Estimation of daily hydrological mass changes using continuous GNSS measurements in mainland China

• Published in: Journal of hydrology (Amsterdam) Vol. 598; p. 126349
• Main Authors: Jiang, Zhongshan, Hsu, Ya-Ju, Yuan, Linguo, Cheng, Shuai, Li, Qinzheng, Li, Meng
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.07.2021
• Subjects: GNSS; Hydrological dynamics; Seasonal water oscillations; Slepian basis functions; Terrestrial water storage; Slepian basis functions; Hydrological dynamics; Terrestrial water storage; Seasonal water oscillations; GNSS
• ISSN: 0022-1694; 1879-2707
• DOI: 10.1016/j.jhydrol.2021.126349

•Daily water storage anomalies are recovered based on the Slepian basis functions.•A sparse GNSS array provides a novel tool to monitor large-scale hydrologic changes.•GNSS is more sensitive to the seasonal characteristic of water storage variations.•Geodetic and hydrological data show significant water variations in southwest China.•GNSS-based standardized water anomalies allow for quantifying hydrological severity. Surface displacements measured by the Global Navigation Satellite System (GNSS) integrate the elastic response of the solid Earth to regional and local hydrologic loading signals and provide an opportunity for near-real-time monitoring of terrestrial water storage variations. Here, we estimate the spectral information of hydrology-induced vertical surface deformation based on spherical Slepian basis functions and recover the daily changes in continental water storage over mainland China from January 2010 to December 2019. Our inversion results, depending on a sparsely-distributed GNSS network, indicate the largest seasonal fluctuation of hydrological mass loads in southwestern China. The GNSS-inferred equivalent water height has an annual amplitude of up to 314 mm, which is greater than 243 mm from the Gravity Recovery and Climate Experiment (GRACE) and 150 mm from the Global Land Data Assimilation System (GLDAS). We also find notable seasonal water oscillations of 153–166 mm in the middle and lower Yangtze River Basin. This feature appears in the GNSS inversion model and GRACE Mascon solutions but is invisible in the GLDAS model, mostly indicating the existence of significant changes in surface water storage that is unmodeled in the GLDAS model. There is board agreement in the water estimates derived from multiple data sets in South China, in contrast to weak temporal coherence of various water estimates in North China. We also demonstrate the ability of GNSS for tracking the drought and wet periods, which can serve as an independent means to characterize hydrological extremes. Our study emphasizes that a sparse GNSS network can still be considered as a complementary tool to map large-scale spatiotemporal variations of water storage and benefit the hydrological community for assessing water storage changes and hydrological dynamics.