Sustainability,
Год журнала:
2022,
Номер
14(21), С. 13719 - 13719
Опубликована: Окт. 22, 2022
Integrated
assessment
of
the
water
environment
has
become
widespread
in
many
rivers,
lakes,
and
reservoirs;
however,
aquatic
organisms
freshwater
are
often
overlooked
this
process.
Zooplankton,
as
primary
consumers,
sensitive
responsive
to
changes
environment.
Water
zooplankton
samples
were
collected
on-site
at
Shanxi
Reservoir
quarterly
determine
12
environmental
indicators
quantify
abundance
Cladocera,
Copepoda
Rotifera
by
using
ZooScan
image-scanning
analysis
system,
combined
with
OLYMPUS
BX51
machine
learning
recognition
classification.
The
aim
was
explore
relationship
between
factors
through
their
spatial
temporal
heterogeneity.
Through
principal
component
analysis,
redundancy
cluster
variations
driving
population
growth
different
seasons
could
be
identified.
At
same
time,
taxa
can
form
clusters
related
during
abundant
period
summer
dry
winter.
Based
on
long-term
monitoring,
used
a
comprehensive
indicator
for
ecological
health
evaluation,
well
providing
scientific
support
regional
resources
deployment
management.
Geoscientific model development,
Год журнала:
2023,
Номер
16(14), С. 4315 - 4329
Опубликована: Июль 28, 2023
Abstract.
Autocalibration
techniques
have
the
potential
to
enhance
efficiency
and
accuracy
of
intricate
process-based
hydrodynamic
water
quality
models.
In
this
study,
we
developed
a
new
R-based
autocalibration
toolkit
for
Environmental
Fluid
Dynamics
Code
(EFDC)
implemented
it
into
recalibration
Yuqiao
Reservoir
Water
Quality
Model
(YRWQM),
with
long-term
observations
from
2006
2015,
including
dry,
normal,
wet
years.
The
facilitated
contributed
exploring
how
model
recalibrated
performs
more
accurately
robustly.
Previously,
original
YRWQM
was
calibrated
validated
dry
years
in
2007,
respectively.
Compared
YRWQM,
performed
just
as
well
surface
elevation,
Kling–Gupta
(KGE)
0.99,
temperature,
KGE
0.91,
while
performing
better
modeling
total
phosphorus
(TP),
chlorophyll
(Chl
a),
dissolved
oxygen
(DO),
KGEs
0.10,
0.30,
0.74,
Furthermore,
improved
by
43
%–202
%
TP–Chl
a–DO
process
when
compared
models
only
overestimated
DO
concentrations,
probably
explained
parameter
algal
growth
rate
that
increased
84
%.
poorly
Chl
a,
due
50
reduction
carbon-to-chlorophyll
ratio,
triggered
changes
composition
population.
Our
study
suggests
calibrating
may
be
an
important
measure
improve
robustness
under
severe
hydrological
variability.
newly
general
automatic
calibration
possible
hierarchical
strategy
will
also
powerful
tool
future
complex
calibration.
