HYDROLOGICAL ASPECTS Concerning

The GCM/RCM

Dr. William M. PutuhenaExperimental Station for Hydrology and Water Management

RESEARCH CENTER FOR WATER RESOURCESMINISTRY OF PUBLIC WORKS

Dr. William M. PutuhenaExperimental Station for Hydrology and Water Management

RESEARCH CENTER FOR WATER RESOURCESMINISTRY OF PUBLIC WORKS

INTERNATIONAL WORKSHOP THE DIGITIZATION OF HYSTORICAL CLIMATE DATA, THE NEW SACA&D DATA BASE AND CLII

IN THE ASEAN REGION02-05 APRIL, CITEKO – BOGOR, INDONESIA

Mechanism of global warming and climate change

Large volumes of greenhouse gas emissions cause CO2 concentration in the air, increase heat absorption, and result in temperature rise, i.e. global warmings.

Increase of precipitation

Change in snow accumulation condition

Thermal expansion of sea water

Change in evapotranspiration

Melting of glaciers, ice caps and ice sheets

More intense typhoons

More frequent storm surges and coastal erosionsMore frequent storm surges and coastal erosions

Increase of river flow rate

More frequent floodsMore frequent floods More serious sediment disastersMore serious sediment disasters

Higher risk of droughtHigher risk of drought

Earlier snow melt and reduction of discharge

Change in water use pattern

More frequent heavy rains and droughts

Sea level rise

Source: Okada, 2008

Two Modeling Systems1. Climate Model (GCM/RCM)2. Hydrological Model

To provide a comprehensive understanding of the climate change impact on water resources

To provide a comprehensive understanding of the climate change impact on water resources

Global Climate Models

Hydrological Models

Target

Event to Continuous ModelLumped to Distributed ModelConceptual to Physical Model

B Model

DOWNSCALING

6

Climate Change Information

Climate Change Information

Discharge(m^3/s)

T

Current Design Rainfall

Future Design Rainfall under

Climate Change

Design HydrographDesign HydrographDesign RainfallDesign Rainfall

1

HydrologicalModel

Current Climate

Climate Change

Existing Gaps Between GCMs ability and Hydrology Need

Some Models Resolution Created By Australia

Spatial Scales Mismatch

Temporal Scales Mismatch

Temporal ScalesSeasonal

Annual

Monthly

Daily

Hourly

Minute

GCMs Hydrological Model

GCMs Ability Declines

Hydrological Importance Increases

Data Feed

Telemetry

Flood

Time

Rive

r dis

char

ge

accuration decreases

Lead Time

Detections Run-off analysis Warning Response

Flood forecasting

Present condition

NWP Satellite Radar

Vertical Scales Mismatch

GCMs

Hydrological Model

Tools for Atmosphere/ Ocean Modeling

Tools for Surface Earth Modeling

GCMs accuracy decreases from free tropospheric variables to surface variables, while the variables at the ground surface have direct use in water balance computations.

Working Variables Mismatch

GCMs accuracy decreases from climate related variables, i.e. wind , temperature, humidity and air pressure to precipitation evapotranspiration , runoff and soil moisture, while the later variables are of key importance in hydrologic regimes.

Declining return period by increasing rainfall

Rainfall amount

Return period (year)Maximum daily rainfall × 1.2

current future

100

50

Return period of flood is declining by increasing rainfall in the future. 　 As a result, future flood safety level is estimated to decrease.

【 Image of declining return period at a certain area 】

r

Rainfall probability sheets

projected datacurrent data

Impact of climate change

Source: Okada, 2008

Decreasing run-offs during the peak demand season Deviation from traditional water use patterns will be required

State of river run-offs after global warming (estimated)

Jan July Apr Oct

Wasteful discharges

Present

Rice paddy preparation

Decreasing river run-offs

Even if the rice paddy preparation season is advanced, available river run-offs in the demand season are insufficient.

Present Future Unable to store

Empty dams

Full

River run-off

Water in storage

Earlier spring flooding

Future

Changing river discharge Impact of climate change

Source: Okada, 2008

Global warming

Water temperature rise(remaining warm)

Fixed thermoclineposition

Decreasingcirculation in lakes

Increase ofE. coli

Decrease of winter ice cover(increasing light transmission)

Temperature rise

Increase of pests

Risk of infectiousdiseases

Increasing pesticide leaks withtheir increased use

Decrease of river DO Leaking hazardoussubstances

Decrease ofbottom-layer DO

Bottom sedimentationof remains

Phytoplankton proliferation

Water safety

From urban areas← 　 increased diffusion of

nitrogen/phosphorus↓

Flux ofhazardoussubstances

Leaking iron/manganese

Landslide inrain storm

Shifts inprecipitation patterns

Soil erosion

Increasedturbidity

Use of fossilfuel, etc.

Changingnitrogen cycle inthe atmosphere

Flux into forests/soil(nitrogen saturation)

NO3-N leaking intorivers upstream

Savory water

Products of treatment

Turbidity

Smell/taste

Color

Water safety

Impact of climate change on water quality Impact of climate change

Source: Okada, 2008

Rainfall Data

SeasonalSeasonal MonsoonMonsoon StormStorm

DRY WETWET

DJFDJF MAMMAM JJAJJA SONSON

DAILY MAXDAILY MAX

TEST FOR THE TREND1916-19801981-2000

TEST FOR THE TREND1916-19801981-2000

TEST FOR THE CHANGES OF THE DISTRIBUTION

1916-19401941-19701971-2000

TEST FOR THE CHANGES OF THE DISTRIBUTION

1916-19401941-19701971-2000

TEST FOR THE TRENDTEST FOR

THE TREND

MAP (result of the test)

YearlyYearly

Identification of the Climate Change in Java IslandIdentification of the Climate Change in Java Island

Source: RCWR-MPW

TREND OF MAXIMUM DAILY RAINFALL IN JAVA ISLANDTREND OF MAXIMUM DAILY RAINFALL IN JAVA ISLAND

• Data :Seri data hujan harian maksimum tahunan dari 1600 buah pos hujan (1916 2004) yang sudah lolos uji• Metode :Non Parametrik Tau Kendall dengan tingkat kepercayaan 95 %

Catatan:

Analysis of Future Precipitation Analysis of Future Precipitation affected by Climate Change on Citarum affected by Climate Change on Citarum

River Basin, IndonesiaRiver Basin, Indonesia

ADB Intern Yutaka Araki

・ Most strategic river basin・ Climate Change could lead to more severe and frequent flooding, and raise sea level in the river mouth

-12,000km^2 basin area-3 hydroelectric dams-1400MW-400,000ha Irrigation-80% of Jakarta’s water

Analysis on Citarum, IndonesiaAnalysis on Citarum, Indonesia

Analysis on Citarum, IndonesiaAnalysis on Citarum, Indonesia

Target periodTarget period

・ 50 & 80 years later(2046-2065, 2081-2100 (+1981-2000))

・ based on 2 CO2-emission-scenario

- SRES A1B & B1ToolsTools

・ 17(/25 )GCMs in CMIP3

A1 ｢ High economic growth ｣ A1FI:enphasis on fossil fuel A1B: Balanced energy use A1T: Non fossil fuel.(Technical innovation in Energy)A2 ｢ Differentiated world ｣　　 slower technological change, less emphasis on

economic, social, and cultural interactions between regions, Economic growth is uneven

B1 ｢ Sustainable development ｣ pay increased attention to the environmental,

Technological change plays an important roleB2 ｢ Local self-reliance and stronger communities ｣ shift toward local and regional decision-making

structures and institutions,

ＳＲＥＳＳＲＥＳ(Special Report on Emissions Scenarios)

Globalization

Regionalization

Environment-oriented

Economy-oriented

A1 B1

B2A2

Originating　Group(s) Country CMIP3　I.D. 20c3m SRES　A1BBeijing　Climate　Center　 China BCC-CM1 - -

Bjerknes　Centre　for　Climate　Research Norway BCCR-BCM2.0 - -

National　Center　for　Atmospheric　Research USA CCSM3 1980-19982046-2064,2080-

2098

Canadian　Centre　for　Climate　Modelling　&　Analysis Canada CGCM3.1(T47) 1981-19992046-2064,2081-

2099

Canadian　Centre　for　Climate　Modelling　&　Analysis Canada CGCM3.1(T63) 1981-19992046-2064,2081-

2099

Météo-France　/　Centre　National　de　Recherches　Météorologiques France CNRM-CM3 1981-20002046-2065,2081-

2100

CSIRO　Atmospheric　Research Australia CSIRO-Mk3.0 1981-19992046-2064,2081-

2099

CSIRO　Atmospheric　Research Australia CSIRO-Mk3.5 1981-19992046-2064,2081-

2099

Max　Planck　Institute　for　Meteorology Germany ECHAM5/MPI-OM 1981-20002046-2065,2081-

2100Meteorological　Institute　of　the　University　of　Bonn,　Meteorological　

Research　Institute　of　KMA,　and　Model　and　Data　group.　Germany　/　Korea

ECHO-G 1979-19972044-2062,2078-

2096LASG　/　Institute　of　Atmospheric　Physics China FGOALS-g1.0 - -

US　Dept.　of　Commerce　/　NOAA　/　Geophysical　Fluid　Dynamics　Laboratory

USA GFDL-CM2.0 1981-19992046-2064,2081-

2099US　Dept.　of　Commerce　/　NOAA　/　Geophysical　Fluid　Dynamics　

LaboratoryUSA GFDL-CM2.1 1981-1999

2046-2064,2081-2099

NASA　/　Goddard　Institute　for　Space　Studies USA GISS-AOM 1981-20002046-2065,2081-

2100NASA　/　Goddard　Institute　for　Space　Studies USA GISS-EH - -NASA　/　Goddard　Institute　for　Space　Studies USA GISS-ER - -

Instituto　Nazionale　di　Geofisica　e　Vulcanologia Italy INGV-SXG - -

Institute　for　Numerical　Mathematics Russia INM-CM3.0 1981-20002046-2065,2081-

2100

Institut　Pierre　Simon　Laplace France IPSL-CM4 1981-19992046-2064,2081-

2099Center　for　Climate　System　Research　(The　University　of　Tokyo),　

National　Institute　for　Environmental　Studies,　and　Frontier　Research　Center　for　Global　Change　(JAMSTEC)

Japan MIROC3.2(hires) 1981-20002046-2065,2081-

2100

Center　for　Climate　System　Research　(The　University　of　Tokyo),　National　Institute　for　Environmental　Studies,　and　Frontier　Research　

Center　for　Global　Change　(JAMSTEC)Japan

MIROC3.2(medres)

1981-20002046-2065,2081-

2100

Meteorological　Research　Institute Japan MRI-CGCM2.3.2 1981-19992046-2064,2081-

2099

National　Center　for　Atmospheric　Research USA PCM 1980-19982046-2064,2080-

2098Hadley　Centre　for　Climate　Prediction　and　Research　/　Met　Office UK UKMO-HadCM3 - -Hadley　Centre　for　Climate　Prediction　and　Research　/　Met　Office UK UKMO-HadGEM1 - -

PCM (USA)CCSM3.0 (USA)

1 2

43 5

←←Citarum River Basin

Target AreaTarget Area

Analysis itemsAnalysis items

• Rainfall days over 50,10 mm/day• No rainfall days / consecutive no rainfall days• Annual rainfall• Seasonal rainfall (dry and rainy)• Probable daily rainfall (5,10,100 years return)

- Flood/City drainage- Irrigation/Drought management 　　- Water Management

No rainfall No rainfall daysdays

number　of　model　which　shows　increase

A1B 50years　later 70%　(12/17)　Likely

80years　later 65%　(11/17)　More　likely　than　not

B1 50years　later 70%　(12/17)　Likely

80years　later 65%　(11/17)　More　likely　than　not

12%UP

Heavy rainfall Heavy rainfall days days (>50mm/day)(>50mm/day)

number　of　model　which　shows　increase

A1B 50years　later 90%　(9/10)　very　likely

80years　later 80%　(8/10)　likely

B1 50years　later 90%　(9/10)　very　likely

80years　later 80%　(8/10)　likely

Annual Annual rainfallrainfall

number　of　model　which　shows　increasing　rainfallA1B 50years　later 53%　(9/17)

80years　later 59%　(10/17)B1 50years　later 53%　(9/17)

80years　later 65%　(11/17)number　of　model　which　shows　increasing　fluctuation

(root-mean-square deviation)A1B 50years　later 53%　(9/17)

80years　later 47%　(8/17)B1 50years　later 53%　(9/17)

80years　later 47%　(8/17)

Seasonal rainfallSeasonal rainfall

number　of　model　which　shows　decreasing　trend　(Dry　season)　

number　of　model　which　shows　increasing　trend　(Rainy　season)　

A1B 50years　later 53%　(9/17) A1B 50years　later 35%　(6/17)

　 80years　later 65%　(11/17) 　 80years　later 71%　(12/17)

B1 50years　later 59%　(10/17) B1 50years　later 41%　(7/17)

　 80years　later 41%　(7/17) 　 80years　later 82%　(14/17)

Longest Longest consecutive consecutive no rainfall daysno rainfall days

number　of　model　which　shows　increase

A1B 50years　later 65%　(11/17)　)　More　likely　than　not

80years　later 65%　(11/17)　)　More　likely　than　not

B1 50years　later 60%　(10/17)　)　More　likely　than　not

80years　later 60%　(10/17)　)　More　likely　than　not

R²　=　0.958R²　=　0.9775R²　=　0.9685R²　=　0.8955R²　=　0.9564

10 100

ECHAM5/MPI-OM,　Log-normal　Probability　Paper　(Cunnane)

0.0001

99.9999

99.999

99.99

99.9

99

90

70

0.001

0.01

0.1

1

10

30

50

0.0001

99.9999

99.999

99.99

99.9

99

90

70

0.001

0.01

0.1

1

10

30

50

0.0001

99.9999

99.999

99.99

99.9

99

90

70

0.001

0.01

0.1

1

10

30

50

0.0001

99.9999

99.999

99.99

99

90

70

0.001

0.01

0.1

1

10

30

50

0.0001

99.9999

99.999

99.99

99

90

70

0.001

0.01

0.1

1

10

30

50

■20C3M 1981-2000▲ A1b 2046-2065◆ A1b 2081-2100■B1 2046-2065●B1 2081-2100

mm/day0.0001

99.9999

99.999

99.99

99

90

70

0.001

0.01

0.1

1

10

30

50

nonexceedance probability

　 A1BA1B B1B12046-2065 2081-2100 2046-2065 2081-2100

Number　of　models　which　show　more　severe　distribution　

than　now

82%14(/17)

94%16(/17)

76%13(/17)

53%9(/17)

5-year　probable　rainfall 1.18 1.31 1.14 1.1810-year　probable　rainfall 1.20 1.35 1.15 1.2100-year　probable　rainfall 1.20 1.36 1.17 1.18

ProbableProbablerainfallrainfall

Incremental Ratio of Daily Probable Rainfall (10year), A1B,50years later, from 17 models

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8

CGCM3.1(T47)CSIRO-Mk3.5

INM-CM3.0PCM

CNRM-CM3MRI-CGCM2.3.2

GISS-AOMECHO-G

ECHAM5/MPI-OMCSIRO-Mk3.0GFDL-CM2.1

MIROC3.2(medres)CCSM3

CGCM3.1(T63)GFDL-CM2.0

MIROC3.2(hires)IPSL-CM4

Average=1.2(from 17 models)

Flood SimulationFlood Simulation

Nanjung

Dayeuh Kolot

Majalaya

Nanjung

Dayeuh Kolot

Majalaya

・ Area Citarum Upper Basin・ Return period 10 years・ Climate Current and 50 years later(A1B)

Discharge(m^3/s)

T

Current Design Rainfall

Future Design Rainfall under

Climate Change

Design HydrographDesign HydrographDesign RainfallDesign Rainfall

1 1.2

HydrologicalModel

Current Climate

Climate Change

05

1015202530354045

0 20 40 60 80 100 120

cibeureum

Current 50 years later(A1B)

0

20

40

60

80

100

120

140

0 20 40 60 80 100 120

Ciwidey

Current 50 years later(A1B)

02468

10121416

0 20 40 60 80 100 120

Citepus

Current 50 years later(A1B)

0

50

100

150

200

0 20 40 60 80 100 120

Cisangkuy

Current 50 years later(A1B)

0

20

40

60

80

100

0 20 40 60 80 100 120

Cikapundung

Current 50 years later(A1B)

0

2

4

6

8

10

12

14

0 20 40 60 80 100 120

Cicadas

Current 50 years later(A1B)

0

5

10

15

20

25

30

0 20 40 60 80 100 120

Cidurian

Current 50 years later(A1B)

0

10

20

30

40

50

0 20 40 60 80 100 120

Cipamakolan

Current 50 years later(A1B)

0

50

100

150

200

250

0 20 40 60 80 100 120

Cikeruh

Current 50 years later(A1B)

0

50

100

150

200

0 20 40 60 80 100 120

Citarik

Current 50 years later(A1B)

0

10

20

30

40

50

60

70

80

0 20 40 60 80 100 120

Cirasea

Current 50 years later(A1B)

0

50

100

150

200

0 20 40 60 80 100 120

majalaya-Citarum Main

Current 50 years later(A1B)

Citarum Upper Basin

0

50

100

150

200

0 20 40 60 80 100 120

Cisangkuy

Current 50 years later(A1B)

Increase!

Flood SimulationFlood Simulation Orange Orange – Current Design Flood– Current Design FloodPurplePurple – Future Design Flood – Future Design Flood

Upper Citarum Basin Flood Management ProjectUCBFM

Flood Management Strategy‘No regret’ – urgent program

February 25, 2011JanJaap Brinkman, Deltares

Institutional Strengthening For Integrated Water Resources Management in the 6 CIS River Basin

Territory (Package C)

Delft　Hydraulics

ADB

Understanding the basicsIs there any change?

• Land-use change? – Yes, urbanization

• Climate change increasing floods? – No, not yet

• Topography change? – Yes, subsidence

• River change? – Yes, maintenance and ‘controlled’ river normalization

• Flood management change?– Yes, urgently required – ‘space for water management’

Climate change?

Climate Change -Trend analysis of daily point and

basin rainfall extremes Annual maximum point and basin daily rainfall extremes in Bandung basin

0

20

40

60

80

100

120

140

1870 1880 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

Ex

tre

me

da

ily

ra

infa

ll (

mm

)

basin rainfall by all stations

basin rainfall by BMKG-stations

average point extremes by BMKG

Linear trend-all stations

Climate Change - Trend analysis annual rainfall in Bandung basin, Period 1879-2007

Estimate of annual rainfall in Bandung basin, Period 1879-2007

0

500

1000

1500

2000

2500

3000

3500

1860 1880 1900 1920 1940 1960 1980 2000 2020

An

nu

al

rain

fall

(m

m)

Annual basin rainfall

Period average

Climate Change - Seasonal rainfall in Citarum u/s Nanjung, Period 1879-2010

Seasonal rainfall (Jan-Mar) in Citarum basin, Period 1979-2010

0

200

400

600

800

1000

1200

1400

1870 1880 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

Ra

infa

ll (

mm

)

Jan- Mar 2010 1285 mm

Rainfall characteristics

Lessons learnt from the 2009-2010 flood season.

Bandung basin – hydrology

• Historic floods not related to basin wide rainfall– Floods relate to local rainfall

5-Day rainfall extremes in basin u/s of Dayeuh Kolot with occurrence of 5-day rain-flood damages

0

25

50

75

100

125

150

175

200

225

250

1920 1930 1940 1950 1960 1970 1980 1990 2000 2010

Ra

infa

ll (

mm

)

5 day rainfall causing flood damage

average

Advanced GCM, RCM, and the hydrological model and also methodologies for comprehensive modeling have been developed. The two modeling systems have recently been used for quantification of the hydrological impacts of future climate change. However, the research on hydrological change is still in its infancy both with respect to model accuracy and uncertainty. Traditionally, based on the output of global or regional climate models, hydrological models have been run as stand alone models. This means that the feedbacks to the atmosphere are neglected which has an unknown impact on the predictions of the climate change, particularly at the local scale.

New model should be developed by combining the regional climate model and the hydrological model. As part of the integrated model a statistical downscaling and bias-correction method should be developed for conversion of data from large climate grids to small hydrological grids.

New model should be developed by combining the regional climate model and the hydrological model. As part of the integrated model a statistical downscaling and bias-correction method should be developed for conversion of data from large climate grids to small hydrological grids.

New methodologies and tools should be developed to enable easier and more accurate use of regional scale climate and hydrological models to address local scale water resources problems.

New methodologies and tools should be developed to enable easier and more accurate use of regional scale climate and hydrological models to address local scale water resources problems.

SUMMARY

KARIKATUR: KOMPAS/ Sabtu 10 Februari 2007

Thank you for your kind attention !