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TitleSpatiotemporal downscaling of GRACE total water storage using land surface model outputs
AuthorZhong, DORCID logo; Wang, SORCID logo; Li, J
SourceRemote Sensing vol. 13, issue 5, 900, 2021 p. 1-19, Open Access logo Open Access
Alt SeriesNatural Resources Canada, Contribution Series 20200787
Mediapaper; on-line; digital
File formatpdf; html
NTS72E; 72L; 72M; 73D; 73E; 73L; 73M; 74D; 74E; 74L; 82G; 82H; 82I; 82J; 82O; 82P; 83; 84A; 84B; 84C; 84D; 84E; 84F; 84G; 84H; 84I; 84J; 84K; 84L
Lat/Long WENS-120.0000 -110.0000 58.5000 49.0000
Subjectsgeophysics; hydrogeology; Nature and Environment; Science and Technology; surface waters; groundwater; soil moisture; snow; ice; remote sensing; satellite imagery; models; observation wells; Gravity Recovery and Climate Experiment (GRACE); Ecological Assimilation of Land and Climate Observations (EALCO) Model; Methodology
Illustrationslocation maps; geoscientific sketch maps; plots; time series; models
ProgramCanada Centre for Remote Sensing Canada Centre for Remote Sensing Water Program
Released2021 02 27
AbstractHigh spatiotemporal resolution of terrestrial total water storage plays a key role in assessing trends and availability of water resources. This study presents a two-step method for downscaling GRACE-derived total water storage anomaly (GRACE TWSA) from its original coarse spatiotemporal resolution (monthly, 3-degree spherical cap/~300 km) to a high resolution (daily, 5 km) through combining land surface model (LSM) simulated high spatiotemporal resolution terrestrial water storage anomaly (LSM TWSA). In the first step, an iterative adjustment method based on the self-calibration variance-component model (SCVCM) is used to spatially downscale the monthly GRACE TWSA to the high spatial resolution of the LSM TWSA. In the second step, the spatially downscaled monthly GRACE TWSA is further downscaled to the daily temporal resolution. By applying the method to downscale the coarse resolution GRACE TWSA from the Jet Propulsion Laboratory (JPL) mascon solution with the daily high spatial resolution (5 km) LSM TWSA from the Ecological Assimilation of Land and Climate Observations (EALCO) model, we evaluated the benefit and effectiveness of the proposed method. The results show that the proposed method is capable to downscale GRACE TWSA spatiotemporally with reduced uncertainty. The downscaled GRACE TWSA are also evaluated through in-situ groundwater monitoring well observations and the results show a certain level agreement between the estimated and observed trends.

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