[1] We present a robust optimization method for estimating aquifer storage parameters (specific yield or storativity) using the Gravity Recovery and Climate Experiment (GRACE) data, in situ well level observations, and other ancillary information. Uncertainty inherent in the remotely sensed and in situ time series can adversely affect the parameter estimation process and, in the worse case, make the solution completely meaningless. Our estimation problem is formulated to directly minimize the negative impact of data uncertainty by incorporating bounds on data variations. We demonstrate our method for the interconnected Edwards-Trinity Plateau and Pecos Valley aquifers in central Texas. The study area is divided into multiple zones based on the geology and monitor well coverage. Our estimated aquifer storage parameters are consistent with previous results obtained from pumping tests and model calibration, demonstrating the potential of using GRACE data for validating regional groundwater model parameters.

[1] The North-Western Sahara Aquifer System (NWSAS), one of the world's largest groundwater systems, shows an overall piezometric decline associated with increasing withdrawals. Estimating the recharge rate in such a semiarid system is challenging but crucial for sustainable water development. In this paper, the recharge of the NWSAS is estimated using a regional water budget based on GRACE terrestrial water storage monthly records, soil moisture from the GLDAS (a land data system that assimilates hydrological information), and groundwater pumping rates. A cumulated natural recharge rate of 1.40 ± 0.90 km3 yr−1is estimated for the two main aquifers. Our results suggest a renewal rate of about 40% which partly contradicts the premise that recharge in this area should be very low or even null. Aquifer depletion inferred from our analysis is consistent with observed piezometric head decline in the two main aquifers in the region. Annual recharge variations were also estimated and vary between 0 and 4.40 km3 yr−1for the period 2003–2010. These values correspond to a recharge between 0 and 6.75 mm yr−1 on the 650,000 km2of outcropping areas of the aquifers, which is consistent with the expected weak and sporadic recharge in this semiarid environment. These variations are also in line with annual rainfall variation with a lag time of about 1 year.

[1] The Murray-Darling Basin in southeast Australia is experiencing one of the most severe droughts observed recently in the world, driven by several years of rainfall deficits and record high temperatures. This paper provides new basin-scale observations of the multiyear drought, integrated to a degree rarely achieved on such a large scale, to assess the response of water resources and the severity of the drought. A combination of Gravity Recovery and Climate Experiment (GRACE) data with in situ and modeled hydrological data shows the propagation of the water deficit through the hydrological cycle and the rise of different types of drought. Our observations show the rapid drying of soil moisture and surface water storages, which reached near-stationary low levels only ∼2 years after the onset of the drought in 2001, with a loss of ∼80 and ∼12 km3 between January 2001 and January 2003, respectively. The multiyear drought has led to the almost complete drying of surface water resources which account for most of the water used for irrigation and domestic purposes. High correlation between observed groundwater variations and GRACE data substantiates the persistent reduction in groundwater storage, with groundwater levels still declining 6 years after the onset of the drought (groundwater loss of ∼104 km3 between 2001 and 2007). The hydrological drought continues even though the region returned to average annual rainfall during 2007.

We present observations of groundwater change in a key, semi- arid, agricultural region of Australia, the Murray Groundwater Basin. Time series of in- situ groundwater levels archived in Government databases were compiled for all the States sharing this groundwater basin. A high quality subset of this dataset in a region affected by dryland salinity provides long-term in- situ observations on the respective impact of (1) increased recharge after deforestation and (2) the recent multi- year drought on groundwater levels. A change in the long- term dynamic of the water table is observed since the beginning of the drought in 1997 (1994 in some regions). The analysis of the bore data fi rst showed a regional rise of the water table by ! 5 cm/a from 1980 to 1992 followed by a regional decline at a rate of 17 cm/a from 1997 to 2009. Time series of groundwater storage anomalies obtained from a combination of total water storage using space gravimetry (GRACE) and soil moisture estimates from hydrological models also indicate a strong decline of the water table from 2002 to 2010. From August 2002 to December 2010, GRACE- based estimates indicate a groundwater loss of ! 18 ! 1.3 mm/a which equates to a total loss of groundwater of ! 45 ! 3 km 3 over the ! 300,000 km 2 hydrogeological basin. These observations suggest that the impact of the drought on groundwater recharge counterbalanced and surpassed the impacts of past land-clearing and has brought a temporary halt to dryland salinity.

To determine the relationship between underground mining, groundwater storage change, and surface deformation, we first used two sets of ENVISAT data and one set of Sentinel-1A data to obtain surface deformation in eastern Xuzhou coalfield based on the temporarily coherent point interferometric synthetic aperture radar (TCPInSAR) technique. By comparison with underground mining activities, it indicated that the surface subsidence is mainly related to mine exploitation and residual subsidence in the goaf, while the surface uplift is mainly related to restoration of the groundwater level. The average groundwater storage change in the eastern Xuzhou coalfield from January 2005 to June 2017 was obtained through the Gravity Recovery and Climate Experiment (GRACE) data, and the results indicated that the groundwater storage changed nonlinearly with time. The reliability of the groundwater monitoring results was qualitatively validated by using measured well data from April 2009 to April 2010. Combining with time of mining and mine closing analysis, groundwater storage change within the research area had a strong correlation with drainage activity of underground mining. An analysis was finally conducted on the surface deformation and the groundwater storage change within the corresponding time. The results indicated that the groundwater storage variation in the research area has a great influence on the surface deformation after the mine closed.

Time series of regional 2 ◊ 2 Gravity Recovery and Climate Experiment (GRACE) solutions have been com- puted from 2003 to 2011 with a 10-day resolution by using an energy integral method over Australia (112 E-156 E; 44 S-10 S). This approach uses the dynamical orbit anal- ysis of GRACE Level 1 measurements, and specially accu- rate along-track K-band range rate (KBRR) residuals with a 1 µm s 1 level of errors, to estimate the total water mass over continental regions. The advantages of regional solutions are a significant reduction of GRACE aliasing errors (i.e. north- south stripes) providing a more accurate estimation of water mass balance for hydrological applications. In this paper, the validation of these regional solutions over Australia is pre- sented, as well as their ability to describe water mass change as a response of climate forcings such as El Nino. Princi- pal component analysis of GRACE-derived total water stor- age (TWS) maps shows spatial and temporal patterns that are consistent with independent data sets (e.g. rainfall, cli- mate index and in situ observations). Regional TWS maps show higher spatial correlations with in situ water table mea- surements over Murray-Darling drainage basin (80-90 %), and they offer a better localization of hydrological structures than classical GRACE global solutions (i.e. Level 2 Groupe de Recherche en Geodesie Spatiale (GRGS)) products and 400 km independent component analysis solutions as a lin- ear combination of GRACE solutions provided by different centers.

The water cycle is the most essential supporting physical mechanism ensuring the existence of life on Earth. Its components encompass the atmosphere, land, and oceans. The cycle is composed of evaporation, evapotranspiration, sublimation, water vapor transport, condensation, precipitation, runoff, infiltration and percolation, groundwater flow, and plant uptake. For a correct closure of the global water cycle, observations are needed of all these processes with a global perspective. In particular, precipitation requires continuous monitoring, as it is the most important component of the cycle, especially under changing climatic conditions. Passive and active sensors on board meteorological and environmental satellites now make reasonably complete data available that allow better measurements of precipitation to be made from space, in order to improve our understanding of the cycle’s acceleration/deceleration under current and projected climate conditions. The article aims to draw an up-to-date picture of the current status of observations of precipitation from space, with an outlook to the near future of the satellite constellation, modeling applications, and water resource management.

The hydrological budget of a region is determined based on the horizontal and vertical water fluxes acting in both inward and outward directions. These integrated water fluxes vary, altering the total water storage and consequently the gravitational force of the region. The time-dependent gravitational field can be observed through the Gravity Recovery and Climate Experiment (GRACE) gravimetric satellite mission, provided that the mass variation is above the sensitivity of GRACE. This study evaluates mass changes in prominent reservoir regions through three independent approaches viz. fluxes, storages, and gravity, by combining remote sensing products, in-situ data and hydrological model outputs using WaterGAP Global Hydrological Model (WGHM) and Global Land Data Assimilation System (GLDAS). The results show that the dynamics revealed by the GRACE signal can be better explored by a hybrid method, which combines remote sensing-based reservoir volume estimates with hydrological model outputs, than by exclusive model-based storage estimates. For the given arid/semi-arid regions, GLDAS based storage estimations perform better than WGHM.

The West Liaohe River Basin (WLRB) is one of the most sensitive areas to climate change in China and an important grain production base in the Inner Mongolia Autonomous Region of China. Groundwater depletion in this region is becoming a critical issue. Here, we used the Gravity Recovery and Climate Experiment (GRACE) satellite data and in situ well observations to estimate groundwater storage (GWS) variations and discussed the driving factors of GWS changes in the WLRB. GRACE detects a GWS decline rate of −0.92 ± 0.49 km3/yr in the WLRB during 2005–2011, consistent with the estimate from in situ observations (−0.96 ± 0.19 km3/yr). This long-term GWS depletion is attributed to reduced precipitation and extensive groundwater overexploitation in the 2000s. Long-term groundwater level observations and reconstructed total water storage variations since 1980 show favorable agreement with precipitation anomalies at interannual timescales, both of which are significantly influenced by the El Nino-Southern Oscillation (ENSO). Generally, the WLRB receives more/less precipitation during the El Nino/La Nina periods. One of the strongest El Nino events on record in 1997–1998 and a subsequent strong La Nina drastically transform the climate of WLRB into a decade-long drought period, and accelerate the groundwater depletion in the WLRB after 1998. This study demonstrates the significance of integrating satellite observations, ground-based measurements, and climatological data for interpreting regional GWS changes from a long-term perspective.

The Three-River Source Region (TRSR) of the Tibetan Plateau (TP) is regarded as the "Chinese water tower". Climate warming and the associated degradation of permafrost might change the water cycle and affect the alpine vegetation growth in the TRSR. However, the quantitative changes in the water budget and their impacts on the vegetation in the TRSR are poorly understood. In this study, the spatial-temporal changes in the hydrological variables and the normalized difference vegetation index (NDVI) during 2003-2014 were investigated using multiple satellite data and a remote sensing energy balance model. The results indicated that precipitation showed an increasing trend at a rate of 14.0 mm 10 a-1, and evapotranspiration (ET) showed a slight decreasing trend. The GRACE-derived total water storage (TWS) change presented a significant increasing trend at a rate of 35.1 mm a-1. The change in groundwater (GW) which showed an increasing trend at a rate of 18.5 mm a-1, was estimated by water budget. The time lag of the GRACE-TWS that was influenced by precipitation was more obviously than was the GLDAS-SM (Soil Moisture) change. The vegetation in the TRSR was greening during the study period, and the accumulation of the NDVI increased rapidly after 2008. The effect of total TWS and GLDAS-SM on vegetation was considerably more than that the effects of other factors in this region. It was concluded that the hydrological cycle had obviously changed and that more soil water was transferred into the GW since the aquiclude changed due to climate warming. The increasing area and number of lakes and the thickening of the active layer in the permafrost area led to the greater infiltration of surface water into the groundwater, which resulted in increased water storage.

The Huang-Huai-Hai (3H) Plain is the major crop-producing region in China. Due to the long-term overexploitation of groundwater for irrigation, the groundwater funnel is constantly expanding and the scarcity of water resources is prominent in this region. In this study, Gravity Recovery and Climate Experiment (GRACE) and hydrological models were used to estimate the spatial-temporal changes of groundwater storage (GWS) and the driving factors of GWS variations were discussed in the 3H Plain. The results showed that GRACE-based GWS was depleted at a rate of −1.14 ± 0.89 cm/y in the 3H Plain during 2003 to 2015. The maximum negative anomaly occurred in spring due to agricultural irrigation activities. Spatially, the loss of GWS in the Haihe River Basin is more serious than that in the Huaihe River Basin, presenting a decreasing trend from south to north. Conversely, the blue water footprint (WFblue) of wheat exhibited an increasing trend from south to north. During the drought years of 2006, 2013, and 2014, more groundwater was extracted to offset the surface water shortage, leading to an accelerated decline in GWS. This study demonstrated that GWS depletion in the 3H Plain is well explained by reduced precipitation and groundwater abstraction due to anthropogenic irrigation activities.

The Gravity Recovery and Climate Experiment (GRACE) satellites provide a new quantitative measurement to observe terrestrial water storage (TWS) variations. In this paper, GRACE data were used to detect TWS changes (TWSC) in last decade in the arid region of northwest China. TWSC of the study area were obtained from RL05 Level 2 GRACE data between August 2002 and July 2013. These obtained GRACE based TWSC were thereafter validated against that calculated from global land data assimilation system (GLDAS) data. The validation showed TWSC from two sources were consistent. Together with precipitation, the analyses showed TWSC in this arid region changed over time, and responded sensitively to climate factors. Results indicated that TWSC showed distinct seasonal variation characteristics and the peaks of TWS appeared corresponding to precipitation. The summers of 2005 and 2012 were wet periods with a mean TWS higher than multiple-year average by about 30 mm, while the falls of 2008 and 2009 were dry seasons with a heavily deficit TWS, lower than multiple-year average by about -30 mm. The winter of 2008 was also in deficit but slightly better than the fall of same year. On average, in the last decade, the period of 2008 to 2009 was in the driest condition. Significant decreases in TWS in 2008 and 2009 were successfully detected by GRACE, and corresponded to drought events in the study area. This study showed in the last decade the changes of climate factors resulted in larger TWS variations in the arid region and proved the capability of GRACE in detecting larger-scale and long-term drought events in arid regions.

The Gravity Recovery and Climate Experiment (GRACE) satellite mission, which was in operation from March 2002 to June 2017, was the first remote sensing mission to provide temporal variations of Terrestrial Water Storage (TWS), which is the sum of the water masses that were contained in the soil column (i.e., snow, surface water, soil moisture, and groundwater), at a spatial resolution of a few hundred kilometers. As in situ level measurements are generally not sufficiently available for monitoring groundwater changes at the regional-scale, this unique dataset, combined with external information, is widely used to quantify the interannual variations of groundwater storage in the world’s major aquifers. GRACE-based groundwater changes revealed significant aquifer depletion over large regions, such as the Middle East, the northwest India aquifer, the North China Plain aquifer, the Murray-Darling Basin in Australia, the High Plains, and the California Central Valley aquifers in the United States of America (USA), but were also used to estimate groundwater-related parameters such as the specific yield, which relates groundwater level to storage, or to define the indices of groundwater depletion and stress. In this review, the approaches used for estimating groundwater storage variations are presented along with the main applications of GRACE data for groundwater monitoring. Issues that were related to the use of GRACE-based TWS are also addressed.

The Gravity Recovery And Climate Experiment (GRACE) satellite mission provides time-variable gravity fields that are commonly used to study regional and global terrestrial total water storage (TWS) changes. These estimates are superimposed by different error sources such as the north–south stripes in the spatial domain and spectral/spatial leakage errors, which should be reduced before use in hydrological applications. Although different filtering methods have been developed to mitigate these errors, their performances are known to vary between regions. In this study, a Kernel Fourier Integration (KeFIn) filter is proposed, which can significantly decrease leakage errors over (small) river basins through a two-step post-processing algorithm. The first step mitigates the measurement noise and the aliasing of unmodelled high-frequency mass variations, and the second step contains an efficient kernel to decrease the leakage errors. To evaluate its performance, the KeFIn filter is compared with commonly used filters based on (i) basin/gridded scaling factors and (ii) ordinary basin averaging kernels. Two test scenarios are considered that include synthetic data with properties similar to GRACE TWS estimates within 43 globally distributed river basins of various sizes and application of the filters on real GRACE data. The KeFIn filter is assessed against water flux observations through the water balance equations as well as in-situ measurements. Results of both tests indicate a remarkable improvement after applying the KeFIn filter with leakage errors reduced in 34 out of the 43 assessed river basins and an average improvement of about 23.38% in leakage error reduction compared to other filters applied in this study.

Summary Regional groundwater models are increasingly used for short- and long-term water resources planning, in anticipation of greater climate variability and population growth. However, many of these models are subject to structural and parametric uncertainties because of the lack of field measurements. In recent years, the Gravity Recovery and Climate Experiment (GRACE) satellite mission has shown great potential for tracking total water storage changes over large regions. The pattern of groundwater storage changes inferred from GRACE may be incorporated as an additional regularization mechanism for calibrating regional groundwater models. Motivated by the demonstrated success of GRACE for monitoring groundwater storage changes, this study explores the combined use of in situ water level measurements and GRACE-derived groundwater storage changes for calibrating regional groundwater models. The resulting optimization problem is solved using an evolutionary optimization algorithm. We demonstrate the proposed calibration strategy for the hydraulically connected Edwards–Trinity Plateau and Pecos Valley aquifers (total area 115,000 km2) in west Texas. Monthly GRACE data from 2002 to 2007 were used to recalibrate a regional groundwater model developed for the area. Our results indicate that (i) calibration using in situ data alone may yield multiple plausible solutions, a phenomenon well known to hydrologists; and (ii) GRACE data helped further constrain model parameters over the study period and, thus, may be continuously assimilated, among other sources of data, for enhancing existing regional groundwater models.

Since its launch in March 2002, the Gravity Recovery and Climate Experiment (GRACE) has provided a global mapping of the time-variations of the Earth’s gravity field. Tiny variations of gravity from monthly to decadal time scales are mainly due to redistributions of water mass inside the surface fluid envelops of our planet (i.e., atmosphere, ocean and water storage on continents). In this article, we present a review of the major contributions of GRACE satellite gravimetry in global and regional hydrology. To date, many studies have focused on the ability of GRACE to detect, for the very first time, the time-variations of continental water storage (including surface waters, soil moisture, groundwater, as well as snow pack at high latitudes) at the unprecedented resolution of ~400–500 km. As no global complete network of surface hydrological observations exists, the advances of satellite gravimetry to monitor terrestrial water storage are significant and unique for determining changes in total water storage and water balance closure at regional and continental scales.

Sea level rise is generally attributed to increased ocean heat content and increased rates glacier and ice melt. However, human transformations of Earth’s surface have impacted water exchange between land, atmosphere, and ocean, ultimately affecting global sea level variations. Impoundment of water in reservoirs and artificial lakes has reduced the outflow of water to the sea, while river runoff has increased due to groundwater mining, wetland and endorheic lake storage losses, and deforestation. In addition, climate-driven changes in land water stores can have a large impact on global sea level variations over decadal timescales. Here, we review each component of negative and positive land water contribution separately in order to highlight and understand recent changes in land water contribution to sea level variations.

Received 27/02/2017 Accepted 23/05/2017 Published 31/05/2017 Article history Change detection Multi-level analysis Land cover Forest-Savannah Ghana

NASA’s Gravity Recovery and Climate Experiment (GRACE) has already proven to be a powerful data source for regional groundwater assessments in many areas around the world. However, the applicability of GRACE data products to more localized studies and their utility to water management authorities have been constrained by their limited spatial resolution (~200,000 km2). Researchers have begun to address these shortcomings with data assimilation approaches that integrate GRACE-derived total water storage estimates into complex regional models, producing higher-resolution estimates of hydrologic variables (~2500 km2). Here we take those approaches one step further by developing an empirically based model capable of downscaling GRACE data to a high-resolution (~16 km2) dataset of groundwater storage changes over a portion of California’s Central Valley. The model utilizes an artificial neural network to generate a series of high-resolution maps of groundwater storage change from 2002 to 2010 using GRACE estimates of variations in total water storage and a series of widely available hydrologic variables (PRISM precipitation and temperature data, digital elevation model (DEM)-derived slope, and Natural Resources Conservation Service (NRCS) soil type). The neural network downscaling model is able to accurately reproduce local groundwater behavior, with acceptable Nash-Sutcliffe efficiency (NSE) values for calibration and validation (ranging from 0.2445 to 0.9577 and 0.0391 to 0.7511, respectively). Ultimately, the model generates maps of local groundwater storage change at a 100-fold higher resolution than GRACE gridded data products without the use of computationally intensive physical models. The model’s simulated maps have the potential for application to local groundwater management initiatives in the region.

Like other agrarian countries, Pakistan is now heavily dependent on its groundwater resources to meet the irrigated agricultural water demand. Groundwater has emerged as a major source with more than 60% contribution in total water supplies. In the absence of groundwater regulation, the uneven and overexploitation of groundwater resource in Indus Basin has caused several problems of water table decline, groundwater mining, and deterioration of groundwater quality. This study evaluates the potential of Gravity Recovery and Climate Experiment Satellite (GRACE)-based estimation of changes in groundwater storage (GWS) as a cost-effective approach for groundwater monitoring and policy recommendations for sustainable water management in the Indus basin. The GRACE monthly gravity anomalies from 2003 to 2010 were analyzed as total water storage (TWS) variations. The variable infiltration capacity hydrological model-generated soil moisture and surface runoff were used for the separation of TWS into GWS anomalies. The GRACE-based GWS anomalies are found to favorably agree with trends inferred from in situ piezometric data. A general depletion trend is observed in Upper Indus Plain (UIP) where groundwater is found to be declining at a mean rate of about 13.5 mm per year in equivalent height of water during 2003-2010. A total loss of about 11.82 km3 per year fresh groundwater stock is inferred for UIP. Based on TWS variations and ground knowledge, the two southern river plains, Bari and Rechna are found to be under threat of extensive groundwater depletion. GRACE TWS data were also able to pick up signals from the large-scale flooding events observed in 2010 and 2014. These flooding events played a significant role in the replenishment of the groundwater system in Indus Basin. Our study indicates that the GRACE-based estimation of GWS changes is skillful enough to provide monthly updates on the trend of the GWS changes for resource managers and policy makers of Indus basin.