Mon Dec 15, F. Flechtner
• Sorted by Date • Sorted by Last Name of First Author •
Li, Houpu, Chao, Nengfang, and Bian, Shaofeng, 2026. Integrating GNSS 3D deformation and GRACE/GRACE-FO gravity observations for terrestrial water storage changes and drought monitoring in Southwest China. Journal of Hydrology, 665:134654, doi:10.1016/j.jhydrol.2025.134654.
• from the NASA Astrophysics Data System • by the DOI System •
@ARTICLE{2026JHyd..66534654L,
author = {{Li}, Houpu and {Chao}, Nengfang and {Bian}, Shaofeng},
title = "{Integrating GNSS 3D deformation and GRACE/GRACE-FO gravity observations for terrestrial water storage changes and drought monitoring in Southwest China}",
journal = {Journal of Hydrology},
keywords = {Hydrogeodesy, Multi-sensor fusion, GNSS, GRACE/GRACE-FO, Terrestrial water storage changes},
year = 2026,
month = feb,
volume = {665},
eid = {134654},
pages = {134654},
abstract = "{This study, for the first time, integrates the horizontal and vertical
(3D) Global Navigation Satellite System (GNSS) displacements and
the Gravity Recovery and Climate Experiment (GRACE) and its
Follow-on mission (GRACE Follow-on, GRACE-FO) observations to
derive terrestrial water storage (TWS) changes. Three different
fusion methods are used to derive daily and monthly TWS changes
in southwestern China. The study also analyzes the
spatiotemporal characteristics of droughts using these
integrated TWS changes. The results show that using only GNSS
vertical displacement reduces the root mean square error of TWS
changes by 28 \% compared to the Slepian basis function when
using Green's function inversion. The improvement increases to
43 \% when both horizontal and vertical displacements are
incorporated. Among the three fusion methods, the virtual
station method performs the best due to its significant
improvement in the spatial distribution of GNSS stations. The
priori information fusion method is particularly advantageous in
enabling daily TWS changes. The drought index derived from the
daily fused TWS changes is below {\ensuremath{-}}1.3 during the
second half of 2022─2023, indicating the most severe drought
period in southwestern China. The findings of this study provide
new data and technical support for monitoring TWS changes by
integrating multi-source satellite observations.}",
doi = {10.1016/j.jhydrol.2025.134654},
adsurl = {https://ui.adsabs.harvard.edu/abs/2026JHyd..66534654L},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
Generated by
bib2html_grace.pl
(written by Patrick Riley
modified for this page by Volker Klemann) on
Mon Dec 15, 2025 18:11:59
GRACE-FO
Mon Dec 15, F. Flechtner