Download Surface Air Temperature change

2015 APEC Typhoon Symposium (APTS)
Lessons Learned from Disastrous Typhoons
Climate Change Impact on Water Resources using
Global Climate and Hydrological Model
Chaiwat Ekkawatpanit, Weerayuth Pratoomchai
Department of Civil Engineering
King Mongkut’s University of Technology Thonburi, Bangkok, Thailand
Naota Hanasaki
National Institute for Environmental Studies, Tsukuba, Japan
So Kazama
Tohoku University, Sendai, Japan
24-25 November, 2015
Outline of presentation

Introduction

Objective of the study

Study area

Methodology

Results and discussion

Conclusions
2
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 ?
3
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.
4
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 forest
35.6% is agricultural area
4.4% is classified to other,
e.g., urban, water bodies
o
o
5
Methodology (Mathematical models):
7 climate
variables:

Kotsuki et al., 2010
CMIP5 - Coupled Model
Intercomparison Project
Phase 5
5 GCMs
Models and Data
- Rainfall
- Air temperature
- Wind speed
K10 data
- Specific humidity
- Surface air pressure
- Longwave downward radiation
- Shortwave downward radiation
Land Surface Module
River Routing Module
Reservoir Operation
Module
Crop Growth Module
Withdrawal Module
Environmental Flow
Module
Three modules that not cover
in this study
under 3
scenarios
Hanasaki et al., 2008; Hanasaki and Mateo (2012)
CMIP5 (GCMs data)
H08
R, E, Ro
Rushton and Ward (1979)
Groundwater
Recharge Model
Prickett and Lonnquist
(1971)
Q
RCP 2.6
RCP 4.5
RCP 8.5
Qi
Groundwater Flow
Model
Aquifer properties (T, S)
Qn
River induced
infiltration
model
Groundwater
Level
Effective porosity
Groundwater
Storage
Where
Kazama et. al. 2007
Qn = Recharge/ Discharge from riverbed
R = Rainfall
E = Evaporation Qi = Recharge from infiltration
Ro = Runoff
Q = River discharge
6
Land Surface Hydrology Module (LSM):
The model was developed by Hanasaki et al., 2008; 2012; 2014
Soil water balance
Energy balance
dW
 Ra inf  Snowf  Qsm  E  Qs  Qsb
Soil water balance 
dt
4
Energy balance  (1   ) SW   LW   Ts  lE  H  G
7
River Module:
Schematic of H08’s river module
RivSto  ( RivInf  Qtot xA  RivOut )t
8
Reservoir Operations Module:
Chao Phraya River Basin
P1
N1
W21
Wa
ng
Y1C
Sirikit Dam
m
Yo
N5A
Pa Sak
W4A
Pi Y4
ng
Y16
n
Na
Bhumibol Dam
P17
Chainat
0-10
20-30
30-50
50-100
100-150
500-1,000
Nakhon Sawan
ya
hra
10-20
C13
N67
oP
Cha
Elev. (m)
C2
in
Tha Ch
• 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.
C35
Ayutthaya
Rojana
Bangkok
1,000-1,500
1,500-2,000
2,000-2,572
9
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)
10
Results: Model Calibration
1975 Observation
1980
1985
3,000
Simulation
Jan-00
Jan-99
Jan-98
Jan-97
Jan-96
Jan-94
Jan-95
1990
2000
Jan-00
1980
Jan-99
1970
Jan-98
1960
Jan-97
1950
R2 = 0.28
Jan-94
0 0
C.2 (Basin outlet)
1995 IOA
2000= 0.93
2005
y = -39.836x + 81203
Jan-93
Jan-00
Jan-99
Jan-98
Jan-97
Jan-96
Jan-95
Jan-94
Jan-93
Jan-92
Jan-91
Jan-90
Jan-89
Jan-88
Jan-87
0
Jan-92
50
Jan-91
4,000
1,500
3,000
1,000
2,000
500
1,000
100
1990
C.2
6,000
2,500
5,000
2,000
Jan-90
150
1970
3,500
Jan-89
200
2005
R2 = 0.0001
4,000
0
C.2
2000
y = 2.0524x + 1389.9
Jan-96
2,000
W.4A (Wang River)
IOA = 0.89
250
1995
4,000
Jan-88
Simulation
1990
Sirikit Dam
Jan-87
300
1985
6,000
Flood peak (CMS)
Discharge (m3 sec-1 )
350
Observation
Jan-86
Discharge (m3 sec-1 )
400
1980
Jan-95
Bhumipol Dam
8,000
1975
Jan-93
Annual Inflow (MCM)
Sirikit Dam
1970
Jan-92
10,0000
Jan-00
Jan-99
Jan-98
Jan-97
Jan-96
Jan-95
Jan-94
Jan-93
Jan-92
Jan-91
Jan-90
Jan-89
Jan-88
Jan-87
Jan-86
0
1965
Jan-91
50
R2 = 0.0835
Jan-90
100
y = -47.498x + 99779
Jan-89
150
Simulation
Jan-88
200
Y.6 (Yon River)
IOA = 0.91
Observation
Jan-87
250
Bhumipol Dam
800
10,000
700
8,000
600
6,000
500
4,000
400
2,000
300
0
200
1960
100
Jan-86
Simulation
N
3 sec
-1 )
Annual(mInflow
(MCM)
Discharge
Discharge (m3 sec-1 )
P.1 (Ping River)
IOA = 0.96
Observation
300
Jan-86
350
2010
11
Results: Annual mean air temperature
Current period
(1986-2000)
Projection period
(2026-2040)
RCP2.6
average from 5 GCMs
Change
(Future – Current)
12
Results: Annual mean air temperature
Surface Air Temperature change ( 0C )
RCP 2.6
RCP 4.5
RCP 8.5
13
Results: Annual mean air temperature
Surface air temperature changes (°C)
2.5
2
0
C
0
C
0
C
1.5
RCP2.6
RCP4.5
RCP8.5
1
0.5
0
MIROC
HadGEM
GFDL
IPSL
NorESM
The increasing of surface air temperature in the near future was in a range of 0.9-2.31 0C
0
which had a 25.38 C as a mean annual surface air temperature.
14
Results: Surface water balance from the LSM
Average annual rainfall, evaporation, and runoff (1986-2000)
Rainfall = 987 mm
Evaporation = 810 mm or 82% of annual rainfall
Surface runoff = 177 mm or 18% of annual rainfall
15
Results: Water balance
1,200
1,000
(mm.)
800
Rainfall
600
Runoff
Evaporation
400
200
History
RCP2.6
RCP4.5
NorESM
IPSL
GFDL
HadGEM
MIROC
NorESM
IPSL
GFDL
HadGEM
MIROC
NorESM
IPSL
GFDL
HadGEM
MIROC
0
RCP8.5
MIROC and NorESM GCMs showed increasing trend for all variables
16
Results: Rainfall
Current period
(1986-2000)
Projection period
(2026-2040) RCP2.6
average from 5 GCMs
Change
(Future – Current)
17
Results: Rainfall
Annual Rainfall change
RCP 2.6
RCP 4.5
RCP 8.5
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.
18
Result: River discharge at Chiang Mai
P.1 (RCP2.6)
Discharge (m3 sec-1 )
200
Area2
Area1
One standard deviation range
Min
Max
Obs (Past)
MIROC
HadGEM
GFDL
IPSL
NorESM
150
100
50
0
1
2
3
Discharge (m3 sec-1 )
Area2
Area1
One standard deviation range
Min
Max
Obs (Past)
MIROC
HadGEM
GFDL
IPSL
NorESM
150
Discharge (m3 sec-1 )
200
50
0
3
4
5
6
7
Month
8
8
9
10
11
12
Area2
Area1
One standard deviation range
Min
Max
Obs (Past)
MIROC
HadGEM
GFDL
IPSL
NorESM
150
100
50
1
2
6
7
Month
0
100
1
5
P.1 (RCP8.5)
200
P.1 (RCP4.5)
4
9
10
11
12
2
3
4
5
6
7
Month
8
9
10
11
12
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.
19
Result: River discharge at Kampangphet
P.7A(RCP2.6)
700
Area2
Area1
One standard deviation range
Min
Max
Obs (Past)
MIROC
HadGEM
GFDL
IPSL
NorESM
Discharge (m3 sec-1 )
600
500
400
300
200
100
0
1
2
3
Discharge (m3 sec-1 )
600
500
400
Discharge (m3 sec-1 )
P.7A(RCP4.5)
500
400
100
0
4
5
6
7
Month
8
10
11
12
200
0
200
3
9
100
300
2
8
300
1
1
6
7
Month
Area2
Area1
One standard deviation range
Min
Max
Obs (Past)
MIROC
HadGEM
GFDL
IPSL
NorESM
600
Area2
Area1
One standard deviation range
Min
Max
Obs (Past)
MIROC
HadGEM
GFDL
IPSL
NorESM
5
P.7A(RCP8.5)
700
700
4
9
10
11
12
2
3
4
5
6
7
Month
8
9
10
11
12
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.
20
Result: River discharge at Nakorn Sawan
C.2 (RCP2.6)
Discharge (m3 sec-1 )
2,000
Area2
Area1
One standard deviation range
Min
Max
Obs (Past)
MIROC
HadGEM
GFDL
IPSL
NorESM
1,500
1,000
500
0
1
2
3
Discharge (m3 sec-1 )
Area2
Area1
One standard deviation range
Min
Max
Obs (Past)
MIROC
HadGEM
GFDL
IPSL
NorESM
1,500
Discharge (m3 sec-1 )
2,000
500
0
3
4
5
6
7
Month
8
8
9
10
11
12
Area2
Area1
One standard deviation range
Min
Max
Obs (Past)
MIROC
HadGEM
GFDL
IPSL
NorESM
1,500
1,000
500
1
2
6
7
Month
0
1,000
1
5
C.2 (RCP8.5)
2,000
C.2 (RCP4.5)
4
9
10
11
12
2
3
4
5
6
7
Month
8
9
10
11
12
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.
21
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.
22
Thank you for your kind attention.
23