Flash Flood Simulation for Hilly Reservoirs Considering Upstream Reservoirs—A Case Study of Moushan Reservoir
Sustainability,
Год журнала:
2024,
Номер
16(12), С. 5001 - 5001
Опубликована: Июнь 12, 2024
With
the
advancement
of
society
and
impact
various
factors
such
as
climate
change,
surface
conditions,
human
activities,
there
has
been
a
significant
increase
in
frequency
extreme
rainfall
events,
leading
to
substantial
losses
from
flood
disasters.
The
presence
numerous
small
medium-sized
water
conservancy
projects
basin
plays
crucial
role
influencing
runoff
production
rainwater
confluence.
However,
due
lack
extensive
historical
hydrological
data
for
simulation
purposes,
it
is
challenging
accurately
predict
floods
basin.
Therefore,
growing
emphasis
on
forecasting
that
takes
into
account
influence
upstream
projects.
Moushan
Reservoir
located
hilly
area
an
arid
semi-arid
region
north
China.
Flooding
characteristics
sudden
strong,
short
confluence
time,
steep
rise,
fall,
especially
caused
by
weather
which
have
high
wide
range
hazards,
become
one
most
threatening
natural
disasters
life
property
safety.
There
are
many
reservoirs
this
basin,
accuracy
prediction.
taking
example,
paper
puts
forward
flash
method
areas,
considering
reservoirs,
can
better
solve
problem
accuracy.
Using
virtual
aggregation
method,
3
93
summarized
7
aggregated
reservoirs.
Then,
we
construct
model
combining
two
sets
with
different
generation
mechanisms.
Finally,
after
calibration
verification,
results
methods
analyzed
terms
peak
discharge
error,
depth
difference
certainty
coefficient.
indicate
flooding
processes
simulated
proposed
line
observed
ones.
errors
ranges
2.3%
15%
0.1%
19.6%,
respectively,
meeting
requirements
Class
B
“Water
Forecast
Code”.
Method
set
1
demonstrates
average
error
5.63%.
All
these
findings
illustrate
developed
model,
utilizing
aggregate
dynamic
parameters
reflect
regulation
storage
functions,
effectively
capture
This
approach
addresses
challenges
simulating
facilitating
basin-wide
Язык: Английский
A Copula Function–Monte Carlo Method-Based Assessment of the Risk of Agricultural Water Demand in Xinjiang, China
Agriculture,
Год журнала:
2024,
Номер
14(11), С. 2000 - 2000
Опубликована: Ноя. 7, 2024
Agricultural
water
resources
in
Xinjiang,
China,
face
significant
supply
and
demand
contradictions.
risk
is
a
key
factor
impacting
resource
management.
This
study
employs
the
copula
function
(CF)
Monte
Carlo
(MC)
methods
to
evaluate
agricultural
at
66
stations
Xinjiang.
The
evaluation
based
on
marginal
distributions
of
precipitation
(PR)
reference
evapotranspiration
(RET).
findings
classify
Xinjiang’s
precipitation–evapotranspiration
relationship
into
three
types:
evapotranspiration,
precipitation,
transition.
Regions
south
Tianshan
Mountains
(TMs)
primarily
exhibit
characteristics.
Ili
River
Valley
areas
north
TMs
display
Other
have
transitional
Both
annual
RET
Xinjiang
follow
Generalized
Extreme
Value
(GEV)
distribution.
Frank
CF
effectively
describes
coupling
between
RET,
revealing
negative
correlation.
correlation
stronger
weaker
south.
varies
significantly
across
regions,
with
precipitation–RET
being
crucial
influencing
factor.
index
(DI)
for
decreases
as
probability
(RP)
increases.
stability
DI
greatest
evapotranspiration-type
followed
by
transition-type,
weakest
precipitation-type
regions.
When
RP
constant,
order
transition,
types.
quantifies
spatial
pattern
advantage
CF–MC
method
lies
its
ability
assess
this
without
needing
crop
planting
structures
variations.
However,
it
less
effective
few
meteorological
or
short
monitoring
periods.
Future
efforts
should
focus
accurately
assessing
data-deficient
areas.
are
guiding
regulation
efficient
use
Язык: Английский