TS-InSAR assessment of groundwater overexploitation-land subsidence linkage: Hengshui case study
Study region: Hengshui City, situated in the North China Plain (NCP), China, is a semi-arid area characterized by intensive agricultural activities and chronic groundwater overdraft due to scarce surface water availability. Study focus: This study aims to quantify long-term groundwater storage chang...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-08-01
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| Series: | Journal of Hydrology: Regional Studies |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214581825003143 |
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| Summary: | Study region: Hengshui City, situated in the North China Plain (NCP), China, is a semi-arid area characterized by intensive agricultural activities and chronic groundwater overdraft due to scarce surface water availability. Study focus: This study aims to quantify long-term groundwater storage changes and reveal the aquifer system's response mechanisms in a typical multi-aquifer setting. We employ Sentinel-1A data for multi-year time-series interferometric synthetic aperture radar (InSAR) analysis to assess surface deformation patterns in Hengshui City from 2017 to 2024. Seasonal deformation was separated, phase lag was corrected, and confined aquifer head changes incorporated to estimate the elastic skeletal storage coefficient (ESSC) and groundwater storage change (GWSC) in deep aquifers. New hydrological insights for the region: Results show subsidence dominates in Hengshui City, with rates up to 141 mm/year (2017–2024), mainly due to falling confined aquifer heads and delayed aquitard drainage. ESSC ranges from 0.98×10−3 to 3.63×10−3, with annual deep groundwater loss around −0.57 km³ . Overall, aquifer heterogeneity contributes to spatial variability in parameters, causing uneven subsidence and water storage dynamics. This work offers new insights into groundwater monitoring in Hengshui, constraining groundwater-subsidence modeling. It also demonstrates InSAR’s strong capability in detecting subsurface deformation and multi-scale hydrological variations. |
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| ISSN: | 2214-5818 |