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• W4387036045 abstract "The observations from Gravity Recovery and Climate Experiment (GRACE) satellites provide total water storage changes (TWSC) at ∼300 km or larger spatial scales. To obtain information at a higher spatial resolution, suitable for management purposes, previous studies combined GRACE TWSC maps with information from hydrological models via assimilation techniques (e.g. CLSM-DA), or with external observations via scaling and machine learning approaches. Both techniques may introduce shrinkage errors, a reduction in amplitude of long spatial wavelength signals, and distorting water budgets at basin scale best observed by GRACE. Here, we present a fusion approach based on wavelet multiresolution analysis to combine long-wavelength GRACE TWSC observations with short-wavelength measurements of TWSC from the GLDAS Noah model in the contiguous United States (CONUS). We decompose TWSC maps into building blocks at different spatial wavelengths, examine their statistical characteristics, and combine complementary components at wavelet coefficient levels. The fused TWSC is then obtained by inverse wavelet transform. A spectral analysis indicates that the fused TWSC comprises frequency content that balances spectral characteristics of both input datasets. The fused TWSC dataset possesses enhanced details in the spatial domain, while it accurately quantifies the water budget and its long-term spatial trend at basin scale during 2003–2015, showing a good agreement with GRACE estimates. Independent validation against elastic hydrologic loading deformation measured at ∼2000 GNSS stations across CONUS shows similar overall performance for GRACE and fused datasets, while it outperforms GRACE in modeling groundwater storage changes in CONUS when compared to CLSM-DA." @default.
• W4387036045 created "2023-09-27" @default.
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• W4387036045 date "2023-11-01" @default.
• W4387036045 modified "2023-10-18" @default.
• W4387036045 title "A shrinkage-free approach for fusing GRACE-based total water storage changes with models using wavelet multiresolution analysis" @default.
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• W4387036045 doi "https://doi.org/10.1016/j.jhydrol.2023.130217" @default.
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