11/18/2016

1

Manisha MAHARJANGraduate School of Engineering

Kyoto University

15 November 20161

Outline

�Background

�Study Area

�Methodology

�Results and Discussion

�Conclusion

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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

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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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Study Area

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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.

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Data Collected for Chi River Basin

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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

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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

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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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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

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Change in temperature climate indices in different stations

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• 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

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Projected precipitation climate indices anomalies across 27 stations

Near Future Mid Future Far Future

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• 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

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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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Calibration and Validation

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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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Conclusion

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� 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 Maharjanmaneesha064@gmail.com

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