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New spectro-spatial downscaling approach for terrestrial and groundwater storage variations estimated by GRACE models
Centre d'applications et de recherches en télédétection (CARTEL), Département de Géomatique appliquée, Université de Sherbrooke, Sherbrooke, Québec (CAN).
University West, Department of Engineering Science, Division of Mathematics, Computer and Surveying Engineering. Centre d'applications et de recherches en télédétection (CARTEL), Département de Géomatique appliquée, Université de Sherbrooke, Sherbrooke, Québec (CAN).ORCID iD: 0000-0003-0067-8631
Centre d'applications et de recherches en télédétection (CARTEL), Département de Géomatique appliquée, Université de Sherbrooke, Sherbrooke, Québec (CAN).
2022 (English)In: Journal of Hydrology, ISSN 0022-1694, E-ISSN 1879-2707, Vol. 615, no Part A, article id 128635Article in journal (Refereed) Published
Abstract [en]

The study proposes a new mathematical method, referred to as spectral combination, to downscale Gravity Recovery And Climate Experiment (GRACE) observations. The goal is to improve the spatial resolution of GRACE from 1̊ to 0.25̊, based upon available hydrological variables. First, a new approach based upon condition adjustment is proposed to estimate uncertainties related to hydrological variables. Second, a spectral-spatial estimator is developed to derive downscaled Total Water Storage Anomalies (TWSA) by optimally combining GRACE models and hydrological variables. Last, groundwater storage anomalies (GWSA) are derived from the downscaled TWSA. The proposed spectral combination approach was tested over the Canadian Prairies by considering GRACE data and required Global Land Data Assimilation System (GLDAS) variables for February 2003 to December 2016. The results reveal greater details in TWSA after spatial downscaling. Quantitatively, retrieved downscaled GWSA were validated using 75 unconfined in situ piezometric wells that were distributed across the Province of Alberta. A correlation of 0.80, with an RMSE of 11 mm, was obtained after downscaling with all wells over the validation area. These results are better than those obtained before downscaling (correlation of 0.42, with an RMSE of 21.4 mm), demonstrating that the proposed approach is successful. 

Place, publisher, year, edition, pages
Elsevier, 2022. Vol. 615, no Part A, article id 128635
Keywords [en]
Estimation; Geodetic satellites; Groundwater; Uncertainty analysis; Water conservation; Down-scaling; Experiment modeling; Gravity recovery and climate experiment satellites; Gravity recovery and climate experiments; Groundwater storage; Groundwater storage variation; Hydrological variables; Spatial downscaling; Spectral combination; Water storage; Digital storage
National Category
Geophysics Oceanography, Hydrology and Water Resources
Identifiers
URN: urn:nbn:se:hv:diva-19434DOI: 10.1016/j.jhydrol.2022.128635ISI: 000913192900004Scopus ID: 2-s2.0-85142155053OAI: oai:DiVA.org:hv-19434DiVA, id: diva2:1729983
Note

This study was funded by the Université de Sherbrooke (Excellence Scholarship Program), and the Natural Sciences and Engineering Research Council of Canada (NSERC Discovery Grant Number: RGPIN-2018- 06101; NSERC Create Grant: 543360-2020). We thank all data and products providers, University of Texas at Austin, Natural Resources Canada, and the Goddard Earth Sciences Data and Information Services Center. We gratefully thank for all valuable suggestions from two reviewers, and JOH editorial team, which help us improve the manuscript significantly. We thank W.F.J. Parsons for correcting the English.

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Available from: 2023-01-23 Created: 2023-01-23 Last updated: 2024-04-12

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Eshagh, Mehdi

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