Global GRACE Data Assimilation for Groundwater and Drought Monitoring: Advances and Challenges

Abstract

The scarcity of groundwater storage change data at the global scale hinders our ability to monitor groundwater resources effectively. In this study, we assimilate a state‐of‐the‐art terrestrial water storage product derived from Gravity Recovery and Climate Experiment (GRACE) satellite observations into NASA's Catchment land surface model (CLSM) at the global scale, with the goal of generating groundwater storage time series that are useful for drought monitoring and other applications. Evaluation using in situ data from nearly 4,000 wells shows that GRACE data assimilation improves the simulation of groundwater, with estimation errors reduced by 36% and 10% and correlation improved by 16% and 22% at the regional and point scales, respectively. The biggest improvements are observed in regions with large interannual variability in precipitation, where simulated groundwater responds too strongly to changes in atmospheric forcing. The positive impacts of GRACE data assimilation are further demonstrated using observed low‐flow data. CLSM and GRACE data assimilation performance is also examined across different permeability categories. The evaluation reveals that GRACE data assimilation fails to compensate for the lack of a groundwater withdrawal scheme in CLSM when it comes to simulating realistic groundwater variations in regions with intensive groundwater abstraction. CLSM‐simulated groundwater correlates strongly with 12‐month precipitation anomalies in low‐latitude and midlatitude areas. A groundwater drought indicator based on GRACE data assimilation generally agrees with other regional‐scale drought indicators, with discrepancies mainly in their estimated drought severity.

Seasonal and Interannual Variations in China’s Groundwater Based on GRACE Data and Multisource Hydrological Models

“…We have to admit that the method used in this study to derive GWS is imperfect and uncertainties exist. Recently, data assimilation techniques have been proposed to improve the simulation of hydrological models by assimilating the GRACE observation into hydraulic models [65][66][67][68][69]. We will use these new techniques in our future studies to enhance the accuracy of the GWS estimate.…”

Application of GRACE to the estimation of groundwater storage change in a data‐poor region: A case study of Ngadda catchment in the Lake Chad Basin

“…In 2015–2016, authors set up over five real‐time monitoring stations for groundwater, soil moisture, and meteorological data along the Chari and Logone rivers in the LCB. Its first set of groundwater data was employed by Li et al () for global groundwater and drought monitoring. Currently, the Lake Chad Basin Commission is building the LCB observatory network by installing over 30real‐time monitoring sensors for groundwater through the international collaboration with the Federal Institute for Geosciences and Natural Resources and the German Corporation for International Corporation in Germany.…”

Earth Observations and Integrative Models in Support of Food and Water Security

“…4) that are disseminated by the National Drought Mitigation Center, used by farmers, ranchers, other agricultural interests, public agencies, and private consultants, among others [55]. Global, GRACE data assimilation-based wetness/drought indicators have recently been developed as well, which will help to satisfy the need for timely freshwater availability data worldwide [67].…”