Since March 2002, the Gravity Recovery and Climate Experiment (GRACE) has provided first estimates of land water storage variations by monitoring the time‐variable component of Earth's gravity field. Here we characterize spatial‐temporal variations in terrestrial water storage changes (TWSC) from GRACE and compare them to those simulated with the Global Land Data Assimilation System (GLDAS). Additionally, we use GLDAS simulations to infer how TWSC is partitioned into snow, canopy water and soil water components, and to understand how variations in the hydrologic fluxes act to enhance or dissipate the stores. Results quantify the range of GRACE‐derived storage changes during the studied period and place them in the context of seasonal variations in global climate and hydrologic extremes including drought and flood, by impacting land memory processes. The role of the largest continental river basins as major locations for freshwater redistribution is highlighted. GRACE‐based storage changes are in good agreement with those obtained from GLDAS simulations. Analysis of GLDAS‐simulated TWSC illustrates several key characteristics of spatial and temporal land water storage variations. Global averages of TWSC were partitioned nearly equally between soil moisture and snow water equivalent, while zonal averages of TWSC revealed the importance of soil moisture storage at low latitudes and snow storage at high latitudes. Evapotranspiration plays a key role in dissipating globally averaged terrestrial water storage. Latitudinal averages showed how precipitation dominates TWSC variations in the tropics, evapotranspiration is most effective in the midlatitudes, and snowmelt runoff is a key dissipating flux at high latitudes. Results have implications for monitoring water storage response to climate variability and change, and for constraining land model hydrology simulations.

Freshwater discharge from the continents is a key component of Earth’s water cycle that sustains human life and ecosystem health. Surprisingly, owing to a number of socioeconomic and political obstacles, a comprehensive global river discharge observing system does not yet exist. Here we use 13 years (1994–2006) of satellite precipitation, evaporation, and sea level data in an ocean mass balance to estimate freshwater discharge into the global ocean. Results indicate that global freshwater discharge averaged 36,055 km ³ /y for the study period while exhibiting significant interannual variability driven primarily by El Niño Southern Oscillation cycles. The method described here can ultimately be used to estimate long-term global discharge trends as the records of sea level rise and ocean temperature lengthen. For the relatively short 13-year period studied here, global discharge increased by 540 km ³ /y ² , which was largely attributed to an increase of global-ocean evaporation (768 km ³ /y ² ). Sustained growth of these flux rates into long-term trends would provide evidence for increasing intensity of the hydrologic cycle.

In this study, new estimates of monthly freshwater discharge from continents, drainage regions, and global land for the period of 2003–05 are presented. The method uses observed terrestrial water storage change estimates from the Gravity Recovery and Climate Experiment (GRACE) and reanalysis-based atmospheric moisture divergence and precipitable water tendency in a coupled land–atmosphere water mass balance. The estimates of freshwater discharge are analyzed within the context of global climate and compared with previously published estimates. Annual cycles of observed streamflow exhibit stronger correlations with the computed discharge compared to those with precipitation minus evapotranspiration (P − E) in several of the world’s largest river basins. The estimate presented herein of the mean monthly discharge from South America (∼846 km3 month−1) is the highest among the continents and that flowing into the Atlantic Ocean (∼1382 km3 month−1) is the highest among the drainage regions. The volume of global freshwater discharge estimated here is 30 354 ± 1212 km3 yr−1. Monthly variations of global freshwater discharge peak between August and September and reach a minimum in February. Global freshwater discharge is also computed using a global ocean–atmosphere mass balance in order to validate the land–atmosphere water balance estimates and as a measure of global water budget closure. Results show close proximity between the two estimates of global discharge at monthly (RMSE = 329 km3 month−1) and annual time scales (358 km3 yr−1). Results and comparisons to observations indicate that the method shows important potential for global-scale monitoring of combined surface water and submarine groundwater discharge at near-real time, as well as for contributing to contemporary global water balance studies and for constraining global hydrologic model simulations.

Freshwater discharge along continental margins is a key Earth system variable that is not well monitored globally. Here we propose a method for estimating monthly river basin outflows based on the use of new GRACE satellite estimates of terrestrial water storage changes in a coupled land‐atmosphere water balance. Using GRACE land water storage changes (which include changes in groundwater storage) in the water balance method results in more holistic estimates of basin discharge, which we call total basin discharge, that include not only streamflow, but the net of surface, groundwater and tidal inflows and outflows. The method was tested on the Amazon and Mississippi river basins, and could ultimately be applied to the major drainage regions and river basins of the globe. Estimated Amazon total basin discharge was well correlated with observed streamflow, but with a phase lag and underestimation of low flows. Estimated total basin discharge in the Mississippi river basin had a greater annual amplitude than observed streamflow, but showed good temporal covariance. Results for both basins highlight important differences between estimated total basin discharge and observed streamflow, at least part of which can be attributed to groundwater storage changes. Atmospheric moisture data and methods of GRACE data processing also contributed to the differences.

Several previous studies have shown the significance of representing shallow groundwater in land surface model (LSM) simulations. However, optimal methods for parameter estimation in order to realistically simulate water table depth have received little attention. The recent availability of Gravity Recovery and Climate Experiment (GRACE) water storage data provides a unique opportunity to constrain LSM simulations of terrestrial hydrology. In this study, we incorporate both GRACE (storage) and estimated base flow (flux) data in the calibration of LSM parameters, and demonstrate the advantages gained from this approach using a Monte Carlo simulation framework. This approach improves parameter estimation and reduces the uncertainty of water table simulations in the LSM. Using the optimal parameter set identified from the multiobjective calibration, water table simulation can be improved due to close dependence of both base flow and total subsurface water storage on the water table depth. Moreover, it is shown that parameters calibrated from short‐term (2003–2005) GRACE and base flow data can be validated using simulations for the periods of 1984–1998 and 2006–2007, which implies that the proposed multiobjective calibration strategy is robust. More important, this study has demonstrated the potential for the joint use of routinely available GRACE water storage data and streamflow records to constrain LSM simulations at the global scale.