil layers under different water head change modes to evaluate the deformation and water storage characteristics of different aquifer groups. This framework is applied to the land subsidence region of the Beijing Plain. We calculated that the settlement proportions of different compression layer groups were 14.75%, 23.65%, 33.44%, and 28.16%. Due to the different lithological compositions and groundwater exploitation of different aquifers, the Sk values exhibit different spatial distribution characteristics. With the continuous development of subsidence, the water storage performance of the aquifer group is continuously declining. These findings contribute to managing the sustainable use of groundwater resources and controlling subsidence. It is demonstrated that the research framework proposed in this article can serve as an effective tool for obtaining settlement information and the Sk of different aquifer groups. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19391404
Volume :
17
Database :
Complementary Index
Journal :
IEEE Journal of Selected Topics in Applied Earth Observations & Remote Sensing
Publication Type :
Academic Journal
Accession number :
174717966
Full Text :
https://doi.org/10.1109/JSTARS.2023.3323699