In total, 29 continuous Global Positioning System (GPS) time series data together with data from Gravity Recovery and Climate Experiment (GRACE) are analysed to determine the seasonal displacements of surface loadings in the North China Plain (NCP). Results show significant seasonal variations and a strong correlation between GPS and GRACE results in the vertical displacement component; the average correlation and weighted root-mean-squares (WRMS) reduction between GPS and GRACE are 75.6 and 28.9 % respectively, when atmospheric and non-tidal ocean effects were removed, but the annual peak-to-peak amplitude of GPS (1.2–6.3 mm) is greater than the data (1.0–2.2 mm) derived from GRACE. We also calculate the trend rate as well as the seasonal signal caused by the mass load change from GRACE data; the rate of GRACE-derived terrestrial water storage (TWS) loss (after multiplying by the scaling factor) in the NCP was 3.39 cm yr⁻¹ (equivalent to 12.42 km³ yr⁻¹) from 2003 to 2009. For a 10-year time span (2003 to 2012), the rate loss of TWS was 2.57 cm yr⁻¹ (equivalent to 9.41 km³ yr⁻¹), which is consistent with the groundwater storage (GWS) depletion rate (the rate losses of GWS were 2.49 and 2.72 cm yr⁻¹ during 2003–2009 and 2003–2012 respectively) estimated from GRACE-derived results after removing simulated soil moisture (SM) data from the Global Land Data Assimilation System (GLDAS)/Noah model. We also found that GRACE-derived GWS changes are in disagreement with the groundwater level changes from observations of shallow aquifers from 2003 to 2009, especially between 2010 and 2013. Although the shallow groundwater can be recharged from the annual climate-driven rainfall, the important facts indicate that GWS depletion is more serious in deep aquifers. The GRACE-derived result shows an overall uplift in the whole region at the 0.37–0.95 mm yr⁻¹ level from 2004 to 2009, but the rate of change direction is inconsistent in different GPS stations at the −0.40–0.51 mm yr⁻¹ level from 2010 to 2013. Then we removed the vertical rates, which are induced by TWS from GPS-derived data, to obtain the corrected vertical velocities caused by tectonic movement and human activities. The results show that there are uplift areas and subsidence areas in NCP. Almost the whole central and eastern region of NCP suffers serious ground subsidence caused by the anthropogenic-induced groundwater exploitation in the deep confined aquifers. In addition, the slight ground uplifts in the western region of NCP are mainly controlled by tectonic movement (e.g. Moho uplifting or mantle upwelling).

Artificial reservoirs are important indicators of anthropogenic impacts on environments, and their cumulative influences on the local water storage will change the gravity signal. However, because of their small signal size, such gravity changes are seldom studied using satellite gravimetry from the Gravity Recovery and Climate Experiment (GRACE). Here we investigate the ability of GRACE to detect water storage changes in the Longyangxia Reservoir (LR), which is situated in the upper main stem of the Yellow River. Three different GRACE solutions from the CSR, GFZ, and JPL with three different processing filters are compared here. We find that heavy precipitation in the summer of 2005 caused the LR water storage to increase by 37.9 m in height, which is equivalent to 13.0 Gt in mass, and that the CSR solutions with a DDK4 filter show the best performance in revealing the synthetic gravity signals. We also obtain 109 pairs of reservoir inundation area measurements from satellite imagery and water level changes from laser altimetry and in situ observations to derive the area‐height ratios for the LR. The root mean square of GRACE series in the LR is reduced by 39% after removing synthetic signals caused by mass changes in the LR or by 62% if the GRACE series is further smoothed. We conclude that GRACE data show promising potential in detecting water storage changes in this ∼400 km² reservoir and that a small signal size is not a restricting factor for detection using GRACE data.

The Three Gorges Reservoir (TGR) in China, with the largest dam in the world, stores a large volume of water and may influence the Earth’s gravity field on sub-seasonal to interannual timescales. Significant changes of the total water storage (TWS) might be detectable by satellite-based data provided by the Gravity Recovery and Climate Experiment (GRACE) mission. To detect these store water changes, effects of other factors are to be removed first from these data due to band-limited representation of near-surface mass changes from GRACE. Here, we evaluated three current popular land surface models (LSMs) basing on in situ measurements and found that the WaterGAP Global Hydrology Model (WGHM) demonstrates higher correlation than other analyzed models with the in-situ rainfall measurement. Then we used the WGHM outputs to remove climate-induced TWS changes, such as surface water storage, soil, canopy, snow, and groundwater storage. The residual results (GRACE minus WGHM) indicated a strong trend (3.85 ± 2 km³/yr) that is significantly higher than the TGR analysis and hindcast experiments (2.29 ± 1 km³/yr) based on in-situ water level measurements. We also estimated the seepage response to the TGR filling, contributions from other anthropogenic dams, and used in-situ gravity and GPS observations to evaluate dominant factors responsible for the GRACE-based overestimate of the TGR volume change. We found that the modeled seepage variability through coarse-grained materials explained most of the difference between the GRACE based estimate of TGR volume changes and in situ measurements, but the agreement with in-situ gravity observations is considerably lower. In contrast, the leakage contribution from 13 adjacent reservoirs explained ~74% of the TGR volume change derived from GRACE and WGHM. Our results demonstrate that GRACE-based overestimate TGR mass change mainly from the contribution of surrounding artificial reservoirs and underestimated TWS variations in WGHM simulations due to the large uncertainty of WGHM in groundwater component. In additional, this study also indicates that reservoir or lake volume changes can be reliably derived from GRACE data when they are used in combination with relevant complementary observations.

Terrestrial water storage (TWS) changes in the Tibetan Plateau (TP) are sensitive indicators for water dynamics associated with climate variability. Joint analyses using both GRACE space mission and satellite altimetry data are increasingly being used to monitor TWS. The objective of this study is to confirm that it is possible to reliably monitor water storage changes in large lakes based on integrative analysis of GRACE data. This study focuses on data integrated and analysed for Lake Qinghai located in the northeast TP, and shows a clear continuous water-level rise since 2004. We have developed a simple framework to estimate water storage variations in individual regions using a spatial averaging kernel, while simultaneously minimizing the effects resulting from uncertainties of GRACE data using Land Surface Models (LSMs) and in situ measurements. Water storage anomalies not related to lakes, such as soil moisture, snow and reservoirs, are estimated using GLDAS/Noah and reservoir gauge station for the period 2004–2012. Our results show that the rate of rise in mass of the GRACE-derived TWS (post GLDAS/Noah anomaly removal) is calculated to be 0.27 ± 0.12 cm yr⁻¹, or an average water-level increase rate of 0.20 ± 0.09 m yr⁻¹ after GRACE-derived TWS (i.e. 0.27 ± 0.12 cm yr⁻¹) multiplied by 1/1.34 to recover the ‘real’ mass variation signal using scaling factor method based on basin function from grids of Lake Qinghai from 2004 to 2012, which is equivalent to the volume change 0.86 ± 0.37 km³ yr⁻¹ and mainly caused by the fast expansion of Lake Qinghai (0.44 ± 0.04 km³ yr⁻¹ from altimetry/in situ measurements) and impoundment of Longyangxia reservoir (0.28 ± 0.17 km³ yr⁻¹ based on the linear height–volume relationship and in situ water-level observations). The residual signal (GRACE−GLDAS/Noah−reservoir−Lake Qinghai) likely reflects the mass leakage from the surrounding lakes in the regions (i.e. Har, Gyaring and Ngoring) and groundwater contributions (i.e. groundwater is not included in GLDAS/Noah) due to the limited spatial resolution of GRACE. The results suggest that the combined use of LSM and GRACE measurements is a useful method for monitoring changes in the mass of large lakes. Additionally, our analysis shows that it is necessary to improve LSM results with in situ forcing parameters and groundwater level data, which will reduce the uncertainty in the application of GRACE data. There is still a need to use complementary models or in situ observations to eliminate the influence of glacial isostatic adjustments and tectonic processes.

The Earth's mass redistribution due to deglaciation and recent ice sheet melting causes changes in the Earth's gravity field and vertical land motion in Greenland. The changes are because of ongoing mass redistribution and related elastic (on a short time scale) and viscoelastic (on time scales of a few thousands of years) responses. These signatures can be used to determine the mantle viscosity. In this study, we infer the mantle viscosity associated with the glacial isostatic adjustment (GIA) and long‐wavelength geoid beneath the Greenland lithosphere. The viscosity is determined based on a spatio‐spectral analysis of the Earth's gravity field and the land uplift rate in order to find the GIA‐related gravity field. We used different land uplift data, that is, the vertical land motions obtained by the Greenland Global Positioning System (GPS) Network (GNET), gravity recovery and climate experiment (GRACE) and glacial isostatic adjustment (GIA) data, and also combined them using the Kalman filtering technique. Using different land uplift rates, one can obtain different GIA‐related gravity fields. As shown in this study, the mantle viscosities of 1.9 × 10²² Pa s and 7.8 × 10²¹ Pa s for a depth of 200–700 km are obtained using ICE‐6G (VM5a) model and the combined land uplift model, respectively, and the GIA‐related gravity potential signal.