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Deriving Scaling Factors Using a Global Hydrological Model to Restore GRACE Total Water Storage Changes for China's Yangtze River BasinThis study used a global hydrological model (GHM), PCR-GLOBWB, which simulates surface water storage changes, natural and human induced groundwater storage changes, and the interactions between surface water and subsurface water, to generate scaling factors by mimicking low-pass filtering of GRACE signals. Signal losses in GRACE data were subsequently restored by the scaling factors from PCR-GLOBWB. Results indicate greater spatial heterogeneity in scaling factor from PCR-GLOBWB and CLM4.0 than that from GLDAS-1 Noah due to comprehensive simulation of surface and subsurface water storage changes for PCR-GLOBWB and CLM4.0. Filtered GRACE total water storage (TWS) changes applied with PCR-GLOBWB scaling factors show closer agreement with water budget estimates of TWS changes than those with scaling factors from other land surface models (LSMs) in China's Yangtze River basin. Results of this study develop a further understanding of the behavior of scaling factors from different LSMs or GHMs over hydrologically complex basins, and could be valuable in providing more accurate TWS changes for hydrological applications (e.g., monitoring drought and groundwater storage depletion) over regions where human-induced interactions between surface water and subsurface water are intensive.
Document ID
20150018074
Acquisition Source
Goddard Space Flight Center
Document Type
Reprint (Version printed in journal)
Authors
Long, Di
(Tsinghua Univ. Bejing, China)
Yang, Yuting
(Commonwealth Scientific and Industrial Research Organization Canberra, Australia)
Yoshihide, Wada
(NASA Goddard Inst. for Space Studies New York, NY, United States)
Hong, Yang
(Tsinghua Univ. Bejing, China)
Liang, Wei
(Shaanxi Normal Univ. Xian, China)
Chen, Yaning
(Academia Sinica Xinjiang, China)
Yong, Bin
(HoHai Univ Nanjing, China)
Hou, Aizhong
(China Inst. of Water Resources and Hydropower Research Beijing, China)
Wei, Jiangfeng
(Texas Univ. Austin, TX, United States)
Chen, Lu
(Huazhong Univ. of Science and Technology Wuhan, China)
Date Acquired
September 17, 2015
Publication Date
July 17, 2015
Publication Information
Publication: Remote Sensing Environment
Publisher: Elsevier
Volume: 168
ISSN: 0034-4257
Subject Category
Earth Resources And Remote Sensing
Report/Patent Number
GSFC-E-DAA-TN26013
Funding Number(s)
CONTRACT_GRANT: sklhse-2014-A-01
OTHER: No. 91437214
OTHER: No. 71461010701
CONTRACT_GRANT: sklhse-2014-A-02
Distribution Limits
Public
Copyright
Other
Keywords
water
surface water
ground water

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