Xiongchuan Chen, Shuangcheng Zhang, Qingtao Zhang, Yong Fang, Guangwei Jiang, Ning Liu, Ningkang An, Jun Li, Chuhan Zhong, Ziheng Ju, Tianyou Wei. Unveiling hydrological drought patterns in coastal Texas through integrated GNSS and InSAR observationsJ. Geodesy and Geodynamics. DOI: 10.1016/j.geog.2026.06.008
Citation: Xiongchuan Chen, Shuangcheng Zhang, Qingtao Zhang, Yong Fang, Guangwei Jiang, Ning Liu, Ningkang An, Jun Li, Chuhan Zhong, Ziheng Ju, Tianyou Wei. Unveiling hydrological drought patterns in coastal Texas through integrated GNSS and InSAR observationsJ. Geodesy and Geodynamics. DOI: 10.1016/j.geog.2026.06.008

Unveiling hydrological drought patterns in coastal Texas through integrated GNSS and InSAR observations

  • Benefiting from significant advances in modern geodetic technologies, Global Navigation Satellite System (GNSS) measurements provide a new means to quantify terrestrial water storage (TWS) and to reveal hydrological-climate interaction mechanisms. This study integrates observational data from GNSS and Interferometric Synthetic Aperture Radar (InSAR), two advanced geodetic techniques, to jointly invert TWS variations in coastal Texas. The results reveal the spatiotemporal fluctuations of TWS and their linkage with large-scale drought and climate processes. Comparisons with GLDAS hydrological model outputs, GRACE-derived gravity solutions, and precipitation observations demonstrate strong consistency, while highlighting the higher spatial resolution and improved sensitivity of the joint inversion approach to local hydrological changes. The correlation coefficient between the TWS derived from the joint inversion of GNSS and InSAR and GRACE-EWH is 0.857, which is slightly higher than the value of 0.825 obtained with GLDAS-EWH. Our findings indicate pronounced seasonal variations in TWS across the study area and highlight the significant impact of drought events on regional hydrological conditions. By incorporating multi-source drought severity index (DSI) data, we further quantify wet and dry conditions, which align well with precipitation anomalies. These results provide a reliable observation and analysis framework for refined monitoring of coastal water cycle dynamics and for advancing the understanding of hydrological-climate interactions.
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