Joint Inversion of InSAR and GNSS for surface subsidence and terrestrial water storage anomalies of small-area in west-central Yunnan Province, China

Study region: The research was conducted in small mountainous region of west-central Yunnan province, China. Study focus: In response to the need for accurate small-area TWSA estimation, this study integrates Global Navigation Satellite System (GNSS) data and Time Series Synthetic Aperture Radar (TS...

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Bibliographic Details
Main Authors: Ming Shangguan, Jingyi Guo, Shuguang Wu, Xu Zhou, Rong Zou, Xin Zhang
Format: Article
Language:English
Published: Elsevier 2025-06-01
Series:Journal of Hydrology: Regional Studies
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Online Access:http://www.sciencedirect.com/science/article/pii/S2214581825002666
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Summary:Study region: The research was conducted in small mountainous region of west-central Yunnan province, China. Study focus: In response to the need for accurate small-area TWSA estimation, this study integrates Global Navigation Satellite System (GNSS) data and Time Series Synthetic Aperture Radar (TS-InSAR) to quantify TWSA for 2019–2020. High spatio-temporal resolution surface deformation data are essential for small-area TWSA estimation, and the fusion of GNSS and TS-InSAR observations using a spatio-temporal Kalman filter (STKF) model enables the derivation of precise vertical deformation. The equivalent water height is then estimated using a water volume inversion model to analyze the spatio-temporal variations of TWSA and investigate the underlying influencing factors. New hydrological insights for the region: The results demonstrate that the STKF significantly enhances data accuracy by 3.43 mm, leading to reliable TWSA predictions. The estimated TWSA show a strong correlation of 0.87 with Gravity Recovery and Climate Experiment (GRACE) products, validating the effectiveness of the proposed approach. Additionally, the study reveals the influence of terrain, precipitation, and vegetation on TWSA variations. Compared to existing TWSA products, the method presented in this study provides a novel approach for calculating high-resolution TWSA, offering valuable insights for water resource management.
ISSN:2214-5818