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The performance of gravity recovery and climate experiment (GRACE) and GRACE-Follow On (GRACE-FO) satellites in estimating groundwater level (GWL) changes on a local scale is a challenging issue. Then, this study aims to investigate the performance of GRACE and GRACE-FO in monitoring GWL changes on a local scale compared to observations at groundwater wells and the results of groundwater modeling. The study utilized hundreds of groundwater observational data points and 180 satellite data from 2002 to 2020 in five Iranian provinces. The data from satellites GRACE and GRACE-FO were modified by subtracting hydrological parameters outputs of the global land data assimilation system (GLDAS) from the satellites’ estimations. The significant trends in GWL changes were studied by Sen’s slope and Mann–Kendall, which represented a significant declining trend in GWL in all studied provinces. Applying 1–2 month time lags to the observational data improved the correlation coefficients between satellite estimations and the observations at groundwater wells. The best correlation coefficients between observational GWL changes and GRACE estimations in Fars, Khorasan Razavi, Sistan and Baluchistan, East Azerbaijan, and Golestan provinces were calculated as 0.53, 0.42, 0.4, 0.51, and 0.36. Those values for GRACE-FO were calculated as 0.95, 0.67, 0.72, 0.78, and 0.3, respectively, which proved the better performance of GRACE-FO compared to GRACE. Meanwhile, the GWL changes estimated from GRACE-FO were compared to the results of groundwater modeling, which was performed by using MODFLOW via the GMS10.4 interface in Azarshahr aquifer located at East Azarbaijan revealed a satisfactory agreement.

We applied a land water mass balance equation over 59 major river basins during 2003-9 to estimate evapotranspiration (ET), using as input terrestrial water storage anomaly (TWSA) data from the GRACE satellites, precipitation and in situ runoff measurements. We found that the terrestrial water storage change cannot be neglected in the estimation of ET on an annual time step, especially in areas with relatively low ET values. We developed a spatial regression model of ET by integrating precipitation, temperature and satellite-derived normalized difference vegetation index (NDVI) data, and used this model to extrapolate the spatio-temporal patterns of changes in ET from 1982 to 2009. We found that the globally averaged land ET is about 604 mm yr−1 with a range of 558-650 mm yr−1. From 1982 to 2009, global land ET was found to increase at a rate of 1.10 mm yr−2, with the Amazon regions and Southeast Asia showing the highest ET increasing trend. Further analyses, however, show that the increase in global land ET mainly occurred between the 1980s and the 1990s. The trend over the 2000s, its magnitude or even the sign of change substantially depended on the choice of the beginning year. This suggests a non-significant trend in global land ET over the last decade.

The Almonte-Marismas aquifer, southwestern Spain, is a critical ecohydrogeological system that features extensive groundwater monitoring. This study investigates the utility of gravity recovery and climate experiment (GRACE) satellite data, specifically obtained from the global land data assimilation system (GLDAS) version 2.2, for assessing groundwater storage variations in the Almonte-Marismas aquifer. The presented research emphasizes the practical application of readily available GLDAS products that do not require data preprocessing. The study validates the GLDAS-2.2-based ready-to-use groundwater storage (GWS) time series by correlating it with precipitation and piezometric information, highlighting its effectiveness in medium-scale aquifers. The results reveal a strong agreement between GLDAS-2.2-derived GWS anomalies and in-situ measurements, confirming GLDAS-2.2’s potential for assessing aquifer depletion. The study discusses the consistency of seasonal variations in groundwater levels and GLDAS-2.2 data, emphasizing their close alignment with precipitation and pumping activities. Importantly, the study introduces GLDAS-2.2-derived volumetric groundwater storage (VGWS) as a valuable calibration parameter for numerical groundwater flow models, enhancing their accuracy over time. Moreover, the analysis reveals disparities in annual recharge values between GLDAS-2.2-derived data and the soil-water mass balance. These variations suggest the importance of additional inputs to precipitation, possibly related to subsurface or lateral connections. Overall, this study contributes to the ongoing discourse on the practical applications of GLDAS-2.2-derived GWS data in groundwater management, offering insights into its effectiveness in diverse hydrogeological settings, particularly in areas that lack monitoring infrastructure.

The Gravity Recovery and Climate Experiment (GRACE) twin satellites introduced a new opportunity to monitor changes in groundwater level. However, the performance of the GRACE-derived Liquid Water Equivalent Thickness (GRACE-LWET) in estimating groundwater-level changes at a local scale requires evaluation. Thus, the main aim of this study is to evaluate the performance of the GRACE-derived estimation in monitoring groundwater-level changes in Iran, which is experiencing decreasing trends and subsequent impacts. Another aim is to investigate the time lag between the water levels derived from the GRACE estimation and direct measurements. Four regions in Iran were studied between the years 2002 and 2016. To evaluate the results of GRACE-LWET, groundwater levels in 144 piezometric wells were measured monthly. The changes of the earth’s mass due to surface-water changes were assessed using four datasets of the Global Land Data Assimilation System. Furthermore, the statistical trend of the groundwater-level changes acquired from the GRACE estimations and observational data was investigated using the Mann-Kendall test and Sen’s slope estimator at a significance level of 0.05. The results showed that the best performance of the GRACE estimations was acquired when considering a 2-month time lag. In this case, the average correlation coefficient of the GRACE estimations against the observational data for the entire study region was 0.57. Moreover, the GRACE-LWET showed a significant decreasing trend for the whole study area using both considered tests. Hence, GRACE-derived estimation of groundwater-level changes can be used in regions with insufficient observational well data with an acceptable accuracy.

The South Aral Sea has been massively affected by the implementation of a mega-irrigation project in the region, but ground-based observations have monitored the Sea poorly. This study is a comprehensive analysis of the mass balance of the South Aral Sea and its basin, using multiple instruments from ground and space. We estimate lake volume, evaporation from the lake, and the Amu Darya streamflow into the lake using strengths offered by various remote-sensing data. We also diagnose the attribution behind the shrinking of the lake and its possible future fate. Terrestrial water storage (TWS) variations observed by the Gravity Recovery and Climate Experiment (GRACE) mission from the Aral Sea region can approximate water level of the East Aral Sea with good accuracy (1.8% normalized root mean square error (RMSE), and 0.9 correlation) against altimetry observations. Evaporation from the lake is back-calculated by integrating altimetry-based lake volume, in situ streamflow, and Global Precipitation Climatology Project (GPCP) precipitation. Different evapotranspiration (ET) products (Global Land Data Assimilation System (GLDAS), the Water Gap Hydrological Model (WGHM)), and Moderate-Resolution Imaging Spectroradiometer (MODIS) Global Evapotranspiration Project (MOD16) significantly underestimate the evaporation from the lake. However, another MODIS based Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) ET estimate shows remarkably high consistency (0.76 correlation) with our estimate (based on the water-budget equation). Further, streamflow is approximated by integrating lake volume variation, PT-JPL ET, and GPCP datasets. In another approach, the deseasonalized GRACE signal from the Amu Darya basin was also found to approximate streamflow and predict extreme flow into the lake by one or two months. They can be used for water resource management in the Amu Darya delta. The spatiotemporal pattern in the Amu Darya basin shows that terrestrial water storage (TWS) in the central region (predominantly in the primary irrigation belt other than delta) has increased. This increase can be attributed to enhanced infiltration, as ET and vegetation index (i.e., normalized difference vegetation index (NDVI)) from the area has decreased. The additional infiltration might be an indication of worsening of the canal structures and leakage in the area. The study shows how altimetry, optical images, gravimetric and other ancillary observations can collectively help to study the desiccating Aral Sea and its basin. A similar method can be used to explore other desiccating lakes.

The Tianshan mountain range is experiencing a notable environmental change as a result of global warming. In this paper; we adopt multiple remote sensing techniques to examine the diversified geophysical changes in the Tianshan; including glacier changes measured by Gravity Recovery and Climate Experiment (GRACE) and Ice, Cloud, and land Elevation Satellite (ICESat); lake level changes measured by radar altimetry; and snow coverage measured by moderate-resolution imaging spectroradiometer (MODIS). We find a rapid transition from dry years to wet years in 2010 in the western and northern Tianshan for all the geophysical measurements. The transition is likely caused by increasing westerlies and greatly pollutes the gravity signals in the edge of Tianshan. However, glaciers in the central Tianshan are unaffected and have been steadily losing mass at a rate of –4.0 ± 0.7 Gt/year during 2003–2014 according to space gravimetry and –3.4 ± 0.8 Gt/year during 2003–2009 according to laser altimetry. Our results show a weaker declining trend and greater linearity compared with earlier estimates; because we investigate the signal pattern in more detail. Finally; water level records of 60 years in Bosten Lake; China; are presented to show that for areas strongly dependent on meltwater; rising temperature can benefit the water supply in the short run; but cause it to deteriorate in the long run.

Many recent mass balance estimates using the Gravity Recovery and Climate Experiment (GRACE) and satellite altimetry (including two kinds of sensors of radar and laser) show that the ice mass of the Antarctic ice sheet (AIS) is in overall decline. However, there are still large differences among previously published estimates of the total mass change, even in the same observed periods. The considerable error sources mainly arise from the forward models (e.g., glacial isostatic adjustment [GIA] and firn compaction) that may be uncertain but indispensable to simulate some processes not directly measured or obtained by these observations. To minimize the use of these forward models, we estimate the mass change of ice sheet and present-day GIA using multi-geodetic observations, including GRACE and Ice, Cloud and land Elevation Satellite (ICESat), as well as Global Positioning System (GPS), by an improved method of joint inversion estimate (JIE), which enables us to solve simultaneously for the Antarctic GIA and ice mass trends. The GIA uplift rates generated from our JIE method show a good agreement with the elastic-corrected GPS uplift rates, and the total GIA-induced mass change estimate for the AIS is 54 ± 27 Gt/yr, which is in line with many recent GPS calibrated GIA estimates. Our GIA result displays the presence of significant uplift rates in the Amundsen Sea Embayment of West Antarctica, where strong uplift has been observed by GPS. Over the period February 2003 to October 2009, the entire AIS changed in mass by −84 ± 31 Gt/yr (West Antarctica: −69 ± 24, East Antarctica: 12 ± 16 and the Antarctic Peninsula: −27 ± 8), greater than the GRACE-only estimates obtained from three Mascon solutions (CSR: −50 ± 30, JPL: −71 ± 30, and GSFC: −51 ± 33 Gt/yr) for the same period. This may imply that single GRACE data tend to underestimate ice mass loss due to the signal leakage and attenuation errors of ice discharge are often worse than that of surface mass balance over the AIS.

Xi, H.; Zhang, Z.; Lu, Y., and Li, Y., 2019. Long-term and interannual variation of the steric sea level in the South China Sea and the connection with ENSO. Journal of Coastal Research, 35(3), 489–498. Coconut Creek (Florida), ISSN 0749-0208. Multisource observation and model data sets, including satellite altimetry, satellite gravimetry (the Gravity Recovery and Climate Experiment mission [GRACE]), ocean model (Estimation of the Circulation and Climate of the Ocean [ECCO]), and oceanographic reanalysis data (Ishii), are used to explore the long-term and interannual sea-level variation (SLV) in the South China Sea (SCS) and the connection with El Niño–Southern Oscillation (ENSO). From 1993 to 2012, the sea level rose at a rate of 4.7 ± 0.3 mm/y, and the steric component contributed approximately 40–55% of the increase shown in the Ishii data (1.9 ± 0.3 mm/y) and the ECCO model (2.6 ± 0.3 mm/yr). Using the GRACE observations from 2003 to 2012 for independent validation, the ECCO-derived steric trend was consistent with the mass-corrected altimetry result, whereas the Ishii data failed to capture the sea-level rise in the central basins. On the interannual scale, both the empirical orthogonal function (EOF) and the wavelet coherence (WTC) analysis indicate that the total SLV and the steric SLV have positive correlations with ENSO. The correlation is stronger between the Southern Oscillation index (SOI) and the ECCO-derived steric SLV than it is between the SOI and the Ishii-based steric SLV. In the time-frequency domain, the WTC shows a clear in-phase coherence in the 2-year cycle between the SOI and the ECCO-derived steric SLV over the entire time span; no significant coherence appears between the SOI and the Ishii-based steric SLV after 2003. The abnormal northerly winds and the increasing intrusion of low-temperature Kuroshio water into the SCS through the Luzon Strait during El Niño years may explain the connection between ENSO and the interannual steric SLV.

Droughts that occurred in the central plateau catchment of Iran have been monitored by Terrestrial Water Storage Deficit Index (TSDI) and three recently modified indices, namely aSPI, aSPEI and eRDI. Terrestrial Water Storage Changes (TWSC) for this area during April 2002–2016 was calculated using the GRACE spherical harmonics. The leakage error and noise of TWSC were evaluated by inter-comparison of this time series with regional mascon solutions; furthermore, to better comprehend the effect of climate on drought, the studied area was divided into semi-arid, arid, and extra-arid zones by using the modified De Martonne method. Using the meteorological data of 105 synoptic stations, the selected indices were calculated within a time scale of 3, 6, 9 and 12 months, and were compared to TSDI. Accordingly, the study area experienced multiple droughts during the studied period. The spatial distribution map for 2008–2009 drought showed that all indices indicated good conformity. The coefficient correlations between TSDI and other indices were different in each zone, but generally, the similarity of TSDI pattern increased with increasing time scales and was the most consistent with 9 and 12-month indices. Based on the spatiotemporal analysis of droughts, the severity, duration, and frequency of drought in the semi-arid zone were more than the other zones while no significant drought occurred in the extra-arid zone. Overall, the result indicated that GRACE-derived TSDI could be implemented successfully to predict spatiotemporal characteristics of droughts in extensive basins.

Time-variable gravity measurements from the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) missions have opened up a new avenue of opportunities for studying large-scale mass redistribution and transport in the Earth system. Over the past 19 years, GRACE/GRACE-FO time-variable gravity measurements have been widely used to study mass variations in different components of the Earth system, including the hydrosphere, ocean, cryosphere, and solid Earth, and significantly improved our understanding of long-term variability of the climate system. We carry out a comprehensive review of GRACE/GRACE-FO satellite gravimetry, time-variable gravity fields, data processing methods, and major applications in several different fields, including terrestrial water storage change, global ocean mass variation, ice sheets and glaciers mass balance, and deformation of the solid Earth. We discuss in detail several major challenges we need to face when using GRACE/GRACE-FO time-variable gravity measurements to study mass changes, and how we should address them. We also discuss the potential of satellite gravimetry in detecting gravitational changes that are believed to originate from the deep Earth. The extended record of GRACE/GRACE-FO gravity series, with expected continuous improvements in the coming years, will lead to a broader range of applications and improve our understanding of both climate change and the Earth system.