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11/18/2016
1
Manisha MAHARJANGraduate School of Engineering
Kyoto University
15 November 20161
Outline
�Background
�Study Area
�Methodology
�Results and Discussion
�Conclusion
2
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2
Background
� Chi River Basin is one of the important river basins in Thailand with two large
reservoirs Nam Phong (Ubol Ratana) and Lam Pao
� Floods and drought are the main issues: High intensity rainfall in the upper part is
causing a quick runoff response and results in flash flood, whilst on flat areas
downstream it causes stagnant flood
� Changing future climate might threaten the water availability especially in low
flow 3
Study Area
4
Location: Northeast of Thailand
Area: 49,477 km2
Groundwater potential: 5,008 million m3
Population: 4.1 million inhabitants
Irrigated area: 4,530 km2
Rainfall: 1,000 – 1,400 mm
Annual discharge: 12,000 million m3
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3
Study Area
5
Ubol Ratana Dam (1985-1986):
Earth core Rock Fill dam
Catchment area: 12,104 km2
Maximum Discharge: 3500m3/s
Maximum height: 186m
Elevation: 1880 m above MSL
Maximum storage capacity: 2,559 million m3
Multipurpose dam: Electricity generation,
irrigation, flood control, transportation, fisheries and as tourist attraction
Lam Pao Dam (1963-1968):
Earth Dam
Storage: 1,430 million m³
Purpose: Flood prevention and Agriculture
Water Resources Related Problems
Drought
Flood:
� high intensity rainfall;
� high discharge from reservoirs;
� inappropriate development in
floodplain;
� deforestation;
� expansion of agriculture and
settlement.
Others:
� domestic and industrial sewage;
� low soil fertility;
� high rates of erosion.
6
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4
Data Collected for Chi River Basin
7
No. Data Resolution Year Source
1.Topographical Maps
1:50,000 Royal Thai Survey Department
2.Digital elevation model
90 m Royal Thai Survey Department
3. Land use map 30 m 2005Thailand Land Development Department
4. Soil map 30 m 2001Thailand Land Development Department
5.Meteorological and Hydrological Data
1981-2011
Thai Meteorological Department
Mean Temperature and Precipitation for the period 1981-2011
0
50
100
150
200
250
300
1 2 3 4 5 6 7 8 9 10 11 12
Mea
n P
reci
pit
ati
on
(m
m)
Month
Khonkara Chaiyaph Roiettmd
• Station Chaiyaph has comparatively
lower value of mean temperature
and amount of precipitation
8
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5
Trend analysis of annual mean temperature
9
y = 0.0038x + 19.802
26
26.5
27
27.5
28
28.5
29
29.5
30
1980 1990 2000 2010 2020
Ave
rag
e A
nn
ua
l T
em
pe
ratu
re
(oC
)
Khonkaen
y = 0.0196x - 11.86
26.5
27
27.5
28
28.5
29
29.5
30
1980 1990 2000 2010 2020
Ave
rag
e A
nn
ua
l T
em
pe
ratu
re
(oC
)
Roiet
y = 0.0164x - 4.8805
26.5
27
27.5
28
28.5
29
29.5
30
1980 1990 2000 2010 2020
Ave
rag
e A
nn
ua
l T
em
pe
ratu
re
(oC
)
Chaiyaph
• Trend of temperature is constant
at Khon Kaen Station over the
period 1981-2011
• Trend of temperature is linearly
increasing at stations Chaiyaph
and Roiet over the period 1981-
2011
Trend analysis of annual precipitation
10
y = 11.23x - 21336
0
200
400
600
800
1000
1200
1400
1600
1800
2000
1980 1990 2000 2010 2020
An
nu
al
Pre
cip
ita
tio
n (
mm
) Khonkaen
y = 8.3642x - 15576
0
200
400
600
800
1000
1200
1400
1600
1800
2000
1980 1990 2000 2010 2020
An
nu
al
Pre
cip
ita
tio
n (
mm
)
Chaiyaph
y = 3.5627x - 5762.2
0
200
400
600
800
1000
1200
1400
1600
1800
2000
1980 1990 2000 2010 2020
An
nu
al
Pre
cip
ita
tio
n (
mm
)
Roiet
• Trend of amount of annual
precipitation is increasing
• Only slight increase in annual
precipitation is observed in Roiet
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Methodology
11
RCM
Outputs
Downscaled
to station
level
Analysis of future
climate projections
Downscaling
Technique
• Meteorological data
• Land use data
• Soil properties data
• Crop data
• DEM data
Calibration
and
Validation
of SWAT
model
Hydrological
Response
Units
Assessment of
impact of future
climate on water
resources
12
RCM Derived from Institute Resolution Historical
Run
Future
Simulation
Scenarios
HADGEM3-
RA
HADGEM2
GCM-AO
Met Office
Hadley Center
under Cordex
East Asia Project
0.44o×0.44o 1950-2005 2006-2100 Historical
RCP4.5
RCP8.5
Climate Projection
� RCP 4.5 scenario is a stabilization
scenario in which total radiative forcing
is stabilized before 2100 through the
employment of a range of technologies
and strategies for reducing greenhouse
gas emissions
� RCP 8.5 scenario is characterized by
increasing greenhouse gas emissions
over time and is representative of
scenarios in the literature which result
in high greenhouse gas concentrationlevels
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7
13
Bias Correction: Quantile mapping � First the ranked precipitation or temperature distribution is divided into number
of discrete quantiles
� Linear correction factor is calculated by dividing the mean observation by the
simulated mean precipitation or temperature for that same quantile which is used as a
transfer function
� Monthly quantile distribution function is used for the bias correction of temperature
and precipitation. The performance of the bias correction method is evaluated using
statistical parameters such as coefficient of determination, root mean square and
standard deviation.
Xo and Xm are observed and modeled variables as temperature orprecipitation and h is the transformation defined as,
Where, Fm is cumulative distribution function of ��
and ��
−1 is the inverse cumulative distribution function also
known as quantile function which corresponds to �0
Change in temperature climate indices in different stations
14
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8
Change in temperature climate indices in different stations
15
• In case of Far Future, variation in range of indices is increased
significantly showing more variation in future periods.
Projected precipitation climate indices anomalies across 27 stations
Near Future Mid Future Far Future
RCP 4.5 RCP 8.5 RCP 4.5 RCP 8.5 RCP 4.5 RCP 8.5
16
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9
Projected precipitation climate indices anomalies across 27 stations
Near Future Mid Future Far Future
17
• Increase in median value of indices related to wet events (Prcptot,
pq95TOT and px5d) but both increase and decrease in median value of
index related to dry event (CDD).
Application of Soil and Water Assessment Tool (SWAT) Model
18
Legend
SwatSoilClass(LandSoils1)
Classes
soil-20
soil-35
soil-18
soil-36
soil-17
soil-49
soil-4
soil-44
soil-40
soil-6
soil-56
soil-62
soil-1
soil-25
soil-38
soil-31
soil-22
soil-55
soil-33
soil-7
soil-48
soil-19
soil-47
soil-24
soil-41
soil-3
soil-29
soil-59
soil-21
soil-2
soil-15
soil-46
soil-5
soil-28
soil-52
soil-60
soil-61
soil-26
soil-50
soil-51
Land use
Slope class Basin delineation
Soil class
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10
Calibration and Validation
19
0
200
400
600
800
1000
1200
1400
1600
1800
Dis
ch
arg
e (
m3/s
)
Observed
Simulated
NSE = 0.82
PBIAS = -13.21 %NSE = 0.73
PBIAS = 4.04 %
Calibration Period Validation Period
Daily observed and simulated discharge for calibration and validation periods at E66A station
Impact of climate change on discharge
20
0
200
400
600
800
1000
1200
J F M A M J J A S O N D
Ave
rag
e m
on
thly
dis
cha
rge
(m3/s
)
1981-2005
2016-2040_4.5
2046-2070_4.5
2076-2100_4.5
0
200
400
600
800
1000
1200
J F M A M J J A S O N D
Ave
rag
e m
on
thly
dis
cha
rge
(m3/s
)
1981-2005
2016-2040_8.5
2046-2070_8.5
2076-2100_8.5
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11
Conclusion
21
� Increase in temperature is higher under RCP 8.5 relatively higher than
under RCP 4.5
� Hot days are going to be hotter and cold nights are expected to be warmer
� Change in precipitation is remarkably higher in the late century period
under RCP 8.5
� Increase in mean annual runoff in both RCP 4.5 and 8.5
� Increase in water availability in wet season RCP 4.5 and 8.5
Thank you for your attention !!
Manisha [email protected]
22