chaiwat ekkawatpanit, weerayuth pratoomchai department of civil engineering king mongkut’s...
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Chaiwat Ekkawatpanit, Weerayuth Pratoomchai Department of Civil Engineering
King Mongkut’s University of Technology Thonburi, Bangkok, Thailand
Naota HanasakiNational Institute for Environmental Studies, Tsukuba, Japan
So KazamaTohoku University, Sendai, Japan
24-25 November, 2015
Climate Change Impact on Water Resources using Global Climate and Hydrological Model
2015 APEC Typhoon Symposium (APTS)Lessons Learned from Disastrous Typhoons
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Outline of presentation
Introduction
Objective of the study
Study area
Methodology
Results and discussion
Conclusions
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Introduction
There is a 95% (IPCC, 2013) consensus among the scientific community that climate change is real and human activity is the main cause (anthropogenic climate change)
In fact, there are uneven temporal and spatial distributions of climate change impacts ?
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Objective
This study aim to investigate the impacts of climate change on water resources in the Upper Chao Phraya River Basin in Thailand, which concerned among climatology and river discharge.
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Study area: The Upper Chao Phraya River basin (UCP)
The basin covers an area of 109,973 km2 or 22% of the country’s area
o 60.0% is foresto 35.6% is agricultural areao 4.4% is classified to other,
e.g., urban, water bodies
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Models and Data
K10 data
Hanasaki et al., 2008; Hanasaki and Mateo (2012)
Kotsuki et al., 2010
CMIP5 (GCMs data)
H08
Land Surface Module
River Routing Module
Reservoir Operation Module
Crop Growth Module
Withdrawal Module
Environmental Flow Module
Groundwater Recharge Model
Groundwater Flow Model
Groundwater Level
Groundwater Storage
Aquifer properties (T, S)
Rushton and Ward (1979)
Prickett and Lonnquist (1971)
- Rainfall- Air temperature- Wind speed- Specific humidity- Surface air pressure- Longwave downward radiation- Shortwave downward radiation
River induced infiltration
model
Q
Qn
R, E, Ro
Effective porosity
R = RainfallE = EvaporationRo = RunoffQ = River discharge
Qn = Recharge/ Discharge from riverbedQi = Recharge from infiltration
Qi
Where
Three modules that not cover in this study
7 climate variables:
Methodology (Mathematical models):
Kazama et. al. 2007
CMIP5 - Coupled Model Intercomparison Project Phase 5 5 GCMs
under 3 scenarios
RCP 2.6RCP 4.5RCP 8.5
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Land Surface Hydrology Module (LSM):
Soil water balance Energy balance
inf sm s sb
dWRa Snowf Q E Q Q
dt
4(1 ) sSW LW T lE H G
Soil water balance
Energy balance
The model was developed by Hanasaki et al., 2008; 2012; 2014
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Schematic of H08’s river module
tRivOutxAQRivInfRivSto tot )(
River Module:
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Reservoir Operations Module:
• In this study, we focused on Bhumibol and Sirikit Reservoirs only.
• In reality, reservoir operations are very complex
• We propose an idealized simple reservoir model.
• Although simple, this simulation offers good insight into river management and planning.
Bhumibol Dam
Sirikit Dam
Nakhon SawanChainat
Ayutthaya
Bangkok
Chao Phraya River Basin
N1
Y1CW21
P1
W4AY4
Y16N5A
P17 N67
C2
C13
C35Rojana
Ping
Wan
g
Yom
Nan
Pa
Sak
Chao P
hraya
Tha C
hin
Elev. (m)
0-10
10-20
20-30
30-50
50-100
100-150
500-1,000
1,000-1,500
1,500-2,000
2,000-2,572
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Climate change conditions: 5 GCMs used in this study
GCMs Institutions Resolution (lon × lat)
Original Applied in the study
MIROC-ESM-CHEM National Institute for Env. studies 2.81° × 2.81° 5.0’ × 5.0’
HadGEM2-ES Met office Hadley centre 1.87° × 1.24° 5.0’ × 5.0’
GFDL-ESM2M Geophysical fluid dynamics Lab. 2.50° × 2.00° 5.0’ × 5.0’
IPSL-CM5A-LR Institute Pierre Simon Laplace 3.75° × 1.87° 5.0’ × 5.0’
NorESM1-M Norwegian Climate Centre 2.50° × 1.87° 5.0’ × 5.0’
Used linear interpolation to interpolate the original resolution of GCM data to the study grid size of 5’ x 5’ or about 10 km x 10 km
Shifting and scaling method was used for removing systematic biases of the original GCM data (e.g., Alcamo et al., 2007; Hanasaki et al., 2013)
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Results: Model Calibration
N
Bhumipol Dam
Sirikit Dam
C.2
0
2,000
4,000
6,000
8,000
10,000
1960 1965 1970 1975 1980 1985 1990 1995 2000 2005
Annu
al Infl
ow (M
CM)
0
2,000
4,000
6,000
8,000
10,000
1970 1975 1980 1985 1990 1995 2000 2005
Annu
al Infl
ow (M
CM)
0
1,000
2,000
3,000
4,000
5,000
6,000
1950 1960 1970 1980 1990 2000 2010
Flood
pea
k (CM
S)
0
50
100
150
200
250
300
350
Jan-
86
Jan-
87
Jan-
88
Jan-
89
Jan-
90
Jan-
91
Jan-
92
Jan-
93
Jan-
94
Jan-
95
Jan-
96
Jan-
97
Jan-
98
Jan-
99
Jan-
00
Dis
char
ge (m
3se
c-1)
Observation
Simulation
P.1 (Ping River)IOA = 0.96
0
50
100
150
200
250
300
350
400
Jan-
86
Jan-
87
Jan-
88
Jan-
89
Jan-
90
Jan-
91
Jan-
92
Jan-
93
Jan-
94
Jan-
95
Jan-
96
Jan-
97
Jan-
98
Jan-
99
Jan-
00
Dis
char
ge (m
3se
c-1)
Observation
Simulation
W.4A (Wang River)IOA = 0.89
0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
Jan-
86
Jan-
87
Jan-
88
Jan-
89
Jan-
90
Jan-
91
Jan-
92
Jan-
93
Jan-
94
Jan-
95
Jan-
96
Jan-
97
Jan-
98
Jan-
99
Jan-
00
Dis
char
ge (m
3se
c-1)
Observation
Simulation
C.2 (Basin outlet)IOA = 0.93
0
100
200
300
400
500
600
700
800
Jan-
86
Jan-
87
Jan-
88
Jan-
89
Jan-
90
Jan-
91
Jan-
92
Jan-
93
Jan-
94
Jan-
95
Jan-
96
Jan-
97
Jan-
98
Jan-
99
Jan-
00
Dis
char
ge (m
3se
c-1)
Observation
Simulation
Y.6 (Yon River)IOA = 0.91
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Results: Annual mean air temperature
Current period(1986-2000)
Projection period(2026-2040)
RCP2.6average from 5 GCMs
Change(Future – Current)
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Surface Air Temperature change ( )
RCP 2.6 RCP 4.5 RCP 8.5
Results: Annual mean air temperature
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C0
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C0 C0
C00
0.5
1
1.5
2
2.5
MIROC HadGEM GFDL IPSL NorESM
Su
rfac
e ai
r te
mp
erat
ure
ch
ang
es (
°C)
RCP2.6
RCP4.5
RCP8.5
Results: Annual mean air temperature
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The increasing of surface air temperature in the near future was in a range of 0.9-2.31 which had a 25.38 as a mean annual surface air temperature. C0
C0
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Results: Surface water balance from the LSM
Average annual rainfall, evaporation, and runoff (1986-2000)
Rainfall = 987 mmEvaporation = 810 mm or 82% of annual rainfallSurface runoff = 177 mm or 18% of annual rainfall
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Results: Water balance
0
200
400
600
800
1,000
1,200
MIR
OC
Had
GE
M
GF
DL
IPS
L
Nor
ES
M
MIR
OC
Had
GE
M
GF
DL
IPS
L
Nor
ES
M
MIR
OC
Had
GE
M
GF
DL
IPS
L
Nor
ES
M
History RCP2.6 RCP4.5 RCP8.5
(mm
.) Rainfall
Runoff
Evaporation
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MIROC and NorESM GCMs showed increasing trend for all variables
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Results: Rainfall
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Current period(1986-2000)
Projection period(2026-2040) RCP2.6
average from 5 GCMs
Change(Future – Current)
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Results: Rainfall
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RCP 2.6 RCP 4.5 RCP 8.5
Annual Rainfall change
There were both increase and decrease in projected rainfall changes except RCP4.5 scenario. This scenario showed that over the whole basin rainfall might be reduced by 20 mm to 50 mm.
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Result: River discharge at Chiang Mai
0
50
100
150
200
1 2 3 4 5 6 7 8 9 10 11 12
Dis
char
ge (
m3
sec-1
)
Month
Area2 Area1
Min Max
Obs (Past) MIROC
HadGEM GFDL
IPSL NorESM
One standard deviation range
P.1 (RCP2.6)
0
50
100
150
200
1 2 3 4 5 6 7 8 9 10 11 12
Dis
char
ge (
m3
sec-1
)
Month
Area2 Area1
Min Max
Obs (Past) MIROC
HadGEM GFDL
IPSL NorESM
One standard deviation range
P.1 (RCP4.5)
0
50
100
150
200
1 2 3 4 5 6 7 8 9 10 11 12D
isch
arge
(m
3se
c-1)
Month
Area2 Area1
Min Max
Obs (Past) MIROC
HadGEM GFDL
IPSL NorESM
One standard deviation range
P.1 (RCP8.5)
From January to June, the river discharge projections from the GCMs decreased.In contrast, during the second monsoon period (August to October), river discharges in the upper area (mountainous region) showed significantly increased.
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Result: River discharge at Kampangphet
0
100
200
300
400
500
600
700
1 2 3 4 5 6 7 8 9 10 11 12
Dis
char
ge (
m3
sec-1
)
Month
Area2 Area1
Min Max
Obs (Past) MIROC
HadGEM GFDL
IPSL NorESM
One standard deviation range
P.7A(RCP2.6)
0
100
200
300
400
500
600
700
1 2 3 4 5 6 7 8 9 10 11 12
Dis
char
ge (
m3
sec-1
)
Month
Area2 Area1
Min Max
Obs (Past) MIROC
HadGEM GFDL
IPSL NorESM
One standard deviation range
P.7A(RCP4.5)
0
100
200
300
400
500
600
700
1 2 3 4 5 6 7 8 9 10 11 12
Dis
char
ge (
m3
sec-1
)
Month
Area2 Area1
Min Max
Obs (Past) MIROC
HadGEM GFDL
IPSL NorESM
One standard deviation range
P.7A(RCP8.5)
March to June, river discharge projections of river discharges from the GCMs are decreased. In contrast, during July to February,the river discharges in the downstream showed significantly increased.
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Result: River discharge at Nakorn Sawan
0
500
1,000
1,500
2,000
1 2 3 4 5 6 7 8 9 10 11 12
Dis
char
ge (
m3
sec-1
)
Month
Area2 Area1
Min Max
Obs (Past) MIROC
HadGEM GFDL
IPSL NorESM
One standard deviation range
C.2 (RCP2.6)
0
500
1,000
1,500
2,000
1 2 3 4 5 6 7 8 9 10 11 12
Dis
char
ge (
m3
sec-1
)
Month
Area2 Area1
Min Max
Obs (Past) MIROC
HadGEM GFDL
IPSL NorESM
One standard deviation range
C.2 (RCP4.5)
0
500
1,000
1,500
2,000
1 2 3 4 5 6 7 8 9 10 11 12
Dis
char
ge (
m3
sec-1
)
Month
Area2 Area1
Min Max
Obs (Past) MIROC
HadGEM GFDL
IPSL NorESM
One standard deviation range
C.2 (RCP8.5)
River discharge in C.2 quite stable from January to May because this period was controlled by reservoir operations. During the wet season (May to October), the river discharge at the basin outlet station was peak in October but the rainfall was maximum in September.
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Conclusions
The increasing of annual surface air temperature in the near
future (2026-2040) was in a range of 0.9-2.31°C, which had a
25.38 °C as a mean annual surface air temperature.
Maximum air surface temperature is projected to increase
by 1.77-2.31 °C in the projected period related to the
reference period (1986-2000).
Rainfall tended to decrease in the near future, on average.
For the river discharge projection, Chiang Mai and
Kampangphet will increase in the risk of both drought (first
monsoon) and flood (second monsoon) but Nakorn Sawan
province might predominate by drought.
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Thank you for your kind attention.
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