Remote Sensing,
Год журнала:
2024,
Номер
16(23), С. 4566 - 4566
Опубликована: Дек. 5, 2024
The
Gravity
Recovery
and
Climate
Experiment
(GRACE)
enables
large-scale
monitoring
of
terrestrial
water
storage
changes,
significantly
contributing
to
hydrology
related
fields.
However,
the
coarse
resolution
groundwater
anomaly
(GWSA)
data
limits
local-scale
research
utilizing
GRACE
GRACE-FO
missions.
In
this
study,
we
develop
a
regional
downscaling
model
based
on
linear
regression
relationship
between
GWSA
environmental
variables,
reducing
grid
obtained
from
approximately
25
km
1
km.
First,
estimate
missing
values
monthly
continuous
(TWSA)
for
period
2003
2020
using
interpolated
multi-channel
singular
spectrum
analysis
(IMSSA).
Next,
apply
balance
equation
separate
TWSA,
which
is
provided
jointly
by
Global
Land
Data
Assimilation
System
(GLDAS)
distributed
ecohydrological
ESSI-3.
We
then
employ
partial
least
squares
(PLSR)
identify
most
significant
variables
GWSA.
Precipitation
(Prec),
normalized
difference
vegetation
index
(NDVI),
actual
evapotranspiration
(AET),
with
variable
importance
in
projection
(VIP)
greater
than
1.0,
are
recognized
as
effective
reconstructing
long-term,
high-resolution
changes.
Finally,
downscale
reconstruct
long-term
(2003–2020),
(1
×
km)
Songhua
River
Basin
fused
supplemented
GRACE/GRACE-FO
data,
employing
either
geographically
weighted
(GWR)
or
random
forest
(RF)
models.
results
demonstrate
superior
performance
GWR
(CC
=
0.995,
NSE
0.989,
RMSE
2.505
mm)
compared
RF
downscaling.
downscaled
not
only
achieves
high
spatial
but
also
exhibits
improved
accuracy
when
situ
observation
records.
This
enhances
understanding
spatiotemporal
variations
due
local
agricultural
industrial
use,
providing
scientific
basis
resource
management.
Scientific Reports,
Год журнала:
2025,
Номер
15(1)
Опубликована: Апрель 26, 2025
Groundwater
serves
as
a
critical
freshwater
reservoir
globally,
essential
for
ecosystem
conservation
and
human
well-being.
Drought
conditions
adversely
impact
groundwater
systems
by
first
reducing
recharge,
followed
declines
in
levels
withdrawal
potential,
which
can
result
agricultural
setbacks
irreversible
consequences
such
land
subsidence.
The
introduction
of
the
Gravity
Recovery
Climate
Experiment
(GRACE)
project
marked
significant
advancement
monitoring
terrestrial
water
storage
anomalies
(TWSA),
encompassing
both
surface
subsurface
water.
Traditional
methods
assessing
(GWSA),
piezometric
wells,
have
proven
to
be
costly
inefficient,
often
lacking
sufficient
spatial
temporal
coverage.
Although
GRACE
data
offers
valuable
insights,
its
large-scale
nature
presents
challenges
localized
basin
aquifer
studies,
compounded
gaps
resulting
from
15-month
interruption
during
transition
GRACE-FO
project.
This
study
investigates
status
across
six
major
river
basins
Iran
utilizing
complementary
Global
Land
Data
Assimilation
System
(GLDAS)
over
255-month
period
2002
2023.
Extreme
Gradient
Boosting
(XGBoost)
algorithm
is
employed
downscaling
TWSA
resolution
0.25°,
achieving
high
Pearson
correlation
(R)
0.99
root
mean
square
error
(RMSE)
22
mm.
downscaled
GWSA,
derived
balance
equation,
exhibits
an
average
0.93
RMSE
39
mm
with
observational
data.
Following
application
Seasonal
Autoregressive
Integrated
Moving
Average
(SARIMA)
model
fill
GWSA
time
series
gaps,
this
models
forecasts
trends
through
2030
using
historical
SSP2
scenario
projections
canESM5
climate
model.
Results
indicate
depletion
29
cm
per
year
Iran's
aquifers
2023,
Caspian
Sea
experiencing
most
decline.
Index
(GGDI)
calculated
compared
Standardized
Precipitation
(SPI),
revealing
8-month
lag
drought
propagation
meteorological
sources
Iran.
Furthermore,
correlations
between
GGDI
teleconnection
indices
highlight
their
substantial
influence
on
adjacent
sources.
results
study,
emphasizing
reliability
satellite
machine
learning
monitoring,
assist
policymakers
enhancing
resource
management,
strategic
planning,
identifying
basins,
particularly
regions
limited
Hydrology,
Год журнала:
2025,
Номер
12(5), С. 105 - 105
Опубликована: Апрель 28, 2025
Terrestrial
water
storage
(TWS)
in
the
Qaidam
Basin
western
China
is
highly
sensitive
to
climate
change.
The
GRACE
mascon
products
provide
variations
of
TWS
anomalies
(TWSAs),
greatly
facilitating
exploration
dynamics.
However,
main
meteorological
factors
affecting
TWSA
dynamics
this
region
need
be
comprehensively
investigated.
In
study,
TWSAs
over
from
2002
2024
were
analyzed
using
three
with
CSR,
JPL,
and
GSFC.
groundwater
(GWAs)
extracted
through
GLDAS
products.
impact
elements
on
GWAs
was
identified.
results
showed
that
a
significant
increasing
trend
rate
0.51
±
0.13
mm
per
month
across
entire
basin
2003
2016.
part
accounted
for
largest
proportion
contributor
increase
basin.
addition
dominant
role
precipitation,
other
elements,
particularly
air
humidity
solar
radiation,
also
identified
as
important
contributors
GWA
variations.
This
study
highlighted
climatic
effect
variations,
which
have
implications
local
resource
management
ecological
conservation
under
ongoing
Remote Sensing,
Год журнала:
2024,
Номер
16(22), С. 4173 - 4173
Опубликована: Ноя. 8, 2024
Gravity
data,
comprising
a
key
foundational
dataset,
are
crucial
for
various
research,
including
land
subsidence
monitoring,
geological
exploration,
and
navigational
positioning.
However,
the
collection
of
gravity
data
in
specific
regions
is
difficult
because
environmental,
technical,
economic
constraints,
resulting
non-uniform
distribution
observational
data.
Traditionally,
interpolation
methods
such
as
Kriging
have
been
widely
used
to
deal
with
gaps;
however,
their
predictive
accuracy
sparse
still
needs
improvement.
In
recent
years,
rapid
development
artificial
intelligence
has
opened
up
new
opportunity
prediction.
this
study,
utilizing
EGM2008
satellite
model,
we
conducted
comprehensive
analysis
three
machine
learning
algorithms—random
forest,
support
vector
machine,
recurrent
neural
network—and
compared
performances
against
traditional
method.
The
results
indicate
that
exhibit
marked
advantage
prediction,
significantly
enhancing
accuracy.
International Journal of Remote Sensing,
Год журнала:
2024,
Номер
unknown, С. 1 - 29
Опубликована: Дек. 4, 2024
The
Gravity
Recovery
and
Climate
Experiment
(GRACE)
GRACE
Follow-On
(GRACE-FO)
data
have
been
widely
used
to
monitor
analyze
extreme
hydrological
events
globally.
However,
their
coarse
spatial
resolution
limits
application
in
small-
medium-scale
regions.
In
this
study,
we
proposed
a
partitioned
random
forest
downscaling
(PRFD)
strategy
improve
the
of
GRACE/GRACE-FO
quantitatively
assessed
performance
using
closed-loop
simulation
experiment.
Our
enhanced
approach
improved
from
1°to
0.1°,
downscaled
were
characterize
2022
drought
Yangtze
River
basin
(YRB),
with
particular
on
smaller
(i.e.
Wu
basin,
WRB).
findings
show
that
PRFD
reduced
root
mean
square
error
by
39.29%
compared
traditional
over
RF
(ORFD),
27.8%
grid
points
showed
significantly
accuracy
improvements.
results
provided
more
detailed
depiction
YRB,
allowing
for
precision
identification
onset,
extent
severity,
accurate
assessment
impacts
WRB.
originated
northern
WRB,
gradually
extending
southward
across
severe
conditions
north
than
south.
High
temperatures
low
precipitation
primary
drives,
while
elevated
high
human
water
use
also
contributed.
This
study
provides
valuable
technique
understanding
regional-scale
areas.
