@InProceedings{LiRKBGZGCBMTTLNLPIDBLMSSB:2018:GlGrSt,
author = "Li, Bailing and Rodell, Matthew and Kumar, Sujay and Beaudoing,
Hiroko and Getirana, Augusto and Zaitchik, Benjamin F. and
Gon{\c{c}}alves, Lu{\'{\i}}s Gustavo Gon{\c{c}}alves de and
Cossetin, Camila and Bhanja, Soumendra Nath and Mukherjee, Abhijit
and Tian, Siyuan and Tangdamrongsub, Nattharchet and Long, Di and
Nanteza, Jamiat and Lee, Jejung and Policelli, Frederick S. and
Ibrahim, Goni and Djoret, Daira and Bila, Mohammed D. and De
Lannoy, Gabrielle and Mocko, David M. and Steele-Dunne, Susan C.
and Save, Himanshu and Bettadpur, Srinivas V.",
affiliation = "{University of Maryland College Park} and {NASA Goddard Space
Flight Center} and SAIC and SAIC and {NASA Goddard Space Flight
Center} and {Johns Hopkins University} and {Instituto Nacional de
Pesquisas Espaciais (INPE)} and Climatempo and {Indian Institute
of Technology Kharagpur} and {Indian Institute of Technology
Kharagpur} and {Australian National University} and School of
Engineering, University of Newcastle and {Tsinghua University} and
{} and {Univ Missouri-Kansas City} and {NASA Goddard Space Flight
Center} and {} and {Lake Chad Basin Commission} and {} and
{Katholieke Universiteit Leuven} and SAIC and {Technische
Universiteit Delft} and {University of Texas at Austin} and
{University of Texas at Austin}",
title = "Global groundwater storage estimates through assimilation of GRACE
data into a land surface model",
year = "2018",
organization = "AGU Fall Meeting",
abstract = "Groundwater is one of the most important natural resources for the
global community, with more than 2 billion people relying
exclusively on groundwater for drinking water and 43% of
irrigation water being supplied by aquifers. However, the scarcity
of groundwater variation data at the global scale hinders our
ability to monitor and manage groundwater resources effectively.
The terrestrial water storage (TWS) changes derived from the
Gravity Recovery and Climate Experiment (GRACE) satellite mission
have shown great promise in detecting groundwater storage changes
around the world. The application of GRACE data for groundwater
hydrology can be facilitated by GRACE data assimilation, which
constrains model estimates while providing vertical disaggregation
and spatial downscaling. Building upon previous studies at
regional to continental scales, this study assimilates a
state-of-the-art GRACE TWS product into NASAs Catchment land
surface model (CLSM) at the global scale with an improved ensemble
smoother. The GRACE data were derived using a regional mass
concentration approach with time variable constraints applied
during the inversion of satellite ranging observations (as opposed
to after inversion) to better preserve the information in those
measurements. Time series of in situ data from nearly 4,000 wells
located in different continents and climate zones were obtained to
evaluate the impact of GRACE data assimilation on CLSM estimated
groundwater. The comparison shows that GRACE data assimilation has
a strong positive impact on simulated groundwater storage, with
estimation errors reduced by 36% and 10% and correlation improved
by 16% and 22% at the regional and point scales, respectively. The
improvements are climate dependent, with the largest observed in
regions with substantial interannual variability in precipitation,
where simulated groundwater responds too strongly to changes in
atmospheric forcing. We discuss the impacts of GRACE data
assimilation on the temporal and spatial variability of TWS and
groundwater storage and model deficiencies, including the lack of
groundwater pumping, that limit its ability to distribute
assimilated TWS properly. Application of this dataset for
groundwater drought monitoring is also described.",
conference-location = "Washington, D. C.",
conference-year = "10-14 dec.",
language = "en",
targetfile = "li_global.pdf",
urlaccessdate = "27 abr. 2024"
}