Search Results (35)

The Qinghai–Tibet Plateau (QTP), a critical hydrological regulator for Asia through its extensive glacier systems, high-altitude lakes, and intricate network of rivers, exhibits amplified sensitivity to climate-driven alterations in precipitation regimes and ice mass balance. While the Gravity Recovery and Climate Experiment (GRACE) and its Follow-On (GRACE-FO) missions have revolutionized monitoring of terrestrial water storage anomalies (TWSAs) across this hydrologically sensitive region, spatial resolution limitations (3°, equivalent to ~300 km) constrain process-scale analysis, compounded by mission temporal discontinuity (data gaps). In this study, we present a novel downscaling framework integrating temporal gap compensation and spatial refinement to a 0.25° resolution through Gated Recurrent Unit (GRU) neural networks, an architecture optimized for univariate time series modeling. Through the assimilation of multi-source hydrological parameters (glacier mass flux, cryosphere–precipitation interactions, and land surface processes), the GRU-based result resolves nonlinear storage dynamics while bridging inter-mission observational gaps. Grid-level implementation preserves mass conservation principles across heterogeneous topographies, successfully reconstructing seasonal-to-interannual TWSA variability and also its long-term trends. Comparative validation against GRACE mascon solutions and process-based hydrological models demonstrates enhanced capacity in resolving sub-basin heterogeneity. This GRU-derived high-resolution TWSA is especially valuable for dissecting local variability in areas such as the Brahmaputra Basin, where complex water cycling can affect downstream water security. Our study provides transferable methodologies for mountainous hydrogeodesy analysis under evolving climate regimes. Future enhancements through physics-informed deep learning and next-generation climatology–hydrology–gravimetry synergy (e.g., observations and models) could further constrain uncertainties in extreme elevation zones, advancing the predictive understanding of Asia’s water tower sustainability. Full article

The monitoring of Poyang Lake water area and storage changes using remote sensing and satellite gravimetry techniques is valuable for maintaining regional water resource security and addressing the challenges of global climate change. In this study, remote sensing datasets from Landsat images (Landsat 5, 7, 8 and 9) and three Gravity Recovery and Climate Experiment (GRACE) and Gravity Follow-on (GRACE-FO) mascon solutions were jointly used to evaluate the water area and storage changes in response to global and regional climate changes. The results showed that seasonal characteristics existed in the terrestrial water storage (TWS) and water area changes of Poyang Lake, with nearly no significant long-term trend, for the period from April 2002 to December 2022. Poyang Lake exhibited the largest water area in June and July every year and then demonstrated a downward trend, with relatively smaller water areas in January and November, confirmed by the estimated TWS changes. For the flood (August 2010) and drought (September 2022) events, the water area changes are 3032 km² and 813.18 km², with those estimated TWS changes 17.37 cm and −17.46 cm, respectively. The maximum and minimum Poyang Lake area differences exceeded 2700 km². The estimated terrestrial water storage changes in Poyang Lake derived from the three GRACE/GRACE-FO mascon solutions agreed well, with all correlation coefficients higher than 0.92. There was a significant positive correlation higher than 0.75 between the area and TWS changes derived from the two independent monitoring techniques. Therefore, it is reasonable to conclude that combined remote sensing with satellite gravimetric techniques can better interpret the response of Poyang Lake to climate change from the aspects of water area and TWS changes more efficiently. Full article

Over the past two decades, the Gravity Recovery and Climate Experiment (GRACE) satellite mission and its successor, GRACE-follow on (GRACE-FO), have played a vital role in climate research. However, the absence of certain observations during and between these missions has presented a persistent challenge. Despite numerous studies attempting to address this issue with mathematical and statistical methods, no definitive optimal approach has been established. This study introduces a practical solution using Linear Regression Analysis (LRA) to overcome data gaps in both GRACE data types—mascon and spherical harmonic coefficients (SHCs). The proposed methodology is tailored to monsoon patterns and demonstrates efficacy in filling data gaps. To validate the approach, a global analysis was conducted across eight basins, monitoring changes in total water storage (TWS) using the technique. The results were compared with various geodetic products, including data from the Swarm mission, Institute of Geodesy and Geoinformation (IGG), Quantum Frontiers (QF), and Singular Spectrum Analysis (SSA) coefficients. Artificial data gaps were introduced within GRACE observations for further validation. This research highlights the effectiveness of the monsoon method in comparison to other gap-filling approaches, showing a strong similarity between gap-filling results and GRACE’s SHCs, with an absolute relative error approaching zero. In the mascon approach, the coefficient of determination (R²) exceeded 91% for all months. This study offers a readily usable gap-filling product—SHCs and smoothed gridded observations—with accurate error estimates. These resources are now accessible for a wide range of applications, providing a valuable tool for the scientific community. Full article

The availability of water is crucial for the growth and sustainability of human development. The effective management of water resources is essential due to their renewable nature and their critical role in ensuring food security and water safety. In this study, the multi-step-ahead modeling approach of the Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage (TWS) was utilized to gain insights into and forecast the fluctuations in water resources within Saudi Arabia. This study was conducted using mascon solutions obtained from the University of Texas Center for Space Research (UT-CSR) over the period of 2007 to 2017. The data were used in the development of artificial intelligence models, namely, an Elman neural network (ENN), a backpropagation neural network (BPNN), and kernel support vector regression (k-SVR). These models were constructed using various input variables, such as t-12, t-24, t-36, t-48, and TWS, with the output variable being the focus. A simple and weighted average ensemble was introduced to improve the accuracy of marginal and weak predictive results. The performance of the models was assessed with the use of several evaluation metrics, including mean absolute error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE), correlation coefficient (CC), and Nash–Sutcliffe efficiency (NSE). The results of the estimate indicate that k-SVR-M1 (NSE = 0.993, MAE = 0.0346) produced favorable outcomes, whereas ENN-M3 (NSE = 0.6586, MAE = 0.6895) emerged as the second most effective model. The combinations of all other models exhibited accuracies ranging from excellent to marginal, rendering them unreliable for decision-making purposes. Error ensemble methods improved the standalone model and proved merit. The results also serve as an important tool for monitoring changes in global water resources, aiding in drought management, and understanding the Earth’s water cycle. Full article

The GRACE twin satellite gravity mission from 2002 to 2017 has considerably improved investigations on global and regional hydrological changes. However, there are different GRACE solutions and products available which may yield different results for certain regions despite applying the same postprocessing and time span. This is especially the case for the Tibetan Plateau (TP) with its special hydrological conditions represented by localized but strong signals that can overlap or merge with signals inside the plateau, which can falsify the determination of terrestrial water storage (TWS) changes in the TP area. To investigate the effect of GRACE solution selection on inverted TWS changes, we analyze quantitatively the secular and monthly changes for 14 glacier areas and 10 water basins in and around the TP area that have been calculated from 16 different available GRACE solutions. Our analysis provides expectable results. While trend results from different spherical harmonic (SH) GRACE solutions match well, there are significant differences to and between mascon GRACE solutions. This is related to the different processing concepts of mascon solutions and their forced handling in our comparisons. SH solution time series match each other when mass changes are strong with a large amplitude and regular periodicity. However, for regions where small TWS changes are associated with small amplitudes, trends, and/or unstable signal periods, SH solutions can also yield different results. Such behavior is known from a time series analysis. Interestingly though, we find that the COST-G and ITSG SH GRACE solutions are closest to the average of all solutions. Therefore, these solutions appear to be preferable for TWS investigations in regions with highly variable hydrological conditions, such as in the Tibetan Plateau and its surroundings. This also indicates that combined solutions such as COST-G provide a promising pathway for an improved TWS analysis, which should be further elaborated. Full article

The extent to which the South-to-North Water Transfer Project has influenced the trend in water storage deficit in the North China Plain since its official opening in late 2014 has not been systematically assessed. We evaluated the changes in terrestrial water storage (TWS) in the North China Plain based on the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-on (GRACE-FO) long-term gravity satellite observations from 2002 to 2022, using spherical harmonic (SH) solutions from the Center for Space Research (CSR), GeoForschungsZentrum (GFZ), Jet Propulsion Laboratory (JPL), and Mass Concentration (Mascon) solutions from CSR, Goddard Space Flight Center (GSFC), JPL, and compared with the South-to-North Water Transfer water supply (13.91 Gt/a). The CSR-SH solution that best matched the water supply was selected, and it was found that the rate of change in TWS in the North China Plain from 2002 to 2015 was (−8.48 ± 1.87) Gt/a, and the rate of change from 2015 to 2019 increased significantly to (5.44 ± 4.87) Gt/a, indicating that the TWS in the plain changed from deficit to gain. The South-to-North Water Transfer Project has played a positive role in significantly improving the water stress situation in North China. Simultaneously, by comparing the inversions of six time-varying gravity field models (CSR-SH, GFZ-SH, JPL-SH, CSR-Mascon, GSFC-Mascon, and JPL-Mascon) with the South-to-North Water Transfer water supply and measured groundwater well data, and by calculating the uncertainty using the ‘three-cornered hat method’ (TCH), a comprehensive comparison is made to conclude that the CSR-SH model is most effective with a minimum difference of 0.01 Gt/a from the annual water supply, a minimum difference of 0.04 Gt/a from the measured well data, and a small uncertainty of 3.04 cm. This study reveals the important impact of the South-to-North Water Transfer Project on TWS in the North China Plain, which is of reference value for water resource management decisions in China. Full article

The Gravity Recovery and Climate Experiment (GRACE), and its follow-on mission (GRACE-FO), provides a novel measurement of the variations in ocean bottom pressure (OBP) at global and basin scales, including those in marginal seas. However, these measurements have not yet been validated rigorously for the South China Sea (SCS). In this study, the accuracy in the monthly GRACE-FO mascon solutions in the SCS from the Jet Propulsion Laboratory (JPL), Center for Space Research (CSR), and Goddard Space Flight Center (GSFC) was validated with the results of the comparison with the in situ OBP records from an array of 25 pressure-recording inverted echo sounders (PIESs) that are located west of the Luzon Strait (LS). The correlation coefficient (Cor) and root mean square difference (RMSD) between the 10-month period of GSFC and PIES, spanning from July 2018 to June 2019 (with missing satellite data for August and September 2018), were 0.77 (p-value = 0.005) and 0.41 mbar (1 mbar = 100 Pa), respectively. These values suggest that the accuracy of GSFC in the SCS in this period was substantially better than that of JPL (Cor = 0.35, p-value = 0.16; RMSD = 0.74 mbar) and CSR (Cor = 0.25, p-value = 0.24; RMSD = 0.89 mbar). Moreover, the volume transport anomaly of the SCS abyssal circulation was estimated and compared based on the OBP records from GSFC and PIES observations, indicating that the GRACE-FO OBP (GSFC) can be used to monitor seasonal or longer-period variations in the SCS abyssal volume transport. Additionally, the variations in OBP from GRACE-FO were significantly overestimated on the continental shelf of the SCS, which may be attributed to signal leakage. Our findings provide reliable evidence for the application of long-term, fully covered OBP records from GRACE-FO in the SCS, and also offer a valuable reference for the application of GRACE-FO in other regions. Full article

We compute the vertical displacements in the Amazon Basin using the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) observations, including both the gravity spherical harmonic (SH) solutions from the Center for Space Research (CSR), GeoForschungsZentrum (GFZ) and Jet Propulsion Laboratory (JPL) and mascons from CSR, JPL and Goddard Space Flight Center (GSFC). The correlation coefficients, annual amplitude and root mean squares (RMS) reductions are calculated to assess the agreements between the GRACE/GRACE-FO and Global Navigation Satellite System (GNSS) vertical displacements at 22 selected GNSS stations. For the six GRACE/GRACE-FO products (i.e., CSR SH, GFZ SH, JPL SH, CSR mascon, GSFC mascon and JPL mascon), the mean annual amplitude reductions are 77.6%, 76.4%, 76.3%, 78.6%, 78.5% and 76.6%, respectively, the corresponding mean RMS reductions are 63.2%, 61.7%, 62.3%, 64.9%, 65.3% and 63.8%, respectively, and the mean correlation coefficients are all over 0.93. On the whole, mascon solutions agree slightly better with GNSS solutions than SH solutions do. The CSR SH and the GSFC mascon solutions show the best agreements with the GNSS solution among the 3 SH and 3 mascon products, respectively. We estimate GRACE/GRACE-FO noises using the three-cornered hat (TCH) method and find that the CSR SH and GSFC mascons also have the smallest noise variances among the SH and mascon products, respectively. By analyzing the GNSS stations from the central and southern Amazon Basin, we find that: (1) the RMS reductions when the mascon solutions are removed from GNSS height series are slightly larger than those using the SH solutions in the center, while in south all the RMS reductions are fairly close; (2) for both SH solutions and mascon solutions, the correlation coefficients in the center are slightly larger than those in the south, but conversely, the mean annual amplitude reductions in the center are much smaller than those in the south. Full article

One of the areas that show the most visible effects of human-induced land alterations is also the world’s most essential resource: water. Decision-makers in arid regions face considerable difficulties in providing and maintaining sustainable water resource management. However, developing appropriate and straightforward approaches for quantifying water use in arid/hyper-arid regions is still a formidable challenge. Meanwhile, a better knowledge of the effects of land use land cover (LULC) changes on natural resources and environmental systems is required. The purpose of this study was to quantify the water consumption in a hyper-arid region (New Valley, Egypt) using two different approaches—LULC based on optical remote sensing data and groundwater storage changes based on Gravity Recovery Climate Experiment (GRACE) satellite data—and to compare and contrast the quantitative results of the two approaches. The LULC of the study area was constructed from 1986 to 2021 to identify the land cover changes and investigate the primary water consumption patterns. The analysis of groundwater storage changes utilized two GRACE mascon solutions from 2002 to 2021 in New Valley. The results showed an increase in agricultural areas in New Valley’s oases. They also showed an increased in irrigation water usage and a continuous decrease in the groundwater storage of New Valley. The overall water usage in New Valley for domestic and irrigation was calculated as 18.62 km³ (0.93 km³/yr) based on the LULC estimates. Moreover, the groundwater storage changes of New Valley were extracted using GRACE and calculated to be 19.36 ± 7.96 km³ (0.97 ± 0.39 km³/yr). The results indicated that the water use calculated from LULC was consistent with the depletion in groundwater storage calculated by applying GRACE. This study provides an essential reference for regional sustainability and water resource management in arid/hyper-arid regions. Full article

Time series of the Gravity Recovery and Climate Experiment (GRACE) satellite mission have been successfully used to reveal changes in terrestrial water storage (TWS) in many parts of the world. This has been hindered in the interior of the Tibetan Plateau since the derived TWS changes there are very sensitive to the selections of different available GRACE solutions, and filters to remove north-south-oriented (N-S) stripe features in the observations. This has resulted in controversial distributions of the TWS changes in previous studies. In this paper, we produce aggregated hydrology signals (AHS) of TWS changes from 2003 to 2009 in the Tibetan Plateau and test a large set of GRACE solution-filter combinations and mascon models to identify the best combination or mascon model whose filtered results match our AHS. We find that the application of a destriping filter is indispensable to remove correlated errors shown as N-S stripes. Three best-performing destriping filters are identified and, combined with two best-performing solutions, they represent the most reliable solution-filter combinations for determination of weak terrestrial water storage changes in the interior of the Tibetan Plateau from GRACE. In turn, more than 100 other tested solution-filter combinations and mascon solutions lead to very different distributions of the TWS changes inside and outside the plateau that partly disagree largely with the AHS. This is mainly attributed to less effective suppression of N-S stripe noises. Our results also show that the most effective destriping is performed within a maximum degree and order of 60 for GRACE spherical harmonic solutions. The results inside the plateau show one single anomaly in the TWS trend when additional smoothing with a 340-km-radius Gaussian filter is applied. We suggest using our identified best solution-filter combinations for the determination of TWS changes in the Tibetan Plateau and adjacent areas during the whole GRACE operation time span from 2002 to 2017 as well as the succeeding GRACE-FO mission. Full article

The Gravity Recovery and Climate Experiment (GRACE) satellite solutions have been considerably applied to assess the reliability of hydrological models on a global scale. However, no single hydrological model can be suitable for all regions. Here, a New Statistical Correction Hydrological Model Weighting (NSCHMW) method is developed based on the root mean square error and correlation coefficient between hydrological models and GRACE mass concentration (mascon) data. The NSCHMW method can highlight the advantages of good models compared with the previous average method. Additionally, to verify the effect of the NSCHMW method, taking the Haihe River Basin (HRB) as an example, the spatiotemporal patterns of Terrestrial Water Storage Anomalies (TWSA) in HRB are analyzed through a comprehensive comparison of decadal trends (2003–2014) from GRACE and different hydrological models (Noah from GLDAS-2.1, VIC from GLDAS-2.1, CLSM from GLDAS-2.1, CLSM from GLDAS-2.0, WGHM, PCR-GLOBWB, and CLM-4.5). Besides, the NSCHMW method is applied to estimate TWSA trends in the HRB. Results demonstrate that (1) the NSCHMW method can improve the accuracy of TWSA estimation by hydrological models; (2) the TWSA trends continue to decrease through the study period at a rate of 15.7 mm/year; (3) the WGHM and PCR-GLOBWB have positive reliability with respect to GRACE with r > 0.9, while all the other models underestimate TWSA trends; (4) the NSCHMW method can effectively improve RMSE, NES, and r with 3–96%, 35–282%, 1–255%, respectively, by weighting the WGHM and PCR-GLOBWB. Indeed, groundwater depletion in HRB also proves the necessity of the South-North Water Diversion Project, which has already contributed to groundwater recovery. Full article

Dense Global Position System (GPS) arrays can be used to invert the terrestrial water-storage anomaly (TWSA) with higher accuracy. However, the uneven distribution of GPS stations greatly limits the application of GPS to derive the TWSA. Aiming to solve this problem, we grid the GPS array using regression to raise the reliability of TWSA inversion. First, the study uses the random forest (RF) model to simulate crustal deformation in unobserved grids. Meanwhile, the new Machine-Learning Loading-Inverted Method (MLLIM) is constructed based on the traditional GPS derived method to raise the truthfulness of TWSA inversion. Second, this research selects southwest China as the study region, the MLLIM and traditional GPS inversion methods are used to derive the TWSA, and the inverted results are contrasted with datasets of the Gravity Recovery and Climate Experiment (GRACE) Mascon and the Global Land Data Assimilation System (GLDAS) model. The comparison shows that values of Pearson Correlation Coefficient (PCC) between the MLLIM and GRACE and GRACE Follow-On (GRACE-FO) are equal to 0.91 and 0.88, respectively; and the values of R-squared (R²) are equal to 0.76 and 0.65, respectively; the values of PCC and R² between MLLIM and GLDAS solutions are equal to 0.79 and 0.65. Compared with the traditional GPS inversion, the MLLIM improves PCC and R² by 8.85% and 7.99% on average, which indicates that the MLLIM can improve the accuracy of TWSA inversion more than the traditional GPS method. Third, this study applies the MLLIM to invert the TWSA in each province of southwest China and combines the precipitation to analyze the change of TWSA in each province. The results are as follows: (1) The spatial distribution of TWSA and precipitation is coincident, which is highlighted in southwest Yunnan and southeast Guangxi; (2) this study compares TWSA of MLLIM with GRACE and GLDAS solutions in each province, which indicates that the maximum value of PCC is as high as 0.86 and 0.94, respectively, which indicates the MLLIM can be used to invert the TWSA in the regions with sparse GPS stations. The TWSA based on the MLLIM can be used to fill the vacancy between GRACE and GRACE-FO. Full article

Commonly used mass-concentration (mascon) solutions estimated from Level-1B Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On data, provided by processing centers such as the Jet Propulsion Laboratory (JPL) or the Goddard Space Flight Center (GSFC), do not give users control over the placement of mascons or inversion assumptions, such as regularization. While a few studies have focused on regional or global mascon optimization from spherical harmonics data, a global optimization based on the geometry of geophysical signal as a standardized product with user-defined points has not been addressed. Finding the optimal configuration with enough coverage to account for far-field leakage is not a trivial task and is often approached in an ad-hoc manner, if at all. Here, we present an automated approach to defining non-uniform, global mascon solutions that focus on a region of interest specified by the user, while maintaining few global degrees of freedom to minimize noise and leakage. We showcase our approach in High Mountain Asia (HMA) and Alaska, and compare the results with global uniform mascon solutions from range-rate data. We show that the custom mascon solutions can lead to improved regional trends due to a more careful sampling of geophysically distinct regions. In addition, the custom mascon solutions exhibit different seasonal variation compared to the regularized solutions. Our open-source pipeline will allow the community to quickly and efficiently develop optimized global mascon solutions for an arbitrary point or polygon anywhere on the surface of the Earth. Full article

In this study, we calculate the hydrological plus cryospheric excitation of polar motion (hydrological plus cryospheric angular momentum, HAM/CAM) using mascon solutions based on observations from the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) missions. We compare and evaluate HAM/CAM computed from GRACE and GRACE-FO mascon data provided by the Jet Propulsion Laboratory (JPL), the Center for Space Research (CSR), and the Goddard Space Flight Center (GSFC). A comparison with HAM obtained from the Land Surface Discharge Model is also provided. An analysis of HAM/CAM and HAM is performed for overall variability, trends, and seasonal and non-seasonal variations. The HAM/CAM and HAM estimates are validated using the geodetic residual time series (GAO), which is an estimation of the hydrological plus cryospheric signal in geodetically observed polar motion excitation. In general, all mascon datasets are found to be equally suitable for the determination of overall, seasonal, and non-seasonal HAM/CAM oscillations, but some differences in trends remain. The use of an ellipsoidal correction, implemented in the newest solution from CSR, does not noticeably affect the consistency between HAM/CAM and GAO. Analysis of the data from the first two years of the GRACE-FO mission indicates that the current accuracy of HAM/CAM from GRACE-FO mascon data meets expectations, and the root mean square deviation of HAM/CAM components are between 5 and 6 milliarcseconds. The findings from this study can be helpful in assessing the role of satellite gravimetry in polar motion studies and may contribute towards future improvements to GRACE-FO data processing. Full article

High spatiotemporal resolution of terrestrial total water storage plays a key role in assessing trends and availability of water resources. This study presents a two-step method for downscaling GRACE-derived total water storage anomaly (GRACE TWSA) from its original coarse spatiotemporal resolution (monthly, 3-degree spherical cap/~300 km) to a high resolution (daily, 5 km) through combining land surface model (LSM) simulated high spatiotemporal resolution terrestrial water storage anomaly (LSM TWSA). In the first step, an iterative adjustment method based on the self-calibration variance-component model (SCVCM) is used to spatially downscale the monthly GRACE TWSA to the high spatial resolution of the LSM TWSA. In the second step, the spatially downscaled monthly GRACE TWSA is further downscaled to the daily temporal resolution. By applying the method to downscale the coarse resolution GRACE TWSA from the Jet Propulsion Laboratory (JPL) mascon solution with the daily high spatial resolution (5 km) LSM TWSA from the Ecological Assimilation of Land and Climate Observations (EALCO) model, we evaluated the benefit and effectiveness of the proposed method. The results show that the proposed method is capable to downscale GRACE TWSA spatiotemporally with reduced uncertainty. The downscaled GRACE TWSA are also evaluated through in-situ groundwater monitoring well observations and the results show a certain level agreement between the estimated and observed trends. Full article