Water Resources andWater-Related Disasters in Asia

Kaoru TAKARA
Disaster Prevention Research InstituteKyoto University
Water Environment Partnership in Asia (WEPA)
The 1st International Workshop– Coping strategies for water environmental challenges in Asia –Hanoi, Viet Nam, 8-9 March 2010

Today’s Talk
• To show hydro-meteorologicalcharacteristics of Asia region interms of water-related disasters• To consider how to cope with thedisasters• To give some ideas emphasizing theimportance of collaboration of WEPA
partner countries with climatechange and water-related disasterexamplesA natural hazard (disaster)
strikes when people lose theirmemory of the previous one.

By Dr. Torahiko Terada(1878-1935)
天災は忘れた頃にやってくる

Hazard and Disaster• Hazards (earthquakes, typhoons, tsunami,
volcanic eruption) cannot be prevented.
• If hazards come to an island with no people
and no property, there are no damages = nodisasters.
• Disasters can be prevented and reduced.

We know the phenomena.

Ex. Hurricane, cyclone and typhoon tracks.

We know
mechanisms
andfrequency.
But, we do notknow whennatural hazards
happen.
Where this time?
How to cope with?

Natural Disasters in 2003

typhoon, Sep.
Korea: 410 mm/day

heat wave, Apr. – Jun.
cold wave Jan.

heavy rain, Jul. – Sep.
rain in Jul. : 555 mm

heat wave / drought / forest fire, Jun. – Aug.

cyclone,May
tornado, May

heavy rain, Jul.
forest fire / draught, Aug.
Kumamoto: 254mm/2days
forest fire / draught, Jun. - Aug.
heavy rain, May
heavy rain, Aug.
drought, Jul. – Aug. 389 mm / 4days
heavy rain, Aug.

heavy rain, Nov.drought, forest fire, Last year Mar. cold wave, Dec.- Jan.

heavy rain, Feb.
heavy rain, Apr. – Mayrain in Apr. 157 mm(206 % of average)

forest fire Oct. – Nov.

heavy rain, Oct. – Nov.

heavy rain, Feb.
more than 500 mm/30days
heat wave, May – Jun.

hurricane, Sep.
tornado, Mar. May

heat wave, drought, forest fire
heavy rain, typhoon, cyclone, etc.
forest fire, drought
cold wave

heavy rain, Jan.
rain in Jan. : 782 mm(257% of average)

Natural Disasters in 2004

heavy rain / snow, Dec.
rain in Dec. : 165 mm
heavy rain / typhoon, (394 % of average)
Jun. – Oct.
rain in Oct. : 780 mm
cold wave / snow, Jan. – Feb.
forest fire,lightning / twister, May
Jun. – Sep.

forest fire, Oct.
drought, Jun. – Jul.

landslide / flood Mar. – Apr.
heavy rain (snow) / flood, Oct. – Nov.

heavy rain / typhoon

drought, Jun. – Jul.

cold wave, Jun. – Jul.

cyclone,Marc
typhoon, May – Jul., Nov. Dec. heavy rain / flood, May.
hheat wave /cold wave, Dec.- Jan.
forest fire,
drought, Sep. – Nov.
hurricane, Aug. Sep.
heavy rain / storm, Apr. – Oct.
Jun. – Jul. heavy rain / flood,Apr.
heat wave, drought, forest fire
more than 500 mm/30days
more thanheavy rain / flood, Feb.
heavy rain, typhoon, cyclone, etc.
heavy rain
/ flood. Apr. – May. heavy rain / flood, Dec.
100mm/dayrain in Jan. 429 mm
more than 180 mm / 5 days
forest fire, droughtrain in Dec. : 226 mm(508 % of average)(332 % of average)
cold wave

Natural Disasters in the World
Among the causes ofnatural disasters,
flood disaster isremarkably increasingin these two decades
in the world.
Especially in humid
Asia, flood problems
are crucial in theirseriousness andfrequency.

Water-related disasters: major issue

Huge Natural Disasters
Tremendous human damages
Indian Ocean Tsunami
Myanmar Cyclone

Economic loss
Hurricane Katrina
Great Kobe Earthquake

Damages are mainly in Asia
EuropeAfricaAmericaAsia
40〜50%

Asia>70%

No. of events

Death toll

Asia
>90%

Affected people

Asia
>50%

Econimic loss

Continuing Population Growth in Asia

Natural disasters strike
our region every year !

Various Patterns ofExtreme Events andDisaster-Resistant Capacity(A) Increasing trend of extreme eventsvs No change in disaster-resistant capacityÆ ex. urbanization(B) Increasing variable range of extreme events
Æ ex. global warming impacts
vs No change in disaster-resistant capacity(C) No trend of extreme eventsvs Decreasing disaster-resistant capacityÆ ex. old facilities, old people, aged society(D) Abrupt extreme eventsvs Enhancement of disaster-resistantcapacity Æ ex. huge earthquakes, floods(E) Gradually increasing hazard
vs No special countermeasures
Æ water quality, groundwater contamination

Catastrophic disaster risk will increase.
Extreme weather amplified by global warming
Frequent disasters exceeding societal capacity

River
flow

FloodsSocietal
capacityDroughts
Presenttime

Is “sustainability science” enough?

Sustainability Science
Extreme weather amplified by global warming
Frequent disasters exceeding societal capacity

River
flow

Catastrophe

FloodsSocietal
capacity

Catastrophe

Droughts
Present

time

Societal capacity should be sustained or
improved by “sustainability science”.

Catastrophic disasters will be still there!

Sustainability/Survivability Science
Extreme weather amplified by global warming
Frequent disasters exceeding societal capacity

River
flow

CatastropheHowcanSocietal
capacity we
surCatastrophe
vive?

FloodsDroughts
Presenttime

We need “sustainability science”+ “survivability science”
to cope with catastrophic disasters.

Sustainability/Survivability Science
Extreme weather amplified by global warming
Frequent disasters exceeding societal capacity

River
flow

FloodsSocietal
capacityDroughts
Present

How
canwe
survive?

time“Survivability science” makes up(compensates) “sustainability science.”Typhoon Rusa
2002/8/31; 15:00
960hPa, Max Wind 35m/s

Precipitation
by Typhoon
Rusa
Based on 80 raingauges
by KMA; 2002/8/30-9/1

Historicalmaximum rainfall:
about 900 mm
during 24 hours

Typhoon RUSA in Korea 2002

Examples of Higher fluctuation
Europe- Floods in summer 2002
- Much snow in winter 2002-2003- Heat wave, snowmelt & floods in summer 2003
Japan
- Cool and long-term rain in summer 1993
- Extremely hot and dry summer 1994
- Cool summer 2003
- Extremely hot summer and 10 Typhoons in 2004
Historical maximum rainfall in Japan: 1317 mm/24 hr inAugust 2004

Extreme floods in Europe
August 2002

Maximum 24-hour rainfall: 687mm

Extreme floods in Europe
August 2002

Extreme snow in February 2003
(Deviation from the average over 1988-2002)

Second maximum snow since 1967
(National Climate Data Center, NOAA)Heat wave in Europe in Summer 2003

Annual Precipitation of Japan

Examples of Higher fluctuation
Europe- Floods in summer 2002
- Much snow in winter 2002-2003- Heat wave, snowmelt & floods in summer 2003
Japan
- Cool and long-term rain in summer 1993
- Extremely hot and dry summer 1994
- Cool summer 2003
- Extremely hot summer and 10 Typhoons in 2004
Historical maximum rainfall in Japan: 1317 mm/24 hr inAugust 2004

July 1993
100%

100%

100%
200%

200%

200%
200%
100%

Precipitation
0

2 0

4 0

7 0

1 0 0

1 5 0

2 0 0

3 0 0

Precipitation in July 1993 comparing with normal year July precipitation

July 1994
70%

70%

70%
40%

40%

70%

40%

Precipitation
0

2 0

4 0

7 0

1 0 0

1 5 0

2 0 0

3 0 0

Precipitation in July 1994 comparing with normal year July precipitation

Tokai Rainstorm:
Historical maximum daily
rainfall (428 mm) at Nagoya

September 2000 Tokai Rainstorm
Maximum hourly rainfall 93 mm, Maximum daily rainfall 428 mm at Nagoya

Dike break at Biwajima, Aichi,
September 12

Damages
Inundated houses: about 70,000
Economic damage: 7-8 billion USD

Niigata-Fukushima Flood, July 2004

Maximum Hourly Rainfall 58mm
Daily Rainfall 421mm

Casualties: 16
Completely destroyed houses: 70
Partly destroyed houses: 5,354
Inundated houses: 8,357

Typhoons directly hit Japan in 2004

Photo by Asahi Shinbun

Asuwa River bank rip point at 1:20 pm on
July 18th , 2004
After Chunichi Shinbun

Asia: Prone to water-related disasters
Geoscientific Characteristics • Rainfall: large seasonal fluctuation• Mountain areas: fragile geology• Alluvial plains: highly populated, humanactivities concentrated• Small islands: vulnerable to sea level riseWhat Characterizes Hydrology and Water Issues
in Monsoon Asia, Especially in Humid Asia?
• Two important factors which characterize regional featuresof hydrology and water issues:- Climatic factor, and- Geomorphologic factor• As for the climatic factor characterizing the Asia,
the Asian monsoon climate is very important.
• As for the geomorphologic factor characterizing the Asia,
land conditions formed by the plate tectonic motion,
called “tectonic zone or orogenic belt”, are very important.
(Musiake, 2007)

Asian Monsoon Climate- includes various climatic regions-

Arid/Semi-arid Temperate
Humid/Semi-humid Temperate

Humid/ semi-humid Tropics• The AMC covers from sub-arctic to tropical in terms of a latitudinal
climatic classification, and from arid/semi-arid to humid.

Water Issues to be Considered in Monsoon Asia

Mountain slope cultivation• Fragile mountain lands formed up due to mountain making activities,
such as slopes of volcanoes, fractured zones, Tertiary formation andweathered granite areas, can be cultivated, if they have necessary
temperature and water.
mountain slope cultivation in Asian tectonic
zones• On the other hand, they are disaster-risk areas vulnerable to slope failure,
landslide, debris/mud flow, etc..
• “Land productivity” and “Disaster risk” are both sides of coin.
Chugoku district, JAPAN

Cameron Highlands, MALAYSIA(Musiake, 2007)

Brantas basin, Java,INDONESIA

Water Issues to be Considered in Monsoon Asia

Heavy Sediment Yield and Water-related Disasters
in Mountain Areas• The steep slope and fragile geology bring about highsediment yield, slope failure, landslide, volcanic
eruption and debris/mud flow in mountainous areas.
• Sabo engineering
works ( debris control,
landslide and slope
failure prevention
works ) are applied toprevent or mitigate
damages caused bythem.

Sabo dam constructed in theupper reaches of Brantas river
basin, Indonesia

Landslide prone areas with heavy rains and tectonic activities such as
earthquakes, volcanoes, faulting and ground deformation (Asian Wet地すべり発生分布図
Tectonic(2003年
zone) – 2006年)
Major Landslide Events (2003-2006, NASA)
韓国
日本
タイ

中国
フィリピン

アジア湿潤変動帯
Asian Wet-Tectonic zone

インドネシアmm

Annual Precipitation of the past 8 years (TRMM, NASA)

アジア湿潤変動帯
Asian Wet-Tectonic Zone

NASA/IPL 2007

Landslide Susceptibility Mapping
High

Low

(NASA / ICL 2007, Tokyo Symposium)Sediment yield and runoff• The source of sediment yield in stable regions is mainly soil
erosion. We have other major sources of sediment in humid Asia,
such as landslide, slope failure, volcanic eruption, debris/mud flow,etc.
• Estimation and prediction of these kinds of sediment yield/runoff
are very difficult due to their discontinuous nature, but we have tocarry out systematic studies on them.
Debris/mud flow with drifting
fallen trees in Ban Nam Kor,
Petchaboon, THAILAND, in 11
August 2001.

Eruption of Mt. Pinatubo,
PHILLIPINES, in July 1991

Landslide due to earthquake.
The Abe River Basin, JAPANSeasonal land cover change
Oct 2002

Feb 2003

Oct 2003

Lesti River basin, East Java, Indonesia(Sayama, Tachikawa and Takara, 2005)

Seasonal variability of vegetation index
MODIS is a optical sensor installed in the satellite “TERRA”
NDVI=(IR-R)/(IR+R)

May, 2002

July, 2002

Dry season : May.- Aug.
Rainy season: Oct. – Mar.

August, 2002

1.0
0.0

October, 2002

December, 2002

March, 2003

Lesti River basin, East Java, Indonesia (Sayama, Tachikawa and Takara, 2005)

NDVI time series in different landuse

Lesti River basin, East Java, Indonesia(Sayama Tachikawa and Takara, 2005)

MODIS/NDVI to monitor land cover change
Lesti River basin, East Java, Indonesia(Sayama Tachikawa and Takara, 2005)

NDVI by MODIS

Dec
Oct 19,12, 2003
2003

Oct 12

Nov 1

Nov 6

Nov 17

Nov 29SAFE (Space Applications For Environment)

DAICHI

TRMM/PR

MTSAT

Datasets
For
Environmental
Monitoring
Land Use
Land Cover
Water
Resources

Social Benefitsin
Asia-Pacific

Water

Weather

Ecosystems

EnergyClimateHealthPhotosyntheticallyAqua/AMSR-E

Terra/MODIS

ActiveRadiation

Datasets
provided byPartner agencies
In Asia-Pacific

Agriculture

Biodiversity

The Overview of SAFE

Feedback by Insitu Observation
MTSAT-1R

ALOS

TRMM/PR

Satellite Datasets forEnvironment Monitoring
Water
Resource
DB by
AMSR-E& TRMM

JAXA/EORC

Land Use Map
by ALOS& MODIS& MTSATdefined by
Global Earth Observation
System of Systems(GEOSS)SAFE Prototyping（Trial Projects in each countries）

Distribution Platform
operated by JAXASAFE Portal

Terra/MODISAqua/AMSR-E

ThemesWater Resources Managementin Vietnam (2008〜）
by MONRE/NHMS and Univ. of Tokyo

Satellite
Datasets forEnvironment
Monitoring

Aggregation-Localization-Distribution

Land Use Managementin Vietnam (2008〜）

Contribution(through thePrototyping)by MARD/FPD and Univ. of Tokyo

Agenciesmanaging
RemoteSensing Datain Asia-Pacific

Agriculture
Agriculture

HealthHealthClimateClimateEnergyEnergy

Water
Water

Weather
Weather

Ecosystem
Ecosystem

Biodiversity
Biodiversity

Photosynthetically

active radiation(PAR)-DB
by MODIS

Datasets Distribution
for basic data
to monitor disasters

Data Sharing
Sentinel Asia
Step2 System

Disaster
Information-Aggregation-Incident
Management-Distribution

Working Groups (Flood, Wildfire)
Agencies managing Disaster in
Asia-PacificContributionDisasterDisaster1st Prototypes: Water Resources Monitoring
For mitigation of flood damage and optimization of water resourcesmanagement, JAXA and Univ. of Tokyo will set up a Water Resources
Monitoring System using satellite data.
1.
2.
3.

Develop methods to detect initial value of atmosphere for heavy rain forecast
Develop models to estimate river runoff for both normal situation and flood
Develop a dam manipulation system for optimized water resource management.

Optimizations of Water
Management

satellite data
River Management Data

In-Situ Data

Water Resources
Monitoring

Interoperation & analysis

GIS/Map Info

Heavy Rain Forecast

ModelsFlood Forecast

Early warningof flood2nd Prototypes: Land Use Management
For sustainable land use, JAXA and Univ. of Tokyo will set up forest
management system and value-added land use monitoring system.
1. Develop Land-Use-Change monitoring system.
2. Develop forest management system with value-added information.
3. Develop the Information Dashboard for optimized Land Use management.

data provisionsatellite data

Forest , Cropland data

In-Situ Data

Land Use Monitoring
SystemValue-added forest
information
Forest Management

GIS/Map Info

Land-Use-Changemonitoring
Agriculture

PHYSICALLYPHYSICALLY BASEDBASED DISTRIBUTED
DISTRIBUTED RAINFALLRAINFALL-SEDIMENT-RUNOFF MODELSEDIMENT-RUNOFF
MODELHydrological Submodel
A Physically based Cell
Distributed
RainfallRunoff Model (Kojima
and Takara, 2003) wasapplied for Simulate
Hydrological Response.

da
dm

p
Slo

(Apip and Takara, 2007)

i-1
nit
U
e

Q(X)

pe
Slo

X

)
∆X
X+
(
W

∆X

Continuous Eq. of Water

The Model Soil Structureand Stage Discharge Relationship CDRM V.3 Model

it i
un

h

D

L

∂h ∂q
+
= r (x,t)
∂t ∂x

X)
W(

(Tachikawa et al, 2004)

X+∆X

Θ

i+1
nit
U
pe
Slo
Q(X+
∆X)

h

(Apip and Takara, 2007)
Runoff and Sediment Yield
Simulation by a Distributed Model

Erosion & Deposition Depth (mm)Erosion
7.00
6.00
5.00
4.00
3.00
2.00
1.00
0.00
-1.00
-2.00
-3.00
-4.00
-5.00
-6.00
-7.00

Deposition

3-D Spatial Distribution

Rainfall event
based(Flood Event)

Rainfall (mm)

Runoff and Sediment Yield Simulation by aDistributed Model(Apip and Takara, 2007)
0
5
10
15
20

Obs. Discharge
Comp. Discharge
Obs. SedimentComp. SedimentHydrograph andSedimentgraph

SIMULATION RESULTS → Case 1 (total rainfall 333 mm)
Discharges

600

40

Discharge (m3 /sec)

50

60

70

80

90

100

110

300

400

400

300

500
600

200
100

130
50

60

70

80

90

100

110

0
1

11

21

31

41

51

61

40

Discharge (m3 /sec)

9000

60

80

100

120

351.3 Km2
80

8000

100

120

60000
50000
40000
30000
20000
10000

900

0

140

1

400

5000

500

4000

600

3000

700
800

1000

900

0
1

11

21

31

41

Time (hr)

51

61

71

21

31

41

51

61

71

by lumped model

200

6000

11

140000

100

300

7000

2000

140
60

70000

800

0

Rainfallby lumped modelby distributed model

10000

40

by distributed model

80000

71

11000

20

20

by lumped model

120

Sediment concentration (mg/l)

40

Rainfall (mm/hr)

30

200

700

25.3 Km2

120

500

Sediment Concentrations

90000

100

Rainfall (mm/hr)

Rainfallby lumped modelby distributed model

30

1000000

Sediment concentration (mg/l)

700

20

120000by distributed model

100000
80000
60000
40000
20000
0
1

11

21

31

41

Time (hr)

51

61

71

Merits and demerits of distributed
rainfall-runoff models• Useful for detecting local phenomena• Useful for considering non-point source
water quality problems in river basins• Can consider spatial distribution of rainfall
and other hydrological parameters• Take more computational time
• Need spatial information• Grid-cell size depending on the problem

Disaster Reduction Hyperbase(DRH)• Database management system ofknowledge and technology for various disasterprevention/reduction, which includes:- Implementation oriented technologies (IOT)- Transferable indigenous knowledge (TIK)- Process technologies (PT)copyright (c) 2007 EDM-NIED. All rights reservedImplementation Oriented Technology

Reduction of tsunami flowpressure in greenbelt(mangrove, waru, etc.)(EqTAP Project: PARI, Japan and
CDRC, Indonesia)
Project in Sulawesi Island, Indonesia*Can not stop tsunamis but can reduce
their effects.
*Inexpensive, no "high-tech" required*Design guideline developed through lab
tests and numerical simulation*Being implemented in Sulawesi Island,and other 14 sites in Indonesia.

Laboratory test
copyright (c) 2007 EDM-NIED. All rights reserved

Criteria for Transferable Indigenous Knowledge (TIK)
ver. 070702(FM1)070917(Stresa)

•
•
•
•
•

Originated within communities, based on local
needs, and specific to culture and context(environment and economy)
Provides core knowledge with flexibility for local
adaptation for implementation
Uses local knowledge and skills, and materials
based on local ecology
Has been proven to be useful in disasters
Is applied or applicable in other communities orgenerations

copyright (c) 2007 EDM-NIED. All rights reserved

Transferable Indigenous Knowledge(Bangladesh) FLOOD MITIGATION(Homestead Raising)(by Moloy Chaki: CMM2)(Japan) "Mizuya" (Flood house)(NIED-KU survey team)

copyright (c) 2007 EDM-NIED. All rights reserved

Disaster management cycle
DisasterPreparedness

Mitigation

Response

RecoveryWater management : to apply structural and non-structural
measures to modify natural and man-made water systems for theenhancement of human welfare as well as the conservation ofnatural environment.
- water supply- wastewater treatment- water quality
improvement- flood disastermitigation- debris/sediments
control- hydropower generation- navigation- recreation- conservation/restorationof eco-system

Water has diverse functions, andthe water management includes various subjects.

Lessons learned from recent
water-related disasters• Awareness of- disaster risks,- vulnerability by social change,- possible climate change impacts• Insufficient preparedness due to- lack of proper information,- overconfidence or ignorance,- limited budget• Needs for- capacity building, education,- integrated disaster (water) management,- fundingVulnerable people are always hit bydisasters.

災害弱者がいつもやられる。
災害は脆弱な人と場所を襲う。

An ounce of prevention is worth
a pound of cure.
1オンスの予防薬は１ポンドの治療薬に値する。
(備えあれば憂いなし）