The Tibetan Plateau (TP) formed due to the collision between the Indian Plate and the Eurasian Plate (Molnar & Tapponnier, 1975), and it remains one of the most tectonically active regions in the world. Numerous studies have focused on the collision, uplift, and extension of the TP and their relationships to geodynamic processes (

The uplift state of the Tibetan Plateau (TP) is determined by tectonic displacement and hydrological load displacement. However, it is unknown how much the load effect contributes to the uplift of the plateau. Typically, the vertical displacement due to the mass load is calculated based on the Gravity Recovery and Climate Experiment (GRACE) data and the spherical harmonic analysis method. However, because the GRACE data are truncated at lower harmonic degrees and tectonic mass changes are contained in the GRACE‐derived mass changes, the validity of using GRACE data to estimate the load displacement of the TP is questionable and needs further discussion. This study presents a reasonable approach to computing the loading effect by considering the global hydrological mass budget (seawater, lake, glacier, river, snow, soil water, canopy water, and groundwater). The TP's mean vertical load displacement rate we obtained is 0.15 mm/yr, contributing to 16 percent of the average TP uplift rate. Comparing the hydrologically computed load displacements and the GRACE‐derived load displacements indicates that the GRACE‐derived displacement differs significantly from the real hydrological load displacement. That is, we found that the GRACE‐derived load effect cannot be applied to correct the Global Positioning System (GPS) displacement, but the one computed with hydrological data works well. We claim that the load displacement effect for any GPS station should be calculated by Green's function method based on global hydrological data. Finally, we present a distribution map of the valid load vertical displacement of the TP and the load displacement correction for all the collected GPS stations.

The spatial distribution of the transfer signals due to nonhydrological mass in mainland China was obtained by subtracting the combined hydrological model from the GRACE time-variable gravity field.q Further studied and discussed the spatial distribution characteristics and mechanism of the nonhydrological mass transfer signals of mainland China.

The gravity recovery and climate experiment (GRACE) and its Follow‐On mission provide a versatile tool for monitoring groundwater depletion in North China Plain (NCP). However, intermittent data gaps and inherent coarse spatial resolution have restricted the continuous detection of regional groundwater storage anomaly (GWSA) after 2014, the period of interest during the implementation of the south‐to‐north water diversion middle route project (SNWDP). Here, we investigated the spatiotemporal changes of GWSA in the NCP during 2004 to 2020 based on continuous downscaled GRACE data. First, we derived the continuous terrestrial water storage anomaly from six GRACE and Follow‐On solutions (i.e., spherical harmonics (SH) and mass concentration [mascon] solutions). Second, we employed a long short‐term memory (LSTM) model and water balance equation to downscale GWSA (i.e., 0.25° × 0.25°). Lastly, we investigated its spatiotemporal characteristics before (2004 to 2014) and after (2015 to 2020) the SNWDP operation. We show the applicability of the continuous downscaled GWSA to capture the characteristics of in situ measurements. The GWSA detects groundwater depletion at a significant (p < 0.05) rate of −17.09 ± 1.80 (SH) and −17.87 ± 1.65 (mascon) mm/a during 2004 to 2014, but a recovering trend of 7.18 ± 3.98 (SH) and 8.23 ± 4.99 (mascon) during 2015 to 2018. The subsequent groundwater extraction and precipitation reduction from 2019 to 2020, resulted in the decreasing trend of GWSA from 2015 to 2020, which is −19.11 ± 8.75 (SH) and −19.72 ± 9.08 mm/a (mascon), respectively. Spatially, the overall depletion trends become nonsignificant along the canals of SNWDP compared to the period 2004 to 2014, and groundwater recovering with trends <6 mm/a near Beijing and Tianjin are detected by the mascon solution during 2015 to 2020.

Summary To obtain the deformation of the solid Earth from a global navigation satellite system (GNSS)-observed velocity field, the loading effect of the surface mass variations should be effectively deducted. However, the GNSS-observed velocity field in mainland China is currently only limited to the loading correction calculated using Gravity Recovery and Climate Experiment (GRACE) spherical harmonic coefficients, which is equivalent to the approximately 300-km smoothed result in the spatial domain, and thus, the derived tectonic deformation is inaccurate. Therefore, it is important to study and identify a reasonable method for calculating the loading effect of the surface mass change model and to carry out an effective loading correction of the GNSS velocity field. In this study, the performances of two calculation methods, namely the GRACE spherical harmonic coefficient and Green's function, were analyzed and compared. In addition, we constructed a comprehensive model of the global surface mass variations, calculated the vertical load velocity in mainland China using Green's function method, and compared the results with those for the GRACE spherical harmonic products. We found that the difference between the results of the GRACE spherical harmonic coefficient and Green's function methods was more than 1 mm/yr in the North China Plain, implying that the GRACE spherical harmonic coefficient method cannot be used for loading correction of the observed GNSS vertical velocity field. In contrast, the loading effect calculated using Green's function method can be more effectively applied for loading correction of the GNSS vertical velocity field in mainland China. The GNSS-observed velocity exhibited a clear uplift in the North China Plain and the west glacier areas; however, the GNSS velocity fields were significantly reduced after the loading correction, indicating that the observed GNSS vertical velocity fields were mainly caused by the surface mass loading due to the negative correlation between the vertical load velocity and the surface mass changes. Moreover, we found that the loading correction accounted for more than 50% of the GNSS vertical velocity field in most of the glaciated regions in eastern and western China, and the maximum value exceeded 300%, indicating that the loading effect was large. Finally, we obtained the GNSS vertical velocity field for mainland China with a loading correction. Additionally, the spectral characteristics of the time-varying gravity field in mainland China were investigated. The results showed that clear annual, semi-annual, and 10-year medium- and long-period signals exist.