tasuku kato1 and ryota tsuchiya2swat.tamu.edu/media/114726/b1-3-kato.pdfpaddy fields is the major...
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![Page 1: Tasuku KATO1 and Ryota TSUCHIYA2swat.tamu.edu/media/114726/b1-3-kato.pdfPaddy fields is the major land use in Monsoon Asian countries. However, it is difficult to apply hydrological](https://reader030.vdocuments.site/reader030/viewer/2022011801/5ae2fa9d7f8b9a495c8ca997/html5/thumbnails/1.jpg)
Tasuku KATO1 and Ryota TSUCHIYA2
1. Associate Prof. TUAT. Email:
[email protected] 2. Graduate student,
TUAT.
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Paddy fields is the major land use in Monsoon Asian countries.
However, it is difficult to apply hydrological models like SWAT for watershed management, because irrigation water use in paddy fields is too complicated to illustrate hydrological processes.
SWAT is applicable for the simulation of observation data, but uncertainty is large then evaluation on land and water management is difficult.
This uncertainty is coming from model structure that is not match with paddy hydrological process.
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To improve surface discharge process in SWAT
both pothole module and new development
module
To understand lateral flow process in small
scale paddy plots with observation data
Methods• Analysis on water & nutrients budget in paddy plots
• Implementation on pot hole option and uncertainty
analysis
• Analysis on lateral flow process, and consider
implementation idea
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Surface flow◦ Xie and Cui, 2011
Pot hole module application to paddy
◦ Boulange et al., 2014
Surface discharge on pesticide
Ground water flow◦ Kim et al., 2003
SWAT-MODFLOW combination
Surface and Lateral flow◦ Kang et. al. 2006.
◦ Sakaguchi et al. 2014 Modified pothole module for paddy application
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Evapo-
transpiration
Rainfall
Ground Water Flow
Lateral Flow
Surface Flow
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Recharge from river
Discharge from background land
use
Irrigatio
n Surface
Drainag
e
RiverBuffering
function:
Storage in ground
Evapo-
transpiration
Rainfall
Drainage
Paddy fields
Lateral
Flow
Buffering function
in surface
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Lateral InflowLateral Outflow
irrigation
Rainfall ET
Interactio
n
Interactio
n
This discharge
process is highly
influenced with flooded
water level/ percolation
rate
Percolatio
n
Current
Model
improvement
Infiltration
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Paddy field SWAT (pothole module)SWAT (CN)
Ra
infa
ll
Irri
ga
tio
n
Ra
infa
ll
Irri
ga
tio
n
Ra
infa
ll
Irri
ga
tio
n
RunoffRunoff
Current proposed model in paddy fields
Runoff
• Runoff as fraction of
rainfall
• Runoff as overflow
• Cone shaped
• Seepage when soil
moisture below field
capacity
• Runoff as overflow
• Cuboid shaped
• Seepage until
saturation
Seepage Constant rate
Seepage
Modification
by Sakaguchi
et al. (2014)
Slower responseQuick response Medium response
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• Location: western of
Tokyo, in Chiba
prefecture.
• Basin area 494km2
• Population 769,000
• Enclosed water
body
• Multi purpose water
resources
Imba
Lake
Imba
Lake
Monitoring point
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166 km2
7m-40m height
Land use data
Soil data
DEM
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Landscape, Landuse, and soil data show quite
similar distribution.
Soil data in deep layers are uniform in whole
watershed, but surface soil layer is difference.
Paddy fields are located in along the riverside, and
generate soil for long term rice cultivation.
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◆Continuous monitoring
Water level, water quality (daily sampling)
Index
pH
Electric Conductivity (EC)
Suspended Solid (SS)
Total Nitrogen (T-N)
Total Phosphorous (T-P)
Nitrate Nitrogen (NO3-N)
Develop Rating Curve
Hydrological measurement
Water depth
Discharge (Rating curve)
Water depth logger
Weather data (Evaporation estimation)
Q=aH b
Water pressure gauge
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Calibrated model (Curve Number)
16
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Calibrated model (Pothole)
17
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Calibrated model (Modified based on pothole)
18
irrigation water was applied
below threshold water level
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P.
1
P.
2
19
• No significance differences in performances
• Modified model have better band during low flow period
Model p-factor r-factor
Best simulation
RSR NSE PBIAS
SWAT with CN 93% 0.73 0.71 0.5 0.7%
SWAT with pothole 88% 0.54 0.69 0.5 -3.8%
Modified SWAT 88% 0.43 0.70 0.5 -0.5%
Satisfactory criteria > 50% < 1 < 0.7 > 0.5 -25% ~ 25%
Uncertainty of observed data can be explained well by simulation
Relatively small error
Simulation fit the dynamics of observed data
No over/under-estimation
How much observed data bracketed by the
uncertainty band?
How narrow the
uncertainty band?
How large the
error?
How the simulation
can represent the
dynamic change of
observed data?
Is there any
systematic
underestimation/
overestimation?
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Model improvement was focused on a surface
process.
Discharge from surface water buffered temporally
and small, then, perpetual fluctuation was
represented.
In actual discharge process, lateral flow from
paddy fields would be more crucial factor.
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Currently, infiltration rate was settled as static
As a real process in paddy, infiltration process is
influenced with percolation and lateral flow
Lateral Outflow
(Almost surface
flow)
Interactio
n This discharge process is highly
influenced with flooded water level/
percolation rate
Percolatio
n
Infiltration
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Irrigation period
(Apr-Aug)
Non-irrigation period
(Sep-Mar)
BG
Dr
Ir
Rc
Ir
Paddy
Sw
Δ17.9
Study
Area
24.6
P
rET
33.217.0
25.5
4.9
4.1
43.4
52.6
ET:Evapotranspiration, Pr:Rainfall, Ir:Irrigation, Dr:Dranage,
Sw:Basin storage, Rc: Recharge from river BG: Background
discharge
Paddy
No
cultivated
0.1
Sw
+11.0
42.2
PrET
Ir
Inflow
(B+C+D
)
Outflow
A
4.1
22.2
9.5
14.5 47.9
63.9
◆Water Balance Equation
Basin scale Q(Rc)-Q(BG)-Q(Dr)+Q(P)+Q(Ir)-Q(ET)=ΔSw
River scale Qin(B+C+D)–Qout(A)-Q(Ir)-Q(Rc)+Q(BG)+Q(D)= 0
unit: 105m3/month
Study
Area
RiverRiver
Inflow
(B+C+D
)
Outflow
A
Other
Landuse(all hydro process)
Other
Landuse(all hydro process)
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Paddy fields: (under development)
Infiltration (flood to soil) is less than percolation
(soil to soil), then, lateral flow is increased.
◦ lateral flow in open condition would be discharged
within 1-several days.
Background landuse: (not consider yet)
It would be increased ground water level, then,
background discharge process would be
prevented.◦ In condition of paddy filed along riverside location,
ground water travelling time would be longer in
irrigation period.
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Surface flooding
• Water and material balance sub-
models are developed .
• Flood depth control activities
• Puddling, as the tillage operation
under the flooded condition, was
developed.
PER
C0
PER
C1
PER
C2
Percolation
• Percolation (PERC1, PERC2, …)
from a soil layer to the next layer is
limited to a value lower than the
value of PERC0,
Lateral Flow
• In pothole module, lateral flow from
surface layer were excess
• This implementation would be
effective increase discharge from
multiple layers
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1. Surface buffering process was considered◦ Pothole module, implementation pothole module are not
enough for fully understanding on hydro process
2. High ground water level would be influenced with
percolation and lateral flow
3. Paddy fields location along riverside would
possibly delayed ground water discharge from
background landuse.
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Date: October 19–23, 2015Venue: Tsukuba Bioscience Hall (TBH),Japan
Abstarct submit: end of August (250-350 words)
Organized by:Monsoon Asia Agro-Environmental Research Consortium (MARCO), National Institute for Agro-Environmental Sciences (NIAES), Japan International Research Center for Agricultural Sciences (JIRCAS) (to be confirmed)
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Narita
Tokyo
Akihabara
Haneda
Tsukuba Express