Abstract:
GRACE has great potential to benefit hydrology, because no other observation system, ground- or space-based, has ever mapped variations in terrestrial water storage (TWS; the sum of groundwater, soil moisture, surface water, and snow). However, because its spatial and temporal resolutions are low relative to other hydrological observing systems and because total terrestrial water storage is a variable unfamiliar to hydrologists, GRACE has yet to become a standard tool for hydrology. Land surface models (LSMs) simulate the redistribution of water and energy incident on the land surface, but their accuracy is limited by the quality of the input data used to parameterize and force the models, the model developers' understanding of the physics involved, and the simplifications necessary to depict the Earth system economically. The advantages of GRACE and LSMs can be harnessed by data assimilation, which synthesizes discontinuous and imperfect observations with our knowledge of physical processes, as represented in a LSM. The model fills observational gaps, provides quality control, and enables data from disparate measurement systems to be merged, while the observations anchor the results in reality. We have assimilated TWS anomalies derived from GRACE into the Catchment LSM. The experimental domain was the Mississippi River Basin. Monthly GRACE estimates were derived for each of the four major sub-basins. Assimilation was performed using an Ensemble Kalman smoother. In addition to simulating soil and snow water storages, the Catchment LSM accounts for variations in the elevation of the water table, making it appropriate for total terrestrial water storage applications. The assimilated results produced groundwater storage time series which more closely resembled piezometer based estimates, relative to the open loop (non-assimilating) simulations. These results emphasize the potential for GRACE to improve the accuracy of hydrologic model output, which will benefit water cycle science and water resources applications. Furthermore, data assimilation enables coarse resolution, vertically integrated terrestrial water storage anomalies from GRACE to be spatially and temporally disaggregated and attributed to different levels of the snow-soil-aquifer column in a physically meaningful way.