Analysis of driving factors for land subsidence in typical cities of the North China Plain based on geodetector technology

Zhao-huan Huang; Zhi-bin Huo; Wei Wang; Ji-xiang Zhu; Chun-hao Zhang; Rui-peng Xi

doi:10.26599/JGSE.2025.9280040

Volume 13 Issue 1

Mar. 2025

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Article Navigation > Journal of Groundwater Science and Engineering > 2025 > 13(1): 74-89

Huang ZH, Huo ZB, Wang W, et al. 2025. Analysis of driving factors for land subsidence in typical cities of the North China Plain based on geodetector technology. Journal of Groundwater Science and Engineering, 13(1): 74-89 doi: 10.26599/JGSE.2025.9280040

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Analysis of driving factors for land subsidence in typical cities of the North China Plain based on geodetector technology

doi: 10.26599/JGSE.2025.9280040

Zhao-huan Huang^{1, 2},
Zhi-bin Huo^{1, 2
,
,},
Wei Wang^{1, 2},
Ji-xiang Zhu^{1, 2},
Chun-hao Zhang^{1, 2},
Rui-peng Xi³

1.
Institute of Hydrogeology and Environmental Geology, Chinese Academy of Geological Sciences, Shijiazhuang 050061, China
2.
Key Laboratory of Groundwater Sciences and Engineering, Ministry of Natural Resources, Shijiazhuang 050061, China
3.
Shijiazhuang Institute of Railway Technology, Shijiazhuang 050041, China

More Information

Corresponding author: huozhibin@mail.cgs.gov.cn
Received Date: 2024-04-25
Accepted Date: 2024-12-11

Available Online: 2025-02-20

Publish Date: 2025-03-10

Abstract

Abstract

The North China Plain is vital hub for agricultural production and urban development. However, decades of excessive groundwater extraction have resulted on significant land subsidence, posing severe threats to the region's socio-economic stability and sustainable development. The relationship between land deformation and groundwater storage Anomalies in this region remains insufficiently understood, and the driving factors behind land subsidence require further exploration. This study employs downscaled GRACE and SBAS InSAR technologies to monitor and analyze land subsidence and groundwater storage Anomalies in four representative cities of the North China Plain: Beijing, Tianjin, Cangzhou, and Hengshui. Using geodetector methods, the study investigates the driving factors of land subsidence, incorporating both natural environmental and human activity factors. The results indicate that: (1) Groundwater storage in the North China Plain generally exhibited an overall declining trend from 2002 to 2022, with the rate of decrease weakening from southwest to northeast, showing a clear spatial clustering pattern. (2) While, land subsidence rates in the main urban areas of each city were relatively low, severe subsidence persisted in the surrounding suburban and rural areas. (3) The temporal trends of land subsidence were consistent with changes in groundwater storage across all cities. (4) Groundwater storage Anomalies emerged as the most significant factor influencing the spatial distribution of land subsidence, with a q-value of 0.387, followed by factors such as DEM, evapotranspiration, and rainfall. Seasonal characteristics were evident in land deformation corresponding to groundwater storage Anomalies: During the spring and summer irrigation periods, land subsidence occurred due to groundwater depletion, while in autumn and winter, the surface uplifted with increased groundwater storage. In Cangzhou and Hengshui, excessive deep groundwater extraction caused a lagged response in land subsidence relative to groundwater storage Anomalies. Furthermore, interaction among various factors significantly amplified their influence on land subsidence. The interaction between groundwater storage Anomalies and rainfall had the strongest combined effect, underscoring its critical role in shaping land subsidence in the study area. The findings offer valuable insights for the scientific prevention and management of land subsidence in the North China Plain.
- Land subsidence,
- InSAR,
- groundwater storage Anomalies,
- Geodetector,
- GRACE

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References(29)

References

Agarwal V, Akyilmaz O, Shum CK, et al. 2023. Machine learning based downscaling of GRACE-estimated groundwater in Central Valley, California. Science of the total Environment, 865: 161138. DOI: 10.1016/j.scitotenv.2022.161138.

An Y, Yang F, Xu J, et al. 2024. Surface deformation analysis and prediction of groundwater changes from joint sar-grace satellite data. IEEE Access, 12: 33671−33686, DOI: 10.1109/ACCESS.2024.3368423.

Bagheri-Gavkosh M, Hosseini SM, Ataie-Ashtiani B, et al. 2021. Land subsidence: A global challenge. Science of the Total Environment, 778(6): 146193. DOI: 10.1016/j.scitotenv.2021.146193.

Berardino P, Fornaro G, Lanari R, et al. 2002. A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms. IEEE Transactions on Geoscience and Remote Sensing, 40(11): 2375−2383. DOI: 10.1109/TGRS.2002.803792.

Cao Q, Zhang Y, Yang L, et al. 2024. Unveiling the driving factors of urban land subsidence in Beijing, China. Science of the Total Environment, 916: 170134. DOI: 10.1016/j.scitotenv.2024.170134.

Huang ZY, Pan Y, Gong HL, et al. 2015. Subregional‐scale groundwater depletion detected by GRACE for both shallow and deep aquifers in North China Plain. Geophysical Research Letters, 42(6): 1791−1799. DOI: 10.1002/2014GL062498.

Gong HL, Pan Y, Zheng LQ, et al. 2018. Long-term groundwater storage changes and land subsidence development in the North China Plain (1971–2015). Hydrogeology Journal, 26(5): 1417−1427. DOI: 10.1007/s10040-018-1768-4.

Guo HP, Bai JB, Zhang YQ, et al. 2017. The evolution characteristics and mechanism of the land subsidence in typical areas of the North China Plain. Geology in China, 44(6): 1115−1127. (in Chinese) DOI: 10.12029/gc20170606.

Guo HP, Li WP, Wang LY, et al. 2021. Present situation and research prospects of the land subsidence driven by groundwater levels in the North China Plain. Hydrogeology & Engineering Geology, 48(3): 162−171. (in Chinese) DOI: 10.16030/j.cnki.issn.1000-3665.202012037.

Khorrami B, Gunduz O. 2021. Evaluation of the temporal variations of groundwater storage and its interactions with climatic variables using GRACE data and hydrological models: A study from Turkey. Hydrological Processes, 35(3): e14076. DOI: 10.1002/hyp.14076.

Lei KC, Luo Y, Chen BB, et al. 2016. Distribution characteristics and influence factors ofland subsidence in Beijing area. Geology in China, 43(6): 2216−2228. (in Chinese) DOI: 10.12029/gc20160628.

Li X, Ye SY, Song F, et al. 2018. Quantitative identification of major factors affecting groundwater change in Beijing-Tianjin-Hebei Plain. Journal of China Hydrology, 38(01): 21−27. (in Chinese) DOI: 10.3969/j.issn.1000-0852.2018.01.004.

Lin JH, Chen WH, Qi XH, et al. 2021. Risk assessment and its influencing factors analysis of geological hazards in typical mountain environment. Journal of Cleaner Production, 309: 127077. DOI: 10.1016/j.jclepro.2021.127077.

Lin M, Biswas A, Bennett EM. 2019. Spatio-temporal dynamics of groundwater storage changes in the Yellow River Basin. Journal of Environmental Management, 235: 84−95. DOI: 10.1016/j.jenvman.2019.01.016.

Liu HL, Zhang GQ, Zhang DS, et al. 2022. Improving the spatial resolution of GRACE satellites based on high-resolution hydrological simulations. Bulletin of Surveying and Mapping, 0(8): 41−47. (in Chinese) DOI: 10.13474/j.cnki.11-2246.2022.0230.

Liu ZQ, Zhang SW, Fan WJ, et al. 2024. Associations between surface deformation and groundwater storage in different landscape areas of the Loess Plateau, China. Land, 13(2): 184. DOI: 10.3390/land13020184.

Pan Y, Zhang C, Gong HL, et al. 2017. Detection of human-induced evapotranspiration using GRACE satellite observations in the Haihe River basin of China. Geophysical Research Letters, 44(1): 190−199. DOI: 10.1002/2016GL071287.

Peng SZ, Ding YX, Liu WZ, et al. 2019. 1 km monthly temperature and precipitation dataset for China from 1901 to 2017. Earth System Science Data, 11(4): 1931−1946. DOI: 10.5194/essd-11-1931-2019,2019.

Peng SZ, Gang CC, Cao Y, et al. 2018. Assessment of climate change trends over the Loess Plateau in China from 1901 to 2100. International Journal of Climatology, 38(5): 2250−2264. DOI: 10.1002/joc.5331.

Singh L, Saravanan S. 2020. Satellite-derived GRACE groundwater storage variation in complex aquifer system in India. Sustainable Water Resources Management, 6(3): 43. DOI: 10.1007/s40899-020-00399-3.

Sorkhabi OM, Asgari J. 2023. Multi-sensor observations for monitoring groundwater depletion and land subsidence. Journal of Hydrology: Regional Studies, 50: 101529. DOI: 10.1016/j.ejrh.2023.101529.

Su YZ, Guo B, Zhou ZT, et al. 2020. Spatio-temporal variations in groundwater revealed by GRACE and its driving factors in the Huang-Huai-Hai Plain, China. Sensors, 20(3): 922. DOI: 10.3390/s20030922.

Wang JF, Xu CD. 2017. Geodetector: Principle and prospective. Acta Geographica Sinica, 72(1): 116−134. (in Chinese) DOI: 10.11821/dlxb201701010.

Xu CJ, He P, Wen YM, et al. 2015. Recent advances InSAR interferometry and its applications. Journal of Geomatics, 40(2): 1−9. (in Chinese) DOI: 10.14188/j.2095-6045.2015.02.001.

Xue DP, Gui DW, Ci MT, et al. 2024. Spatial and temporal downscaling schemes to reconstruct high-resolution GRACE data: A case study in the Tarim River Basin, Northwest China. Science of the Total Environment, 907: 167908. DOI: 10.1016/j.scitotenv.2023.167908.

Yu W, Gong HL , Chen BB, et al. 2021. Combined GRACE and MT-InSAR to assess the relationship between groundwater storage cchange and land subsidence in the BeijZing-Tianjin-Hebei Region. Remote Sensing, 13(18): 3773. DOI: 10.3390/rs13183773.

Zhang XY, Ruan YC, Xuan WH, et al. 2023. Risk assessment and spatial regulation on urban ground collapse based on geo-detector: A case study of Hangzhou urban area. NaturalHazards, 118: 525−543. DOI: 10.1007/s11069-023-06016-8.

Zhang Y, Liu YF, Liu Y, et al. 2022. Spatial-temproal variation characteristics and geographic detection mechanism of land subsidence in wuhan city from 2007 to 2019. Geomatics and Information Science of Wuhan University, 47(9): 1486−1497. (in Chinese) DOI: 10.13203/j.whugis20210143.

Zhong YL, Feng W, Zhong M, et al. 2020. Dataset of reconstructed terrestrial water storage in China based on precipitation (2002–2019). A Big Earth Data Platform for ThreePoles. CSTR: 18406.11.Hydro.tpdc.270990. DOI: 10.11888/Hydro.tpdc.270990.

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