Estimation of Terrestrial Water Storage Variations in Sichuan-Yunnan Region from GPS Observations Using Independent Component Analysis

GPS can be used to measure land motions induced by mass loading variations on the Earth’s surface. This paper presents an independent component analysis (ICA)-based inversion method that uses vertical GPS coordinate time series to estimate the change of terrestrial water storage (TWS) in the Sichuan-Yunnan region in China. The ICA method was applied to extract the hydrological deformation signals from the vertical coordinate time series of GPS stations in the Sichuan-Yunnan region from the Crustal Movement Observation Network of China (CMONC). These vertical deformation signals were then inverted to TWS variations. Comparative experiments were conducted based on Gravity Recovery and Climate Experiment (GRACE) data and a hydrological model for validation. The results demonstrate that the TWS changes estimated from GPS(ICA) deformations are highly correlated with the water variations derived from the GRACE data and hydrological model in Sichuan-Yunnan region. The TWS variations are overestimated by the vertical GPS observations the northwestern Sichuan-Yunnan region. The anomalies are likely caused by inaccurate atmospheric loading correction models or residual tropospheric errors in the region with high topographic variability and can be reduced by ICA preprocessing.

Improving the Accuracy of Groundwater Storage Estimates Based on Groundwater Weighted Fusion Model

It is an effective measure to estimate groundwater storage anomalies (GWSA) by combining Gravity Recovery and Climate Experiment (GRACE) data and hydrological models. However, GWSA results based on a single hydrological model and GRACE data may have greater uncertainties, and it is difficult to verify in some regions where in situ groundwater-level measurements are limited. First, to solve this problem, a groundwater weighted fusion model (GWFM) is presented, based on the extended triple collocation (ETC) method. Second, the Shiyang River Basin (SYRB) is taken as an example, and in situ groundwater-level measurements are used to evaluate the performance of the GWFM. The comparison indicates that the correlation coefficient (CC) and Nash-Sutcliffe efficiency coefficient (NSE) are increased by 9–40% and 23–657%, respectively, relative to the original results. Moreover, the root mean squared error (RMSE) is reduced by 9–28%, which verifies the superiority of the GWFM. Third, the spatiotemporal distribution and influencing factors of GWSA in the Hexi Corridor (HC) are comprehensively analyzed during the period between 2003 and 2016. The results show that GWSA decline, with a trend of −2.37 ± 0.38 mm/yr from 2003 to 2010, and the downward trend after 2011 (−0.46 ± 1.35 mm/yr) slow down significantly compared to 2003–2010. The spatial distribution obtained by the GWFM is more reliable compared to the arithmetic average results, and GWFM-based GWSA fully retain the advantages of different models, especially in the southeastern part of the SYRB. Additionally, a simple index is used to evaluate the contributions of climatic factors and human factors to groundwater storage (GWS) in the HC and its different subregions. The index indicates that climate factors occupy a dominant position in the SLRB and SYRB, while human factors have a significant impact on GWS in the Heihe River Basin (HRB). This study can provide suggestions for the management and assessments of groundwater resources in some arid regions.

Gravity acceleration changes in Russian stations of comparing absolute gravimeters

The article deals with the study of changes in the values of gravitational accelerations at the Russian comparison’s sites of the absolute gravimeters “Pulkovo”, “Svetloye” and “Zvenigorod” for the years of 2007–2013. A significant increase of the values instead of the expected decrease was obtained. The authors make an attempt to reveal the reasons for that basing on the calculation of the change in the gravitational field using the Bouguer and Faye corrections. The estimates do not fully explain the phenomenon, according neither to gravimeters nor to satellite data. At the sites of “Pulkovo” and “Svetloye”, the measured changes in the values differ from the calculated ones by +5,7 and 6,6 μGal, which significantly exceeds the errors of the absolute gravimeters. The change of the gravity varies from satellites GRACE data by 9,4 μGal at the “Zvenigorod” site. This may be due to local hydrological reasons. Determining the causes of gravity changes at the absolute stations of gravity network is an urgent task.

A Spatial Downscaling Methodology for GRACE Total Water Storage Anomalies Using GPM IMERG Precipitation Estimates

A downscaling framework for coarse resolution Gravity Recovery and Climate Experiment (GRACE) Total Water Storage Anomaly (TWSA) data is described, exploiting the observations of precipitation from the Global Precipitation Measurement (GPM) mission, using the Integrated Multi-satellite Retrievals for GPM (IMERG). Considering that the major driving force for changes in TWS is precipitation, we tested our hypothesis that coarse resolution, i.e., 1°, GRACE TWSA can be effectively downscaled to 0.1° using GPM IMERG data. The algorithm for the downscaling process comprises the development of a regression equation at the coarse resolution between the GRACE and GPM IMERG data, which is then applied at the finer resolution with a subsequent residual correction procedure. An ensemble of GRACE data from three processing centers, i.e., GFZ, JPL and CSR, was used for the time period from June 2018 until March 2021. To verify our downscaling methodology, we applied it with GRACE data from 2005 to 2015, and we compared it against modeled TWSA from two independent datasets in the Thrace and Thessaly regions in Greece for the same period and found a high performance in all examined metrics. Our research indicates that the downscaled GRACE observations are comparable to the TWSA estimated with hydrological modeling, thus highlighting the potential of GRACE data to contribute to the improvement of hydrological model performance, especially in ungauged basins.

Studying recent hydroclimatic variability in Madagascar despite deficient measurement networks: use of CHIRPS and GRACE data at the scale of the Mahajunga province

Given the lack of in situ hydroclimatic measurements and networks in Madagascar, the GRACE (2003–2016) spatial gravimetry data, combined with other satellite data such as CHIRPS rainfall estimates or fire monitoring using GFED products, make it possible to establish an interannual assessment of certain climatic and environmental covariations at the northwest scale of the country. The results show a negative trend in continental rainfall and water content, especially after 2007, but also a time lag in the linear variations and trends of the Water Equivalent Height as well as the number of detected fires (variable indirectly measuring the pressure of deforestation by slash and burn agriculture).

Using GRACE Data to Estimate Climate Change Impacts on the Earth’s Moment of Inertia

The widely used 15-year Gravity Recovery and Climate Experiment (GRACE) measured mass redistribution shows an increasing trend in the nontidal Earth’s moment of inertia (MOI). Various contributing components are independently evaluated using five high-quality atmospheric reanalysis datasets and a novelty numerical modeling system. We found a steady, statistically robust (passed a two-tailed t-test at p = 0.04 for dof = 15) rate of MOI increase reaching ∼11.0 × 1027 kg m2/yr, equivalent to a 11.45 sμ/yr increase in the length of day, during 2002–2017. Further analysis suggests that the Antarctic ice sheet contributes the most, followed by the Greenland ice sheet, the precipitation-driven land hydrological cycle, mountain glaciers, and the fluctuation of atmosphere, in this order. Short-term MOI spikes from the GRACE measurements are mostly associated with major low/mid-latitude earthquakes, fitting closely with the MOI variations from the hydrological cycle. Atmospheric fluctuation contributes the least but has a steady trend of 0.5 sμ/yr, with horizontal mass distribution contributing twice as much as the vertical expansion and associated lift of the atmosphere’s center of mass. The latter is a previously overlooked term affecting MOI fluctuation. The contribution to the observed MOI trend from a warming climate likely will persist in the future, largely due to the continuous mass loss from the Earth’s ice sheets.

Improving the Resolution of GRACE Data for Spatio-Temporal Groundwater Storage Assessment

Groundwater has a significant contribution to water storage and is considered to be one of the sources for agricultural irrigation; industrial; and domestic water use. The Gravity Recovery and Climate Experiment (GRACE) satellite provides a unique opportunity to evaluate terrestrial water storage (TWS) and groundwater storage (GWS) at a large spatial scale. However; the coarse resolution of GRACE limits its ability to investigate the water storage change at a small scale. It is; therefore; needed to improve the resolution of GRACE data at a spatial scale applicable for regional-level studies. In this study; a machine-learning-based downscaling random forest model (RFM) and artificial neural network (ANN) model were developed to downscale GRACE data (TWS and GWS) from 1° to a higher resolution (0.25°). The spatial maps of downscaled TWS and GWS were generated over the Indus basin irrigation system (IBIS). Variations in TWS of GRACE in combination with geospatial variables; including digital elevation model (DEM), slope; aspect; and hydrological variables; including soil moisture; evapotranspiration; rainfall; surface runoff; canopy water; and temperature; were used. The geospatial and hydrological variables could potentially contribute to; or correlate with; GRACE TWS. The RFM outperformed the ANN model and results show Pearson correlation coefficient (R) (0.97), root mean square error (RMSE) (11.83 mm), mean absolute error (MAE) (7.71 mm), and Nash–Sutcliffe efficiency (NSE) (0.94) while comparing with the training dataset from 2003 to 2016. These results indicate the suitability of RFM to downscale GRACE data at a regional scale. The downscaled GWS data were analyzed; and we observed that the region has lost GWS of about −9.54 ± 1.27 km3 at the rate of −0.68 ± 0.09 km3/year from 2003 to 2016. The validation results showed that R between downscaled GWS and observational wells GWS are 0.67 and 0.77 at seasonal and annual scales with a confidence level of 95%, respectively. It can; therefore; be concluded that the RFM has the potential to downscale GRACE data at a spatial scale suitable to predict GWS at regional scales.

Reduced misclosure of global sea-level budget with updated Tongji-Grace2018 solution

The global sea-level budget is studied using the Gravity Recovery and Climate Experiment (GRACE) solutions, Satellite Altimetry and Argo observations based on the updated budget equation. When the global ocean mass change is estimated with the updated Tongji-Grace2018 solution, the misclosure of the global sea-level budget can be reduced by 0.11–0.22 mm/year compared to four other recent solutions (i.e. CSR RL06, GFZ RL06, JPL RL06 and ITSG-Grace2018) over the period January 2005 to December 2016. When the same missing months as the GRACE solution are deleted from altimetry and Argo data, the misclosure will be reduced by 0.06 mm/year. Once retained the GRACE C20 term, the linear trends of Tongji-Grace2018 and ITSG-Grace2018 solutions are 2.60 ± 0.16 and 2.54 ± 0.16 mm/year, closer to 2.60 ± 0.14 mm/year from Altimetry–Argo than the three RL06 official solutions. Therefore, the Tongji-Grace2018 solution can reduce the misclosure between altimetry, Argo and GRACE data, regardless of whether the C20 term is replaced or not, since the low-degree spherical harmonic coefficients of the Tongji-Grace2018 solution can capture more ocean signals, which are confirmed by the statistical results of the time series of global mean ocean mass change derived from five GRACE solutions with the spherical harmonic coefficients truncated to different degrees and orders.