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

The research was conducted in small mountainous region of west-central Yunnan province, China. 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. 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. • GNSS and InSAR data are jointly used to estimate TWSA at small regional scales. • Spatio-temporal Kalman filtering enhances vertical displacement signals at high precision. • The estimated TWSA aligns well with GRACE data and offers finer spatial resolution (0.25° × 0.25°).