Assessing flood risk globally using an
improved country-based risk index
UNESCO-JASTIP Joint Symposium at Manila
November 15, 2017

Yoshiyuki Imamura
Center for Research and Application ofSatellite Remote Sensing (CRASS)

Yamaguchi University, Japan

Introduction

Increasing water disasters
1

droughtflood

Number of disasters

landslidewindstorm
total

Number of water-related disasters（1980-2009）
Water-related disasters are increasing.
Especially damage in Asia is serious.
出典）ICHARM HP（http://kankyorenrakukai.org/symposium_12/pdf/koen_7.pdf）（Made by ICHARM database from EM‐DAT)Why do we need to assess flood risk?
Increasing flood damage

ICHARM developed water-related risk assessment
indicators (Asian Water Development Outlook(AWDO)
issued by Asian Development Bank (ADB))
Assessing andquantifying floodrisk of countries

・・・

Easy to understand by
policy makers andgeneral public

Guiding policy makers and planners for reducing flood
damage and sustainable development

AWDO（Asian Water Development Outlook）
・・・Five key dimensions on water security
KD5: Resilience to water-related disasters（Resilience） Reducing water-related risks andminimizing impacts of disastersCountries with larger GDP per capita havemore resilience to water-related disasters.

Economic development increases resilience to waterrelated disasters, which supports sustainabledevelopment.

Focusing on floods※AWDO：evaluated water-related disasters(Flood, Drought, Storm surge).
More than half
damage is cuased byfloods(affected population)

Storm surge
FloodDrought

Focusing on floods

Affected population

Ref) ICHARM HP（http://kankyorenrakukai.org/symposium_12/pdf/koen_7.pdf）

Objectives
AWDO
・Limitation on global datasets.
・Only in the Asia-Pacific countries.

Objectives① Improving flood risk index
・・・Updating data＋Factoring in more factors②Applying from Asia-Pacific countries to the world
・・・Flood damage is increasing in other than regions
as well.

Methodology

How the Flood Risk Index is computed
Indicator and Subindicator・Indicators
The Flood Risk Index is computed by five indicators.

Flood Risk Index

HazardExposure
Vulnerability
Hard Coping Capacity
Soft Coping Capacity

・Subindicators
An indicator is calculated by subindicators.
Maximum precipitation (weekly average)

E.g.
HazardCyclone pronenessMonthly precipitation etc.
・・Concept
Causes and improvements

Hazard: Dangerousphenomenon or situation.

People, property, system・・・

High exposure tofalling rocks(Hazard).

Low exposure tofalling rocks(Hazard).

Low vulnerability

High vulnerability

Ref) N. Waidyanatha (https://www.slideshare.net/waidyanatha/overview-em-commnuwandayone）

How to compute the Flood Risk Index① Selecting subindicators
AWDO’s factors

New factors

More holistic aspects② Calculating a subindicator from factors（Normalization）③ Calculating an indictor by adding subindicators.
④ Computing the index from five indictors

How to compute the flood risk index from five indicators

Hazard × Exposure × Vulnerability
Flood Risk Index =Soft Coping Capacity × Hard Coping Capacity

Indicators to increase risk
• Hazard : Magnitude of natural phenomena that cause floods• Exposure : Scale of people or areas exposed• Vulnerability : Susceptibility to the damaging effects of floods
Indicators to reduce risk
• Hard Coping Capacity :Ability to manage flood disasters bystructural measures• Soft Coping Capacity :Ability to manage flood disasters by nonstructural measures

How to calculate a subindicatore.g. Maximum precipitation (weekly average)
Subindicator =𝒔𝒖𝒃𝒋𝒆𝒄𝒕 𝒄𝒐𝒖𝒏𝒕𝒓𝒚−𝒎𝒊𝒏𝒊𝒎𝒖𝒎 𝒄𝒐𝒖𝒏𝒕𝒓𝒚
𝒎𝒂𝒙𝒊𝒎𝒖𝒎 𝒄𝒐𝒖𝒏𝒕𝒓𝒚−𝒎𝒊𝒏𝒊𝒎𝒖𝒎 𝒄𝒐𝒖𝒏𝒕𝒓𝒚

246mm − 40mm== 0.24889mm − 40mm

e.g.
Subject country: Japan, 246mm,
Maximum country: Papua New Guinea 889m,
Minimum country: Mongolia, 40mm,
The subindicator is calculated as 0.24.
※An indicator is summing up of subindicators

Indicators and Subindicators
Indicator

Hazard5Subindicator
Maximum precipitation ( weekly average)
Cyclone pronenessHard Coping
Capacity

Subindicator
GDP per land area

Frequency of heavey rainfall (more than100mm/day)Total water storage capacity
per land area

Maximum precipitation (monthly average)

Road pavement rate

Ratio of the maximum precipitation ofmonthly average to the minimum
Maximum precipitation of monthly
average/Annual average precipitation

Exposure

Indicator

Population density
Urban population growth rate
Population growth rate

Soft Coping
Capacity

Literacy rate
Enrollment rate
Number of television
receivers
Number of mobile phoneownersPercentage of GDS in GDP

Inland water area
Waterway length

Vulnerability

Corruption perception index

Internet users
Public medical expenditure

Percentage of daily consumption less than 1$
Official development assistance ratio
Deforestation rate
Infant mortality rate

Unhealthy life
Gini coefficientBlack: Subindicators used inAWDO
Red: New subindicators

Results(Asia-Pacific countries)

Result 1
9Number of fatalities per 100,000 people and flood riskindex (33 Asia-Pacific countries)
14
Bangladesh③
12High Risk
Vanuatu
Lao PDR

10Flood Risk Index

Once a great flood occurs, manypeople may be killed.
NepalIndia
Papua New Guinea
Samoa

8② Kiribati
64Malaysia
Uzbekistan
2New Zealand
0-2

MongoliaJapan
Azerbaijan Korea, Rep.
Armenia①Cambodia

A circle size
indicates GDP percapita of a country

Low Risk, More developed countries

Australia

0-2

Philippines
Viet NamFiji
PR China Tajikistan
PakistanIndonesia
Thailand Sri Lanka

24

68

Fatalities per 100,000 population by flood

1012

Result 210High risk countries and causes
Bangladesh

India

HazardHazard

0.8

0.8

0.6

0.6

11

1-SoftC. C.

Exposure
1-SoftC. C.

0.4
0.2
01-Hard C. C.

1-Hard C. C.
Vulnerability

Low literacy rate,enrollment rate

Exposure

0.4
0.20

Vulnerability

Rapid Urban
population growthResult 311

Low risk countries and reasons
JapanAustralia

HazardHazard
11

0.8

0.8
0.6

1-SoftC. C.

1-Hard C. C.

0.4
0.2
01-SoftC. C.

Exposure

1-Hard C. C.
Vulnerability

0.6
0.4

Exposure

0.20

Vulnerability

Result 4
Flood Risk Index and five indicators
12Reduction indicators

Increase indicators

Hazard Exposure Vulnerability

HardSoft

Correlation
coefficient R

0.88

0.58

0.65

-0.51

-0.75

Coefficient ofdetermination R2

0.77

0.34

0.42

0.26

0.57

“positive” with increase factor ,”negative” withdecrease factor.
→The subindicators used in the study are reasonable.

Results(Global)Results 1
Flood Risk Index (146 countries)

Flood Risk Index
HighLow

7.84-17.04
4.62-7.83
2.73-4.61
1.34-2.72
0.257-1.33

Countries near the equator and in Africa have high Flood Index.
・・・High risk：Central Africa, Pacific countries
・・・Low risk：Developed countries, such as Japan, Australia

Result 2
GDP per capita and flood risk index

18Gambia
16High risk countries

14

ChadFlood Risk Index

12

Liberia

10

Niger

86

Central AfricanRep.

4y = 149.93e-1.095x
R² = 0.46

SenegalBangladesh
Nepal Zambia
Sudan
Lao PDR
India
AngolaCosta Rica

Congo, Dem.
Togo
Rep.
Swaziland

202

2.5

3Yemen, Rep.

Ukraine

3.5

4

GDP per capita (US$)

4.5

United ArabEmirates
Singapore
Qatar
Japan
KuwaitAustralia
55.5

Results 3

High risk countries and its factors
GambiaChadHazard
1Hazard
10.8

0.8

0.6

1-SoftC. C.

0.4
0.2
01-Hard C. C.

0.6Exposure

0.4

1-SoftC. C.

0.2
01-Hard C. C.
Vulnerability

High urban population growth,
Low infrastructure development

Exposure

Vulnerability

Low information system

Result 4
Relative high countries with large GDP per capita
United Arab Emirates

Qatar

HazardHazard

11

0.8

0.8

0.6

0.6

1-SoftC. C.

1-Hard C. C.

0.4
0.2
0Exposure
1-SoftC. C.

1-Hard C. C.
Vulnerability

High urban population growth
Rapid deforestation

0.4

Exposure

0.20Vulnerability

Result 5: Indicators by region

Hazard0.4
0.3

1/Soft Coping
Capacity0.2

Exposure
0.1
01/Hard coping

Vulnerability

Capacity
先進国
先進国 economies
Advanced

アフリカ
アフリカ
Africa東ヨーロッパ・
EastEurope and東ヨーロッパ・中央アジア
中央アジア
CentralAsia
南アジア
South Asia
南アフリカ

ラテンアメリカ・
Latin
America andラテンアメリカ・カリブ海
カリブ海諸国theCaribbean

東アジア・
East
Asia and東アジア・太平洋諸国
太平洋諸国
thePacific
中東・北アフリカ
中東・
MiddleEast and
北アフリカ
North
AfricaAfrica is the highest flood risk region⇒ All 5 indicators increase risk highlyConclusion
・Developed the flood risk index thatvisualizes causes of risk and contribute tonational policy in mitigating damage.
・Applied the developed index to 146

countries globally and illustrated features ofcountries and regions.
Way forward
Utilizing remote sensing data tocomplement global datasets← global coverage, updatinge.g. GSMaP for precipitation

Universities

Basic techniquesDiv. 1

Div. 2Integration of SpaceTechnologies,
such as SRS, GIS,
GPSBig Data Analysis,
Basics of SRS
Image Processing

・JAXA
Quick Response to Disaster・SteeringCommitte

Div. 3

Leaders
meeting

Application of SRS to
DisasterManagement,
EnvironmentalIssues

Support system・（Div. 4

Application of SRS toSocial and/or
Economic Issues

Div. 5Construction ofDatabase, Information
and Network SystemInternational Contribution

Applicationtechniques

SENTINAL ASIA

Local govs

CRASS: Divisions）

International Cooperation (ＡＳＥＡＮ Countries, South AmericanCountries)（Kizuna
JAXAWest
Japan
ResearchCenter

The future network regarding the usage of satellite data, i.e.,
research and human development. YU will cooperate with otheruniversities and research institutions. In addition, we will
accelerate and expand international cooperation.

Activities and Network of CRASSＪＡＸＡTsukuba

ＪＡＸＡ

Back up West Japan research

Cooperativecenter
Research &Cooperation
Capacity
Cooperation
Building

Cooperation
LAPAN
Indonesia
Cooperative
Cooperative
Research &YU
Research
Education
CRASSIndonesia
Divisions
UNUD
for Research on
Cooperation
Information
Disaster andIndonesia
Environmental
DMR
IssuesOrganizations CooperativeAnd
Cooperati
Research &Education for Research on
ASEAN
on

Big-Data
Processing

Countries

CapacitySouthbuilding
AmericaCountries
Information

Asian Disaster
Reduction

Sentinel
Asia

Emergenc
ysituation
YPG

Information Cooperation
Cooperation
DMR
Organizations
Informatio
Information
nCooperation

Universities

Cooperation

Developmentof Software
Informationcompanies

Support