Thu Apr 10, F. Flechtner
• Sorted by Date • Sorted by Last Name of First Author •
Wang, Xuanxuan, Liu, Liu, Niu, Qiankun, Li, Hao, and Xu, Zongxue, 2021. Multiple Data Products Reveal Long-Term Variation Characteristics of Terrestrial Water Storage and Its Dominant Factors in Data-Scarce Alpine Regions. Remote Sensing, 13(12):2356, doi:10.3390/rs13122356.
• from the NASA Astrophysics Data System • by the DOI System •
@ARTICLE{2021RemS...13.2356W,
author = {{Wang}, Xuanxuan and {Liu}, Liu and {Niu}, Qiankun and {Li}, Hao and {Xu}, Zongxue},
title = "{Multiple Data Products Reveal Long-Term Variation Characteristics of Terrestrial Water Storage and Its Dominant Factors in Data-Scarce Alpine Regions}",
journal = {Remote Sensing},
keywords = {climate change, TWSC, GRACE, ERA5, GLDAS, Qinghai{\textendash}Tibet Plateau, Yarlung Zangbo River Basin},
year = 2021,
month = jun,
volume = {13},
number = {12},
eid = {2356},
pages = {2356},
abstract = "{As the ``Water Tower of Asia'' and ``The Third Pole'' of the world, the
Qinghai-Tibet Plateau (QTP) shows great sensitivity to global
climate change, and the change in its terrestrial water storage
has become a focus of attention globally. Differences in multi-
source data and different calculation methods have caused great
uncertainty in the accurate estimation of terrestrial water
storage. In this study, the Yarlung Zangbo River Basin (YZRB),
located in the southeast of the QTP, was selected as the study
area, with the aim of investigating the spatio-temporal
variation characteristics of terrestrial water storage change
(TWSC). Gravity Recovery and Climate Experiment (GRACE) data
from 2003 to 2017, combined with the fifth-generation reanalysis
product of the European Centre for Medium-Range Weather
Forecasts (ERA5) data and Global Land Data Assimilation System
(GLDAS) data, were adopted for the performance evaluation of
TWSC estimation. Based on ERA5 and GLDAS, the terrestrial water
balance method (PER) and the summation method (SS) were used to
estimate terrestrial water storage, obtaining four sets of TWSC,
which were compared with TWSC derived from GRACE. The results
show that the TWSC estimated by the SS method based on GLDAS is
most consistent with the results of GRACE. The time-lag effect
was identified in the TWSC estimated by the PER method based on
ERA5 and GLDAS, respectively, with 2-month and 3-month lags.
Therefore, based on the GLDAS, the SS method was used to further
explore the long-term temporal and spatial evolution of TWSC in
the YZRB. During the period of 1948-2017, TWSC showed a
significantly increasing trend; however, an abrupt change in
TWSC was detected around 2002. That is, TWSC showed a
significantly increasing trend before 2002 (slope = 0.0236
mm/month, p < 0.01) but a significantly decreasing trend (slope
= -0.397 mm/month, p < 0.01) after 2002. Additional attribution
analysis on the abrupt change in TWSC before and after 2002 was
conducted, indicating that, compared with the snow water
equivalent, the soil moisture dominated the long-term variation
of TWSC. In terms of spatial distribution, TWSC showed a large
spatial heterogeneity, mainly in the middle reaches with a high
intensity of human activities and the Parlung Zangbo River
Basin, distributed with great glaciers. The results obtained in
this study can provide reliable data support and technical means
for exploring the spatio-temporal evolution mechanism of
terrestrial water storage in data-scarce alpine regions.}",
doi = {10.3390/rs13122356},
adsurl = {https://ui.adsabs.harvard.edu/abs/2021RemS...13.2356W},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
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