Cover page

ISSN

0386 – 5878

Technical Memorandum of PWRI
No. 3985

Technical Report on Global Trends ofWater-related Disasters

October 2005

Secretariat for Preparatory Activities of
UNESCO-PWRI Centre

Public Works Research Institute (PWRI)

Copyright  (2005) by P.W.R.I.
All rights reserved. No part of this book may be reproduced by any means,nor transmitted, nor translated into a machine language without the written
permission of the Chief Executive of P.W.R.I.
この報告書は、独立行政法人土木研究所理事長の承認を得て刊行したものである。したがって、本報告書の全部又は一部の転載、複製は、独立行政法人土木研究所理事長の文書による承認を得ずしてこれを行ってはならない。

Front page

Technical Report on Global Trends ofWater-related Disasters

Tarek Merabtene
andJunichi Yoshitani

Synopsis:
The aim behind this research is to develop our understanding of therelations between water-related disasters and their impacts on society, so as toimprove policies for hazards mitigation. This technical report presents theresults of our assessment and analysis of water-related disasters during thepast four decades (1960 to 2004) in particular as reported in the OFDA/CRED
Emergency Disaster Database (EMDAT), University of Louvain, Belgium.
The results presented in graphics and tabular forms for each type ofwater-related disasters allow the reader to evaluate the current state of the
global and regional trends. The outcome of the report puts emphasis on
numbers of emerging issues and challenges for the concrete evaluation ofsocial and economic vulnerabilities to water-related disasters. The findings
introduced in this study were presented in front of the UN Expert Group on
Risk Management led by WMO and ISDR for consideration during the
production of the 2nd Edition of the World Water Development Report(WWDR) managed by the Secretariat of the UN-World Water Assessment
Programme (UN-WWAP) hosted by UNESCO.
Keywords: OFDA/CRED EMDAT, trend of disaster, water-related disaster,flood, windstorm, landslide, drought, famine, epidemic water-related,
technologic water-related disaster.

Table of Contents
Foreword...............................................................................................................................vi
Acknowledgments ............................................................................................................. viii
Preface....................................................................................................................................x
List of Tables and Figures.................................................................................................xiv
List of Figures ..................................................................................................................xiv
List of Tables....................................................................................................................xvi
Chapter 1: Background and Objectives .............................................................................1
1.1. Introduction...............................................................................................................1
1.2. Methodology.............................................................................................................3
Chapter 2: The Global Disasters Database EMDAT ........................................................7
2.1. General criteria .........................................................................................................7
2.1.1. EMDAT Sources of Data...................................................................................7
2.1.2. Events Entry Criteria .........................................................................................82.2. EMDAT typology of disasters and structure of the database ...................................92.3. EMDAT data quality and limitations ......................................................................13
Chapter 3: Global assessment of human disasters ..........................................................15
3.1. Trends in natural disasters ......................................................................................15
3.2. Assessment of the social impact of natural disasters ..............................................22
3.2.1. Trend of the number of dead people .................................................................22
3.2.2. Trend of the number affected people ................................................................28
Chapter 4: Trends Analysis of water-related disaster ....................................................31
4.1. Trends of water-related disasters ............................................................................31
4.2. Regional assessment of social impacts of water-related disasters ..........................46
Temporal trend analysis based on each decade....................................................46
Temporal trend analysis based on each 5-year period .........................................52
4.2.1. Regional trends of killed people by type of water-related disasters .................57
4.2.2. Regional trends of affected people by water-related disasters..........................66
Chapter 5. Technical aspects and challenges ahead ........................................................79
Appendix..............................................................................................................................89
Annex 1: National, Regional and International disaster databases ................................95
Annex 2: EMDAT Water-related Disaster Glossary......................................................97
Annex 3: Processed Five-year data series of EMDAT data 1960-2004.......................100
Annex 4: Largest Disastrous Events: EMDAT data from 1900 to 2004......................117
A: Top 100 disastrous events in terms of killed people ....................................117
B: Top 100 disastrous events in terms of affected people.................................119
References..........................................................................................................................123iv

Foreword
Foreword
Water-related disasters afflict our societies in different forms and have continuously
taken an enormous toll on our socio-economic development. The increasing trend ofnegative socio-economic impact worldwide affirms that there is a shortage of effective
disaster preparedness and mitigation methods. This global shortage is due not only to thefact that risk reduction is not yet properly implemented as an integral part of water
resource management, but also to the social, economical and political factors that force
people to live in risky areas. To achieve our goals for sustainable development there are
emerging needs to develop novel concepts and management strategies to tackle themultifaceted complex issues hampering our progress in water-related disaster mitigation.
The development of strategic processes for water hazards mitigation requires a solid baseof concrete assessment and understanding of the risk levels that our societies are facing.
A holistic risk management approach is essential to build sound and sustainable policies
for mitigation of water-related disasters. A critical step forward in this direction is todevelop and sustain a reliable water-related disaster database to assess the vulnerabilityof people and property to each type of water-related disasters and propose tailoredadaptive actions to secure sustainable development.
Under our current preparatory activities for the establishment of the International Centre
for Water Hazard and Risk Management under the auspices of UNESCO (ICHARM),
research on flood risks and policy analysis has been initiated by the Secretariat of
ICHARM. This research is also part of our active collaboration to the United Nations World
Water Assessment Programme (WWAP) hosted by the UNESCO headquarters in Paris. In
addition to the Japan Case Study prepared for the second World Water Development
Report and coordinated by the Ministry of Land, Infrastructure and Transport (MLIT), ourinstitute is taking active participation to support the UN-Expert Group on Risk led by theWorld Meteorological Organization (WMO) and the United Nation International Strategy
for Disaster Reduction (UN-ISDR).
This technical report presents the first results of the investigation conducted by theauthors to analyze the global and regional trends of water-related disasters and theirsocial impacts during the past decades based on OFDA/CRED disaster databasedeveloped at the University of Louvain, Belgium. I welcome readers from all over theworld to evaluate through the results presented in this report the emerging needs forfurther research, information sharing and capacity building in the field of water hazard
and risk management. Today, the world is convinced that the need for a strong platformof cooperation to share science, knowledge bases and expertise, is more valuable thanever before. I invite you all to join Japan collaborative leadership in this direction throughyour support and contribution to the mission of the international center to ensure a safer
world and build more resilient nations against water-related disasters.

Dr. Tadahiko Sakamoto

Chief Executive
Public Works Research Institute (PWRI)

vi

Acknowledgments
Acknowledgments

The authors acknowledge the valuable advice of the anonymous reviewers. We also
acknowledge the comprehensive and high quality work of the people of the Centre
for Research on Epidemiology of Disasters (OFDA/CRED) of the University ofLouvain, Belgium, for creating and maintaining the Emergency Disasters Database(EMDAT) and for their initiative to make it open to public and accessible free ofcharge via their web site (http://www.em-dat.net).
We would like to thank all individuals and organizations working in the field of
natural disasters and risk management, namely the United Nations Educational,
Scientific and Cultural Organization (UNESCO), the World MeteorologicalOrganization (WMO), the UN International Strategy for Disaster Reduction(UN-ISDR), the United Nations Environment Programme (UNEP), the United
Nation Development Programme (UNDP), The Asian Disaster Reduction Center(ADRC), the Social Studies Network for Disaster Prevention in Latin America (LARED), and ReliefWeb, to site only few along many other national and regional
centers, for their initiatives to make their work and publications publicly available ina digital format and accessible via the Internet.

viii

Preface
PrefaceOf all natural disasters, water-related disasters (i.e., floods, droughts and epidemic
water related at the top of the list) are prevailing in number and their overwhelming
consequences for the society and the environment cannot be overemphasized. The
disaster database EMDAT reported that the number of people killed by flood andwindstorms during the period from 1960 to 2004 was as high as one million people
or about 20,000 people every year in average. The number of affected people bythese two disasters during the same period was as high as 300 million people or
about 7 million people every year in average. Dr. Jonas Bogardi, Director of UNU
Institute for Environment and Human Security (UNU-EHS) warns that unlesspreventative efforts are stepped up worldwide, the number of people worldwide
vulnerable to a devastating flood is expected to mushroom to 2 billion by 2050 due
to climate change, deforestation, rising sea levels and population growth inflood-prone lands. (The newsletter of United Nations University and its international
network of research and training centres/programmes, Issue32: July - August 2004).
Mitigation, alleviation, and reduction of water hazards are terminologies usedalternatively to express a common focal objective that can be addressed as: tominimize the negative impacts of disastrous events on people and property in a waythat ensures a stable society and sustainable progress. Many countries havedeveloped at varying levels their respective capacities for disasters risk reduction
and have put forward numerous preventive and mitigations actions. Nevertheless,the complex dynamics of water hazards determinants, both natural (such as climate
variability) and human-made (such as population explosion in hazardous area), haveincreased the vulnerability of people and property to the wide diversity of water
related disasters. In other words, the perennial toll on human lives and property
challenges the effectiveness and sustainability of adopted policies for water-related
disaster reduction and calls to search for innovative and holistic strategies forwater-related disasters mitigation and risk management. To this end building acommon platform to share knowledge and expertise among nations has become
more crucial than ever before. Our experience in water-related disasters mitigationin Japan and other Asian countries confirms that there is a prevailing need for thewater community to develop a more in-depth and common understanding of themechanisms underlying the risks associated with each type of water hazards. The
usefulness of coherent and comprehensive disaster databases as a fundamental
information in the learning, planning and decision processes has become
increasingly evident to many governmental and international agencies engaged indisaster management at both proactive and reactive stages.

xThis technical report presents the first phase of our assessment of the global andregional trends of water-related disasters and their social impacts. The assessment
processed in this study is based on the Emergency Disaster Database (EMDAT)
developed and maintained by the World Health Organization (WHO) Centre for
Research on Epidemiology of Disasters (CRED) at the University of Louvain,
Belgium. This work has been initiated as one of the contributions of the Public
Works Research Institute (PWRI) to support the United Nations World Assessment
Water Programme (UN-WWAP) hosted by UNESCO Headquarters. Ourcontribution to this collective effort, as members of the UN-Expert Group on Risk,
is to provide input (as contributing authors) and technical assistance to the World
Meteorological Organization (WMO) and the United Nations International Strategy
for Disaster Reduction (UN-ISDR) during the development phases of the Second
World Water Development Report (WWDR II).
The ultimate goal behind the assessment of the EMDAT database carried out in thisreport is to acquire and provide a more in-depth understanding of the global andregional social impacts of water-related disasters, specifically:- to understand the relationship between the increasing trends of each individual
type of natural and human-made water-related disasters and their social impacts(i.e., trends of killed people and affected people); and- to develop our understanding of the future requirements to build standardized
indicators in order to assist in the identification of the underlying risks fromwater-related disasters, perform policy analysis and evaluate the effectiveness ofadopted measures in water hazard mitigation.
To this end, the present technical report is structured around five chapters supported
by four related annexes. Chapter 1 introduces and then briefly discusses the scopeand range of our review assessment. EMDAT has been widely used as a reference
database in natural and technological disasters and this introductory chapter
addresses the fundamentals of our concepts in the assessment process of reported
water-related disasters data.
Chapter 2 introduces the disaster database EMDAT of OFDA/CRED, University ofLouvain, Belgium. This chapter in association with Annex1 brings together basic
information to understand the structure and terminology of EMDAT database
without major need to consult additional materials. Along with Annex 2, the chapter
also introduces other major disaster databases and initiatives such as GLIDE of the
Asian Disaster Reduction Center (ADRC). The end of the chapter put emphasis on
our disclaimer on the quality of information processed and the limitation of theresults of this investigation.

xi

Chapter 3 offers a review of the global picture of reported disasters in EMDAT. In
recent years in addition to natural disasters, technological (i.e., human made)disasters are drawing increasing attention due to their increasing pressures on humanhealth, the natural environment and ecologic diversity. Therefore, this chapter also
looks at the global distribution of this category of disaster. The overwhelming
difficulties underlying the assessment process are clarified by a series of graphs andtables presented from different perspective analyses. Emphasis is put on the global
assessment of the trends of disasters and their social impacts in terms of killed andaffected people.

Chapter 4 exclusively focuses on the processing of water-related disasters divided
into eight major types as defined within EMDAT, namely flood, windstorm, slide,wave and surge, drought, famine, epidemic water-related, and technologicalwater-related hazards (reported under “epidemic” and “technological” types,
respectively). The chapter analyzes the database from the global and regional
perspectives and puts emphasis on the underlying complexity and confusion that
may results during such an important exercise. The processed data on a 5-year
period basis are given in Annex 3.
Chapter 5 gives an overview of the results presented and highlights from theauthors’ viewpoints some important challenges and needs to build and promotecomparable eminent initiative such as the EMDAT of OFDA/CRED but with focus
and study-oriented to water-related disasters.

xii

List of Tables and Figures
List of Tables and Figures
List of Figures
Figure 1.1. Flow chart of the reporting methodology
Figure 3.1. Economic loss by year and by disaster reported in EMDAT from 1900 to 2004.
Figure 3.2. Trend of the number of natural disasters per year: EMDAT from 1900 to 2004.
Figure 3.3. Global distribution of disasters by category and for each 5-year period: EMDATfrom 1900 to 2004.
Figure 3.4. Moving average of the total number of killed people from 1900 to 2004.
Figure 3.5. Number of killed people by natural disaster from 1900 to 2004.
Figure 3.6. Temporal distribution of the number of killed people per year and per disasterfrom 1900 to 2004.
Figure 3.7. 100 and 200-event moving average of the total number of affected people from1900 to 2004.
Figure 3.8. Total number affected people by individual natural disaster events 1900 to 2004.
Figure 3.9. Temporal distribution of the number of affected people per year and by disasterfrom 1900 to 2004.
Figure 4.1.a. Global distribution of water-related disasters vis-à-vis other types of natural
disasters for the period from 1900 to 2004.
Figure 4.1.b. Global distribution of water-related disasters from 1900 to 2004.
Figure 4.2.a. Global distribution of water-related disasters for the period 1990-2004.
Figure 4.2.b. Global distribution of water-related disaster by continent for the period
1990-2004.
Figure 4.3. Trends of water-related disasters for each 5-year period since 1960 to 2004.
Figure 4.4. Trends of water-related disaster by continent for each 5 year period from 1960
to 2004.
Figure 4.5. Distribution of water-related disaster by continent from 1990 to 2004.
Figure 4.6. Trends of flood disaster by continent for each 5-year period: 1960-2004.
Figure 4.7. Trends of windstorm disaster by continent for each 5-year period: 1960-2004.
Figure 4.8. Trends of landslide and avalanche disaster by continent for each 5-year period:
EMDAT 1960-2004.
Figure 4.9. Trends of wave and surge disaster by continent for each 5-year period: EMDAT
1960-2004
Figure 4.10. Trends of drought disaster by continent for each 5-year period: 1960-2004.
Figure 4.11. Trends of famine disaster by continent for each 5-year period: 1960-2004.
Figure 4.12. Temporal distribution of epidemic disasters versus epidemic water-related
disasters for each 5-year period: EMDAT 1960-2004.
Figure 4.13. Distribution of epidemic water-related disaster by continent for each 5-year
period: EMDAT 1960-2004.

xiv

Figure 4.14. Trends of epidemic water-related disaster by continent for each 5-year period:
EMDAT 1960-2004.
Figure 4.15. Trends of the number of killed people versus affected people: EMDAT
1960-1990 and the 5-year period 200-2004.
Figure 4.16. Trend of the number of killed people by water-related disaster by continent foreach 5-year period since 1960 to 2004.
Figure 4.17. Trend of the number of affected people by water-related disaster by continent
for each 5-year period since 1960 to 2004.
Figure 4.18. Distribution of the number of killed people by flood disaster by continent foreach 5-year period from 1960 to 2004.
Figure 4.19. Distribution of the number of killed people by windstorm disaster by continent
for each 5-year period from 1960 to 2004.
Figure 4.20. Distribution of people killed by both flood and windstorm disaster bycontinent for each 5-year period from 1960 to 2004.
Figure 4.21. Distribution of people killed by landslide and avalanche disaster by continent
for each 5-year period from 1960 to 2004.
Figure 4.22. Distribution of the number of people killed by wave and Surge disaster bycontinent for each 5-year period from 1960 to 2004.
Figure 4.23. Distribution of the number of people killed by drought disaster by continent
for each 5-year period from 1960 to 2004.
Figure 4.24. Distribution of the number of people killed by famine disaster by continent foreach 5-year period from 1960 to 2004.
Figure 4.25. Distribution of the number of people killed by epidemic water-related disasterby continent for each 5-year period from 1960 to 2004.
Figure 4.26. Distribution of the number of people killed by technological water-related
disaster by continent for each 5-year period from 1960 to 2004.
Figure 4.27. Distribution of the number of affected people by flood disaster by continent foreach 5-year period from 1960 to 2004.
Figure 4.28. Distribution of the number of affected people by flood disaster by continent foreach 5-year period from 1960 to 2004.
Figure 4.29. Distribution of the number of affected people by landslides and avalanche
disasters by continent for each 5-year period from 1960 to 2004.
Figure 4.30. Distribution of the number of affected people by wave and surge disasters bycontinent for each 5-year period from 1960 to 2004.
Figure 4.31. Distribution of the number of affected people by drought disaster by continent
for each 5-year period from 1960 to 2004.
Figure 4.32. Distribution of the number of affected people by both famine disaster bycontinent for each 5-year period from 1960 to 2004.
Figure 4.33. Distribution of the number of affected people by epidemic water-related
disaster by continent for each 5-year period from 1960 to 2004.
Figure 4.34. Distribution of the number of affected people by technological water-related
disaster by continent for each 5-year period from 1960 to 2004.
Figure 5.1. Top 1000 disastrous events in terms of affected people from 1900 to 2004.

xv

Figure 5.2.a. Ratios of numbers of events of water-related disaster per type.
Figure 5.2.b. Ratios of numbers of killed people by type of water-related disaster.
Figure 5.2.c. Ratios of numbers of affected people by type of water-related disaster.
Figure 5.3. Extreme one hundred extreme water-related disaster classified by largest
number of affected people since 1960 to 2004.
Figure 5.4. Extreme one hundred extreme water-related disaster classified by largest
number of killed people since 1960 to 2004.
Figure 5.5. Selected indicators for PWRI Flood Risk Index to assess policy effectiveness inflood mitigation.

List of Tables
Table 2.1. Entry criteria of disaster database information by major organizations.
Table 2.2. Outlook of EMDAT structure and fields of information as of March 2005.
Table 3.1. Relative values of economic loss when using different conversion indices.
Table 3.2. General figures of natural and technological disasters from 1900 to 2004.
Table 4.1. Entry of epidemic water-related disasters in EMDAT.
Table 4.2. EMDAT top 10 water-related disasters in terms of killed people in the 1960s.
Table 4.3. EMDAT top 10 water-related disasters in terms of killed people in the 1970s.
Table 4.4. EMDAT top 10 water-related disasters in terms of killed people in the 1980s.
Table 4.5. EMDAT top 10 water-related disasters in terms of killed people in the 1990s.
Table 4.6. EMDAT top 10 water-related disasters in terms of affected people in the 1960s.
Table 4.7. EMDAT top 10 water-related disasters in terms of affected people in the 1970s.
Table 4.8. EMDAT top 10 water-related disasters in terms of affected people in the 1980s.
Table 4.9. EMDAT top 10 water-related disasters in terms of affected people in the 1990s.
Table 4.10. Top 10 most disastrous floods in terms of affected people.
Table 4.11. Top 10 most disastrous windstorms in terms of affected people.
Table 4.12. Total affected people by regional major wave and surge disasters.

Table 4.13. Top 15 drought disasters in terms of total affected in EMDAT.
Table 4.14. Top 15 famine disasters in terms of total affected people reported in EMDAT.
Table 4.15. Top 10 drought disasters in terms of total affected people in each continent.

xviChapter 1: Background and Objectives
Chapter 1: Background and Objectives
1.1. Introduction
Trends in natural disasters are continuously increasing in most regions of the world.
Among all observed natural and anthropogenic adversities, water-related disasters
are undoubtedly most recurrent and pose major impediments to achieving humansecurity and sustainable socio-economic development. Natural pressures such as
climate variability, managemental pressures such as lack of appropriate organization
systems, inappropriate land management and uncertainty in water hazard planning,along with social pressures such as escalation of population and settlements in highrisk areas (particularly the poor people) amongst others, are factors that haveincreased the vulnerability of population and property to the wide diversity ofnatural and human-made water-related disasters. For instance, during the period
2000 to 2004, 1362 water-related disasters have been reported by EMDAT database,killing more than 40,000 people and afflicting more than 810 million people.
The escalating figures of socio-economic impacts affirm the existence of an overall
deficiency in up to date managemental strategies to reduce risks from water-related
disasters. Consequences that have increasingly forced governments and concerned
institutions to intervene directly by formulating policies that places risk management
as elements of integrated water resources management. The World Conference on
Disaster Reduction, held in Kobe, Hyogo, Japan, from 18 to 22 January 2005,
resolved “that Disasters have a tremendous detrimental impact on efforts at all levels
to eradicate global poverty; the impact of disasters remains a significant challenge tosustainable development”. The Hyogo Declaration adds “that it is criticallyimportant that the Hyogo Framework for Action 2005-2015: Building the Resilienceof Nations and Communities to Disasters be translated into concrete actions at alllevels and that achievements are followed up through the International Strategy for
Disaster Reduction, in order to reduce disaster risks and vulnerabilities”. Theinternational community “also recognize the need to develop indicators to trackprogress on disaster risk reduction activities as appropriate to particular
circumstances and capacities as part of the effort to realize the expected outcome
and strategic goals set in the Hyogo Framework for Action 2005-2015: Building theResilience of Nations and Communities to Disasters.” (WCDR 2005: extracts fromthe Hyogo Declaration).
In this direction, the end goal of this research is to develop a globally applicablewater-related disaster index (i.e., flood risk index at this first stage) to assess theeffectiveness of flood mitigation policies and furthermore to be used as a decision1

tool for policy analysis and assessment of proposed mitigation measures andstrategies. The index is built as functional aggregation of constructive set ofindicators measurable at the national and global scales. This work has been initiatedas a contribution to the ongoing international efforts to produce the second edition of
the World Water Development Report (WWDR 2) managed by the UNESCO
Secretariat of the World Water Assessment Programme (WWAP).
This technical report presents our preliminary assessment of the trends of different
type of water-related disasters at the regional and global scales. The database used inthis analysis is based upon the Emergency Events Database (EMDAT), developedby the WHO Centre for Research on the Epidemiology of Disasters (CRED) of the
University of Louvain in Belgium. Our primary objective behind this assessment isto acquire and provide a more in-depth understanding of the impacts of natural
disasters triggered by hydrometeorological events, specifically, to understand therelationship between the increasing trends of each individual type of water-related
disasters and their social impacts (i.e., the trends of the number of killed people andaffected people in particular). The other concurrent objective is to develop ourunderstanding of the global requirements and challenges to build standardized global
indicators to assist in the identification of underlying risks from water-related
disasters and to evaluate the effectiveness of adopted policies in water hazard
mitigation.
It is one of the goals of the International Centre for Water Hazards and Risk
Management under the auspices of UNESCO after its establishment to undertake asystematic initiative to build a comprehensive water hazard database. We lookforward that this analysis will serve to draw practical conclusions on the futureneeds to construct reliable disaster and risk information system that will be able torespond to the particular challenges imposed by water hazards and related risk
management issues. However, it is needless to emphasize that the accomplishment
and success of such hardship mission requires synergic cooperation involving allconcerned parties to create a safer world from water-related disasters.

21.2. Methodology
Establishing a central database on all disaster events occurring in the world requires
a great deal of efforts and commitments from all relevant institutions at the national,
regional and international levels. Up to date there is no known standard method toaccount impact of disasters particularly the accountability of affected people anddamages in terms of direct economic loss (not to mention the evaluation of indirect
impacts). Our objective is to create the capacity and information base to analyze
water hazards and understand the risk mechanism (including the resiliency ofaffected society) and potential effects (i.e., vulnerability) in time and space for the
purpose of its use in disaster management and planning. The usefulness of a sound“disaster database” as a fundamental tool to support this process has become
increasingly evident to many government and international agencies engaged indisaster relief and mitigation. To respond to the emerging needs for better disasterrecords, a number of databases have been established around the world, withdifferent criteria, formats and purposes1. While these databases are individually
useful, their inconsistencies, data gaps and ambiguity of terminology makecomparison and use of the different data sets difficult. This has led to a fair amountof confusion in the perception and evaluation of a disaster situation and poses
serious obstacles for planning and fund raising (Guha-Sapir and Below, 2002).
Statistics show that among all natural disasters, water-related disasters are the major
cause for loss of life and damage to property. Despite this global recognition there is
not yet a single central platform or clearing house for water-related disasters
databases with the scope to compile, compatibilize, coordinate and analyze thepresently dispersed information. The success of such effort requires a great deal ofcommitments and collaboration from all national, regional and international engaged
parties. Technically, for such project to be efficient there is a need to create
systematic, homogeneous, and compatible standard procedures for monitoring andaccounting disasters’ risk as well as for collecting and reporting disasters
information.
At the global scale the most widely used and accepted disaster database is the"EMDAT: The OFDA/CRED International Disaster Database” (hereafter referred toas EMDAT) developed and managed by the Centre for Research on the
Epidemiology of Disasters (CRED), University Catholic of Louvain, Belgium. As
described in Chapter 2, only events responding to what is called “entry criteria” arereported in EMDAT. The results of this entry selection process will therefore hide1

At the national level, governments undertake continuous efforts to build and maintain disaster databases.
Chapter 2.3 and Annex 1 of this book introduce some of the existing disaster databases worldwide.

3

thousands of small and medium scale disasters that occur every year in different
regions of the world.
-

Since its creation in 1988, EMDAT was structured around two major groups ofdisasters, namely natural disasters and technological disasters. Disaster
information for each event entry is presented in a tabular form. As it will be
detailed in Chapter 2, in addition to the temporal (i.e. year of the event) andgeographical (i.e. country and region) information, each specific events is
described by multi-field entries such as the number of dead, number of injured
people, economic loss, etc.

As EMDAT is regularly updated and validated, it is important to notice that theresults and figures processed in this report are based on the disasters data last
downloaded on 25 March 2005. As mentioned earlier, the fields of data processed
are limited to the social impacts of water-related disasters, namely: temporal trendsof the number of killed people and the total number of affected people in each of thefive regions (Africa, Asia, Americas, Europe and Oceania). Hereafter, the word
“water-related disasters” refers to the following eight categories:- flood (flood, plain flood, valley flood and flash flood);- windstorm (typhoon, hurricane, cyclone, tornado, tropical or winter storm andothers);- wave & surge (tide wave and tsunami);- slides (landslide and avalanche);- drought;- famine (triggered by drought, food shortage and crop failure);- epidemic water-related (classified as Epidemic in EMDAT. In this report, type of
epidemic water-related are selected based on the WHO definitions); and- technologic water-related disasters
The flowchart of Figure 1.1 shows the chapters dependencies in this technical report.
We have tried to keep the perquisite material between the chapters to a minimum
level to allow greater flexibility.

4

Global Trends ofWater-related Disasters
Chapter 1
Background andObjectives

Chapter 2:
Global Disasters
Database EMDAT- Table of contents- List of tables- List of graphs

Foreword
Chapter 3
Global Assessmentof Human Disasters

PrefaceAnnexes
Chapter 4
Global Assessment of
Water-related Disasters

Chapter 5
Technical Aspects andChallenges Ahead
Figure 1.1. Flow chart of the reporting methodology.

5Chapter 2: The Global Disasters Database EMDAT
Chapter 2: The Global Disasters Database EMDAT
2.1. General criteria
The development and maintenance of an up-to-date informative disaster database isa major concern in many countries. As mentioned earlier, one of our objectives forthe development of a disaster database is to create a disaster analysis tool andvulnerability assessment methodology serving the purposes of formulating policy
scenarios and rationalizing decision making for disaster proactive preparedness.
There are numbers of national and international efforts to create disaster databases.
While national databases are built to respond to governments’ strategic goals in
disaster mitigation, international databases are mainly developed and maintained tohelp achieving global goals and developing institutions and international standards.
The widely accepted international database on natural and man-made disasters isundoubtedly the OFDA/CRED International Disaster Database (EMDAT). The
OFDA/CRED International Disaster Database (EMDAT) is a global database,
supplied and maintained since 1988 by the World Health Organization (WHO)Collaborating Centre for Research on the Epidemiology of Disasters (CRED) at the
University of Louvain. January 1999 saw the start of collaboration between the
Office of Foreign Disaster Assistance (OFDA) of the United States Agency forInternational Development (USAID/OFDA) and CRED, with a view to completingthe EMDAT database and validating its content. Since then, OFDA and CRED havemaintained a single database (OFDA/CRED, 2002). In a way this initiative cameinto being as a response to one of the priorities of the international aid community,
namely making better preparations to deal with disasters and doing more to prevent
them happening (OFDA/CRED, 2002). The main objective of the database is toserve the purposes of humanitarian action at the national and international levels. It
is an initiative aimed to rationalize decision making for disaster preparedness, aswell as to provide an objective base for vulnerability assessment and priority setting(EMDAT, 2005).
2.1.1. EMDAT Sources of Data
EMDAT is regularly validated and updated by compiling disaster data collectedfrom various national and international organizations specialized in disaster
information analysis and dissemination. Guha-Sapir et al. 2004, reported that thesource of information for EMDAT includes:7

1. United Nation Agencies;
2. Non governmental institutions;
3. Research institutes;
4. Insurance companies;
5. Humanitarian and disaster agencies;
6. Specialized agencies;
7. Government agencies; and8. The media.

The primary source for each disaster is defined according to a priority information
source-list set up by CRED. The sources identified by CRED as "priority" -judged
on their consistency and reliability- include in order of preference: The United
Nations agencies are first in line, in the order shown hereafter:--

UN Agencies: the Office for Coordination of Humanitarian Affairs (OCHA), theWorld Food Program (WFP) and WHO;
US Government Agencies: USAID/OFDA, the US National Oceanic andAtmospheric Administration and the US Federal Emergency Management
Agency;Official government sources in the affected nations;
The International Federation of Red Cross and Red Crescent Societies;
Research Centers;
Lloyd's of London; andReinsurance sources.

The sources are continually being assessed with a view to achieving improved
reliability. Normally a single primary source will be used to develop disaster entry
information. The information is verified with as many as ten other confirming data
sources. Where official estimates of the number of killed people or homeless areunavailable, informed proxies are used to develop estimates (ProVention, 2001).
2.1.2. Events Entry Criteria:
The classification of an event as “a disaster” varies from database to database dueto the large difference in scope, focus and objectives of the organizations engaged
in collecting and distributing disaster information. This variation in classification
strategy creates major discrepancies between the existing disaster databases not
only in terms of the number of disasters reported but also in terms of the magnitude
8and impact of each disaster. Guha-Sapir (2002), Arakida and Murata (2003)
reported that one of the major factors creating differences between popular disasterdatabases resides in the disaster entry criteria as shown in Table 2.1.
Table 2.1. Entry criteria of disaster database information by major organizations (*)
Relief Web

ADRC•Declarationof state of
emergency;
and/or•Based of on
the IFRC
report•>=1 death (Japan); or•>= 5 death (Mem.); or•>= 10 death (other area); or•>=1 injured (Japan); or•>= 5 injured (Mem.)•>= 10 injured (other area•>=100 affected (Japan); or•>= 500 affected (Mem.); or•>= 1000 affected (other area); or•Serious economic damage; or•Call for international assistance.

DesInveter
NatCat(LARED)(MunichRe)•Any•Any loss of
disaster inlife orthe Latin
livelihood or
Americaany serious
injury (Onlymajor events
before 1980)

Sigma(SwissRe•>= 20 death; or•>= 50 injured; or•>= 2000
homeless; or•> 14M US$ ofmarine loss; or•>28M US$ ofaviation loss; or•>35M US$ ofothers losses; or•>70M US$ of
total loss(*) See Chapter 2.3 and Annex 1 for further information on these databases.

Under the specific scope of the OFDA/CRED EMDAT project, an event is classified
as “a disaster” and entered into EMDAT if at least one of the following criteria isfulfilled:- 10 or more people reported killed; or- 100or more people reported affected; or- Declaration of a state of emergency; or- Call for international assistance.
2.2.

EMDAT typology of disasters and structure of the database

A disaster in EMDAT is defined as: “A situation or event which overwhelms local
capacity, necessitating a request to the national or international level for external
assistance, or is recognized as such by a multilateral agency or by at least twosources, such as national, regional or international assistance groups and the media.”(EMDAT, 2005).
As of 23 March 2005, the EMDAT database presents the core data on the occurrence
and effects of 14,740 disasters covering the period from 1900 to 2004 (the database
covers shorter periods for some types of disasters). Disasters in EMDAT aretypically classified into two categories as either natural or technological (i.e.
human-made). Following the typology adopted by EMDAT natural and9technological disasters are defined as:• Natural

disasters: are disasters triggered by natural geological and/orhydro-meteorological events. This group encompasses 13 disaster types, namely:
Drought, Earthquake, Epidemic, Extreme temperature, Famine, Flood, Insect
infection, Slides, Volcano, Wave & Surge, Wild fire, and Windstorm. The
detailed definitions adopted by EMDAT as well as the sub-sets of each type aresummarized in “Annex 2: EMDAT Glossary” for convenience and readability.

• Technological disasters: are disasters triggered by technological hazard or

anthropogenic influence. This group of disasters is classified into three majordisaster types, namely: Industrial accident (Gas leak, Poisoning, Industrial Fire,etc.), Miscellaneous accident (Explosion, Fire, Collapse, etc.), and Transport
accident. For the detailed definition and sub-sets enclosed in each type refer to“Annex 2: EMDAT Glossary” of this technical report.
Each disaster entry is described by 42 fields of data or information as shown in
Table 2.2. It includes the main following fields:- Country: Country(ies) in which the disaster has occurred.
- Disaster group: Two groups of disasters as mentioned above: natural disasters andtechnological disasters. Some entries are classified as complex emergencies.
- Disaster type: Description of the disaster according to a pre-defined classification.
- Date: When the disaster occurred. The date is entered in three fields as year, monthand day (for both the start date and end date of the event).
- Dead or Killed: Persons confirmed as dead and persons missing and presumed

dead (official figures when available). Information assessed in this study.
- Injured: People suffering from physical injuries, trauma or an illness requiring

medical treatment as a direct result of a disaster (included in the field ‘total
affected’).
- Homeless: People needing immediate assistance for shelter (included in ‘total

affected’).
- Affected: People requiring immediate assistance during a period of emergency, i.e.

requiring basic survival needs such as food, water, shelter, sanitation and
immediate medical assistance (included in the field ‘total affected’).
- Total affected: Sum of injured, homeless, and affected people; it can also include

displaced or evacuated people. Information assessed in this study.

10

- Estimated Damage: The economic impact of a disaster usually consists of direct(e.g. damage to infrastructures, crops, housing) and indirect (e.g. loss of revenues,
unemployment, market destabilization) consequences on the local economy.
- Additional fields: Other geographical information (such as location, latitude andlongitude), the value and scale of the events (such as the Richter scale value for anearthquake), the international status (international response, aid contribution, request
for international assistance, disaster/emergency declaration), and the sectors affected,
etc.

11

12

5
1
9
61
55
121
244
211
241
598
132
645
599
435
830
141
644
588
465
659
383
580
16

1923
1932
1950
1963
1970
1975
1978
1980
1989
1990
1991
1994
1999
2002
2002
2003
2004
2004
2004
2004
2004
2004
2005

SlidesVolcanoWave / Surge

EpidemicDrought

NaturalWind Storm
Natural
FamineNaturalWind Storm
NaturalExtreme Temperature
NaturalFlood
NaturalWind Storm
NaturalInsect Infestation
NaturalWild FiresNatural
FamineTechnologicalIndustrial Accident
NaturalVolcanoNaturalExtreme Temperature
NaturalWave / Surge
NaturalEpidemic
NaturalSlidesTechnological Transport Accident
Technological
Misc Accident
NaturalSlidesTechnological Transport Accident
NaturalWave / Surge
NaturalWild FiresNaturalWind Storm
NaturalEarthquake

NaturalNaturalNaturalNaturalNaturalTable 1 (Continue): Fields Entries for each disaster
end_year end_month
end_day
dis_subset2
1900
0
0
-1900
1
13
-1900
7
7
-1902
1
2
-1908
4
26
-1923
7
10
-1932
0
0
-1950
9
1
-1963
1
0
-1970
10
7
-1975
5
29
-1978
9
0
-1980
6
0
-1989
0
0
-1990
9
15
-1991
6
22
-1994
12
0
-1999
12
23
-2002
7
17
-2002
12
21
-2003
3
24
-2004
12
22
-2004
11
12
-2004
9
11
-2004
12
26
-2004
8
0
-2004
11
19
-2005
1
10
--

8
2

11

1908

7

1900

1900
1902

2

1900

dis_subset3-----------------------------

Storm
Food shortage
Hurricane
Cold wave
Flood
CycloneInsect infestation
Scrub
Crop failure
Ind:Poisoning
VolcanoHeat wave
Tidal wave
UnknownLandslide
Water
Explosion
Mudflow
Air
TsunamiForestTyphoonEarthquake

Landslide

VolcanoTsunamiDiarrhoeal/EntericDrought

Table 1: Data Structure and fields of information of EmDAT as of March 25, 2005
Yearseq
dis_group
dis_type
dis_subset

dis_subset4-----------------------------

Muifa

Helicopter

Ferry 'Kasobwe'
Oleoduc

Unknown

Drug (cough syrip)
Mount Pinatubo

Dog

Gastroenteritis

event_name

iso
CPV
JAM
JPN
SLV
CAN
SUN
SUN
ATG
USA
ITA
IND
VNM
CAN
RWA
NGA
PHL
AUS
THA
CHN
BRA
BDI
NGA
TTO
GRC
LKA
PRT
PHL
IRN

Kill
Kill
OFDA
Kill
Kill
GovernSigDamAffect
Kill
Kill
Kill
AffectAffectAffect
Kill
Kill
Kill
Affected
Kill
Kill
SigDisAffected
Affected

Kill

Kill
Kill

Kill

Kill

entry_criteria

regionWest Africa
Caribbean
East Asia
Central America
North America
Russian Federation
Russian Federation
Caribbean
North America
European Union
South Asia
South-east Asia
North America
East Africa
West Africa
South-east Asia
OceaniaSouth-east Asia
East Asia
South America
Central Africa
West Africa
Caribbean
European Union
South Asia
European Union
South-east Asia
South Asia

Soviet Union
Soviet Union
Antigua and Barbuda
United States
Italy
India
Viet Nam
CanadaRwandaNigeria
Philippines
Australia
ThailandChina P Rep
BrazilBurundiNigeria
Trinidad and Tobago
GreeceSri Lanka
Portugal
Philippines
Iran Islam Rep

CanadaJapan
El Salvador

Jamaica

Cape Verde Is

country_namecontinent
AfricaAmericas
Asia
Americas
Americas
EuropeEuropeAmericas
Americas
EuropeAsia
Asia
Americas
AfricaAfricaAsia
Oceania
Asia
Asia
Americas
AfricaAfricaAmericas
EuropeAsia
EuropeAsia
Asia

Vila Real, Santarem, Faro,
Viseu, Bragance
Catanduanes Isl., Bicol
peninsula, Mindoro Isl.,
Agh Ghala region

Near Alonissos Isl. (Egeesea)

Zambales, Pampanga,
Olongapo, Tarlac (Luzon Isl.)
Southern NSWSurat Thani, Nakhon Si
Thammarat, Chumphon
Mishan city (Heilongjiang
province)
Teresopolis
Tanganyiaka lake (between
RDC and Burundi)
Near Ilado

South, West of Kigali

Red Lake, Ontario

Maharashtra (Coast)

Genoa provinces

Nationwide

Rostov

Notre Dame de La Salette,
Quebec

Porus

Countrywide

location

Overloaded boat

Landslide / Mudslide

Earthquake

Heat Wave
Landslide / Mudslide

associated_dis2

00001300000
0
0
5000
60000
0
1035870
1000000
0
1000
0
48
0
1200
0
12443300838434
0

0

0
0

0

0

no_affectedassociated_dis

0
0
0
0
0
0
0
0
0
0
195
34
0
0
0
0
0
0
0
23176
0
240
110

23
5000000
2
150
37
0
0
0
237
109
640
0
0
0
13
150
27
2
17
35672
2
104
0

origin

0

0
0

30
185
33

0

0

11000
30

no_injured

no_killed

ofda_response
true
false
false
false
false
true
true
true
false
true
false
false
false
true
true
true
false
false
false
false
false
false
false
false
false
false
false
false

0
0
0
0
1650
0
0
0
0
0
0
0
200
0
0
0
0
0
0
0
0
0
0

0

0
0

0

0

no_homeless

false
false
false
false
false
false
false
false

false

eu_response

00001301650
0
0
5000
60000
0
1036065
1000034
200
1000
0
48
0
1200
0
12675060838674
110

0

0
0

0

0

false
false
false
false
false
false
false
false

false

appeal001000
026830000000211000
0
267
0
0
0
0
0
0
1000000
0
6000
0

0

0
0

0

0

false
false
false
false
false
false
false
false

false

declaration

1923
1932
1950
1963
1970
1975
1978
1980
1989
1990
1991
1994
1999
2002
2002
2003
2004
2004
2004
2004
2004
2004
2005

1908

1900
1902

1900

1900

start_year

1080
120
5.8

0
0

44
4

3550
436

Km2
Kph
RichteroCheight (m)vaccinated

kph
oC
km2
kph
km22
km2

kph

Richter

dis_mag_value dis_mag_scale
km2
vaccinatedtotal_affected damage_us damage_eu aid_contribution

Table 2.2. Outlook of EMDAT structure and fields of information as of March 2005.

37.103 N

15.13 N

latitude

7
0
9
1
10
5
9
6
0
9
6
12
12
7
12
3
12
11
9
12
7
11
1

4

7
1

1

0

54.574 E

120.35 E

longitude

10
0
1
0
7
29
0
0
0
15
9
0
23
17
21
24
22
12
11
26
0
19
10

26

7
2

13

0

start_month start_day

22:16

local_time

Tanganyiaka
lake

river_basin

2.3. EMDAT data quality and limitations
Data quality is one of the major critical problems facing risk managers today. As
management becomes more dependent on information systems to fulfill their
missions, data quality becomes a larger issue for its impacts on decision making.
The results of the global analysis processed in this study clearly prove that thereporting of disasters in EMDAT has greatly improved over the last 40 years. The
reason of such progress is due to the evolution of information systems, increasing
availability of statistical data and evolution of EMDAT’s sources in reporting natural
disasters.
Quoting Guha-Sapir et al. (2004), the database has gradually increased the use of
insurance companies' reports, while using those form humanitarian and disasteragencies has remained relatively constant over time. Despite efforts to verify andreview the data, the quality of disaster databases can only be as good as the reporting
systems that feed them. There are strong reasons to believe that the figures presented
in EMDAT are probably underestimates. For example, droughts reportedly killed
500,367 people in Ethiopia over the last three decades. But some estimate that the
number of people who died from the great Ethiopian drought of 1984-1985 alone
may have numbered between 600,000 and one million people1. Even worse is thecase of economic damages, where not more than a third of reported disasters
estimate economic losses (Guha-Sapir et al., 2004).
Under these considerations, the quality and extent of the results are limited by thequality and validity of the original data-sources assuming operator error free. In our
coming report on flood disasters we have focused on the numbers of quantitativeand qualitative aspects in evaluating economic damages with practical examples
from Japan. The future undoubtedly requires great efforts to create a homogenous
global strategy to quantify and report disaster information. An initiative toward thisglobal standardization is the “GLobal unique disaster IDEntifier number” known as
the GLIDE initiative by the Asia Disaster Reduction Centre (ADRC). At this stage
GLIDE defines a globally common identification number or ID code for every
disaster that occurs in the world. This initiative will surely make it easier to identify
and compare the data on disasters reported in the different existing databases. Annex
1 reviews some major regional and international disaster databases.
Hereafter the abbreviation “EMDAT” is used to refer to the citation requirements of
OFDA/CRED and should be literally read as: “Source: "EM-DAT: The
OFDA/CRED International Disaster Database, www.cred.be/emdat - Université
Catholique de Louvain - Brussels - Belgium".
1

Refer to Chapter 5 to overview our comments on data reporting for some particular events.

13

Chapter 3: Global Assessment of Human Disasters
Chapter 3: Global assessment of human disasters
3.1. Trends in natural disasters
The viability of risk management approach in water-related disasters is surroundedwith complexity as it is subject to multifaceted management of land and water.
While water disasters are triggered by hydro-meteorological phenomena yet hard toaccurately forecast, the impacts on people and property are very much sensitive tothe static and dynamic states of the surrounding environment and its resiliency torisk. Thus, building strategic mitigation plan implies undertaking comprehensive
risk assessment of actual and potential causes and consequences of the disaster.
Parameters used to evaluate the state of the natural environment and consequent
impacts of water hazards are often referred to as indicators (WWAP, 2003).
Identification of liable indicators is a complex evolutionary process that is still ill
defined for the various types of water-related disasters triggered by natural andhuman-made factors with diverse direct and indirect social and economic impacts(i.e. also vulnerability). The future is to identify the best and well balanced
combination of structural and non-structural measures to alleviate disasters’ impact
in sustainable manner. We cannot overemphasize that the construction andachievement of a sustainable mitigation policy requires balanced and high-quality
disaster database framed to respond to the challenges imposed by water hazards. At
this stage, we limited ourselves to analyze the trend of natural water-related disasters
as reported in EMDAT that is mainly to assess the social impacts in terms of killed
people and total affected people as acknowledged by many practitioners to bevaluable global indicators to assess progress in disasters mitigation.
From the period 1900 to 2004 EMDAT reported 14,740 events of natural andtechnological disasters. The overall events have claimed the life of more than 37
million people and affected the livelihood of nearly 6000 million people. Within thisglobal picture, disasters triggered by hydrometeorological events such as floods,
droughts and windstorms, etc., are larger in number and wider in impact ascompared to natural disasters triggered by geological hazards such as earthquakes
and volcanoes. Table 1 presents comparative values between the different types ofdisasters as defined by the EMDAT typology. As can be seen from the table theproportion of people killed by natural disasters accounted for more than 70% of thetotal compared to 30% killed by technological disasters. The figure was even higher
in terms of affected people by natural disasters which accounted for 90% of the total
as compared to 10% affected by technological disasters. A closer look at the impactof each type of natural disasters, the table reveals a complex inter-relation between

15the number of killed and the number of affected people by each type of water related
disasters. For instance, during the period from 1900 to 2004, flood accounted forabout 28 % of the total number of disasters claiming 19% of the total casualties and
48% of the total affected people. When accounting both flood and windstorm events(also acknowledged as major events triggering floods) the values rise up to morethan 50% for both killed and total affected people. On the other hand, epidemics
which accounted for about 10% of the number of disasters claimed 26% of the total
casualties but accounted only for 1% of the total affected people. Other interestingdata to explore are the data for earthquake and famine which accounted for 10% and
1% of the total number of disasters, while respectively, killed 5% and 19%, andaffected 2% and 1% of the totals reported.
The examination of the dissimilarities underlying the effects related to the trend ofdisasters and the trend of their respective impacts clearly shows the complexity ofrisk disasters assessment. While global data can help understand the world statusvis-à-vis the impacts of water-related disasters, it is clear that further analysis basedon disasters type is a perquisite before concrete conclusions can be drawn on theefficiency of current international actions and practices to mitigate water-related
hazards. A complete comparative study shall also include an assessment of theeconomic damages as more valuable property and high-tech assets are nowadays
concentrated in high risk areas.
The value of the global economic damage (or economic loss) reported in Table 3.1 iscalculated by accumulating the real value of the accounted damage for the year of
the event without any relative conversion to a specific year. The reasons for using
brut values are three folds, first, as mentioned above, our main objective is tocompare the social impacts of water-related disasters at the global and regional
levels and draw explicit figures to help our understanding in the process of
indicators development as well as to identify areas of improvement in water-related
disaster databases for reliable assessment of vulnerabilities and policy analysis.
Second, several institutions have developed methodologies to quantify economic
losses. However, there is no globally agreed standard procedure to determine thereal figure of economic damages. Therefore, in-depth research is still required todefine and set the most appropriate method to calculate the relative value of
economic losses at a given year from water disasters in particular. Third, the existing
methods and indices of comparison such as GDP or the Consumer Price Index (CPI)
among others are often used without deep thought to their consequences andapplicability to the multifaceted and diversity of types of direct and indirect
economic damages endured by water disasters. In other words, it is clear that using
different indices will lead to completely different conclusions. For instance thewindstorm (i.e., hurricane) disaster of 8 September 1900 in USA resulted in US$1

16

million worth of economic loss. Table 3.1 shows that the relative value of the loss of
US$1 million in the year 1900 varies, depending on different indices (see Economic
History, 2005), from 19 million to 600 million in the year 2003. Thus it is imperative
to decide which of these indices (or combination of indices) is more appropriate to
analyze the true damage from water-related disasters. Nevertheless, using the brutvalue as indicator (regardless of using a conversion index) Figure 3.1 shows that
economic damages had been continuously increasing during the past three decades
in particular (improvement in EMDAT reporting has also to be sought). Floods andwindstorms are at the top of the list followed by earthquake disasters as can be seenfrom Table 3.2.
Number of deadEconomic loss by year and by disastser reported in EmDAT from 1900-2004

100000000

10000000

1000000

100000

10000

1000

100

10

Year

Figure 3.1. Economic loss by year and by disaster reported in EMDAT from 1900 to 2004.

Table 3.1. Relative values of economic loss when using different conversion indices.
In 2003, $1,000,000 of economic loss in 1900 is worth: $21,788,515
using the Consumer Price Index $18,533,333
using the GDP deflator $107,446,043
using the unskilled wage $154,014,335
using the GDP per capita
 $588,003,212
using the relative share of GDP

17

2004

2000

1996

1992

1988

1984

1980

1976

1972

1968

1964

1960

1956

1952

1948

1944

1940

1936

1932

1928

1924

1920

1916

1912

1908

1904

1900

1

Table 3.2. General figures of natural and technological disasters from 1900 to 2004.
Impact
Event
Flood
Wind Storm
Earthquake
EpidemicDrought
SlidesWild Fire
Extreme Temperature
VolcanoInsect Infection
FamineWave/Surge
Totals of Natural Disasters
Technological
TotalsNumber ofDisasters
2636
2569
978
937
807
477
292
270
176
83
76
52
9353
5387
14740

Number of
Dead
6,888,152
1,199,041
1,881,041
9,520,307
10,008,644
53,7832,650
64,69995,9090
7,158,299
295,011
37,167,536
272,471
37,440,007

Total Affected Real Damage
People($USx1000)
2,921,323,648
322,552,819
636,706,948
347,099,342
96,294,254
309,181,417
39,566,095
4,737
2,192,716,836
58,108,208
9,797,760
3,469,311
4,011,734
29,307,293
11,402,747
20,688,659
4,199,184
3,692,646
2,200
230,125
70,996,301
93,4492,561,120
7,848,747
5,989,578,827 1,102,276,753
7, 516,095
24,211,042
5, 997,094,922 112,648,7795

Looking to the number of disasters from the global scale, there is a continuous
increasing trend from decade to decade. For instance (see Figure 3.2), the minimum
threshold of the number of natural disasters occurring per year in 1970s was about
50 events, this minimum threshold of recurrent events was 100 events in 1980s,
increased to 200 events in 1990s and up to 350 events per year during the past
5-years (i.e., since the beginning of the 21st century). During the years 2000 and2002 more than 500 disasters occurred, respectively. As shown in Figure 3.3, theaverage rate at which the number of disasters increased after every 5 years was
about 3%. The 5-year periods 1990-1994 and 1995-1999 accounted for about 13%
and 16% of the total disasters respectively. The last 5 years 2000-2004 accounted for
24% of the total reported disasters, which represents an increasing rate of about 8%
as compared to the previous 5-year period. As depicted in Figure 3.3 the number ofdisasters attributed to natural phenomena is predominant in number accounting for
63% of the globally reported disasters over the entire period (from 1900 to 2004).
Among all natural disasters, disasters triggered by hydrometeorological events
accounted for 77% of the sub-total. In addition to this heavy global picture, it isimportant to add the number of people killed and affected by technologicalwater-related disasters (mainly accidents triggered by heavy rains, storms and otherclimate variations). As depicted in Figure 3.3, the number of technological18

water-related disasters accounted for 14% of the total technological disasters.
Despite that only disasters responding to one of the four entry criteria listed above
are reported in EMDAT, the statistics show that the trend of natural disasters withwater-related disasters at the top of the list has not ceased to increase exponentially.
In addition to periodic disasters of given disaster thresholds, extreme events as neverexperienced before are proven to occur continuously though occasionally. Historicalexamples are, to cite only few, the flood of July 1931 in the China Republic, whichclaimed the life of nearly 4 million people, and the Sumatra earthquake triggered
Tsunami of December 2004, which claimed the life of nearly 300,000 people.
Therefore, in the course of building a so-called holistic risk management strategy fordisasters mitigation it is vital to consider such overwhelming events despite theirvery low probability of occurrence.

19

20

0

100

200

300

400

500

1908

1904

1900

1984

1980

1976

1972

1968

1964

1960

1956

1952

1948

1944

1940

1936

1932

1928

1924

1920

1916

1912

Figure 3.2. Trend of the number of natural disasters per year: EMDAT from 1900 to 2004.

Number of events
Per year
600

2004

2000

1996

1992

1988

21

Technologicalothers86%

37%

Technological

63%

NaturalDisasters

6%

Year 1935-1939: 1%
Year 1940-1944: 1%

Year 1930-1934: 1%

Year 1925-1229: 1%

Year 1920-1924: 0%

Year 1915-1919: 0%

Year 1910-1914: 1%

Year 1900-1904: 0%
Year 1905-1909: 0%

Year 1955-1959:
2%
Year 1960-1964:
2%

Year 1945-1949: 1%
Year 1950-1954: 2%

Year 1965-1969:
4%
Year 1970-1974:
4%
Year 1975-1979:

Year 2000-2004:
24%

Others23%

Water
related77%

Figure 3.3. Global distribution of disasters by category and for each 5-year: EMDAT from 1900 to 2004.

Technologicalwater related
14%

Year 1980-1984:
9%

Year 1985-1989:
11%

Year 1990-1994:
13%

Year 1995-1999:
16%

3.2. Assessment of the social impact of natural disasters
Whether devastating disasters are triggered by natural or technological events, they
can have unexpectedly large countable (i.e. direct) and uncountable (i.e., indirect)social and economic effects on individuals, communities, and national stability. With
the evidently increasing trend of the number of natural disasters over the past
decades, the trends of impacts on people specifically the number of killed and thenumber of affected people as well as the impact on economy (specifically direct
measurable economic losses) shows large variations in scales and numbers. While itis not an end by itself, the examination of the global trends of diverse effects ofnatural disasters is undoubtedly important to assess the progress made at the global
scale to mitigate these negative impacts.
3.2.1. Trend of the number of dead people
Protecting human life from natural disasters has been the goal of major national andinternational initiatives in hazard mitigation and disaster reduction. Figure 3.4
depicts the 100 and 200-event moving averages of the global trend of the number ofkilled people by natural disasters. The global picture shows a clear overall
decreasing trend. The most distinctive period is from 1900 to the beginning of the
1980s, the trend during the following decades also decreased but evidently at a
slower rate marked by severe concurrent increases as shown by the scattered peakvalues in the graph. Although the peaks from 2000 to 2004 were temporally more
scattered, they were severer in magnitude. Special emphasis is placed on the loss oflife in 2004 which includes in addition to the large severe flooding that occurred
around the globe, the Sumatra earthquake triggered Tsunami, which claimed the lifeof nearly 300,000 people from nations in the Asian region and others from aroundthe world. In other words, despite the decrease in the number of killed people, when
seen from a large temporal scale, the current situation warns that we should raise oursocial resiliency to face unusual disastrous events that have net yet occurred.
In order to understand the range of these erratic values of the number of killed
people per individual disasters reference is made to Figure 3.5. It is clear from thedata that extreme disasters claiming the life of more than 100,000 people havebecome very rare events since the Tangshan earthquake of 1976 in the China
Republic, which claimed the life of more than 240,000 people. In recent decades, theonly events of similar massive disastrous scale are the windstorm of 1991 in
Bangladesh, reported to have killed near 140,000 people, and the Sumatra tsunami
of December 2004. On the other hand, the figure shows that since 1994 at least one
disaster killing more than 10,000 people has occurred every year.

22With the increasing in frequency of natural disasters claiming the life of more than
1,000 people per event, the temporal distribution of disasters warns of new
thresholds in terms of the number of people under the threat of death by any one of
the 200 events occurring every year in average (see Figure 3.5). To closely examine
the variation of the thresholds over time reference is made to Figure 3.6. For
instance, while the number of death per event seems to be an independent stochastic
process, Figure 3.6 indicates several grouping of nearly the same threshold of
casualties. For lower magnitude events, nearly every year the same number ofpeople at different scales (e.g. 10 people, 50 people, and 100 people as new
threshold standards) are killed by a single natural disaster event. For several eventsof higher magnitude, though the impact density lines (i.e. impact on human life, e.g.
1,000; 10,000; or 100,000 etc.) are sparser, consecutive events on a yearly basis
which killed nearly the same number of people are clearly seen (e.g. more or less
10,000 death for the period 1960 to 1974, and more or less 50,000 death for theyears from 1995 to 2004).

23

24

1

10

100

1000

10000

200 events Moving Average

1991

1990

2000

2000

1999

1999

1998

1997

1996

1995

1993

1992

1989

1988

1986

1985

1983

1982

1980

1978

1976

1973

1969

1965

Figure 3.4. Moving average of the total number of killed people from 1900 to 2004.

Year

100 events Moving Average

2003

2003

2002

2002

2001

1959

1949

1930

1900

Moving average of thenumber of killed people

2004

25
1

10

100

1,000

10,000100,000

1,000,000

10,000,000

Number of deadFigure 3.5. Number of killed people by natural disaster from 1900 to 2004.

Year

Number of killed people reported in EmDAT from 1900-2004

1900
1912
1923
1932
1940
1946
1951
1954
1958
1961
1964
1965
1966
1968
1969
1970
1972
1973
1974
1975
1977
1977
1978
1979
1979
1980
1981
1981
1982
1983
1983
1983
1984
1985
1985
1986
1986
1987
1987
1988
1988
1988
1989
1989
1990
1990
1991
1991
1991
1992
1992
1993
1993
1993
1994
1994
1995
1995
1995
1996
1996
1997
1997
1997
1998
1998
1998
1999
1999
1999
1999
2000
2000
2000
2000
2000
2000
2001
2001
2001
2001
2002
2002
2002
2002
2002
2002
2003
2003
2003
2004
2004
2004
2004

26
1956

1952

Year

1992

1988

1984

1980

1976

1972

1964

1960

1948

1944

1940

1936

1932

1928

1924

1920

1916

1912

1908

1904

1900

Figure 3.6. Temporal distribution of the number of killed people per year and per disaster from 1900 to 2004.

1

10

100

1,000

10,000100,000

1,000,000

10,000,000

Number of killed people reported in EmDAT from 1900-2004

1968

Number of dead

2004

2000

1996

27

1

10

100

1000

10000

100000

1991

1990

2000

2000

1999

1999

1998

1997

1996

1995

1994

1993

1992

1989

1988

1987

1986

1985

1984

1982

1981

1979

1978

1976

1973

1969

1966

1963

1955

1945

1927

Figure 3.7. 100 and 200-event moving average of the total number of affected people from 1900 to 2004.

Year

2001

1900

Trend (200 events MA)

2001

Trend (100 events MA)

2002

200 events Moving Average

2002

100 events Moving Average

2003

Moving average of thenumber of affected people

2004

2003

3.2.2. Trend of the number of affected people
The number of affected people by a single natural disaster largely varies fromseveral million to several hundred thousands depending on the type of the natural
disaster. Attempting to conceive the global resiliency standard, Figure 3.7 draws themoving averages of the number of affected people after 100 and 200 successive
events, respectively. The overall trend shows that following every 100 to 200 events
the number of affected people at any one year by any one natural disaster is likely toincrease by nearly 3000 people in average. In other words, following the minimum
threshold of the number of concurrent disasters that are likely to occur at any one
year, the global resiliency standard of people to disasters is continuously decreasing.
Acknowledging the overall increase of the trend with an erratic conduct, a critical
period of the increasing trend is observed for the periods from 1940 to 1980 andfrom 2000 to 2004. In order to decipher the magnitude of the impact of natural
disasters on event basis reference is made to Figures 3.8. Despite that disasters
affecting several hundred million people (such as the droughts of 1987 and 2002 in
India with 300 million affected people each; or the floods of 1998 and 2002 in the
China Republic with 200 million affected people each) are rare events, Figure 3.9
clearly shows that natural disasters affecting 100,000 people and over have occurredat least once in every 5 years. The frequency of natural events affecting from 5 to 10
million people each time a disaster do occur was higher in recent decades and theyeven occurred several times a year. A clear picture of this increasing frequency canbe seen from Figure 3.9 representing the same data as of Figure 3.8 on a temporalbasis. This figure also confirms that EMDAT knew clear improvements in thereporting process. Thus, besides undertaking an event based analysis, for instance ofthe critical successive drought years in Canada from 1931 to 1940, the trend of thenumber of affected people for the period from 1900 to 1960 (as shown in Figures 3.4
and 3.7) should be interpreted with caution. The largest disasters in terms of thenumber of affected people are the two droughts of 1987 and 2002 in India, which
affected 300 million people in each year, followed by the three flood disasters of
1991, 1998 and 2002 in the China Republic, which were reported to affect nearly
200 million people each.

28

29
1991
Year

2002

2002

2001

2001

2000

1999

1999

1998

1997

1996

1995

1994

1993

1992

1990

1989

1988

1987

1986

1984

1983

1982

1980

1978

1977

1974

1970

1967

1964

1956

1946

1928

1900

Figure 3.8. Total number of affected people by individual natural disaster events: EMDAT from 1900 to 2004.

1

10

100

1,000

10,000100,000

1,000,000

10,000,000

100,000,000

1,000,000,000

Distribution of the number of affected people per natural disasters: EmDAT from 1900-2004

2000

Number ofaffected people

2004

2004

2003

30
1952
Year

1996

1992

1988

1984

1980

1972

1968

1964

1960

1956

1948

1944

1940

1936

1932

1928

1924

1920

1916

1912

1908

1904

1900

Figure 3.9. Temporal distribution of the number of affected people per year and by disaster from 1900 to 2004.

1

10

100

1,000

10,000100,000

1,000,000

10,000,000

100,000,000

1,000,000,000

Number of Total affected people reported in EmDAT from 1900-2004

1976

Number ofaffected people

2004

2000

Chapter 4: Trends Analysis of Water-related Disaster
Chapter 4: Trends Analysis of water-related disaster4.1. Trends of water-related disasters
The global picture of the decreasing trend in the number of killed people by natural
disasters is an important indicator on the degree of achievements made at the global
scale in the field of natural disasters reduction. Nevertheless, the peak values ofkilled people by extreme disastrous events, the trend of the number of affected
people and the trend of economic damages clearly state the importance of carryingout an in-depth analysis by type of disaster at both regional and national scales. This
chapter focuses on the analysis of the trends of water-related disasters and theirsocial impacts, namely the number of killed people and the number of total affected
people at the global scale in general and at the regional scale in particular. As
mentioned earlier, 77% of all natural disasters are triggered by hydrometeorologicalphenomena either directly such as flood and drought, or indirectly such as famine,water-related epidemic and technological water-related disasters. Despite thattsunami disasters are triggered by earthquakes they are included in the category of“wave/surge” for the consequence of a tsunami disaster is driven by sea-water.
As shown in Figure 4.1.a, disasters other than water-related disasters accounted for
43% of the total number of disasters. Technological water-related disasters (mostly
ferry accidents) accounted for 10% of the total. Nonetheless, this later proportion
should be carefully interpreted especially when a multi-disaster does occur, such as
the earthquake of 2004 in Niigata, Japan. In Niigata earthquake of 5 November 2004,
40 people were reported to be killed and 2,900 injured. There were 395 buildings
destroyed and 3,473 damaged in Niigata Prefecture. About 100,000 people had tolive in emergency shelters. The main event was followed by strong series ofaftershocks, fires, heavy flooding and large scale landslides (at least 151 landslides),some have caused deadly traffic accidents. Under such a dramatic sequence ofdisasters mainly implicating heavy physiological disturbance, not all countries havethe ability or disasters reporting system to accurately distinguish the consequences
driven by each individual type of disasters and the real causes of death (in Niigata
case: earthquake, flood, landslide, fire, and technologic water-related disasters).
Figure 4.1.b, plotted for the whole period from 1900 to 2004, shows that the
proportion of disasters driven by both floods and windstorms accounted for 73% of
the total. Drought and famine disasters accounted for 12% of the total. However, it isimportant to notice that 20% of the famine disasters reported in EMDAT are
attributed to drought (i.e., 66% of famine disasters were attributed to food shortage31

and 14% were attributed to crop failure). Slides accounted for 6% of the total, only
25 among the 477 slide/avalanche events were attributed to heavy rain (for the restof the events the main triggering causes were not mentioned). In the same scale,epidemic water-related accounted for 7% of the total (i.e., six sub-types of water
epidemic were identified based on the WHO definitions). Diarrhoeal/entericaccounted for 79% of the total number of water epidemic disasters. Wave/surge
accounted for 1% of the total number of disasters including 37 tsunami events (i.e.,
71% of the sub-total) as compared to tidal wave disasters with 15 events.
Figure 4.1.a. & b. Global distribution of water disasters from 1900 to 2004
Epidemicwater related
Figure 4.2.a. & b. Global distribution of water disasters 1990-2004
6%
Famine1%

Others
43%

Flood
25%

Drought
11%

Wave &
Surge
1%

Flood
37%

Technologic
water related
10%

Slides7%

Wind Storm
25%

Epidemicwater related
6%

Drought
8%Wind Storm
36%

Famine1%
Wave &Surge
1%

Slides5%

Global distribution of water related disasters: EmDAT 1900-2004

Figure 4.1.a. Global distribution of water-related
disasters vis-à-vis other types of natural disasters
for the period from 1900 to 2004.

Famine1%

Wave & Surge
1%

Figure 4.1.b. Global distribution ofwater-related disasters for the period from1900 to 2004.

Epidemicwater related
10%Europe11%

Drought
8%

Americas
25%
Flood
41%

Landslide andAvalanche
7%

Africa21%
Oceania
5%
Asia
38%

Wind Storm
32%

Figure 4.2.a. Global distribution ofwater-related disasters for the period
1990-2004.

Figure 4.2.b. Global distribution of water-related
disaster by continent for the period 1990-2004.

32

FloodWave and Surge
Epidemic Water related

Numberof Disasters

Wind Storm
Drought

Landslide
Famine

800

Flood

700
600
Wind Storm
500
400
300
200

Epidemic
Water related

Drought
100

Landslide

34

0
64
-19
60
9
1

-19
65
19

69

74
-19
70
9
1

Numberof Disasters

-19
75
19

84
-19
80
9
1

79

Landslide

Drought

89
-19
85
9
1

9
-19
90
9
1

4

99
-19
95
9
1

04
-20
00
0
2

Epidemic Water related

200
180
160
140
120
100
80
60
40
20
0
19

60

-19

64
19

65

-19

69
19

70

-19

74
19

75

-19

79
19

80

-19

84
19

85

- 19

89
19

90

-19

94
19

95

-19

99
20

00

- 20

04

Trends of drought, landslide and water epidemic disasters for each 5 year period: 1960-2004
Numberof Disasters

Wave and Surge

Famine

35

30

25

20

15

10

5

0
60
19

-19

64
19

65

-19

69
19

70

-19

74
75
19

-19

79
19

80

-19

84
19

85

-19

89
19

90

-19

94
95
19

-19

99
20

00

-20

04

Trends of famine and wave/surge disasters for each 5 year period: EmDAT 1960-2004

Figure 4.3. Trends of water-related disasters for each 5-year period from 1960 to 2004.

33

Attention is drawn to the fact that this proportionality is very much influenced by thelength of time period taken into consideration. The same data (i.e., water-related
disasters not including technological water-related disasters), when plotted for theperiod 1990-2004 (see Figure 4.2.b) shows a clear difference in the share ascompared to the plot for the period from 1900 to 2004 (Figure 4.1.b). For instance,
while surge/wave and famine disasters are in the same proportion for both figures,
flood accounted 41% (see Figure 4.2.a) (compared to 37% in Figure 4.1.b), drought
accounted for 8% (compared to 11%) and water-related epidemic accounted for 10%(compared to 6%). These differences in terms of statistical percentage have greater
evidence and importance when analyzing the consequences of disasters in terms ofkilled or affected people (where 1% may represent as high as 1 million people, as
discussed later in this chapter). From another perspective, the distribution ofwater-related disaster by continent received a disproportional share in terms of thenumbers of events and disasters impacts. The data of the recent decades from 1990
to 2004 shows that Asia accounted for more than 40% of the total number ofdisasters occurring worldwide followed by Americas and Africa with the nearly thesame percentage (22%) as shown in Figure 4.2.b. These differences show some of
the controversial issues confronting decision makers during the process of risk
quantification as will be discussed later in the course of this chapter.
Based on the above and the observations made in Chapter 3 vis-à-vis the qualitativeand quantitative aspects of information in EMDAT, most of the rest of the analysis
presented hereafter will be based on the disasters database for the period from 1960
to 2004. In the aim of extracting the most comprehensive information from thedatabase in terms of global trends and consequences by type of disaster as well as
the share of each of the 5 regions (i.e., Africa, Americas, Asia, Europe and Oceania)
the data are processed for each 5-year period with some informative graphs on a
decade basis.
Figure 4.3 depicts the global trends of different water-related by type of disasters forthe period 1960 to 2004 plotted for each 5-year period. Due to the large difference inthe scale of the number of events when comparing the different types of disasters(particularly flood and windstorm to other water disasters) the two sub-groups[drought, slide (including landslide and avalanche), and epidemic water-related], and[wave and surge (includes tsunami), and famine] are re-plotted separately forreadability. Globally the number of floods that have turned into disasters, based on
the EMDAT criteria, showed a quasi-steady increase of more or less 100 events (inaverage) after each 5-year period. Unlike the periods from 1965-1969 to 1970-1974with nearly the same numbers, the first 5-year period of the 21st century was above
all expectation with just about 4 times higher number of flood disasters as comparedto the 5-year increasing average since 1960. Windstorm events that turned into34

disasters showed nearly the same trend as floods. In contrast with the decreasing
trend for the decade from 1990 to 1999 (i.e. the international decade for disasters
reduction), the beginning of the 21st Century showed an alarming increase withnearly 2.5 times higher windstorm disaster events as compared to the 5-yearincreasing average. The increasing trend of drought disasters showed a drastic raiseduring the period 1980-1984 and the period 2000-2004 which was about 4 times the
5-year increasing average (which is about 20 events after each successive 5-year). In
the same quasi-study increasing scale are landslide disasters with an average ofabout 20 event increase after each successive 5-year period (save the periods
1975-1979 and 1995-1999). Since 1984 water-related epidemic disasters havecontinuously increased at the same rate of 20 events after each 5-year period savethe drastic increase by nearly 3 times during the period 1995-1999. Although at alower scale the famine disasters showed an exponential increase in numbers fromthe period 1980 to 1999, whereas the total number has dropped from 30 events tonearly 10 events for the 5-year period 2000-2004. The characteristics of these trends
will be further discussed based on the analysis of the impact in terms of the number
affected people. Unlike other events, wave/surge disasters occur at a much lower
scale in the range of a single disaster per year in average. Nevertheless, the trend
increased tremendously in a quasi polynomial shape at the rate of 2n since the period
1985-1989 (where n is the increment step unit for each 5-year period).
Figure 4.4 illustrates the state of the trends of water-related disasters in eachcontinent. Evidently, all 5 continents have continuously suffered a larger number ofwater-related disasters with a particularly drastic increase since the end of 1990s.
The regional trend and proportion of water-related disasters, plotted for the period
1960-2004, showed quasi-exponential increasing rates after each successive 5-year
period. While the number of disasters for the period 1960-1964 was as low as 170
events for all continents, the global end range of disastrous events by the period
2004-2005 was as high as 1700 events. For instance, the number of disasters in the
Oceania increased from 5 events for the period 1960-1964 to 20 events by 1974 to
45 events during the next 5 year period (1975-1979). While the trend from 1979 to
1999 was quasi-invariable the following 5-year period showed a drastic increase bynearly 20 events. In Europe, beside the decreasing trend during the period
1984-1989, the European continent suffered continuous increase at different rates.
For instance, the increasing rate was quasi-linear for the periods 1960-1979 and1985-1999 (i.e., an increase by 10 and 20 events correspondingly as compared to therespective previous 5-year period). The rate exponentially increased for the period
2000-2004 by about 100 events. In Africa, unlike the steady period from 1980 to
1994 (i.e., equal number of disasters for each 5-year period), two distinctive trends
were representative of the data, the linear increasing rate of about 25 events inaverage for every 5-year period (period from 1960 to 1984), and a drastic increase at35

the rate of 25 events per year (i.e., 100 events per successive 5-year period) for theperiod from 1994 to 2004. In the Americas, apart from the steady increase of nearly
10 events after each 5-year period for the periods from 1965 to 1979 and the period
1995-1999, the number of water-related disasters has uniformly increased at the rateof 50 events in average after each 5-year period. At the top of the list of allcontinents, the number of water disasters after each 5-year period in Asia has
increased from about 90 events in the period 1960-1964 to more than 600 events by
the end of 2004. While the increasing rate was at about 20 events for each 5-year
period in average by the year 1974, the increasing magnitude rose to nearly 70
events in average for each 5-year period by 1999. The period 2000-2004 counted
nearly 200 additional events as compared to the previous periods.
As commented earlier (see in particular Figures 3.2, 3.6 and 3.9), there isundoubtedly an increasing improvement in the reporting mechanism of disasters in
EMDAT. Nevertheless, the temporal variation of the trends plotted for eachindividual water-related disaster as in Figure 4.3 and the temporal variation of thetrends by continent as in Figure 4.4 clearly reflect the decreasing resiliency of theworld communities to water-related disasters. Figure 4.5 illustrates the exposure
ratio of each continent to the different types of water-related disasters (for this figure
we have excluded the technological water-related disasters from the statistics). The
figure shows flood and windstorm at the top of the list of water-related disasters
striking most of the continents (i.e. accounted for more than 80% of the total numberof disasters that occurred in each continent). The exception is for the African
continent where the number of flood disasters (including flood and windstorm),
drought (including famine) and epidemic water-related disasters are relatively equalin scale. The number of water-related disasters in Asia exceeded a total of 1400
events, which is about one third higher than the number of disasters in the Americas
and Africa and more than three times the total disasters in Europe and Oceania.
Under these conditions it is one of our set targets to acquire an in-depth
understanding of the major temporal variations of each type of water-related disasterin terms of the trends of events and impacts. The assessment is separated into threegroups, namely the trends of events, the trends of the number of killed people andtrends of the total number of affected people as reported in EMDAT. At the national
levels further analysis is undergoing to define similarities and differences in thevulnerability and resiliency of affected countries to particular water-related disasters.
In-depth knowledge of the details behind such classification and resulting
consequences is a step forward to enhance know-how sharing between countries
suffering from similar water-related disasters.

36

37
118
47
94
18
16

89

13

54

9

5

Asia

AfricaAmericas

EuropeOceania

20

27

90

67

121

1970-1974

Asia

45

37

91

84

199

1975-1979

Africa

44

88

159

141

263

1980-1984

Americas

52

60

234

130

298

1985-1989

Europe

50

101

269

136

412

1990-1994

53

115

304

259

410

1995-1999

Oceania

Figure 4.4. Trends of water-related disaster by continent for each 5 year period from 1960 to 2004.

1965-1969

1960-1964

0

100

200

300

400

500

600

700

Numberof Disasters

70

216

387

413

618

2000-2004

Oceania

EuropeAmericas

Africa

Asia

38

0

200

400

600

800

1000

1200

1400

1600

number of
eventsAsia

Oceania

Americas

Figure 4.5. Distribution of water-related disaster by continent for the period from 1990 to 2004.

AfricaEpidemic water related

FamineEuropeWave & Surge

SlidesDrought

Wind Storm

Flood

Distrubution of number of water related disasters by continent: 1990-2004

Figures 4.6 through 4.14 depict the temporal variations of the trends of the numberof water-related disasters reported for each continent plotted on a 5-year period basis.
Flood, windstorm, landslide and wave/surge disasters are the highest for Asia andAmericas, while the trends in Europe, Africa and Oceania were closely within thesame scale. On the other hand drought, famine and epidemic water-related disasters
have shown drastic increases in Africa while the trends for all other continents
increased at lower rates or even decreasing.
Figure 4.6 illustrates that the number of flood events have increased globally during
the past decade interfered by a number of decreasing and steady periods (i.e.,
periods of a decreasing or eventually equal number of disasters during two
successive 5-year periods). Unlike Oceania which witnessed an increasing trend by
few events after each period, Europe and Africa showed large shifts in the trends’
directions since early 1990s. In recent decades, the data shows that the American
continent was continuously the second most vulnerable continent to flood after Asia.
The most affected countries in terms of the number of disasters in Asia are India andChina Republic, followed by Bangladesh, the Philippines and Iran. Japan ranked
number 10 after Pakistan in terms of the numbers of flood disasters.

Number offlood Disasters

Asia

Americas

AfricaEuropeOceania

300
Asia

250
200

Africa150
EuropeAmericas100
50

Oceania01960-1964 1965-1969 1970-1974 1975-1979 1980-1984 1985-1989 1990-1994 1995-1999 2000-2004

Asia

30

49

36

68

110

117

157

166

Americas

9

34

41

41

66

97

102

94

170

Africa

10

14

13

29

19

46

42

103

172

Europe

4

6

7

17

32

22

42

65

132

Oceania

1

3

10

11

18

9

13

22

Figure 4.6. Trends of flood disaster by continent
for each 5-year period: EMDAT 1960-2004.

39

261

At the global scale, windstorm disasters are about 100 events fewer in number ascompared to floods. The number of events showed continuously increasing trends in
Asia and the Americas (save the exceptional decrease in Asia for the period
1995-1999). For the rest of the continents the range was quasi-uniform around 30 to
40 events per 5-year period since the early 1980s (see Figure 4.7). At this stage it isimportant to notice the difficulties to distinguish between flood disaster andwindstorm disaster (i.e., for instance, most floods occurring in Asia and Americas
are triggered by typhoons and tropical cyclones, respectively.).
Figure 4.8 depicts the trend of landslide disasters (including avalanche) for the fivecontinents from 1960 to 2004. Africa, Europe and Oceania suffered nearly constantnumber of disastrous landslide events since the mid 1980s. In contrast, the numberof disasters in Americas has nearly doubled since 1980s, while the number in Asia
has increased with quasi exponential rate from nearly 10 to 70 events by the end of
the year 2004.
Figure 4.9 depicts the number of wave and surge disasters (including tsunami).
Beside the increasing trend in Asia the data for the other continents are scattered andrare events. The historical event was undoubtedly the Indian Ocean Tsunami
triggered by the Sumatra Earthquake in 26 December 2004.

Number ofWindstorm Disasters

Asia

Americas

AfricaEuropeOceania

200
Asia

150
Americas100
EuropeAfrica50

Oceania01960-1964 1965-1969 1970-1974 1975-1979 1980-1984 1985-1989 1990-1994 1995-1999 2000-2004

Asia

45

50

64

82

108

122

181

124

194

Americas

37

44

27

36

64

101

119

146

153

Africa

1

4

3

14

20

17

16

21

48

Europe

3

8

13

10

38

26

39

30

63

Oceania

4

15

15

27

29

31

35

26

41

Figure 4.7. Trends of windstorm disaster by continent
for each 5-year period: EMDAT 1960-2004.

40

Number ofLandslide Disasters

Asia

Americas

AfricaEuropeOceania

70
Asia
60
50
40
30
20

Americas
EuropeAfrica1001970-1974

1975-1979

1980-1984

1985-1989

1990-1994

1995-1999

Oceania
2000-2004

2

9

10

16

29

32

46

66

8

17

4

9

22

16

22

22

2

3

4

3

8

10

10

10

12

7

3

1

5

3

1960-1964

1965-1969

Asia

4

Americas32Africa2

Europe4

Oceania

6

6

1

2

Figure 4.8. Trends of landslide and avalanche disaster by continent
for each 5-year period: EMDAT 1960-2004.
Number of Wave and Surge
Disasters

Asia

Americas

AfricaEuropeOceania

12

10

8

6

4

2

0

1960-1964

1965-1969

Asia

2

2

Americas1

Africa1970-1974

1975-1979

1980-1984

1985-1989

1990-1994

1995-1999

2000-2004

1

2

1

3

4

11

2

1

1

4

Europe1

Oceania1

1Figure 4.9. Trends of wave and surge disaster by continent
for each 5-year period: EMDAT 1960-2004.

41

Droughts and famines (which are also a major direct consequence of drought) are
the most prevailing disasters in Africa. As shown in Figure 4.10, the average numberof drought disasters in Africa were about 40 events in average, while for the othercontinents the number was around 10 events at each 5-year period. The demarcating
value is the total number of droughts in the 1980-1984 period. Unlike the limited
spatial coverage of flood disasters, most of the countries in Africa were stricken an
annual average of 2 to 4 events. Among the 41 affected states, 16 states werestricken by a single drought event while as high as 6 events were recorded in
Mozambique alone. Another demarcating, if not alarming, condition is the drastic
increase in the number of drought events during the 2000-2004 period.
Figure 4.11 depicts the number of famine disasters during the past four decades anda half. The continuous and drastic increase of famine disasters in Africa since themid 1970s and Asia during the 1990s requires an in-depth assessment to evaluate theeffectiveness of decades of international actions to reduce extreme poverty (i.e.,famine at the top of the list). The radical declining numbers in 2000-2005 are not astrong evidence to claim victory against poverty, indeed famine disasters in theAmericas had periodically occurred since the 1990s and Europe was not an
exception for the period 1995-1999.

Number ofDrought Disasters
100

AfricaAsia

Americas

EuropeOceania90
80
70

Africa

60
Asia
50
40
Americas3020Europe100Oceania
1960-1964

1965-19691970-1974

1975-1979

1980-1984

1985-1989

1990-1994

1995-1999

2000-2004

Africa

2

25

47

32

90

33

40

32

65

Asia

5

10

12

17

17

15

12

19

53

Americas

3

7

5

7

19

11

9

15

32

1

7

8

4

9

4

4

4

8

1

EuropeOceania1

Figure 4.10. Trends of drought disaster by continent
for each 5-year period: EMDAT 1960-2004.

42

Number ofFamine Disasters
18

AfricaAsia

Americas

EuropeOceania

16
14
12
10
8
6
4
2
0

1960-1964

1965-19691970-1974

Africa1975-1979

1980-1984

1985-1989

1990-1994

1995-1999

2000-2004

2

3

9

11

17

5

5

11

3

1

1

1

1

Asia

1

Americas1Europe1

Oceania

Figure 4.11. Trends of famine disaster by continent
for each 5-year period: EMDAT 1960-2004.
Number of epidemic vsWater related epidemic
disasters

Water related epidemic
Epidemic

600

500

400

300

200

100

0
1960-1964

1965-19691970-1974

1975-1979

1980-1984

1985-1989

1990-1994

1995-1999

2000-2004

Figure 4.12. Temporal distribution of epidemic disasters versus epidemic water-related
disasters for each 5-year period: EMDAT 1960-2004.

43

Number of epidemic
water related disasters

Water epidemic
Epidemic

800

700

600

500

400

300

200

100

0

AfricaAsia

Americas

EuropeWater epidemic

258

144

62

16

Oceania5

Epidemic

485

256

99

52

12

Figure 4.13. Distribution of epidemic water-related disaster by continent
for each 5-year period: EMDAT 1960-2004.
Number of epidemic
water related disasters

AfricaAsia

Americas

EuropeOceania120
Africa
100

80

60

40
Asia
20
Americas
Europe
0

64
-19
60
19

Oceania

69
-19
65
19

1

4
97
0-1
97

79
-19
75
19

84
-19
80
19

89
-19
85
19

94
-19
90
19

1

9
99
5-1
99

04
-20
00
20

Figure 4.14. Trends of epidemic water-related disaster by continent
for each 5-year period: EMDAT 1960-2004.

44

Along with famine disasters, epidemic disasters also increased in number during thepast decades. Epidemic disasters in EMDAT are reported by type with reference tothe disease names and categories. The list of epidemic water-related consideredhereafter (see Table 4.1) was made based on the World Health Organization (WHO)definitions (WHO, 2005). As can be seen from Figure 4.12, water-related epidemics
accounted for nearly a third of the total number of epidemic disasters.
Whereas the number of epidemic disasters were expected to decrease as results ofthe continuous worldwide efforts to ensure increasing access of population to safe
drinking water and better sanitation, controversially the figure shows continuous
sever increase in number after each period. The geographical distribution by region(see Figure 4.13) places Africa at the top of the list with nearly 250 water-related
epidemic events out of a total of nearly 700 epidemic disasters.
The related temporal variation of trends plotted for each 5-year period is shown in
Figure 4.14. The figure shows that the number of disastrous events in Africa stillshows an exponential increase, while the trends in Asia and Americas have started todecrease since the beginning of the 21st Century.
In the following sections we present the analysis undertaken on the consequences ofeach of the above introduced water-related disasters in terms of the numbers ofkilled people and the number of total affected people.
Table 4.1. Entry of epidemic water-related disasters in EMDAT.
Type of epidemic
Arbovirus
Diarrhoeal/EntericDiarrhoeal/EntericDiarrhoeal/EntericDiarrhoeal/EntericDiarrhoeal/EntericDiarrhoeal/EntericDiarrhoeal/EntericDiarrhoeal/EntericDiarrhoeal/EntericDiarrhoeal/Enteric
Viral Hepatitis
Malaria

Disease name
Acute Hepatitis
CholeraTyphoid
Shigellosis
Acute diarrhoeal syndrome
Acute respiratory syndrome
Acute watery diarrhoeal syndrome
Typhoid fever
Shigellosis
Typhoid fever{NOT DEFINED in EMDAT}
Acute Hepatitis E

45

4.2. Regional assessment of social impacts of water-related disasters
Undoubtedly, the development of an appropriate mitigation plan begins by
developing a mechanism for accurate risk quantification leading to accurate
assessment of socio-economic damages and impacts of disasters. The United Nation
General Assembly, held in 1998, has declared the decade 1990-1999 the“International Decade for Natural Disaster Reduction”. One of the specific goals set
for the decade is “to disseminate existing and new information related to measurefor the assessment, prediction, prevention, and mitigation of natural disasters.” Itsobjectives were to reduce the loss of life and property damage by natural disasters
through concreted international action and appropriate use of science and technology(Ajmad, 1999). While a lot has been achieved since the start of the decade, the UN
Secretary General declared that: “…we continue to confront major challenges…It isa tragic irony that 1998, the penultimate year of the Disaster Reduction Decade wasalso a year in which natural disasters increased so dramatically.”
The analysis of actual and potential impacts of water-related disasters is problematicdue to the multifaceted uncertainties and challenges that we are still confronting toaccurately define and afterward evaluate social damages. The most ambiguous
definition is undoubtedly that of affected people. The countability of social impacts(i.e., the number of killed people and the number of total affected people as reported
in the existing international databases) responds to the goal and objectives of thedeveloping institute. Nevertheless, the reported values are also affected by the socialand political conditions imposed in the country where the disaster has occurred.
Some of these issues, particularly related to EMDAT and other natural disasterdatabases, have been discussed elsewhere and are not repeated here (see for example
Guha-Sapir 2002; Wisner et Al. 2004). In addition to the influence of the reporting
mechanism, reliable identification and quantification of the social and economical
damages are also strongly biased by the assessment methodology.
 Temporal trend analysis based on each decade:In the aim of clarifying some of the dilemma coupled with the assessment of social
impacts, the analysis of the trends of the number of killed people and the number of
total affected people by water-related disasters was carried out under two time scales,
specifically decade period and 5-year period scales. Each value on the decade graphrepresents the total of all reported data (the number of killed or affected) during thespecific decade, whereas for the 5-year period the value on the graph is theaccumulated data reported during the considered 5-year period.
The analysis of disasters data on a decade basis has gained wide acceptance amongprofessionals and practitioners at all levels of decision making especially when it is46

desired to understand the trend of impacts of hazards and/or mitigation progress overlong-term periods. Nevertheless, it is important to note that while the decade
analysis of impact of disasters allows to put clear emphasis on the long-term
variation of the trends from a global standpoint, results such as of figures 3.1, 3.5
and 3.9 put strong emphasis on the importance to carry out vigilant data processing
on short-term basis in order to draw reliable conclusions for assessing the progressachieved and effectiveness of adopted policies in water-related disaster mitigation.
The analysis of the social impacts reported by EMDAT database for the period from1960 to 1999 is shown in Figure 4.15. The figure allows to extract focal particulars
concerning the temporal variation of the trends of social impacts which are hardly
visible under different time scales. From this long-term and global perspective it isclear that the numbers of killed people after each successive decade showed acontinuous decrease from nearly 2 million people in the 1960s to 0.5 million in the
1990s. A distinctive characteristic is the variations of the values of the successive
gradients of the trends of killed people between decades. Particular denomination is
the gradient of the trend between the 1960s and the 1970s dropping by nearly 10
million people compared to about 0.2 million people each for the trends during the
successive between the 1970s and the 1990s. It is not granted that the steep gradientof killed people shown by the trend between 1960s and the 1970s is a result ofeffective policies at the global level to mitigate water-related disasters. In fact, whilesome of this success could be attributed to what is called an improved disaster
reduction polices, a close examination of the database reveals that the picture ismore complex and might also include an improved political will to fairly reportdisasters’ information (especially records on extreme disastrous events).
Tables 4.2 through 4.5 show the impacts of the top 10 disastrous events in terms ofthe number of killed people as reported by EMDAT for each decade from the 1960s
to the 1990s. It is clear from the tables that the respective trends and their gradients(see Figure 4.15) are delineated by the trend of top ten disastrous events reported
during the decade. In other words, about 90% of the total number of killed people
during the decade in question is included within the top 10 events. For instance,
Table 4.1 shows that the trend 1960s-1970s is mainly delineated by the extreme
events during the period 1965-1969 characterized by the three successive years of
the sever drought in India (from 1965 to 1967), which claimed the life of 500,000
people at each one year (i.e., 1.5 million people were reported killed in total)1. The
1 For this particular drought, in spite of the reported 500,000 death each year, the total number of affected
people was 100 million people (about 1/5 of the population in 1965) during the first year (1965) whereas thevalues for the 2nd and 3rd year were zero, respectively. While we can provide a series of assumptions to
explain these data, it is clear that the consistency of such extreme values should be interpreted with caution as
it can only be verified with reference to the national disasters database.

47

deadliest calamities after the 1965 drought in India are the epidemic malaria in Sri
Lanka (which killed 200,000 people killed), followed by the series of floods in
Bangladesh (reported to kill between 10,000 and 36,000 people) and lastly the
drought in Indonesia, which killed 8,000 people. The maximum, minimum andaverage values of killed people during the two decades 1970s and 1980s wereclosely the same which delineates the gentle gradient between the two decades. In
the 1990s the only event that killed more than 100,000 people was the windstorm of1991 in Bangladesh. Demarcating data are the five successive years (1995-1999) of
famine disasters in the Democratic People's Republic of Korea. While no location
was specified for the years 1995, 1996 and 1999, the disaster of 1997 had occurredin the Northern and Southern Hamgyong provinces, whereas in 1998 it affected thewhole country. In addition to the above, the disasters were reported to kill the same
number of 27,500 people each year. The quality assessment of such data is notdiscussed herein, but for this particular disaster we highly recommend reviewing thereport by Action for Hunger (see ReliefWeb, 2000).
In the contrast to the slow rate decrease in the number of killed people during thepast decades, the trends of the total numbers of affected people had exponentially
increased from nearly 500 million in the 1960s to about 3000 million people in the
1990s (see Figure 4.15). In other words, at each decade the number of affected
people have increased by over 3 times as compared to the former decade. Tables 4.6
through 4.9 report the top 10 disastrous events in terms of affected people bywater-related disasters. Demarcating data are the numbers of affected people by the
top most devastating water-related disasters in each decade ranging from 100
million to 300 million people for the droughts of 1965, 1979 and 1987 in India. The
top 10 disastrous events in the 1990s were all flood type affecting between 240
millions (flood of 1998 in China Rep.) to 30 millions people (flood of 1997 in India).
Comparing respective tables (table of killed people and respective table of affected
people) for each decade, it is clear that the term “disastrous event” is subjective as
we do not consider the exposed population to the disaster (see UNDP, 2004). It isalso interesting to notice that the same event is rarely reported in both tables (i.e.,table of killed people and table of total affected people for each decade). If
occasionally the same event is reported in both tables (such as the floods of 1987
and 1974 in Bangladesh) then their ranking in terms of severity is different (save thedrought of 1965 in India, which is the most disastrous event in EMDAT reporting
history). A close look at larger ranking (e.g., top 100 events for example) shows
further complicated interrelation between the multifaceted consequences triggeredby any single event (a further discussion on some of these issues is presented in
Chapter 5).

48

As presented earlier (see Figure 3.3), 24% of the total number of natural disasters(assessed on a 5-year period basis) have occurred during the 2000-2004 period. Inorder to delineate the ratio of the global social impacts since the beginning of the
21st century (2000-2004) as compared to the past decades, the numbers of killed andaffected people are also depicted in Figure 4.15 (dotted bar graph of the figure). The
figure points out that since the beginning of the 21st Century the number of killed
people is nearly in the same range as of the past decade, whereas the number ofaffected people has already surpassed two-thirds of the records in the 1990s decade.
The conclusions behind these numbers are better understood when seen from theglobal picture plotted for each 5-year period and for each continent as shown in
Figure 4.16 (trends of the number of killed people) and Figure 4.17 (trends of thetotal number of affected people).

Number ofpeople dead(in million)
1.8

number ofpeople affected(in million)
3000

Affected people
Dead people

1.6

2500

1.4

2000

1.2
1.0

1500

0.8

1000

0.6
0.4

500

0.2

0

0.0
60s

70s

80s

90s

2000-2004

Trends of dead vs affected people by water related disasters

Figure 4.15. Trends of the number of killed people versus affected people: EMDAT
1960-1990 and the 5-year period 200-2004.

49

Table 4.2. EMDAT top 10 water-related disasters in terms of killed people in the 1960s.
Rank year

dis_type

dis_subset country_name no_killed

1
2
3
4
5
6
7
8
9
10

Drought
Drought
Drought
Wind Storm
Wind Storm
Wind Storm
Wind Storm
Flood
Wind Storm
Drought

Drought
Drought
Drought
CycloneCycloneCycloneCycloneFlood
CycloneDrought

1965
1966
1967
1965
1965
1963
1961
1960
1965
1966

India
India
India
Bangladesh
Bangladesh
Bangladesh
Bangladesh
Bangladesh
PakistanIndonesia
Average 60s

500,000
500,000
500,000
36,00012,047
11,50011,00010,00010,0008,000
159,855

Table 4.3. EMDAT top 10 water-related disasters in terms of killed people in the 1970s.
Rank year

dis_type

dis_subset

country_name no_killed

1
2
3
4
5
6
7
8
9
10

Wind Storm
Drought
Drought
Flood
Drought
Wind Storm
Wind Storm
Wind Storm
Flood
SlidesCycloneDrought
Drought
Flood
Drought
CycloneCycloneHurricane
FloodLandslide

Bangladesh
Ethiopia
Ethiopia
Bangladesh
Somalia
India
India
Honduras
India
Honduras
Average 70s

1970
1974
1973
1974
1974
1977
1971
1974
1978
1973

300,000
200,000
100,000
28,70019,00014,204
9,658
8,000
3,800
2,800
68,616

Table 4.4. EMDAT top 10 water-related disasters in terms of killed people in the 1980s.
Rank
1
2
3
4
5
6
7
8
9
10

year
1984
1984
1984
1985
1980
1989
1984
1988
1982
1987

dis_type
dis_subset
country_name no_killed
Drought
Drought
Ethiopia
300,000
Drought
Drought
Sudan
150,000
Drought
Drought
Mozambique 100,000
Wind Storm Cyclone
Bangladesh
10,000Flood
Flood
China P Rep
6,200
FamineFood shortage
Mozambique
5,200
Drought
Drought
Chad
3,000
Epidemic
Arbovirus
India
3,000
Epidemic
Diarrhoeal/Enteric Bangladesh
2,696
Flood
Flood
Bangladesh
2,379
Average
58,24850

Table 4.5. EMDAT top 10 water-related disasters in terms of killed people in the 1990s.
Rank
1
2
3
4
5
6
7
8
9
10

year
1991
1999
1995
1996
1997
1998
1999
1998
1999
1991

dis_type
dis_subset
country_nameno_killed
Wind Storm Cyclone
Bangladesh
138,866
Flood
Flood
Venezuela
30,000FamineFood shortage
Korea Dem P Rep
27,500FamineFood shortage
Korea Dem P Rep
27,500FamineFood shortage
Korea Dem P Rep
27,500FamineFood shortage
Korea Dem P Rep
27,500FamineFood shortage
Korea Dem P Rep
27,500Wind Storm Hurricane
Honduras
14,600Wind Storm Cyclone
India
9,843
Epidemic
Diarrhoeal/Enteric Peru
8,000
Average 90s
33,881

Table 4.6. EMDAT top 10 water-related disasters in terms of affected people in the 1960s.
Rank
1
2
3
4
5
6
7
8
9
10

year
1965
1968
1965
1968
1963
1966
1965
1968
1967
1966

dis_type
dis_subset country_name no_affected
Drought
DroughtIndia
100,000,000
Flood
Flood
Bangladesh
14,910,892
Wind Storm Cyclone
Bangladesh
10,000,000
Flood
Flood
India
7,500,000
Wind Storm Storm
India
5,000,000
SlidesLandslide Brazil
4,000,000
Flood
Flood
Japan
3,000,000
Drought
Drought
Korea Rep
2,800,000
Drought
Drought
Korea Rep
1,905,944
Wind Storm Cyclone
Bangladesh
1,500,000
Average 60s
15,061,684

Table 4.7. EMDAT top 10 water-related disasters in terms of affected people in the 1970s.
Rank
1
2
3
4
5
6
7
8
9
10

year
1979
1972
1973
1974
1978
1975
1979
1970
1970
1970

dis_type dis_subset country_name no_affected
Drought Drought
India
190,000,000
Drought Drought
India
100,000,000
Drought Drought
India
100,000,000
Flood
Flood
Bangladesh
36,000,000
Flood
Flood
India
32,000,000
Flood
Flood
India
27,000,000
Flood
Flood
India
26,000,000
Flood
Flood
India
10,000,000
Drought Drought
Brazil
10,000,000
Flood
Flood
Bangladesh
10,000,000
Average 70s
54,100,000

51

Table 4.8. EMDAT top 10 water-related disasters in terms of affected people in the 1980s.
Rank year

dis_type

dis_subset country_name total_affected

1
2
3
4
5
6
7
8
9
10

Drought
Flood
Drought
Drought
Flood
Flood
Drought
Flood
Wind Storm
Flood

Drought
Flood
Drought
Drought
Flood
Flood
Drought
Flood
Storm
Flood

1987
1989
1982
1983
1987
1988
1988
1982
1989
1980

India
China P Rep
India
India
Bangladesh
Bangladesh
China P Rep
India
China P Rep
India
Average 80s

300,000,000
100,010,000
100,000,000
100,000,000
73,000,000
73,000,000
49,000,000
33,500,000
30,007,500
30,000,023
88,851,752

Table 4.9. EMDAT top 10 water-related disasters in terms of affected people in the 1990s.
Rank year

dis_type dis_subset country_name total_affected

1
2
3
4
5
6
7
8
9
10

Flood
Flood
Flood
Flood
Flood
Flood
Flood
Flood
Flood
Flood

1998
1991
1996
1993
1995
1999
1994
1995
1994
1997

Flood
Flood
Flood
Flood
Flood
Flood
Flood
Flood
Flood
Flood

China P Rep
China P Rep
China P Rep
India
China P Rep
China P Rep
China P Rep
India
China P Rep
India
Average 90s

238,973,000
210,232,227
154,634,000
128,000,000
114,470,249
101,024,000
78,974,400
32,704,000
30,547,665
29,259,000
111,881,854

 Temporal trend analysis based on each 5-year period:

Figure 4.16 (trends of the number of killed people) and Figure 4.17 (trends of thetotal number of affected people) show that Asia is the most affected region bywater-related disasters in the world. The number of killed people in Asia accounted
for 73% of the total number of people killed by water-related disasters as compared
to 24% for Africa and 3% for the Americas (ranked 3rd and 2nd respectively in termsof number of events). While statistically uncountable (>>1% for the entire period)
the table of Figure 4.16 exemplifies the high number of people killed bywater-related disasters in Europe and Oceania (about 12,000 and 5,000 people
respectively).

52

Total numbers of affected people bywater-related disasters from 1960 to 2004
Continent
Asia
AfricaAmericas
EuropeOceania

Rank
1
3
2
4
5
Total

Killed people
2,912,700
955,891
138,610
11,736
5,274
470,842,591

Africa
24%

%
73
24
3
-

Americas
3%
Other: 4%
Other:
3%
Asia
73%

Europe: Oceania: -Total of killed peoplein Thousands

Number of killed in each continent
by water related disasters
10,000,000

1,800
1,600

1,000,000

1,400
100,000
1,200
10,000

1,000

1,000

800
600

100
400
10
1

200
1960-1964

1965-19691970-1974

1975-1979

1980-1984

1985-1989

1990-1994

1995-1999

2000-2004

Asia

60,902

1,585,940

359,193

33,25641,33252,016

187,760

200,976

391,325

Americas12,512

6,914

17,065

4,231

8,839

6,352

17,59055,201

9,906

Africa626

3,227

322,800

1,451

556,413

14,52919,74824,933

12,420Europe

2,219

1,242

1,455

443

1,026

784

2,000

1,513

1,054

Oceania

262

768

326

322

140

405

346

2,506

199

Total

76,521

1,598,091

700,839

39,703607,750

74,086

227,444

285,129

414,904

0

Figure 4.16. Trend of the number of killed people by water-related disasterby continent for each 5-year period from 1960 to 2004.

Concurrently the number of affected people in Asia accounted for 89% of the world
total compared to 7% in Africa and 3% in Americas. As mentioned earlier, for moreaccurate risk evaluation these ratios should be also regarded with reference to thecountry population or the total exposed population (see UNDP 2004, and ISDR
2004). Nevertheless, the examination of the results presented in figures 4.16 and4.17 explicitly confirms several important reflections:53

Total numbers of affected people bywater-related disasters from 1960 to 2004
Rank
1
3
2
4
5
Total

Continent
Asia
AfricaAmericas
EuropeOceania

Killed people
5,127,208,992
426,953,362
156,638,252
29,071,205
14,818,024
470,842,591

%
89
7
3
1
-

Africa7%
Asia
89%

Americas
3%

Other: 4%
Other:
3%

Europe: 1%
Oceania: -Numbers of affected people
by water related disasters per region

Total affected
people in Millions

10,000,000,000

1,600

1,000,000,000

1,400

100,000,000
1,200
10,000,000
1,000

1,000,000
100,000

800

10,000

600

1,000
400
100
200

10
1

1960-1964

1965-19691970-1974

1975-1979

1980-1984

1985-1989

1990-1994

1995-1999

Aff. Asia

14,396,328

159,560,261

300,071,854

353,035,574

427,254,276

796,972,697

706,982,721

990,062,212 1,378,873,069

Aff. Americas

827,992

7,465,598

18,445,519

11,297,746

38,650,257

18,819,732

11,561,484

29,641,086

19,928,838

Aff. Africa

835,5105,000,229

18,039,827

15,350,220

81,787,301

43,297,762

99,330,525

46,722,040

116,589,948

Aff. Europe

255,000

200,122

1,546,290

1,186,941

907,260

52,213

5,746,604

12,834,887

6,341,888

Aff. Oceania

30,000107,204

186,090

88,932

611,755

685,078

8,909,076

4,004,877

195,012

16,344,830

172,333,414

338,289,580

380,959,413

549,210,849

859,827,482

Aff. Total

2000-2004

832,530,410 1,083,265,102 1,521,928,755

Figure 4.17. Trend of the number of affected people by water-related disasterby continent for each 5-year period since 1960 to 2004.

1. The statistical ratios are hardly representative of the true global image ofdisasters impact. For instance, during the period from 1960 to 2004, 3% ofkilled people by water-related disasters in Americas accounted for as high as
138,610 lives (see table of Figure 4.16); whereas 1% in terms of affected
people in Europe accounted for as high as 20 million people (see table of
Figure 4.17).
2. The global trend of dead people showed a continues increase since the end of
the 20th Century. This finding put clear emphasis that the decreasing trend

540between 1980s and 1990s plotted on decade basis is mainly driven by the low
scale values of the 1990s decade as compared to the values of the 1980s
decade;3. The global trends of social impacts (both killed and affected people) aremainly delineated by the respective trends in Asia. Exceptionally, the trends
for the periods between 1975 and 1989 are delineated by the trends in Africa;
4. At the regional level the trend of killed people is rather erratic with several
drops and peaks with a slight decrease in the 2000-2004 period. Major drops
are seen for the 1975-1979 and 1985-1989 periods. These deeps are the major
values delineating the decreasing trends between the 1970s and 1980s plottedon a decade basis;
5. In the Americas, excepts the slight drop in the 1980-1984 period, the trend of
killed people drastically increased from nearly 9,000 to 60,000 people; and6. Apart from Asia the number of killed people showed a clear regional decreaseat different scales and magnitudes. These regional characteristics must be
taken into consideration when analyzing the results plotted on a decade basis.
Further investigation in the following section is also undertaken for each typeof disasters.
In terms of affected people:
7. Excepts the slight drop in the 1990-1994 period, the gradients of the trends ofthe total number of affected people showed continuous steepness after each5-year period;
8. Apart from the continuous increase from 1960-1964 period to 1970-1974
period, the trend of affected people in Africa was demarcated by numerous
peaks and drops (the average peaks were about 100 millions and the average
drops were about 50 millions). The value by the end of the 2004 period wasabout 120 million people;
9. The trends of affected people in Americas observed similar erratic behavior.
The range of affected people is however equivalent to the size of the
population in the region (peaks were in the range of 40 million and drops
were in the range of 10 million affected people);
10. The trend in Europe showed distinctive decrease during the periods from1970 to 1989. However, the trends drastically increased from about 50,000
people in the 1985-1989 period to about 13 million in the 1995-1999 period;
11. The trend in Oceania drastically increased from 30 thousand people in the
1960s to 8 million people in the 1990-1995 period compared to 4 million
people in 1996-2000 period. During the 2000-2004 period the total number ofaffected people in Oceania dropped to nearly 200 thousands people; and55

12. During the 2000-2004 period, demarcating values are the decreasing trends
of affected people in Europe, the Americas and Oceania as compared to thelarge increase in Asia and Africa.
In order to build a complete understanding of the regional characteristics of thesocial impacts, further analysis was carried out for each type of water-related
disasters. The above observations and the following analysis of the regional
trends carried out at finer temporal scale (5-year period basis) highlights some of
the complication underlying the quantification of risks in water-related disasters
from global and regional perspectives. In other words, extreme vigilance issought in handling the data and interpreting the results of risk quantification inwater-related disasters.

56

4.2.1. Regional trends of killed people by type of water-related disasters
All the results hereafter are assessed on the basis of 5-year period from 1960 to 2004.
 Flood (Figure 4.18):
During the period from 1960 t0 2004 flood disasters claimed the life of nearly 300
thousand people. The trends of the number of killed people observed erratic conduct
with an average of 5000 people killed each year. In contrast to the increasing values
during the periods from 1975 and 1999, the trend of killed people in most continents
was nearly 50% less in 2000-2004 (save Oceania, which showed a 50% increase) as
compared to the previous period 1995-1999.
Total numbers of people killed by flood
disasters from 1960 to 2004
Rank
1
2
3
4
5
Total

Continent Killed people
180,354
Asia
54,224
Americas15,581Africa5,306Europe269
Oceania
255,734

Americas
21%

%
71
21
6
.2
-

Africa6%
Other: 8%

Asia
71%

Europe: 2%
Oceania: -Total killed peoplein Thousands
70

Regional: numbersof killed by flood
40,00035,00060

30,00050

25,00040
20,00030
15,00020

10,000

10

5,000
0

1960-1964

1965-19691970-1974

1975-1979

1980-1984

1985-1989

1990-1994

1995-1999

2000-2004

Asia

15,59910,27935,426

9,309

21,64023,083

20,19527,882

16,941

Americas

1,195

2,782

2,195

1,144

4,228

3,068

1,844

32,5595,209

Africa

534

809

705

623

460

1,238

2,049

5,208

3,955

Europe

495

896

1,085

229

350

216

620

814

601

Oceania

1

53

7

94

68

13

11

22

39,464

11,312

26,772

27,67324,721

66,474

26,728

Total

17,824

14,766

Figure 4.18. Distribution of the number of killed people by flood disasterby continent for each 5-year period from 1960 to 2004.

57

0 Windstorm disasters (Figure 4.19):
In average, during any 5-year period from 1960 to 2004, 40% of the number ofwindstorm disasters occurred in Asia and the Americas, respectively. As can be seenfrom Figure 4.19, the share of the globally killed people is equivalent to the size
number of disasters at regional level. Demarcating is the continuous decreasing
trend between 1970 and 1989 in both Asia and Americas and the continuous
increasing trend in Africa. In contrast to the severe peaks in the 1990s the trend of
killed people largely decreased during the period 2000-2004, which for nearly 20%of the total number of disasters.
Total numbers of people killed by windstorm
disasters from 1960-2004
Rank
1
2
3
4
5
Total

Continent
Asia
Americas
AfricaOceania
EuropeKilled people
680,336
56,865
3,594
2,609
1,358
.744,762

Africa%92
8-

Americas
8%

Asia
92%

Other
EuropeOceania

Total killedin Thousands
350

Number of killed
by windstrom
1,000,000

300

100,000

250
10,000
200
1,000
150
100
100
10

1

50

1960-1964

1965-19691970-1974

1975-1979

1980-1984

1985-1989

1990-1994

1995-1999

2000-2004

Asia

44,121

65,867323,254

21,077

12,631

22,327

Americas

9185

3149

9161

2984

3,603

1,478

157,090

27,457

6,512

2,053

21,382Africa

42

110

163

252

704

3870

384

554

563

Europe

390

85

187

83

822

517

172

457

447

Oceania

261

168

173

271

85

46

250

126

146

103

Total

53,99969,379332,938

24,481

17,501

24,611

160,280

49,995

11,578Figure 4.19. Distribution of the number of killed people by windstorm disasterby continent for each 5-year period from 1960 to 2004.

58

0 Flood and windstorm disasters (Figure 4.20):

In Asia and Americas (most vulnerable continents to flood and windstorm) it is notan easy practice to separate between the consequences of the two events. For
instance, in the monsoon Asia major large floods are triggered by typhoons. As seenfrom Figure 4.20, the 1970-1974 period and the 1990-1999 period have witnessed
the most disastrous flooding events around the world. Besides, the slight numbers ofpeaks and drops during the whole period, demarcating values are the increasing
trends in Africa, and the steady average numbers in Europe and Oceania for anumber of periods. Detailed analysis on flood and windstorm disasters focusing on acomparative assessment between the national data of Japan and EMDAT isunder-progress and will be the outcome of our next technical report.
Total numbers of people killed by flood
and windstorm disasters from 1960-2004
Rank
1
2
3
4
5
Total

Continent
Asia
Americas
AfricaEuropeOceania

Killed people
860,690111,089
19,1757,915
1,627
1,000,496

Africa2%

Americas
11%

%
92
11
2
1
-

Other: 3%
Asia
86%
Europe1%

Oceania

Total
in Thousands

Number of killedby flood and windstorm
1,000,000

400
350

100,000
300
10,000
250
1,000

200
150

100
100
10
50
1

1960-1964

1965-19691970-1974

1975-1979

1980-1984

1985-1989

1990-1994

1995-1999

2000-2004

Asia

59,72076,146358,680

30,38634,27145,410Americas10,3805,931

11,356

4,128

7,831

4,546

177,285

55,33923,453

3,897

53,941Africa

576

919

868

875

1,164

9,079

1,622

2,603

5,771

4,777

Europe

885

981

1,272

312

Oceania

262

168

226

92

867

388

1,077

1,261

872

140

318

139

157

Total

71,82384,145

372,40235,793125

44,27352,284

185,001

116,469

38,306

Figure 4.20. Distribution of people killed by both flood and windstorm disasterby continent for each 5-year period from 1960 to 2004.

59

0 Landslide disasters (Figure 4.21):
As can be seen from Figure 4.21, despite that over 50% of slide disasters occurred in
Asia (compared to 25% in Americas and 10% in Europe) during each 5-year period,
the most appealing values are the global equivalent ratios of killed people in Asia
and Americas (despite the large difference in population). Particular increasing
trends were observed during the periods from 1970 to the mid 1990. However, thisglobal ratio is mainly delineated by the extreme value of 1970-1975 in Americas andthe quasi-steady increase in Asia. Despite that the number of disasters in eachcontinent was nearly the same at each 5-year period since 1990 (in average 25% in
Asia, 18% in Americas and 15% in Europe), the number of killed people during theperiod 2000-2004 globally decreased by over 15% in average as compared to
1995-1999 period with clear distinctive ratios between continents.
Total numbers of people killed by landslideand avalanche disasters from 1960-2004
Rank
1
2
3
4
5
Total

Continent
Americas
Asia
EuropeAfricaOceania

Killed people
14,037
13,864
3,603
721
528
32,780

%
43
42
11
2
2

Americas43%Europe11%
Oceania2%
Africa
2%

Asia
42%

Number of killed by flood and windstorm

Total

10,000

7,000

6,000
1,000

5,000

4,000
100
3,000

2,000

10

1,000

1

1960-1964

1965-1969

Asia

414

Americas2071

1975-1979

1980-1984

1,064

513

738

983

5709

103

1,334

261

Oceania
Total

1985-1989

1990-1994

1,227

1,923

688

1,769

47
133

308

AfricaEurope1970-1974

3,819

2,616

183

120

100

13

6,505

974

2,095

1995-1999

2000-2004

1,788

3,254

2,943

972

1,051

691

31

84

141

110

351

832

234

182

87

200

79

49

4,161

3,876

4,759

3,975

Figure 4.21. Distribution of people killed by landslide and avalanche disasterby continent for each 5-year period from 1960 to 2004.

60

0 Wave and surge disasters (Figure 4.22):
It is clear from Figure 4.22 that the data on wave and surge disasters must be
undertaken at a finer temporal scale (e.g. on a yearly basis) due to the sparseinformation. At this stage the reporting mechanism on wave and surge events is notargued, nevertheless in order to draw concrete conclusion it is necessary toundertake an in-depth analysis including the events that do not meet the EMDAT
criteria. From Figure 4.22 there is clearly higher social vulnerability to this type ofdisaster as compared to flood or landslide. The year 2004 was marked in ourmemories by the tsunami tragedy in the Indian Ocean, which claimed the life of
more than 200,000 people. In response to this disaster UN Commission agreed tolaunch the first tsunami warning system in the Indian Ocean. The permanent system,in development, is expected to be operational by July 2006.
Total numbers of people killed by wave &surge disasters from 1960-2004
Rank
1
2
3
4
5
Total

Continent
Asia
Oceania
AfricaAmericas
EuropeKilled people
282,386
2382
164
76
11
1,000,496

AfricaAmericas%991-Europe

Asia
99%

Other
Oceania1%

Total

Number of killed by flood and windstorm

1,000,000

1,000,000
include the tragedic Sumatra
earthquake trrigered Tsunami

100,000

100,000

10,00010,000

1,000

1,000

100

100

10

10

1

1960-1964

1965-1969

Asia

170

264

Americas61

1970-1974

1975-1979

1980-1984

539

1985-1989

1990-1994

1995-1999

2000-2004

11

100

420

280,88215
164

Africa11

Europe200

Oceania
Total

1

231

264

2,182

750

11

100

2,617

281,046

Figure 4.22. Distribution of the number of people killed by wave and Surge disasterby continent for each 5-year period from 1960 to 2004.

61

 Drought disasters (Figure 4.23):
It is clear from the database that since 1960 all reported drought disasters withextreme impact on human life are regionally localized. For instance, during theperiod 1965-1969 the 1.5 million death in Asia were attributed to the drought of1965 to 1968 in India and the drought of 1966 in Indonesia, which killed 8,000
people. In Africa 99% of the drought disasters reported during the period 1980-1984
have actually occurred in 1984 (which was a sever drought year for the entire
African continent). Nevertheless, it is interesting to note that all the heavy casualties
occurred only in four countries with the following figures: Sudan 150,000; Ethiopia
300,000; Mozambique 100,000; and Chad 3,000 people. In EMDAT the numbers
above were reported as the consequence of one single event per country
acknowledging the long-term impact of drought events in the continent.
Total numbers of people killed by drought
disasters from 1960-2004
Rank
1
2
3
4
5
Total

Continent
Asia
AfricaOceania
Americas
EuropeKilled people
1,511,408
876,474688
742,388,644

Americas
Asia:
63%

%
63
37
-

Other

Oceania

Africa:37%
EuropeTotal
in Thousands

Number of killedby flood and windstorm
10,000,000

1,600

1,000,000

1,400
1,200

100,000

1,000
10,000
800
1,000
600
100

400

10

1

200

1960-1964

1965-19691970-1974

1,508,000

Asia

1975-1979

1980-1984

1985-1989

81

510

1995-1999

2000-2004

1,894

680

243

553,500

1,017

12

895

554,030

2,911

780

20

Americas
Africa1990-1994

50

2,000

50

1,510,600

319,000

54

Europe600

OceaniaTotal

88319,000

81

1,192

Figure 4.23. Distribution of the number of people killed by drought disasterby continent for each 5-year period from 1960 to 2004.

620 Famine disasters (Figure 4.24):
Despite the heavy figures of dead people plotted in Figure 4.24, the related data on
famine disasters undoubtedly requires more strict and objective analysis in order todraw constructive conclusions. For instance, in Asia the data for the period
1995-1999 and 2000-2004 were attributed to two series of famine disasters in North
Korea with the following scenario 27,500 x 5years = 137,500 death, and 27,500 x
2years = 82,500 death. In Africa the figures were shared between 4 countries,
namely Mozambique and Rwanda in 1989 with 5,200 death and 237 death
respectively; Mauritania 2,243 death in 1992; and Mali 3,615 death in 1998.

Total numbers of people killed by famine
disasters from 1960-2004
Rank
1
2
Total

Continent
Asia
AfricaKilled people
220,760
11,539232,299%95
5Africa
5%

Asia
95%

Total

Number of killed by famine disasters

150,000

1,000,000

100,000

120,000

10,00090,0001,000
60,000100
30,00010

1

1960-1964

1965-19691970-1974

1975-1979

1980-1984

1985-1989

Asia

1990-1994

1995-1999

2000-2004

760

137,500

82,500Americas
Africa

15

5,437

2,443

3,644

15

5,437

3,203

141,144

EuropeOceania
Total

82,500Figure 4.24. Distribution of the number of people killed by famine disasterby continent for each 5-year period from 1960 to 2004.

630 Epidemic water-related disasters (Figure 4.25):
Epidemic water-related has undoubtedly known a drastic improvement in thereporting mechanism due to the global efforts of the UN Agencies to motivate
countries to improve public access to safe drinking water and better sanitation.
Figure 4.25 shows that there were two distinctive phases in terms of the number ofkilled people by epidemic water-related, an increasing phase of the trend up to themid 1990s and a decreasing phase up to the end of the 2000-2004 period. The big
exception was for the African Continent where the number of killed people
increased from nearly 1,000 death in 1970s to about 15,000 death in 1990s. The
figure during the period 2000-2004 was as high as 6,474 death. Nevertheless, it isimportant to notice that more than 50% of all reported epidemic disasters for a given
period are mainly triggered by a single hazard at a country level. For instance, thecholera epidemic of 1991 killed 7,289 in Nigeria (Africa), and a Diarrhoeal/Enterictype epidemic in 1991 was reported to kill 8,000 people in Peru (Americas).
Total numbers of people killed by epidemic
water-related disasters from 1960-2004
Rank
1
2
3
4
5
Total

Continent
AfricaAsia
Americas
EuropeOceania

Killed people
48,074
23,592
13,334180
49
85,229

Asia
28%

%
56
28
16
-

Americas16%EuropeOther

Africa56%

Oceania

Number of killed by epidemic water related

Total

100,000

40,00035,00010,00030,00025,0001,000

20,000100

15,00010,000

10
5,000
1
Asia

1960-1964

1965-1969

598

466

1970-1974

1975-1979

1980-1984

1985-1989

1990-1994

1995-1999

2000-2004

1,512

5,324

2,778

7,827

3,783

1,304

300

37

12721

194

82

1,687

6,422

14,61815,365

6,474

26

45

91

18

Americas2,932

Africa576

Europe17

Oceania
Total

598

466

2,932

7

2,105

7,337

9,282

35,2640

25
19,3607,885

Figure 4.25. Distribution of the number of people killed by epidemic water-related disasterby continent for each 5-year period from 1960 to 2004.

64 Technological water-related disasters (Figure 4.26):
The disasters of this type reported in EMDAT were with no exception, attributed totransportation accidents. Most of the reported disasters are of marine type and only
few were attributed to bad weather conditions or floods in particular. Unlike all othertypes of disasters attributed to water, the trend for the period 2000-2004 has
increased from 30 to 50% in all continents save the Americas, where continuous
decrease is observed since the early 1990s. In addition to the heavy figures of killed
people, very large environmental and ecological disasters have accompanied thesemarine disasters as reported by other information systems.
Total numbers of people killed bytechnological water-related disasters from
1960-2004
Rank
1
2
3
4
5
Total

Continent
Asia
AfricaAmericas
EuropeOceania

Killed people
34,58014,165
6,547
4,728
267
.60,287

Americas
11%

%
58
23
11
8
-

Asia
58%

Europe8%

Other: 8%

Africa23%
Oceania
Total

Number of killed by technological water related disasters

20,000100,000

18,00016,00010,00014,00012,0001,000

10,000
8,000

100

6,000
4,000

10

2,000
1

1965-19691970-1974

1975-1979

1980-1984

1985-1989

1990-1994

1995-1999

2000-2004

Asia

39

360

700

2,553

14,076

5,929

4,806

6,117

Americas

90

30

43

644

1021

3080

1042

597

Africa

100

596

1,495

3,033

3,893

5,048

400

1,017

1,575

609

944

10,35012,887

Europe1960-1964

13

39

81

50

86

Oceania
Total

13

268

471

793

4,193

17,60913,7030

181

Figure 4.26. Distribution of the number of people killed by technological water-related
disaster by continent for each 5-year period from 1960 to 2004.

65

4.2.2. Regional trends of affected people by water-related disasters
All the results bellow are assessed for each 5-year period from 1960 to 2004.
 Flood disasters (Figure 4.27):
The gradient of the global trend of affected people by flood had drastically changed
over 3 major periods as clearly seen in Figure 4.27. Despite that the global trend ismainly delineated by the trend in Asia, demarcating data are the decreasing values
for the period 2000-2004 in all continents. During the previous decades the number
of affected people by flood in Asia increased from 3.3 millions people in 1960-1964
period to above 840 millions in the 1995-1999 period . The average in Americas was
about 3 millions people in each period save the drastic increase in the 1980s.
Besides the slight drops in the period 1980-1984, the number in Africa has increased
from 130 thousand to nearly 12 million by 1999. The figure in Europe followed thesame drastic increase from about 240 thousand people to 3 million by 1999. The
data for Oceania were extremely variable with a maximum peak of 200 thousand in
1985-1989 and a minimum value of 12 thousand in the period 1970-1975, the period
2000-2004 ended with the value of nearly 28 thousand affected people.
As mentioned above when presenting the impacts of water-related disasters instatistical ratios one must be aware of the magnitude of the impacts at the regionaland global levels. For instance, the table of Figure 4.27 shows that 1% of affected
people by flood in Africa accounted for about 40 million people, and while theimpact can be statistically negligible (<0.1%) for Europe the value was as high as 11
million people.
 Windstorm disasters (Figure 4.28):
Acknowledging the scale of globally affected people by windstorms (in the range of
200 million people as compared to about 900 million by flood), the trends’ gradientswere as acute as for the case of flood. An exception is for the period 2000-2004 thatwitnessed a drastic increasing number of affected people in Asia, Americas andAfrica. For this later period, while the trend in Europe was in the range of 3 million
people, the reported number for Oceania dropped from 1 million in the 1995-1999
period to about 160 thousands in the 2000-2004 period. The global picture of theaffected people by windstorm jumped from 9.5 millions in 1960-1964 period to near
200 million in 2000-2004 period. The combined effect of flood and windstorm
exponentially rose from about 13 million in 1960-1964 to nearly one billion in
1990s and over 800 million in 2000-2004. To understand the magnitude of thesenumbers as well as their impacts on the regional trends, reference is made to tables
4.10 and 4.11. The tables outline the magnitudes of the top 10 disastrous flood andwindstorm events in terms of total affected people. A single flood disaster in66

populated regions is likely to kill as high as 100 million people in average (themaximum was over 200 million in China Republic). The top 10 windstorm disasters
have all occurred in Asia with larger geographic spread as compared to top 10 floods.
The magnitude of the impact of windstorms is nearly 10% of the impacts measured
for floods.
Aware of the aggravating condition worldwide it is important to initiate pilot casestudies at country levels in order to identify accurate and healthy indicators to
explain the reasons behind these increasing trends in the number of affected people
and the humble decrease in the number of killed people.
Total numbers of affected people by flood
disasters from 1960-2004
Rank
1
2
3
4
5
Total

Continent
Asia
Americas
AfricaEuropeOceania

Affected people
2,763,819,066
51,244,764
36,014,832
10,916,943.552,159
2,862,547,764

%
97
2
1
-

Africa: 1%

Asia
97%

Other: 3%
Americas: 2%

Europe: Oceania: -Number of affected by flood
Scale for other regions in Millions

Scale for Total and Asia in
Millions
1,000

16

900

14

800
12
700
10

600

8

500
400

6

300
4
200
2
0

100
1960-1964

1965-19691970-1974

1975-1979

1980-1984

1985-1989

6,669,785

3,535,740

13,184,145

13,714,920

2,974,684

1,624,842

1,467,719

6,010,913

1,541,005

1,086,870

828,247

34,58012,00012,97525,095219,9121990-1994

1995-1999

2000-2004

Americas120,000

1,757,747

Africa130,310

736,7313,182,908

5,593,659

3,485,860

2,361,934

11,887,220

Europe243,000

196,200

8,820,479

1,520,147

3,019,596

Oceania

18,0002,447,298

170,935

65,251Asia

3,317,421

34,650,437

70,892,281 119,539,124 161,328,823 344,149,344 567,632,267 841,000,440 621,308,929

27,991Flood

3,828,731

37,341,115

82,089,755 125,799,551 176,834,029 364,129,669 574,868,191 861,566,166 636,090,557

Figure 4.27. Distribution of the number of affected people by flood disasterby continent for each 5-year period from 1960 to 2004.

67

0Total numbers of affected people bywindstorm disasters from 1960-2004
Rank Continent Killed people%
Asia
562,293,392 90
1
Americas36,899,615
6
2
Africa13,701,655
23Europe7,736,270
1
4
Oceania
6,005,686
1
5
Total.626,636,618

Africa: 2%

Asia
90%

Other
10%

Americas: 6%

Europe: 1%
Oceania: 1%

Number of affected people by windstorm disasters
Scale for other continents than Asia in Millions

Scale for Total and Asia in
Millions
200

14

180
12
160
10

140
120

8

100
6

80
60

4

40
2
20
0
Americas1960-1964

1965-1969

91,868AfricaEurope12,0001970-1974

1975-1979

1980-1984

1985-1989

1990-1994

1995-1999

2000-2004

652,508

922,706

2,311,483

1,474,004

4,127,618

2,937,112

11,241,455

13,140,861

141,5792,545,072

1,628,592

1,910,950

258,4443,324,048

849,871

3,043,099

3,900

5,200

19

71,962

1,022,071

3,793,421

2,827,697

3,481,917

1,096,504

162,140

Oceania

12,000107,204

174,090

75,005435,660

Asia

9,477,059

19,746,665

21,303,460

23,574,046

38,240,203

91,342,961 106,438,734 89,201,795 162,968,469

461,166Wind Storm

9,592,927

20,651,856

24,950,528

27,589,145

42,132,779

96,190,189 117,203,882 106,183,046 182,142,266

Figure 4.28. Distribution of the number of affected people by flood disasterby continent for each 5-year period from 1960 to 2004.

68

0

year
1998
1991
2002
1996
2003
1993
1995
1999
1989
1994

Table 4.10. Top 10 most disastrous floods
in terms of affected people.
Total affected People
Disaster Subset Country
Flood
China Pop. Rep.
238,973,000
Flood
China Pop. Rep.
210,232,227
Flash Flood
China Pop. Rep.
190,035,257
Flood
China Pop. Rep.
154,634,000
Flood
China Pop. Rep.
150,146,000
Flood
India
128,000,000
Flood
China Pop. Rep.
114,470,249
Flood
China Pop. Rep.
101,024,000
Flood
China Pop. Rep.
100,010,000
Flood
China Pop. Rep.
78,974,400

year
1989
1965
1991
1996
1977
1999
1994
1998
1988
1980

Table 4.11. Top 10 most disastrous floods
in terms of affected people.
Disaster Subset
Country
Total affected People
Storm
China Pop. Rep.
30,007,500
CycloneBangladesh
15,600,000
CycloneBangladesh
15,438,849
TyphoonChina Pop. Rep.
15,005,000
CycloneIndia
14,469,800
CycloneIndia
12,628,312
TyphoonChina Pop. Rep.
11,001,800
Storm
China Pop. Rep.
11,000,038
CycloneBangladesh
10,568,860
TyphoonViet Nam
9,027,17469

 Slide disasters (Figure 4.29):
In average there is no clear global decrease in the number of affected people by slidedisasters. The global trend is mainly delineated by the trends in Asia and theAmericas. However, it is important to notice that 85% of the total in the Americas
was attributed to the impact of single event in Brazil (4 million were people affected).
Concurrently 70% of the total number in Asia was attributed to two events in India(2.5 million people in 1986 and 1.1 million people in 1995). These annotations
applies to even smaller scale disasters such as for the 2000-2004 period in Americas
where over 90% of the period-total was attributed to the landslide(s) of 2000 in
Brazil that affected 143 thousands people in four states. Beside these extreme events
the trends in most continents showed periodic peaks and drops over time.
Total numbers of affected people bylandslide disasters from 1960-2004
Rank
1
2
3
4
5
Total

Continent
Asia
Americas
EuropeAfricaOceania

Affected people
5,056,326
4,667,096
41,156
19,74011,015
9,795,333

Americas
48%

%
51.6
47.7
0.4
0.2
0.1

AfricaOther: 1%
EuropeAsia
52%
Oceania

Total in Millions

Number of killed by landslide

5

10,000,000

1,000,000
4100,000
3

10,000

1,000

2

100
1
10

1

1960-1964

1965-19691970-1974

1975-1979

1980-1984

1985-1989

1,113

80,1253,150

4,000,022

16,028

116

40

Asia
Americas
Africa1,436Europe2285

50

4,001,480

17,22680,891

Slides

1995-1999

2000-2004

2,571,402

215,196

1,328,503

856,837

119,302327,849

46,757

156,982

12,416

1,648

1,025

2,500

715

7,035

16,841

2,834

11,278

3,011

4,000

5,000

620

795

22,6412,713,193

551,904

1,389,658

1,018,340

600

Oceania

1990-1994

Figure 4.29. Distribution of the number of affected people by landslides and avalanche
disasters by continent for each 5-year period from 1960 to 2004.

70

0 Wave and surge disasters (Figure 4.30):
Major wave and surge disaster were
attributed to tsunamis. Table 4.12
gives the number of affected people
by major tsunami disasters. In Asia
most of the disasters are attributed
to the Sumatra tsunami ofDecember 2004.

Table 4.12. Total affected people by regional
major wave and surge disasters.
year dis_subset Country
2004 Tsunami Sri Lanka
2004 Tsunami India
2004 Tsunami Indonesia
2004 Tsunami Thailand
2004 Tsunami Somalia
2002 Tsunami Honduras
1998 Tsunami Papua New Guinea

t. affected
1,267,506
654,512419,682
66,45754,283
1,720
9,199

Total numbers of affected people by wave andsurge disasters from 1960-2004
Rank
1
2
3
4
5
Total

Continent
Asia
AfricaOceania
Americas
EuropeKilled people%
2,491,929 98
56,478 2
9,867 2,844 2 2,561,120

Africa
2%

Asia
98%

Other: 4%

Americas
Oceania

Total in Millions

Number of affected people by wave and surge (includes tsunami) disasters

3

10,000,000

1,000,000

100,000
2
10,000

1,000
1
100

10

1

1960-1964

1965-1969
97

Asia

1970-1974

1975-1979

1980-1984

1985-1989

23

818

2,000

2000-2004

29,2002,459,791

2,000

1,720
54,4782

Europe9,867

Oceania
Wave and Surge

1995-1999
1,124

Americas
Africa1990-1994

2,097

25

818

2,000

40,191

2,515,989

Figure 4.30. Distribution of the number of affected people by wave and surge
disasters by continent for each 5-year period from 1960 to 2004.

710Europe0% Drought disasters (Figure 4.31):
The figure of affected people by a single drought disaster is the highest in number ascompared to other water-related disasters (see Figure 4.31 and Table 4.13). Table 4.13
shows that nearly all the top fifteen drought disasters during the past decades have occurredin Asia with the highest figure in India (as high as 300 million people were affected by the
1987 and 2002 droughts respectively). During the past four decades and a half over 2
billion people were affected by drought (1.8 billion in Asia alone as compared to 300
thousand in Africa). Demarcating values are the historical extremes during the period
2000-2004 that occurred worldwide.
Figure 4.31 illustrates that since the 1980s there were no clear increase or decrease inregional trends as compared to the global increase during the periods from 1960 to 1984.
Nevertheless, the data of Table 4.13 clearly pinpoints that this global trend variation plottedon a 5-year basis is particularly delineated by a number of historical peaks. Additionally,
Table 4.14 illustrates that 50% of top ten famine disasters were also triggered by drought.
At the regional level, though Ethiopia is at the top of the ten most vulnerable countries inAfrica, many countries are equivalently affected (such as South Africa, Sudan, and Malawi
among others). The trend of affected people in Europe (see Figure 4.31) can not be used toaffirm an increasing trend of droughts in the region, as the values reported for each 5-year
period since 1990 are rather focally centered in time and geographic distribution.
Concurrently, the trend of drought in Oceania was delineated by the series of drought inAustralia reported affecting 1.75 million people at every single year since 1992 to 1995.

 Famine disasters (Figure 4.32):
Data on famine disasters continuously affected the largest population in Africa (see Figure
4.32 and Table 4.14). For instance, a famine disaster in 1982 affected over 12 million
people. During the year 2002, famine attributed to crop failure mainly affected four
countries in Africa, namely 500 thousands people in Lesotho, 400 thousand people in
Madagascar, 150 thousand people in Swaziland, and 30 thousand people in Cape Verde Is).
In Asia the average of affected people by famine disasters was about 1 million people
geographically distributed among 9 countries. As shown in Table 4.14, the largest disaster
was attributed to the famine event of 2002 in Korea Democratic Popular Republic (with 2.9
million affected people), and the two second largest disasters were the famines of 1995 and1996 in Cambodia, which affected 2.5 million people, respectively. During the periods
1995 through 2001 the database reported that 1 million people at each single year wereaffected by famine in Korea Democratic Popular Republic. Among the 9 affected countries
in Asia, the only famine disaster attributed to Arab states was the famine of 1995 in Iraq
(which affected over 800 thousand people). In Europe beside the famine disaster of 1932 in
the former Soviet Union (reported to kill 5 million people but zero affected people), theonly recent famine disaster was in 1995 in Macedonia, which was reported to have affected
10 thousand people nation wide.

72

Table 4.13. Top 15 drought disasters
in terms of total affected in EMDAT.

Table 4.14. Top 15 famine disasters in terms of total
affected people reported in EMDAT.

year
1987
2002
1979
1965
1972
1973
1982
1983
2000
1988
2003
2000
2001
1983
1983

year
1982
1999
1993
1994
2002
1998
1995
1996
1989
1990
1993
1987
1988
1988
1992

country_name
India
India
India
India
India
India
India
India
India
China P Rep
China P Rep
Iran Islam Rep
Iran Islam Rep
Bangladesh
Braziltotal_affected
300,000,000
300,000,000
190,000,000
100,000,000
100,000,000
100,000,000
100,000,000
100,000,000
90,000,000
49,000,000
48,000,000
37,000,000
25,000,000
20,000,000
20,000,000

dis_subset
Drought
Crop failure
Food shortage
Food shortage
Food shortage
Food shortage
Drought
Drought
Food shortage
Food shortage
Food shortage
Drought
Drought
Drought
Food shortage

country_namet. affectedGhana
12,500,000
Ethiopia
7,767,594
Ethiopia
6,700,000
Ethiopia
3,900,000
Korea Dem P Rep
2,900,000
Sudan
2,600,000
Cambodia
2,500,000
Cambodia
2,500,000
Ethiopia
1,850,000
Niger
1,630,000
Eritrea
1,600,000
Malawi
1,429,267
South Africa
1,350,000
South Africa
1,320,000
Armenia
1,300,000

Table 4.15. Top 10 drought disasters in terms of total affected people
in each continent (for Asia see Table 4.13)
Top 10 drought disasters in Africa

Top 10 drought disasters in Americas

year

countryt. affected

year

country

2004
2002
2003
2000
1991
1984
1984
1983
1987
1993

South Africa
Ethiopia
Ethiopia
Ethiopia
Sudan
Sudan
Ethiopia
Ethiopia
Ethiopia
Malawi

15,000,000
14,300,000
13,200,000
10,500,000
8,600,000
8,400,000
7,750,000
7,000,000
7,000,000
7,000,000

1983
1970
1998
1979
1990
1983
1983
1992
2001
2001

BrazilBrazilBrazilBrazilPeru
Bolivia
Bolivia
Peru
BrazilHonduras

Top 10 drought disasters in Europe

t. affected
20,000,000
10,000,000
10,000,000
5,000,000
2,200,000
1,583,049
1,500,000
1,100,000
1,000,000
791,394

Top 10 drought disasters in Oceania

year

countryt. affected

year

country

1995
1921
1991
2003
2003
1976
2000
1983
2003
1991

Spain
Soviet Union
Albania
RussiaBosnia-Hercegovenia
Belgium
Bosnia-Hercegovenia
Bulgaria
Croatia
Cyprus6,000,000
5,000,000
3,200,000
1,000,000
62,575
0
0
0
0
0

1992
1993
1994
1995
1997
1998
1999
1982
1981
1983

Australia
Australia
Australia
Australia
Papua New Guinea
FijiKiribati
Australia
Papua New Guinea
Fiji

73

t. affected
1,750,000
1,750,000
1,750,000
1,750,000
700,000
263,455
84,00080,00040,00031,000Total numbers of affected people bydrought disasters from 1960-2004.
Rank Continent
Killed people%
Asia
1,770,081,014 82
1
Americas.317,143,582 15
2.61,714,030 3
Africa3
Europe.10,262,575 4
Oceania.8,233,635 5
Total
2,167,434,836

Americas
3%
Asia
82%

Other: 4%
Africa15%
EuropeOceania

Number of affected people by drought

Total in Millions

1,000,000,000

800

100,000,000

700

10,000,000

600

1,000,000
500
100,000
400
10,000
300
1,000
200

100

100

10
1

1960-1964

1965-19691970-1974

1975-1979

1980-1984

Asia

1,291,000

104,957,944 207,875,000 209,772,885 227,502,000 357,737,000 28,746,385

Americas613,400

1,054,821

10,837,000

5,450,000

23,992,049

823,000

3,713,160

12,298,200

Africa705,000

4,118,483

12,506,595

11,780,400

65,260,840

28,027,000

71,575,007

20,586,349 102,583,908

Europe151,000

Oceania
Drought

2,609,400

1985-1989

1990-1994

1995-1999

2000-2004

46,049,000 586,149,800

3,200,000

6,000,000

5,250,000

2,832,635

2,932,400
1,062,575

110,131,248 231,218,595 227,003,285 316,905,889 386,587,000 112,484,552 87,766,184 692,728,683

Figure 4.31. Distribution of the number of affected people by drought
disaster by continent for each 5-year period from 1960 to 2004.

74

0Total numbers of affected people by famine
disasters from 1960-2004
Rank Continent Killed people%
Africa50,983,301
72
1
Asia
19,000,000 27
2
Europe1,003,000
1
3Americas.10,000
4
Oceania--5
Total
70,996,301

Asia
27%
Americas
1%
Other: 1%

Africa72%

EuropeTotal in Millions

Number of affected people by continent
by famine disasters in Millions

30

16
14

25
12
20
10
15

8
6

10
4
5
2
0
Asia

1960-1964

1965-19691970-1974

1975-1979

1980-1984

1985-1989

300,000

1990-1994

1995-1999

2000-2004

1,812,000

11,988,000

4,900,000

12,339,134

1,080,000

1,000,000

Americas300,000

Africa13,123,000

8,937,267

15,203,900

3,000
10,000EuropeOceania
Famine300,000

300,000

13,123,000

8,937,267

18,015,900

24,337,134

5,983,000

Figure 4.32. Distribution of the number of affected people by both famine
disaster by continent for each 5-year period from 1960 to 2004.

 Epidemic water-related disasters (Figure 4.33):
As mentioned earlier over 50% of water-related epidemic occurred in Africa with a drastic
increase in number during the two past decades. Figure 4.33 shows that the trend ofaffected people at all regions started to know a net decrease since the mid 1990s after the
drastic decrease and alarming figures during the period 1990-1994. The figure also
illustrates that during the past fifteen years, the average number of affected people byepidemic water-related in Africa is over one million people. The largest figure was75

0attributed to the malaria disaster of 1994 in Kenya, which affected over 6 million people. In
Asia the largest disasters was the 1991 Diarrhoeal/Enteric type disaster in Bangladesh,which affected 1.5 million people. Other largely affected countries in Asia are India,
Indonesia and Bangladesh. In Europe after the malaria disaster of 1923 in the former Soviet
Union, which affected 1.8 million people and the malaria of 1977 in Turkey, which affected
100 thousand people, no large scale water epidemic disasters have since been recorded in
EMDAT. Nevertheless, individual epidemic water-related disasters likely to affectthousands of people have been higher in number during the past decade and a half.
Total numbers of affected people byepidemic water-related disasters from
1960-2004
Rank Continent Killed people%
Africa8,981,942 61
1
Asia
4,463,798 30
2
Americas
1,105,932 8
3Europe103,303 1
4
Oceania
5,638
5
Total
14,660,613

Asia
30%

Europe1%Americas: 8%

Africa61%

Oceania

Total in Millions

Number of affected people by epidemic water related disasters

10

10,000,000

91,000,000
8
100,000

7
6

10,000

5
1,000

4
3

100

2
10
1
1

1960-1964 1965-1969 1970-1974 1975-1979 1980-1984 1985-1989 1990-1994 1995-1999 2000-2004

Asia

10,848Americas

2,724

205,118

69,371

178,375

407
13,476

1,169,700

2,137,951

465,221

227,21434,892400,435

459,779

207,695

16,386

12,37662,4906,813,919

1,056,966

1,006,329

Europe100,000

16

294

1,333

554

1,106

Oceania352

1,982,520

1,446,430

AfricaEpidemic Water related

13,572

205,118

13,476

186,516

1,200
190,767

1,267,376

9,354,838

4,086

Figure 4.33. Distribution of the number of affected people by epidemic water-related
disaster by continent for each 5-year period from 1960 to 2004.

76

0 Technological water-related disasters (Figure 4.34):
Technological water-related disasters attributed to water are all associated with transport
accidents, mainly of marine type (i.e., out of the 770 disasters reported, 365 accidents wereboat, ferry, or submarine accidents, etc.) Only 16 disasters out of the 365 known ones were
attributed to bad weather conditions (such as storm, fog, etc.) the cause of other accidents
were unknown. The largest disaster reported in terms of affected people is the 1992
Petrolier 'Katina' in Mozambique reported to affect over 50 thousand people. Figure 4.34
illustrates the trends of this type of disaster for each continent.

Total numbers of affected people bytechnological water-related disasters from
1960-2004%
Rank Continent Affected people
Africa51,832 97
1
Asia
3,467
6
2
Americas971
23Europe956
2
4
Oceania24
5
Total
57,250Asia
6%Americas2%Europe2%

Africa90%

Oceania-

Total in Thousands

Number of killed by technological water related

60

100,000

50

10,000

40
1,000
30
100
20
10

10

1

0
1960-1964

1965-19691970-1974

1975-1979

Asia
500

Americas
Africa1980-1984

1985-1989

1990-1994

907

290

19

200

2000-2004

188

53

2,029

20

112

320

38

201

203

3,490

50,692Europe

498

219

788

51,143940

24

Oceania
Totals

1995-1999

200

500

926

Figure 4.34. Distribution of the number of affected people by technological water-related
disaster by continent for each 5-year period from 1960 to 2004.

77

Chapter 5: Technical Aspects and Challenges Ahead
Chapter 5. Technical aspects and challenges ahead

As proved from the results above water-related disasters are prevailing in time andcommonly shared burden among all the continents. Reciprocally to the size of thecontinent’s population, their negative impacts on society and economy are still
exponentially increasing despite all national, regional and international efforts in
disasters mitigation. Managers and scientists working in the field of natural disasters
mitigation are convinced more than ever before that sustainable solution can only besought under the umbrella of what we can generalize under the name of“multidisciplinary risk management science”. Indeed, while water hazards are
triggered by hydrometeorological phenomena (coupled with geological factors), thescales of their multifaceted impacts are resolved by the complex social andenvironmental conditions of the country and community afflicted by the disaster.
There are numbers of pragmatic issues for proper implementation of integrated
multidisciplinary approach in water resources management. These issues are being
stressed and discussed at many scientific and political gatherings and are mainlyreflected as an integral part of the action plan of the 4th phase of the International
Hydrological Program (IHP-VI Plan: 2002-2007). In water-related disasters further
problematic issues are found within the risk management process and cycle. The
major issue is the reliability of the risk quantification and assessment which we
acknowledge to be among the most important steps in risk management and also themost difficult and prone to error regarding the diversity of the type of water-related
disasters and concurrent impacts. The reliability of risk assessment does not only
relay on the quality of reporting, but also on the methodology to monitor and assess
disasters’ impacts at the first stage. A direct problem resulting from such pragmatic
assessment is at least of two folds, first, the uncertainties surrounding the accuracyof the numbers quantifying the impacts, second, the meaning behind the numbers
resulting from the risk assessment upon which most mitigation strategies are built on.
It is therefore extremely valuable to create a strong international platform forcooperation with primary focus on water-related disasters and related risk
managemental issues. This body when created shall work to fill in the gap in thisarea and promote the development of standardized methodology for disasters
impacts quantification (see Guha-Sapir & Below, 2002; Merabtene et al., 2004; andWisner et al., 2004).
At the global scale and regardless of existing uncertainties and challenges ahead,
there is an increasing consensus on the important role of risk management and its
implementation in decision making to define safer and sustainable holistic strategies
in natural disasters mitigation. This alone justifies the great importance ofundertaking further vigilant quantification of disaster loss data at finer temporal and79

geographical scales than as reported herein. Among other great benefits behind suchdisaster quantification is to allow analysis of trends which in turn provides strong
indicators for vulnerability and resiliency analysis as well as to assess theeffectiveness of adopted policies in disasters mitigation.
As proven throughout the results of this technical analysis, there are numerous
overwhelming difficulties underlying the assessment of disaster impacts. There isdefinitely urgent need to undertake a more in-depth survey and analysis in order todraw conclusive concepts for vulnerability analysis and water-related risk
management in general. For instance, there is no clear evidence to fully support thelargely acknowledge perspective that death toll from water-related disasters isdecreasing, at least not for each continent and not for each type of water-related
disaster. Our assessment draws the attention to the pragmatic aspect of dataprocessing based on different time scales and analysis periods, which might often
lead to controversial conclusions if the results are not handled and interpreted withextreme care. To further emphasis some of these technical issues, reference is madeto figures 5.1 to 5.5 discussed hereafter.
Figure 5.1 depicts the number of affected people by the top 1000 disastrous natural
events reported in EMDAT since 1900 to 2004. The figure reports that all the 11
types of natural disasters categorized in EMDAT had a clear impact share on world
population despite the distinctive difference between the stressors and determinants
susceptible to influence the scale and number of affected people. Among all water
disasters, the figure largely endorses what we have stated earlier on the
predominance in the numbers and impacts of hydrometeorological disasters such as
flood, drought and windstorm over other natural disasters such as earthquake,
extreme temperature (i.e. cold and heat waves), and volcano, etc. Flood, drought andwindstorm accounted respectively for 35%, 27.6% and 24.1% of the total top 1000
disasters. For these three types of disasters, a notable aspect of the graph is thequasi-analogue form of the gradients of the trends of affected people (i.e., the top
1000 disasters events are plotted in a decreasing order and the time/year ofoccurrence of simultaneous events are different.) Technically, before drawing
concrete conclusions on such interesting behaviors, it is important to recall thedifference between the temporal and geographical spreading of the impacts of eachtype of disasters particularly of floods and droughts. A concurrent interesting
example in Figure 5.1 is the trends of famine and earthquake disasters which areclosely in the same range despite that earthquakes are mainly focal disasters (likely
to affect any class of the community at a very localized scale) and famine disasterare widespread (likely to affect the whole nation and further impoverish the poor
class). The most disastrous events in terms of killed people for the period from 1900
to 2004 were mainly driven by the extreme events reported in the early 1900s andare not reported herein (see Annex 4).

80

79

100,000

1,000,000

10,000,000

Drought : 28%276 events

Flood: 34%
350 events

Famine: 4%
39 events

181

151

136

91

Volcano: 4 evenst

Extreme Temp.: 1%
8 events
Slides: 5 events

Epidemic: 2%
16 events

Wind Storm

Wild Fires

VolcanoSlidesFlood

FamineExtreme Temperature

Epidemic

Wild Fires: 1 event

226

Wave / Surge

241

Wave & Surge: 3 events

271

256

121

76

61

46

31

16

Figure 5.1. 1000 most disastrous events in terms of affected people: EMDAT from 1900 to 2004.

106

Wave Volcano:& Surge: 43 evenst
eventsNumber of events by type

166

Earthquake: 6%57 events

286

100,000,000

196

Earthquake

301

Wind Storm: 24%
241 events

211

drought

316

1,000,000,000

331

1Number of affected people346Drought
12%Wind Storm
37%

Epidemicwater related
4%
Famine1%

Other: 13%

Wave/Surge
1%
Slide
7%

Flood
38%

Figure 5.2.a. Distribution of numbers of events of water-related disasters per type:
EMDAT 1960-2004.

Epidemicwater related
0%

Flood
27%

Famine28%

Slides0%Wind Storm
5%
Other
2%
Wave/Surge
1%
Drought
39%

Figure 5.2.b. Ratios of numbers of killed people by type of water-related disasters:
EMDAT 1960-2004.

82

Wave/Surge<1%
Drought
38%
Wind Storm
11%
Other: 2%

Famine1%Slides<1%
Epidemicwater related
<1%

Flood
50%

Figure 5.2.c. Ratios of numbers of affected people by type of water-related disasters:
EMDAT 1960-2004.

Flood
44%

Slides0%

Drought
8%

Famine0%

Other
2%
Wave/Surge
1%

Wind Storm
47%

Epidemicwater related0%

Figure 5.2.d. Ratios of added real economic damage by type of water-related disasters:
EMDAT 1960-2004.

83

Table 5.1. Equivalent ratios between number of disasters and number of killed and affected
people respectively: EMDAT 1960-2004 (technological water-related disasters not included)
Type of water
related disaster

Flood
Windstorm
Drought
Slide
Water Epidemic
FamineWave and surge

Ratio of thenumbers ofevents(% of total)

38.32
37.35
11.73
6.93
3.81
1.10
0.76

Ratio of thenumbers of killed
people(% of total)

Ratio of thenumbers ofaffected people(% of total)

26.84
4.67
39.00
0.21
0.23
27.90
1.15

50.00
10.90
37.53
0.16
0.15
1.22
0.04

Ratio of real
economicdamage(% of total)

43.64
46.96
7.86
0.47
0.00
0.01
1.06

Figure 5.2 (plotted for the period 1960-2004) and concurrently Table 5.1 show the
distribution of the ratio of the total numbers of events by type of water-related
disaster (Figure 5.2.a) and the respective equivalent ratios in terms of total killed
people (Figure 5.2.b), total affected people (Figure 5.2.c) and total economic
damage (Figure 5.2.d) (i.e., economic damage is based on the real values reported
without conversion to the referential year). Attention shall be drawn to the differencein the ratios when the same information is plotted for different periods (compare theratios of Figure 5.1 to those of Figure 4.1.b, plotted for the period 1900-2004, andFigure 4.2.a, plotted for the period 1990-2004). In addition to what we have statedabout the net improvement in the reporting mechanism in EMDAT, the three figures
could be an indicator on the way the impacts of different types of disasters canevolve in time. In Figure 5.1 the total number of drought events for the period 1960
to 2004 accounted for 12% of the total disasters reported. Total numbers of killed
and affected people were nearly 40% of the totals, respectively, whereas only 8% of
the total economic damage was attributed to drought. At this stage no further
analysis is conducted, but as mentioned earlier the death toll in China Republic andIndia and the number of affected people in India in particular are larger than those of
the rest of the world by several digits. In contrast, the ratio of famine events
accounted for only 1.1% of the total number of disasters. The result shows thatfamine killed 28% of the world total but affected only 1% of the world afflicted
population by water-related disasters. Another interesting figure is the interrelation
between the number of windstorm disasters and concurrent impacts (the total killed
people 5%, the total affected people 11% and the total economic damage 47% of the
global picture.) This later figure put clear emphasis on the importance toconcurrently carry out an economic loss evaluation.

84

Undoubtedly, for us to have a complete picture behind these numbers a morein-depth event based analysis is required. Nevertheless, in order to put further clear
emphasis on the complexity of such quality assessment of water-related disasters
databases in particular, reference is made to figures 5.3 and 5.4. When producing
figures 5.3 and 5.4 we have excluded all extreme values that were repeated over
several years (with exactly the same numbers) such as the droughts in India or thefamines in Korea Democratic Popular Republic. Such values are taken into
consideration only once or twice at most depending on the decade of occurrence.
- Figure 5.3 looks at the database in terms of the top one hundred most disastrous

events classified in reference to the largest numbers of killed people by water
disasters since 1960 to 2004.
- Figure 5.4 looks at the database in terms of the top one hundred most disastrous
events classified in reference to the largest numbers of affected people by water
disasters since 1960 to 2004.
A classification as of Figure 5.3 shows that most devastating water disasters are
drought, flood, windstorm and famine. For drought, the figure includes only 6
events with both social impacts (killed and affected people), however, the meaning
behind these numbers is questionable. In other words, what does a drought event
killing hundred thousands or one thousand or hundred people or even one personmean to us as water professionals? Are they killed by water shortage, epidemic
disease such as HIV/AIDS or most likely by famine caused by droughts or others? Ifsome deaths are attributed to famine then why are these data not reported as famine
disasters? In other words for us to carry a reliable assessment of disasters a clear
identification of the real root or cause of death is rudimentary. Though separating
the real impact of drought from other factors is still a big challenge, attention is
directed to the famine data in Figure 5.4 showing zero people killed by the largest
famine disasters as well as to the famine data plotted in terms of largest killed
people (see Figure 5.4) showing nearly zero affected people (save the North Korea
disaster in 2002). Thus, even after isolating large extreme events there is still an
important work to be carried out on event-basis to accurately identify the statisticaltrends of water-related disasters, especially if sought as indicators to compare
between regions or countries.
For flood and windstorm a classification as in Figure 5.4 shows a more logicalresponse in terms of social resiliency to water-related disaster. Nevertheless, clear
data incompatibility is also found in reporting flood disasters. For instance, the flood
events of 1970 in Bangladesh (10 million people affected), 1979 in India (26 million
people affected), and 2002 in the China Rep. (20 million people affected) all
reported zero killed people. In contrast Figure 5.4 (plotted in terms of the largest

85

number of killed people) shows that 19 events out of the 100 most disastrous events
under this classification counted numbers of zero affected people. These numbers
clearly emphasize the extreme importance to verify these data with reference to theofficial statistics at the national level. This complex large diversity of interrelation
between the numbers of killed people and affected people, especially under theclassification shown in Figure 5.4, can be further investigated for wave/surge,
famine, epidemic water-related, slide and windstorm. Needless to re-emphasis thatthe consistency of reported data can only be verified through a comprehensive
comparative study with national disasters databases. However, we all recognize thatfor achieving this basic assessment goal there is a need for a strong political andscientific will to share data and open the national databases.

86

87
DroughtFloodno_killed

Top 100 disasterous events classified in term of largest numbers of affected people

total_affected

Windstorm
FamineFigure 5.3. Extreme one hundred water-related disasters classified by largest number of affected people since 1960 to 2004.

1

10

100

1,000

10,000100,000

1,000,000

10,000,000

100,000,000

1,000,000,000

Number of affected
and killed people

1987
1979
1965
2000
1988
2003
2000
2001
1983
1983
1999
2001
2001
2000
2004
2002
2003
1992
2000
1970
1979
1998
1995
1991
1984
1984

1998
1991
2002
1996
2003
1993
1995
1999
1989
1994
1987
1988
2002
1974
1975
2004
2004
1982
1995
1978
1994
1980
1984
1997
1998
1990
1979
2000
1999
1988
2002
1987
1988
1981
1984
1990
1968
1998
2000
1995
1992
1994
2004
1993
1995
1970
1985
1980
1970
2001
2004
1995
1968

2002
1989
1965
1991
1996
2001
1977
1999
1994
1998
1988
1980
2004
1994
1992
2003
1989
2002
1996

1982
1999

88
DroughtFloodno_killed

Wave/surge

total_affected

Windstorm
FamineTop 100 disasterous events classified in term of largest numbers of killed people

water Epidemic Slide

Figure 5.4. Extreme one hundred water-related disasters classified by largest number of killed people since 1960 to 2004.

1

10

100

1,000

10,000100,000

1,000,000

10,000,000

100,000,000

1,000,000,000

Number of killed andaffected people

1965
1984
1974
1984
1973
1984
1974
1966
1984
1965
1988

1999
1974
1960
1980
1968
1978
1998
1996
2004
1987
1988
1997
1994
1989
1961
1998
1991
1980
1989
2002
1995
1997
1995
1992
1992
1981
2000
1984
1987

1970
1991
1965
1998
1977
1965
1963
1961
1985
1965
1999
1971
1974
1964
1991
1960
1963
1997
1998
1960
1998
2004
1974
1963
1973
2004
1970
1979
1984

2004
2004
2004
2004
1998

2002
1995
1989
1998
1992

1991
1991
1982
2002
1971
2002
1998
1991
2001
1991
2002
1998
1996
1991
1996
1986
1991
1985
1992

1973
1962

The analysis above has brought to us a far clearer understanding of the complexityof water-related disaster quantification worldwide. The results show that theconclusions on the trends of death tolls and affected people by any type ofwater-related disasters should be questioned with even more vigor in the light of
more rigorous scientific approach in data selection and data processing. For instance,
while famine disasters are attracting many political and international attentions,
there are still many events dropped from the database such as the famine disaster of2002 in Malawi, described by Wisner 2004 as the worst disaster in the African
modern history. It is believed that other water-related disasters are also undergoingsuch incomplete vision in reporting for many technical and political factors. A
number of comparative studies between existent databases have put the light onsome of these deficiencies (see Guha-Sapir (2002) and LA-RED (2002)), but very
little was done to conduct a comparative study between these disasters databases andofficial national databases.
As mentioned earlier the goal behind such disaster data processing and analysis is to
identify the means to build a reliable database with the quality to serve as base to
first understand and quantify the vulnerability of people and property towater-related disasters and second to assess the effectiveness of adopted policies indisasters mitigation. Figure 5.5 introduces our case study to apply global indicators
as a proof-of-concept implementation to assess ‘policy effectiveness’ toward theachievement of national and international goals in flood mitigation (i.e., MDGs in
the first line). The case study uses the national disaster databases produced bydifferent concerned agencies in Japan such as the Ministry of Land, Infrastructure
and Transport (MLIT), the Japan Meteorological Agency, the Statistical Survey
Department, the Statistics Bureau, and the Ministry of Public Management, Home
Affairs, Posts and Telecommunications, to site only few.
The analysis focuses on flood disasters and reported socio-economic impacts. The
data are analyzed and processed on a yearly basis for the period 1980 to 2000.
Defining target indicators (e.g., reduce inundated area, reduce economic losses andreduce property damages), the modeling aims to explain the risk target to be reduced
as functional relation of the stressors and determinants (also called indicators)
identified to play a weighted role in influencing both the vulnerability and resiliencyof the system (e.g., social and physical structure of the country or river basin) topositively respond to the mitigation actions. Despite a number of challenges toovercome, the methodology aims not only at evaluating the effectiveness ordeficiency of applied policies but furthermore advises on the immediate and future
actions necessary to be undertaken by decision makers in order to ensure progress
toward the defined goals and mitigate risk from water hazards (see Merabtene et al.
2004).

89

87

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

1992

1991

1990

1989

1988

1987

1986

1985

1984

1983

1982

1981

Figure 5.5. Selected indicators for PWRI Flood Risk Index to assess policy effectiveness in flood mitigation.

Historical trends in standarized form of PWRI selected indicators: Japan Case Study, 5 years moving average.

1993

1980

Perfomance Indicator (Budget allocation for flood mitigation)

1994

Determinant Indicator (Urbanization)

1995

Determinat indicator (Precipitation)

1996

Policy objetive indicator (reduce intensity of flood damage to property)

1997

Policy objective indicator (Reduce total economic loss)

1998

Policy objective indicator (Reduce total inundated area)

2000

1999

Several ways of analysis are necessary in order to understand the interrelationships
between all factors that determine the vulnerability and resiliency of a society toeach type of water-related disasters. The analysis is even more complex if all
playing factors including environmental and ecological stressors are integrated as
meant by the philosophy of integrated water management. Figure 5.5 not only showsthe effectiveness of decades of progress in flood mitigation in Japan but also brings
about the complex interaction between flood risk determinants (such as hydrologicaland social conditions) and flood risk reduction actions (such as budget allocation forflood mitigation).
The figure also stresses the importance to deeply analyze the real cause of disasters.
To this end we it is imperative to maintain a coherent database on every single water
hazard along consistent information on water hazard/risk determinants andmitigation responses (from legislation to action). This is important because an
integrated and well designed water-related disasters database can help us leverage
the disaster information amassed from various sources and transform our data into a
strategic decisions resource. In other words, creating a well-designed andstandardized database will give us true understanding of the complex riskmechanism underlying each type of water-related disaster and will lead us to define
more reflective and sustainable disaster mitigation strategies. From this objective
point of view, it is clear that current disaster databases are not adequately organized
or designed to allow undertaking comprehensive water hazard assessment, as of
Figure 5.5 for flood, at the global and regional levels.
The assessment presented in this report recalls the challenges in delineating theassessment of the global and regional trends of water-related disasters and emerging
need to sustain and promote similar eminent initiative such as the EMDAT of
OFDA/CRED but with focus and study-oriented to water-related disasters. It is oneof the goals of the future International Centre for Water Hazards and Risk
Management under the auspices of UNESCO after its establishment to undertakesuch a systematic initiative to build a water hazard database. Nevertheless, we can
not overemphasis that the accomplishment and success of such hardship mission
requires synergic cooperation involving all concerned people and bodies to create asafer world from water-related disasters.

91

Appendix
Appendix

Annex 1: National, Regional and International Disaster Databases
Annex 2: EMDAT Water-related Disaster Glossary
Annex 3: Processed Five-year data series of EMDAT data 1960-2004
Annex 4: Largest Disastrous Events: EMDAT data from 1900 to 2004

Annex 1: National, Regional and International Disaster Databases• DesInventar: DesInventar is a conceptual and methodological development about

disasters of any magnitude and about local, regional and national surrounding
diversity in Latin-America. It is an inventory system, a methodology to registerdata about characteristics and effects of diverse types of disasters, with special
interest in disasters that are invisible from global or national scales. The inventory
allows to watch accumulated data of these invisible disasters at a global or
national scale. DesInventar disaster database in managed by the Social Studies
Network for Disaster Prevention in LatinAmerica (LA RED), Further details arefound at http://www.desinventar.org/desinventar.html.
• ADRC Natural Disaster Data Book: The Asian Disaster Reduction Center(ADRC) maintains a Disaster information database and publishes a yearly
analytical review under the title “Natural Disaster Data Book”. The disasters
entries in the data book are enhanced by the use of the Global Identification
Number (GLIDE Number). The GLIDE initiative of ADRC was shared andpromoted by the Center for Research on the Epidemiology of Disasters (CRED),UCL University, Belgium, OCHA/ReliefWeb, OCHA/FSCC, ISDR, UNDP, WMO,
IFRC, OFDA-USAID, FAO, LA-RED and The Word Bank (Araki and Murata
2002 and 2003). Further information about GLIDE initiative can be found at
www.glidenumber.net.
• Relief Web: “ReliefWeb is the world’s leading on-line gateway to information(documents and maps) on humanitarian emergencies and disasters. An
independent vehicle of information, designed specifically to assist theinternational humanitarian community in effective delivery of emergency
assistance, it provides timely, reliable and relevant information as events unfold,while emphasizing the coverage of "forgotten emergencies" at the same time.
ReliefWeb was launched in October 1996 and is administered by the UN Officefor the Coordination of Humanitarian Affairs (OCHA).” For further information
on how disaster information is handled by ReliefWeb see http://www.reliefweb.int.
• NatCat of Munich Re Group: “NatCatSERVICE® is a product that Munich Re

launched in 1974. NatCatSERVICE® is an information and service package
devoted to natural catastrophes. At its centre is a comprehensive database of loss
events which can be used to perform complex analyses. It contains more than
20,000 entries on material and human losses caused by natural catastrophes
worldwide. This data represents an important resource for the insurance sector andinternational research institutions. Insurers around the world can access details andtrends concerning the various types of loss event.” (Munich Re Group, 2003).

95

• Sigma of Swiss Re: “Swiss Re approached their database in a similar fashion to

Munich Re. Swiss Re devoted somewhat less resources to their database than
Munich Re but used these slightly differently by focusing on a number of annual
publications. The publications provide international insurance markets withanalyses of market trends and forecasts and summaries of prevailing premium/loss
volumes. The most recognized of these publications was the annual Sigma Reportof global disaster losses produced in 7 languages. Whilst, every effort is made toensure consistency and reliability of data, Sigma does not claim to be fullycomprehensive. In a brief and limited data comparison between Swiss Re and
CRED, approximately 40% of entries were found to be identical to CRED's
reports.” (ProVention 2001).
• The Natural Disaster Reference Database (NDRD): NDRD is a bibliographic

database on research, programs, and results which relate to the use of satellite
remote sensing for disaster mitigation. The NDRD was compiled and abstracted
from articles published from 1981 though January 2000. Major sources for thecontents of this database were the NASA RECON and ISI Current Contents
databases. This database focuses on the nexus of hazards and satellite remotesensing as well as models and process studies through which these can be brought
together. Although the NDRD is no longer updated, it remains on-line as a useful
resource for disaster researchers worldwide and as a legacy web site of the Earth
Sciences Directorate, NASA Goddard Space Flight Center located in Greenbelt,
Maryland, USA. (for further details see http://ndrd.gsfc.nasa.gov).

96

Annex 2: EMDAT Water-related Disaster Glossary
Definitions are from: International Agreed Glossary of Basic Terms Related toDisaster Management (1992) UN-DHA, IDNDR, Geneva, 83 pages. For non
water-related Glossary visit EMDAT web page at http://www.EMDAT.net.
- Avalanche: Rapid and sudden sliding and flowage of masses of usually unsorted
mixtures of snow/ice/rock material (in EMDAT, «avalanche» is a disaster subset
of disaster type «slide»).
- Collapse: Accident involving the collapse of building or structure. Can either
involve industrial structures (in EMDAT referred to as «Ind:Collapse» and forms
a disaster subset of disaster type «industrial accident») or domestic /non-industrial structures (in EMDAT referred to as «Misc: Collapse» and forms
a disaster subset of disaster type «miscellaneous accident»).
- Crop failure: Abnormal reductions in crop yield such that is insufficient to meetthe nutritional or economic needs of the community (in EMDAT, «crop failure»is a disaster subset of disaster type «famine»).
- Cyclone: Large-scale closed circulation system in the atmosphere above the Indian
Ocean and South Pacific with low barometric pressure and strong winds thatrotate clockwise. Maximum wind speed of 64 knots or more [See «hurricane»
for the western Atlantic and eastern Pacific and «typhoon» for the western
Pacific]. (in EMDAT, « cyclone » is a disaster subset of disaster type «wind
storm»).
- Drought: Period of deficiency of moisture in the soil such that there is inadequate
water required for plants, animals and human beings.
- El Niño («little child» in Spanish): Anormalous warming of ocean water resulting
from the oscillation of current in the South Pacific, usually accompanied byheavy rainfall in the coastal region of Peru and Chile, and reduction of rainfall inequatorial Africa and Australia.
- Epidemic: Either an unusual increase in the number of cases of an infectious
disease, which already exists in the region or population concerned; or theappearance of an infection previously absent from a region (in EMDAT the
epidemic disease in included as a disaster subset).
- Famine: Catastrophic food shortage affecting large numbers of people due toclimatic, environmental and socio-economic reasons (in EMDAT, famine canhave four disaster subsets: «crop failure», «food shortage» and «drought»).
- Flood: Significant rise of water level in a stream, lake, reservoir or coastal region.

97

- Food shortage: Lack of alimentation bases (in EMDAT, «food shortage» is adisaster subset of disaster type «famine»).
- Hazard: Threatening event, or probability of occurrence of a potentially damaging
phenomenon within a given time period and area.
- Hurricane: disaster subset of disaster type «wind storm»Large-scale closed
circulation system in the atmosphere above the western Atlantic with low
barometric pressure and strong winds that rotate clockwise in the southernhemisphere and counter-clockwise in the northern hemisphere. Maximum windspeed of 64 knots or more.
- La Niña (« little girl » in Spanish): It is essentially the opposite of El Niño. The
ocean becomes much cooler than normal. Although, La Niña is not as wellunderstood as El Niño, it is thought to occur due to an increase in the strength of
the trade winds. This increases the amount of cooler water that upwells toward
the West Coast of South American and reduces water temperatures.
(Environnement Canada).
- Landslide: In general, all varieties of slope movement, under the influence ofgravity. More strictly refers to down-slope movement of rock and/or earth
masses along one or several slide surfaces (in EMDAT, « landslide » is adisaster subset of disaster type « slide »).
- Slide: Disaster type term used in EMDAT comprising the two disaster subsets«avalanche» and «landslide».
- Storm: Wind with a speed between 48 and 55 knots; (in EMDAT, «storm» is adisaster subset of the disaster type «wind storm»).
- Tidal wave: Abrupt rise of tidal water (caused by atmospheric activities) moving
rapidly inland from the mouth of an estuary or from the coast (in EMDAT,« tidal wave » is a disaster subset of the disaster type «wave/surge»)(OFDA).
- Tornado: Violently rotating storm diameter; the most violent weather
phenomenon. It is produced in a very severe thunderstorm and appears as afunnel cloud extending from the base of a cumulonimbus to the ground (inEMDAT, « tornado » is a disaster subset of the disaster type « wind storm »).
- Tropical storm: Generic term for a non-frontal synoptic scale cyclone originatingover tropical or sub-tropical waters with organised convection and definite
cyclonic surface wind circulation (in EMDAT, « tropical storm » is a disaster
subset of the disaster type « wind storm »).
- Tsunami (« wave in the port » in Japanese): Series of large waves generated bysudden displacement of seawater (caused by earthquake, volcanic eruption orsubmarine landslide); capable of propagation over large distances and causing a98

destructive surge on reaching land. The Japanese term for this phenomenon,
which is observed mainly in the Pacific, has been adopted for general usage (inEMDAT, « tsunami » is a disaster subset of the disaster type « wave/surge »).
- Typhoon: Large-scale closed circulation system in the atmosphere above thewestern Pacific with low barometric pressure and strong winds that rotate
clockwise in the southern hemisphere and counter-clockwise in the northernhemisphere. Maximum wind speed of 64 knots or more. (in EMDAT,« typhoon » is a disaster subset of disaster type « wind storm »).
- Wave/surge: Disaster type term used in EMDAT comprising the two disaster
subsets « tsunami » and « tidal wave ».
- Wind storm: Disaster type term comprises the following disaster subsets cyclone,
hurricane, storm, tornado, tropical storm, typhoon, winter storm.
- Winter storm: Snow (blizzard), ice or sleet storm; (in EMDAT, « winter storm »is a disaster subset of the disaster type « wind storm »).
Other General Related Glossary to EMDAT:- Disaster: Situation or event, which overwhelms local capacity, necessitating arequest to national or international level for external assistance (definition
considered in EMDAT); An unforeseen and often sudden event that causes greatdamage, destruction and human suffering. Though often caused by nature,disasters can have human origins. Wars and civil disturbances that destroy
homelands and displace people are included among the causes of disasters. Other
causes can be: building collapse, blizzard, drought, epidemic, earthquake,
explosion, fire, flood, hazardous material or transportation incident (such as achemical spill), hurricane, nuclear incident, tornado, or volcano (Disaster
Relief).
- Emergency: Sudden and usually unforeseen event that calls for immediate
measures to minimize its adverse consequences.
- Hazard: Threatening event, or probability of occurrence of a potentially damaging
phenomenon within a given time period and area.
- Risk: Expected losses (of lives, persons injured, property damaged and economic
activity disrupted) due to a particular hazard for a given area and reference
period. Based on mathematical calculations, risk is the product of hazard andvulnerability.
- Vulnerability: Degree of loss (from 0% to 100%) resulting from a potential
damaging phenomenon.

99

Annex 3: Processed Five-year data series of EMDAT data 1960-2004- The table hereafter reports the EMDAT water-related disasters database used.
- The database is categorized by: Events: Flood, Windstorm, Slide, Wave & surge, Drought, Famine,
Water-related epidemic, and Water-related technologic disasters (traffic
accident in particular); and by
 Continent: Africa, Asia, Americas, Europe, and Oceania- Each field of data reports the accumulated value over five year period of
successive data.
- From the 42 fields originally available in EMDAT the four related to this project
are reported are number of events, dead people, affected people and economic
damage.
- Empty field: refers that none data were reported for the concerned 5 years period
Tables Legend:• no_Disasters: Total of number of water-related disasters for the 5 year period ofdata;• no_Killed: Total of number of people killed within the 5 year period of data;• Total_Affected: Total affected people (including injured and homeless);• Damage_US$: Actual economic damage in US$ within the 5 year period of data;100

Flood:AfricaEvent
Period1900-1959
1960-1964
1965-19691970-1974
1975-1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Total (1960-2002)
Total (1900 to 2004)

no_Disasters
6
10
14
13
29
19
46
42
103
172
448
454

no_Killed
3237
534
809
705
623
460
1238
2049
5208
3955
15581
18818

Flood
Total_Affected01303107367312974684
1624842146771960109132361934
11887220
882047936014832
36014832

Damage_US$
0300041537079250
17220092406
8429054388292258951117078
3386933
3386933

no_Disasters
65
30
49
36
68
110
117
157
166
261
994
1059

no_Killed6579132
15599
10279
35426
9309
21640
23083
20195
27882
16941
1803546759486

Flood
Total_Affected
58360534
331742134650437
70892281
119539124
161328823
344149344
567632267
841000440
621308929
2763819066
2822179600

Damage_US$
1450000
6000
629811
1755357
2095521573101018191764
33641501
79089067
31178343
172318374
173768374

Asia
Event
Period1900-1959
1960-1964
1965-19691970-1974
1975-1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Total (1960-2002)
Total (1900-2004)

Americas
Event
Period1900-1959
1960-1964
1965-19691970-1974
1975-1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Total (1960-2002)
Total (1900 to 2004)

no_Disasters
29
9
34
41
41
66
97
102
94
170
654
683

no_Killed
45678
1195
2782
2195
1144
4228
3068
1844
32559
5209
54224
99902

101

Flood
Total_Affected
10900012000017577476669785353574013184145
13714920
31829085593659348586051244764
51353764

Damage_US$
3162230
8205006269781237679
7899007659200
5038190
19305370
13847287
437462053699724
56861954

Europe
Event
Period1900-1959
1960-1964
1965-19691970-1974
1975-1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Total (1960-2002)
Total (1900 to 2004)

no_Disasters
24
4
6
7
17
32
22
42
65
132
327
351

no_Killed
4280
495
896
1085
229
350
216
620
814
601
5306
9586

Flood
Total_Affected
3063502430001962001541005
108687082824734580
1520147
30195962447298
10916943
11223293

Damage_US$
6700001426002350000
1273300
8301005602500
3414800
31795700
12230650
28074297
85713947
86383947

Oceania
Event
Period1900-1959
1960-1964
1965-19691970-1974
1975-1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Total (1960-2002)
Total (1900 to 2004)

no_Disasters

no_Killed

2
1

91
1

3
10
11
18
9
13
22
87
89

53
7
94
68
13
11
22
269
360

Flood
Total_Affected
0
18000
12000
12975
25095
219912
17093565251
27991
552159552159102

Damage_US$
0
1100
96972
93080
23441517323328080055452871748321516112151611

Windstorm:
AfricaEvent
Period1900-1959
1960-1964
1965-19691970-1974
1975-1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Total (1960-2002)
Total (1900 to 2004)

no_Disasters
5
1
4
3
14
20
17
16
21
48
144
149

Wind Storm
no_Killed
Total_Affected
833
0
42
0
110
1415791632545072252
1628592704
1910950384
258444554
3324048563
849871822
30430993594
13701655
4427
13701655

Damage_US$
0
0
13300
23820
774600114025028196154356560600035022237337183733718

no_Disasters
126
45
50
64
82
108
122
181
124
194
970
1096

Wind Storm
no_Killed
Total_Affected
410733968411044121
9477059
65867
19746665
32325421303460
21077
23574046
12631
38240203
22327
91342961
157090106438734
27457
89201795
6512
162968469
680336562293392
1091069571977502

Damage_US$
1280000
24505026748189148931538382448374565924629030494
21037554
37691474
100425000
101705000

Asia
Event
Period1900-1959
1960-1964
1965-19691970-1974
1975-1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Total (1960-2002)
Total (1900 to 2004)

103

Americas
Event
Period1900-1959
1960-1964
1965-19691970-1974
1975-1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Total (1960-2002)
Total (1900 to 2004)

Wind Storm
no_Disasters
114
37
44
27
36
64
101
119
146
153
727
841

no_Killed
37875
9185
3149
9161
2984
3603
1478
2053
21382
3870
56865
94740

Total_Affected
38382091868
65250892270623114831474004
4127618293711211241455
13140861
36899615
37283435

Damage_US$
3899000
22973903718350
43315803893950
10908655
13887391
50501525
52671596
43915942
186126379
190025379

1900-1959

no_Disasters
10

no_Killed
4300

Total_Affected0

Damage_US$
80000

1960-1964
1965-19691970-1974
1975-1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Total (1960-2002)
Total (1900 to 2004)

3
8
13
10
38
26
39
30
63
230
240

390
85
187
83
517
172
457
447
271
2609
6909

12000
3900
5200
19
71962
0
1022071379342128276977736270773627060220053600
9802001301000
3096100
5222600
16497300
13524741
1075198
42352939
42432939

no_Disasters
20
4
15
15
27
29
31
35
26
41
223
243

Wind Storm
no_Killed
Total_Affected
538
2400
261
12000
168
107204173
1740908575005
46435660250
461166
1263481917146
1096504103
1621401358
6005686
1896
6008086

EuropeWind Storm

Event
PeriodOceania
Event
Period1900-1959
1960-1964
1965-19691970-1974
1975-1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Total (1960-2002)
Total (1900 to 2004)

104

Damage_US$
4450250541
3838
13114111458504
2891278503672545173
1907995
58090091978569202306

Slides:
AfricaEvent
Period1900-1959
1960-1964
1965-19691970-1974
1975-1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Total (1960-2002)
Total (1900 to 2004)

no_Disasters

no_Killed

SlidesTotal_Affected

Damage_US$

2

308

1436

0

2
3
4
3
8
22
22

47
31
84
141
110
721
721

12416
1648
1025
2500
715
19740
19740

0
0
0
0
0
0
0

no_Disasters
11
4
2
9
10
16
29
32
46
66
214
225

no_Killed
1978
414
1064
513
738
1227
1923
1788
3254
2943
13864
15842

Asia
Event
Period1900-1959
1960-1964
1965-19691970-1974
1975-1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Total (1960-2002)
Total (1900 to 2004)

105

SlidesTotal_Affected
0
0
0
1113
80125
3150
2571402215196132850385683750563265056326

Damage_US$0000100000013413025904500
125798534229534229

Americas
Event
Period1900-1959
1960-1964
1965-19691970-1974
1975-1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Total (1960-2002)
Total (1900 to 2004)

no_Disasters
18
3
8
17
4
9
22
16
22
22
123
141

no_Killed
6523
2071
983
5709
103
688
1769
972
1051
691
14037
20560

SlidesTotal_Affected2069
04000022
16028
116
40
11930232784946757
15698246670964669165

Damage_US$0200000
27
21700
0
3000
800
9154000
86000
1226927
1226927

no_Disasters

no_Killed
12528
1334
261
183
120
133
351
832
234
182
3630
16158

SlidesTotal_Affected
380
0
22
85
50
7035
16841
2834
11278
3011
41156
41536

Damage_US$
20000
0
0
0
11000
7000009500002600
22089
01685689
1705689

no_Killed

SlidesTotal_Affected

Damage_US$

EuropeEvent
Period1900-1959
1960-1964
1965-19691970-1974
1975-1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Total (1960-2002)
Total (1900 to 2004)

8
2
4
6
6
10
10
10
12
7
67
75

Oceania
Event
Period1900-1959
1960-1964
1965-19691970-1974
1975-1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Total (1960-2002)
Total (1900 to 2004)

no_Disasters

1
2
0
3
1
5
3
15
15

100
13
0
87
200
79
49
528
528

0
600
0
4000
5000
620
795
11015
11015

106

0
2466
0
0
0
0
0
2466
2466

Wave and Surge:
AfricaEvent
Period1900-1959
1960-1964
1965-19691970-1974
1975-1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Total (1960-2002)
Total (1900 to 2004)

Wave / Surge
Total_Affected

no_Disasters

no_Killed

Damage_US$

1

0

2000

50

4
5
5

164
164
164

54478
56478
56478

30000
30050
30050

no_Disasters
7
2
2

no_Killed
7319
170
264

1
2
1
3
4
11
26
33

539
0
11
100
420
280882282386289705Asia
Event
Period1900-1959
1960-1964
1965-19691970-1974
1975-1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Total (1960-2002)
Total (1900 to 2004)

107

Wave / Surge
Total_Affected0097

Damage_US$
0
50000
0

23
818
2000

0
2330
0

29200
245979124919292491929267
7765200
78177977817797

Americas
Event
Period1900-1959
1960-1964
1965-19691970-1974
1975-1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Total (1960-2002)
Total (1900 to 2004)

Wave / Surge
Total_Affected
00

no_Disasters
4
1

no_Killed
312
61

2
1
4
8

15
0
76
388

no_Killed
1

Wave / Surge
Total_Affected
Damage_US$
2300
0

no_Disasters
0

1

11

2

0

1
2

11
2311

2
2

0
0

Wave / Surge
no_Disasters2

no_Killed
61

Total_Affected0

Damage_US$
0

1

200

0

0

1

2182

9867

0

2
4

2382
2443

9867
9867

0
0

1124
1720
2844
2844

Damage_US$
900
0

0
0
0
900

EuropeEvent
Period1900-1959
1960-1964
1965-19691970-1974
1975-1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Total (1960-2002)
Total (1900 to 2004)

Oceania
Event
Period1900-1959
1960-1964
1965-19691970-1974
1975-1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Total (1960-2002)
Total (1900 to 2004)

108

Drought:
AfricaPeriod1900-1959
1960-1964
1965-19691970-1974
1975-1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004

Event
no_Disasters
96
2
25
47
32
90
33
40
32
65

no_Killed
17000050
20003190000553500
1017
0
12
895

Drought
Total_Affected
32000
7050004118483
12506595
11780400
65260840
28027000
71575007
20586349
102583908

Total
Total

366
462

8764741046474317143582
317175582

no_Disasters
5
5
10
12
17
17
15
12
19
53
160
165

no_Killed
625000001508000
0
81
510
1894
0
680
243
1511408
7761408

Drought
Total_Affected
20000000
1291000
104957944
207875000
209772885
227502000
357737000
28746385
46049000
586149800
1770081014
1790081014(1960-2002)(1900 to 2004)

Damage_US$
0
0
22500
1108400
4015002501434
1463200291939044720934472093

Asia
Event
Period1900-1959
1960-1964
1965-19691970-1974
1975-1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Total (1960-2002)
Total (1900 to 2004)

109

Damage_US$0012731822350020120009428871202003106325
10089546
14810976
14810976

Americas
Event
Period1900-1959
1960-1964
1965-19691970-1974
1975-1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Total (1960-2002)
Total (1900 to 2004)

no_Disasters
20
3
7
5
7
19
11
9
15
32
108
128

no_Killed
0
0
0
0
0
20
0
0
0
54
74
74

Drought
Total_Affected
250000613400105482110837000
5450000
23992049
823000371316012298200
2932400
61714030
61964030

Damage_US$
0
0
71500
62100
3550000
3319000
1559400
1981000
2459000
50553913507539
13507539

no_Disasters
1

no_Killed
1200000

Drought
Total_Affected
5000000

Damage_US$
0

1
7

0
0

0
0

0
3055000

8
4
9
29
30

0
0
0
0
1200000

3200000
6000000
1062575
10262575
15262575

2188600
7700000
1368000
14311600
14311600

no_Disasters

no_Killed

1

600

0

0

4
4

0
0

0
15100006030000

4
8
1
22
22

0
88
0
688
688

5250000
283263508233635
82336353623000
1053000
30000011006000
11006000EuropeEvent
Period1900-1959
1960-1964
1965-19691970-1974
1975-1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Total (1960-2002)
Total (1900 to 2004)

Oceania
Event
Period1900-1959
1960-1964
1965-19691970-1974
1975-1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Total (1960-2002)
Total (1900 to 2004)

110

Drought
Total_Affected Damage_US$

Famine:AfricaEvent
Period1900-1959
1960-1964
1965-19691970-1974
1975-1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Total (1960-2002)
Total (1900 to 2004)

FamineTotal_Affected0

no_Disasters
1

no_Killed
26000

2
3
9
11
17
5
47
48

0
15
5437
2443
3644
0
11539
37539

no_Disasters

no_Killed

10300000

0

5
11
3
20
20

760
13750082500
2207602207601812000
11988000
4900000
19000000
19000000

4399
0
0
4399
4399

30000013123000
893726715203900
12339134
1080000
50983301
50983301

Damage_US$
0

0
0
0
0
89000
0
89000
89000

Asia
Event
Period1900-1959
1960-1964
1965-19691970-1974
1975-1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Total (1960-2002)
Total (1900 to 2004)

111

FamineTotal_Affected

Damage_US$

Americas
Event
Period1900-1959
1960-1964
1965-19691970-1974
1975-1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Total (1960-2002)
Total (1900 to 2004)

FamineTotal_Affected

no_Disasters

no_Killed

Damage_US$

1

0

0

50

1
1
1
4
4

0
0
0
0
0

1000000
0
3000
1003000
1003000

0
0
0
50
50

EuropeEvent
Period1900-1959
1960-1964
1965-19691970-1974
1975-1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Total (1960-2002)
Total (1900-2004)

FamineTotal_Affected0

no_Disasters
1

no_Killed
5000000

Damage_US$
0

1

0

10000

0

1
3

0
10000000

10000
10000

0
0

Oceania
Event
Period
１９00-1959
1960-1964
1965-19691970-1974
1975-1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Total (1960-2002)
Total (1900 to 2004)

FamineTotal_Affected

no_Disasters

no_Killed

1

0

0

0

1
1

0
0

0
0

0
0

112

Damage_US$Epidemic water-related:
AfricaEvent
Period1900-1959
1960-1964
1965-19691970-1974
1975-1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Total (1960-2002)
Total (1900 to 2004)

1

Epidemic Water-related
no_Killed
Total_Affected
10276
0

0

1
4
7
7
22
23
83
111
258
259

0
2932
576
1687
6422
14618
15365
6218
47818
58094

0
0
0
0
4692
0
0
38
4730
4730

no_Disasters
2
2
5

Epidemic Water-related
no_Killed
Total_Affected
800000
0
598
10848
466
205118

Damage_US$
0
0
0

21
10
14
22
40
30
144
2900

1512
5324
2778
7827
3783
1304
23592
7851533

0
0
0
0
0
0
0
508187423

no_Disasters

0
13476
16386
12376
62490
6813919
1056966
100355389791668979166

Damage_US$

Asia
Event
Period1900-1959
1960-1964
1965-19691970-1974
1975-1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Total (1960-2002)
Total (1900 to 2004)

113

69371
1783751169700
2137951465221
2272144463798
7964553444

Americas
Event
Period1900-1959
1960-1964
1965-19691970-1974
1975-1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Total (1960-2002)
Total (1900 to 2004)

no_Disasters
2
1

Epidemic Water-related
no_Killed
Total_Affected
46
0
0
2724

Damage_US$
0
0

3
1
3
22
24
8
62
64

0
300
37
12721
194
82
13334
13380

0
0
0
0
0
0
0
0

no_Disasters
1

Epidemic Water-related
no_Killed
Total_Affected018000000

Damage_US$
0

1
2
1
2
2
3
5
16
17

0
0
26
45
91
18
0
180
180

0
0
0
0
0
0
0
0
0

407
0
34892
4004354597792076951105932
1105932

EuropeEvent
Period1900-1959
1960-1964
1965-19691970-1974
1975-1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Total (1960-2002)
Total (1900 to 2004)

0100000
16
294
1333
554
1106
10330318103303

Oceania
Event
Period1900-1959
1960-1964
1965-19691970-1974
1975-1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Total (1960-2002)
Total (1900 to 2004)

no_Disasters

Epidemic Water-related
no_Killed
Total_Affected

Damage_US$

1

17

352

0

1

7

1200

0

3
5
5

25
49
49

4086
5638
5638

0
0
0

114

Technologic water-related:
AfricaEvent
Period1900-1959
1960-1964
1965-19691970-1974
1975-1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Total (1960-2002)
Total (1900 to 2004)

no_Disasters

Technological Water-related
no_Killed
Total_Affected

Damage_US$

1
1

0
100

200
0

0
0

6
14
34
38
87
181
181

596
1495
3033
3893
5048
14165
14165

0
0
50692
0
940
51832
51832

0
0
0
0
0
0
0

Asia
Event
Period1900-1959
1960-1964
1965-19691970-1974
1975-1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Total (1960-2002)
Total (1900 to 2004)

7

Technological Water-related
no_Killed
Total_Affected
6146
0

0

1
3
2
17
100
95
77
87
382
3143

39
360
700
2553
14076
5929
4806
6117
34580
7068667

0
0
0
0
0
0
0
0
0
508187423

no_Disasters

115

0
0
0
907
290
188
53
2029
3467
7960093113

Damage_US$

Americas
Event
Period1900-1959
1960-1964
1965-19691970-1974
1975-1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Total (1960-2002)
Total (1900 to 2004)

no_Disasters
12

Technological Water-related
no_Killed
Total_Affected
5564
16600

0

1
1
2
4
21
18
20
25
92
104

90
30
43
644
1021
3080
1042
597
6547
12111

0
0
0
0
0
0
0
0
0
0

no_Disasters
4
1
1
2
1
1
11
18
12
33
80
84

Technological Water-related
no_Killed
Total_Affected
2563
2200
13
0
39
0
81
0
50
0
400
0
1017
498
1575
219
609
38
944
201
4728
956
7291
3156

no_Disasters

Technological Water-related
no_Killed
Total_Affected

500
0
0
19
0
20
112
320
971
17571

Damage_US$

EuropeEvent
Period1900-1959
1960-1964
1965-19691970-1974
1975-1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Total (1960-2002)
Total (1900 to 2004)

Damage_US$
0
0
0
0
0
0
0
0
0
0
0
0

Oceania
Event
Period1900-1959
1960-1964
1965-19691970-1974
1975-1979
1980-1984
1985-1989
1990-1994
1995-1999
2000-2004
Total (1960-2002)
Total (1900 to 2004)

Damage_US$

3

86

24

0

2
5
5

181
267
267

0
24
24

0
0
0

116

Annex 4: Largest Disastrous Events: EMDAT data from 1900 to 2004
A: Top 100 disastrous events in terms of killed people
year
1932
1931
1928
1917
1959
1920
1943
1909
1942
1907
1900
1921
1939
1920
1920
1965
1966
1967
1926
1918
1970
1924
1984
1901
1974
1984
1935
1991
1922
1911
1923
1973
1984
1942
1935
1910
1949
1912
1918
1942

dis_type
dis_subset
FamineFood shortage
Flood
Flood
Drought
Drought
EpidemicUnknown
Flood
Flood
Epidemic
PlagueFamineFood shortage
Epidemic
PlagueDrought
Drought
Epidemic
PlagueDrought
Drought
Drought
Drought
Flood
Flood
Epidemic
Diarrhoeal/EntericDrought
Drought
Drought
Drought
Drought
Drought
Drought
Drought
Epidemic
Small pox
Epidemic
Respiratory
Wind Storm Cyclone
Epidemic
Diarrhoeal/EntericDrought
Drought
EpidemicUnknown
Drought
Drought
Drought
Drought
Flood
Flood
Wind Storm Cyclone
Wind Storm Typhoon
Flood
Flood
Epidemic
Meningitis
Drought
Drought
Drought
Drought
Wind Storm Cyclone
Wind Storm Cyclone
Epidemic
PlagueFlood
Flood
Wind Storm Typhoon
Epidemic
Respiratory
Wind Storm Cyclone

country_name
Soviet Union
China P Rep
China P Rep
Soviet Union
China P Rep
India
Bangladesh
China P Rep
India
India
India
Soviet Union
China P Rep
India
China P Rep
India
India
India
India
Bangladesh
Bangladesh
India
Ethiopia
UgandaEthiopia
Sudan
China P Rep
Bangladesh
China P Rep
China P Rep
Niger
Ethiopia
Mozambique
Bangladesh
India
China P Rep
China P Rep
China P Rep
CanadaIndia

117

no_killed total_affected
5,000,000
03,700,000
28,500,000
3,000,000
02,500,000
02,000,000
02,000,000
01,900,000
01,500,000
01,500,000
01,300,000
01,250,000
01,200,000
5,000,000
500,0000
500,0000
500,000
20,000,000
500,000
100,000,000
500,0000
500,000
0423,000
0393,0000
300,000
3,648,000
300,0000
300,000
7,750,000
200,0000
200,0000
150,000
8,400,000
142,000
10,030,000
138,866
15,438,849
100,0000
100,0000
100,0000
100,000
3,000,000
100,000
2,466,000
61,000060,000060,000057,000050,000050,0002,000,000
40,000
0

year
1949
1965
1954
1999
1946
1974
1995
1996
1997
1998
1999
1931
1920
1910
1911
1912
1913
1974
1933
1998
1977
1965
1949
1963
1937
1961
1900
1947
1906
1965
1985
1960
1999
1971
1974
1991
1966
1988
1991
1964
1918
1980
1900
1991
1989

dis_type
Flood
Wind Storm
Flood
Flood
Drought
Flood
FamineFamineFamineFamineFamineFamineDrought
Drought
Drought
Drought
Drought
Drought
Flood
Wind Storm
Wind Storm
Wind Storm
SlidesWind Storm
Wind Storm
Wind Storm
Drought
Epidemic
Wind Storm
Wind Storm
Wind Storm
Flood
Wind Storm
Wind Storm
Wind Storm
EpidemicDrought
Epidemic
Epidemic
Wind Storm
Epidemic
Flood
Wind Storm
Wind Storm
Faminedis_subset
Flood
CycloneFlood
Flood
Drought
Flood
Food shortage
Food shortage
Food shortage
Food shortage
Food shortage
Food shortage
Drought
Drought
Drought
Drought
Drought
Drought
Flood
Hurricane
CycloneCycloneLandslide
CycloneTyphoonCycloneDrought
Diarrhoeal/EntericTyphoonCycloneCycloneFlood
CycloneCycloneHurricane
Diarrhoeal/EntericDrought
Meningitis
Diarrhoeal/EntericTyphoonRespiratory
Flood
Hurricane
TyphoonFood shortage

country_nameno_killed total_affected
Guatemala
40,0000
Bangladesh
36,00015,600,000
China P Rep
30,0000Venezuela
30,000483,635
Cape Verde Is
30,0000
Bangladesh
28,70038,000,000
Korea Dem P Rep
27,5001,000,000
Korea Dem P Rep
27,5001,000,000
Korea Dem P Rep
27,5001,000,000
Korea Dem P Rep
27,5001,000,000
Korea Dem P Rep
27,5001,000,000
Niger
26,0000Cape Verde Is
24,0000
Niger
21,2508,000
Niger
21,2508,000
Niger
21,2508,000
Niger
21,2508,000
Somalia
19,000230,000
China P Rep
18,0003,600,000
Honduras
14,6002,112,000
India
14,204
14,469,800
Bangladesh
12,0470
Soviet Union
12,0000
Bangladesh
11,5001,000,000
Hong Kong (China)
11,0000
Bangladesh
11,0000Cape Verde Is
11,0000
Egypt
10,2760Hong Kong (China)
10,0000
Pakistan
10,0000
Bangladesh
10,0001,810,000
Bangladesh
10,000
0
India
9,843
12,628,312
India
9,658
6,900,000
Honduras
8,000
600,000
Peru
8,000
0
Indonesia
8,000
204,000
Ethiopia
7,385
41,139Nigeria
7,289
10,000Viet Nam
7,000
700,000
New Zealand
6,700
0China P Rep
6,200
67,000
United States
6,000
0Philippines
5,956
647,254
Mozambique
5,200
0

118

year
1960
1959
1927
1941
1943
1963
1941
1968
1951
1996
1917
1952
1940
1941
1942

dis_type
dis_subset
Wind Storm Cyclone
Wind Storm Typhoon
Wind Storm Typhoon
Wind Storm Cyclone
Wind Storm Cyclone
Wind Storm Hurricane
SlidesLandslide
Flood
Flood
Flood
Flood
Epidemic
Meningitis
Wind Storm Typhoon
Wind Storm
Storm
Drought
Drought
Drought
Drought
Drought
Drought

country_nameBangladesh
Japan
China P Rep
Bangladesh
India
Haiti
Peru
India
China P Rep
Burkina Faso
Japan
United Kingdom
Cape Verde Is
Cape Verde Is
Cape Verde Is

no_killed total_affected
5,149
200,000
5,098
1,500,000
5,000
0
5,000
0
5,000
0
5,000
0
5,000
0
4,892
7,500,000
4,800
0
4,071
40,506
4,000
0
4,000
0
4,000
0
4,000
0
4,000
0

B: Top 100 disastrous events in terms of affected peopleyear

dis_type

dis_subset

country_nameno_killed

total_affected

1987
1998
1991
1979
1996
1993
1995
1999
1989
1965
1972
1973
1982
1983
1994
1987
1988
1988
1974
1975
1982
1995
1978
1994
1989

Drought
Flood
Flood
Drought
Flood
Flood
Flood
Flood
Flood
Drought
Drought
Drought
Drought
Drought
Flood
Flood
Flood
Drought
Flood
Flood
Flood
Flood
Flood
Flood
Wind Storm

Drought
Flood
Flood
Drought
Flood
Flood
Flood
Flood
Flood
Drought
Drought
Drought
Drought
Drought
Flood
Flood
Flood
Drought
Flood
Flood
Flood
Flood
Flood
Flood
Storm

India
China P Rep
China P Rep
India
China P Rep
India
China P Rep
China P Rep
China P Rep
India
India
India
India
India
China P Rep
Bangladesh
Bangladesh
China P Rep
Bangladesh
India
India
India
India
China P Rep
China P Rep

300
3,656
1,729
0
2,775
827
1,437
725
2,000
500,000
0
0
0
0
1,001
2,379
2,379
1,400
28,700
350
932
1,479
3,800
258
157

300,000,000
238,973,000
210,232,227
190,000,000
154,634,000
128,000,000
114,470,249
101,024,000
100,010,000
100,000,000
100,000,000
100,000,000
100,000,000
100,000,000
78,974,400
73,000,000
73,000,000
49,000,000
38,000,000
34,000,000
33,500,000
32,704,000
32,000,000
30,547,665
30,007,500

119

year

dis_type

dis_subset

country_nameno_killed

total_affected

1980
1984
1997
1998
1931
1990
1979
1999
1988
1920
1983
1983
1999
1987
1923
1988
1981
1984
1990
1968
1965
1991
1996
1998
1977
1995
1999
1982
1992
1994
1992
1993
1995
1994
1998
1988
1970
1985
1935
1980
1950
1970
1970
1979
1998

Flood
Flood
Flood
Flood
Flood
Flood
Flood
Flood
Flood
Drought
Drought
Drought
Drought
Flood
Epidemic
Flood
Flood
Flood
Flood
Flood
Wind Storm
Wind Storm
Wind Storm
Flood
Wind Storm
Flood
Wind Storm
FamineFlood
Flood
Drought
Flood
Flood
Wind Storm
Wind Storm
Wind Storm
Flood
Flood
Flood
Flood
Flood
Flood
Drought
Drought
Drought

Flood
Flood
Flood
Flood
Flood
Flood
Flood
Flood
Flood
Drought
Drought
Drought
Drought
Flood
Malaria
Flood
Flood
Flood
Flood
Flood
CycloneCycloneTyphoonFlood
CycloneFlood
CycloneDrought
Flood
Flood
Drought
Flood
Flood
TyphoonStorm
Cyclone
Flood
Flood
Flood
Flood
Flood
Flood
Drought
Drought
Drought

India
Bangladesh
India
India
China P Rep
China P Rep
India
India
China P Rep
China P Rep
BrazilBangladesh
China P Rep
India
Soviet Union
India
India
India
China P Rep
Bangladesh
Bangladesh
Bangladesh
China P Rep
Bangladesh
India
Bangladesh
India
Ghana
Pakistan
India
China P Rep
Bangladesh
China P Rep
China P Rep
China P Rep
Bangladesh
India
India
China P Rep
Bangladesh
China P Rep
Bangladesh
BrazilIndia
Brazil

1,600
1,200
1,442
1,811
3,700,000
363
0
229
577
500,000
20
0
0
1,200
0
250
553
245
60
221
36,000138,866
197
140
14,204
250
9,843
0
1,334
2,001
0
162
61
1,174
17
1,000
627
741
142,000
655
500
0
0
0
0

30,000,023
30,000,000
29,259,000
29,227,200
28,500,000
26,130,805
26,000,000
22,120,000
22,000,200
20,000,000
20,000,000
20,000,000
19,000,000
18,000,000
18,000,000
16,500,000
16,000,000
16,000,000
16,000,000
15,889,616
15,600,000
15,438,849
15,005,000
15,000,050
14,469,800
12,656,006
12,628,312
12,500,000
12,324,024
12,060,050
12,000,000
11,469,537
11,100,162
11,001,800
11,000,038
10,568,860
10,351,000
10,225,000
10,030,000
10,000,000
10,000,000
10,000,000
10,000,000
10,000,000
10,000,000

120

year

dis_type

dis_subset

country_nameno_killed

total_affected

1995
1980
1991
1994
1984
1995
1999
1984
1992
1968
1989
1996
1986
1997
1983
1987
1993
1971
1993
1994
1980
1991
1994
1990
1990
1992
1996
1991
1990
1978

Drought
Wind Storm
Drought
Wind Storm
Drought
Flood
FamineDrought
Wind Storm
Flood
Wind Storm
Wind Storm
Flood
Flood
Drought
Drought
Drought
Wind Storm
FamineDrought
Wind Storm
Wind Storm
Epidemic
Wind Storm
Drought
Flood
Flood
Drought
Wind Storm
Drought

Drought
TyphoonDrought
TyphoonDrought
Flood
Crop failure
Drought
Storm
Flood
TyphoonCycloneFlood
Flood
Drought
Drought
Drought
CycloneFood shortage
Drought
TyphoonTyphoon
Malaria
CycloneDrought
Flood
Flood
Drought
TyphoonDrought

China P Rep
Viet Nam
Sudan
China P Rep
Sudan
Bangladesh
Ethiopia
Ethiopia
China P Rep
India
China P Rep
India
China P Rep
China P Rep
Ethiopia
Ethiopia
MalawiIndia
Ethiopia
China P Rep
Viet Nam
Philippines
Kenya
India
Ethiopia
Pakistan
Bangladesh
Ethiopia
Philippines
China P Rep

0
176
0
90
150,000400
0300,000
109
4,892
550
708
233
164
0
0
0
9,658
0
0
132
754
1,000
957
0
221
33
0
748
0

9,060,000
9,027,174
8,600,000
8,488,684
8,400,000
8,000,000
7,767,594
7,750,000
7,700,000
7,500,000
7,002,696
7,000,000
7,000,000
7,000,000
7,000,000
7,000,000
7,000,000
6,900,000
6,700,000
6,690,000
6,624,710
6,547,592
6,500,000
6,500,000
6,500,000
6,184,418
6,163,319
6,160,000
6,159,869
6,000,000

121References
1) Amjad Bhatti, (1999): “International Decade for Natural Disaster Reduction;
Relevance to South Asia”, IDNDR Program Forum, WMO Geneva, 4-9 July
1999.
2) Arakida M. and Murata M. (2003): “Disaster informational common means
with high promptness and reliability: The GLobal unique disaster IDEntifier
number (GLIDE)” in Japanese, Asia Disaster Reduction Center publication.
3) DesInventar, (2005): “Disaster inventory system for Latin America”, Social
Studies Network for Disaster Prevention in LatinAmerica (LA RED),
http://www.desinventar.org. or http://www.desenredando.org.
4) EMDAT, (2005): “The OFDA/CRED international disaster database”,
University Catholic Louvain- Brussels, Belgium, http://www.EMDAT.net.
5) Economic History, (2005): “What is its relative value in US dollars”,
http://eh.net/hmit/compare/.
6) Guha-Sapir D., Hargitt D., and Hoyois P., (2004): “Thirty years of natural
disasters 1974-2003: The Numbers”, Centre for Research on the Epidemiology
of Disasters, UCL Press, pp 76.
7) Guha-Sapir D., and Below R., (2002): “The quality and accuracy of disaster data
A comparative analysis of there global sets”,
http://www.proventionconsortuim.org/files/sapir.pdf.
8) Hoyois P., and Guha-Sapir D., (2004): “Disasters caused by flood : Preliminary
data for a 30 year assessment of their occurrence and human impact”,
International workshop organised by the Tyndall Centre for Climate Change
Research, University of East Anglia, Norwich,18th to 20th July 2004.
9) ISDR, (2004): “Living with risk: A global review of disasters reduction
initiatives”, United Nations Publication, Geneva 2004, pp. 429.
10) LA-RED, (2002): “Comparative analysis of disaster databases”, (LA
RED-OSSO- UNDP) Final report of the Inter-Agency Task Force (IATF) of
ISDR on Risk,
http://www.unisdr.org/unisdr/eng/task%20force/working%20groups/wg3/Comparative%20Analysis%20of%20Disaster%20Database.pdf.
11) Merabtene T., Yoshitani J., and Kuribayashi D., (2004.a): “Managing Flood andWater-related Risks: A challenge for the future”, Paper presented at the special
Session (JS6) on - Basin-wide Policy Scenarios to Secure Sustainability Against
Population Explosion: Strategy to Cope with Water Variability in
Monsoon-Asia Region-, AOGS 2004 Joint 1st Annual Meeting & 2nd APHW
Conference, Singapore 2004.

12312) Merabtene T., Yoshitani J., and Kuribayashi D., (2004.b): “Report on the PWRIInternational Workshop on Water Hazard and Risk Management”, Public Works
Research Institute, 20-22 January 2004,
http://www.unesco.pwri.go.jp/ja/publication/report/jan_20_22_2004_ws/index.htm.

13) Munich Re Group, (2003): “NatCat Service: A guide to the Munich Re databasefor natural catastrophes”, www.munichre.com/publications/302-03901_en.pdf
14) ProVention , (2001): “ProVention Consortium Disaster Database Working
Group Meeting, February 5, 2001”,
www.proventionconsortium.org/files/disastersdb_020501/proceedings_db.pdf.
15) Reliefweb (2000): “Action against hunger withdraws from N. Korea”,
http://www.reliefweb.int/rw/rwb.nsf/AllDocsByUNID/f64f8a57c500b81d85256
8ac005a634d.
16) UNDP, (2004): “A Global report: Reducing Disaster Risk: A challenge fordevelopment”, United Nations Development Programme, pp.149.
17) WCDR, (2005): “Hyogo Framework for Action 2005-2015: Building theResilience of Nations and Communities to Disasters”, World Conference on
Disaster Reduction, 18-22 January 2005, Kobe, Hyogo, Japan,
www.unisdr.org/wcdr.
18) WHO, (2005), World Health Organization, http://www.who.int/en/19) Wisner B., Blaikie P., Terry C., and Davis I., (2004): “At Risk, Natural Hazards,
People's Vulnerability, and Disasters”, Routledge, 2nd Edition.
20) WWAP, (2003) “Water for People Water for life”, the United Nations World
Water Development Report, World Water Assessment Programme (WWAP),UESCO Publishing/Berghahn Books, p.576.

124

Plea