Mon Oct 13, F. Flechtner
• Sorted by Date • Sorted by Last Name of First Author •
Liu, Chuanqi, Zhang, Zhijie, Xu, Chi, and Zhang, Wanchang, 2024. Reconstructing Long-Term, High-Resolution Groundwater Storage Changes in the Songhua River Basin Using Supplemented GRACE and GRACE-FO Data. Remote Sensing, 16(23):4566, doi:10.3390/rs16234566.
• from the NASA Astrophysics Data System • by the DOI System •
@ARTICLE{2024RemS...16.4566L,
author = {{Liu}, Chuanqi and {Zhang}, Zhijie and {Xu}, Chi and {Zhang}, Wanchang},
title = "{Reconstructing Long-Term, High-Resolution Groundwater Storage Changes in the Songhua River Basin Using Supplemented GRACE and GRACE-FO Data}",
journal = {Remote Sensing},
keywords = {GRACE, GWSA, downscaling method, Songhua River Basin, ESSI-3 model},
year = 2024,
month = dec,
volume = {16},
number = {23},
eid = {4566},
pages = {4566},
abstract = "{The Gravity Recovery and Climate Experiment (GRACE) enables large-scale
monitoring of terrestrial water storage changes, significantly
contributing to hydrology and related fields. However, the
coarse resolution of groundwater storage anomaly (GWSA) data
limits local-scale research utilizing GRACE and GRACE-FO
missions. In this study, we develop a regional downscaling model
based on the linear regression relationship between GWSA and
environmental variables, reducing the grid resolution of GWSA
obtained from GRACE from approximately 25 km to 1 km. First, we
estimate the missing values of monthly continuous terrestrial
water storage anomaly (TWSA) for the period from 2003 to 2020
using interpolated multi-channel singular spectrum analysis
(IMSSA). Next, we apply the water balance equation to separate
GWSA from TWSA, which is provided jointly by the Global Land
Data Assimilation System (GLDAS) and the distributed
ecohydrological model ESSI-3. We then employ a partial least
squares regression (PLSR) model to identify the most significant
environmental variables related to GWSA. Precipitation (Prec),
normalized difference vegetation index (NDVI), and actual
evapotranspiration (AET), with variable importance in projection
(VIP) values greater than 1.0, are recognized as effective
variables for reconstructing long-term, high-resolution
groundwater storage changes. Finally, we downscale and
reconstruct the long-term (2003{\textendash}2020), high-
resolution (1 km {\texttimes} 1 km) monthly GWSA in the Songhua
River Basin using fused and supplemented GRACE/GRACE-FO data,
employing either geographically weighted regression (GWR) or
random forest (RF) models. The results demonstrate superior
performance of the GWR model (CC = 0.995, NSE = 0.989, RMSE =
2.505 mm) compared to the RF model in downscaling. The
downscaled GWSA in the Songhua River Basin not only achieves
high spatial resolution but also exhibits improved accuracy when
compared to in situ groundwater observation records. This
research enhances understanding of spatiotemporal variations in
regional groundwater due to local agricultural and industrial
water use, providing a scientific basis for regional water
resource management.}",
doi = {10.3390/rs16234566},
adsurl = {https://ui.adsabs.harvard.edu/abs/2024RemS...16.4566L},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
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Mon Oct 13, F. Flechtner