Expert Meeting on Hazard/Disaster DataEU Flood Information

EEA/CRED, Brussels, 19 May 2011

Debarati Guha-SapirDirector, CRED

What is EM-DAT?

International Disaster Database, created in 1988

Project funded by OFDA/USAID, USA

Occurrence , human and economic impacts of over 18,000 natural (62%) and technological disasters (38%) from 1900 to present

Objective: Provide evidence-base to humanitarian and development actors at national and international levels

www.emdat.be

EM-DAT Entry Criteria

10 or more people killed

and/or

100 or more people affected

and/or

Call for international assistance/ declaration of a state of emergency

EM-DAT Methodology

Data is comparable over time and space

Normative rules, clear definition and standard methodology for entering data

Transparent methodology, based on 20 years experience and posted on the website

Figures confirmed by at least 2 sources

Automatization (data entry and outputs)

Strengths of EM-DATUnique database with online search engine

Global reference for analysis of disaster occurrence and impact

Unique basis for policy on disaster reduction and risks

International recognition and CREDibility

Capacity to provide methods and guidelines (20 years experience)

Limitations of EM-DAT

Global database with limited sub-national data

Public aspect of EM-DAT leads to inappropriate use of data

Weak reporting of admin. districts

Lack of common institutional governance

COUNTRIES OCCURENCEAustria 6Belgium 6Bulgaria 11Canary Is 2Czech Rep 6Finland 1France 18Germany 6Greece 14Hungary 8Ireland 2Italy 16Lithuania 1Poland 5

Portugal 5Romania 30Slovakia 6Slovenia 1Spain 8United Kingdom 15Grand Total 167

COUNTRIES OCCURRENCEBelgium 1Bulgaria 1Czech Rep 3France 1Germany 1Greece 1Hungary 1Italy 1Lithuania 1Poland 2Portugal 1Romania 1Slovakia 2Spain 1Grand Total 18

Floods in EU 2000-2009 Floods in EU 2010

Source: EMDAT

Floods, Europe, 2000-2010 – Missing Information

Indicators Missing Information

Deaths* 40%*

Total Affected 24%

Economic Losses 65%

Localization 5%* No deaths

Health Impacts of Floods in EuropeBackground: MICRODIS Project

Goals and Objectives: Strengthen the quality, accuracy and completeness of disaster impact data in Europe; Analyze the impact of recent disasters using both statistical and spatial data

Activities:

(i) Based on EM-DAT, analysis and simple mapping of natural disasters and their impact in the EU-27

(ii) Creation of geo-coded maps using specialized data standard systems (GAUL) and tools such as ARCGIS

(iii) Development of recommendations for statistical, spatial and geo-referenced data required for measuring future natural disaster impacts in Europe

Conclusions

- Floods most common disasters in EU countries

- Significant impact on health and mental status of the community

- Human impact indicators monitored at national level; not consistent at a higher level of resolution

- Providing flood occurrence and impact at sub-national levels can serve policy-makers and international community

- Gaps in data, poor data access

Estimation of Human Exposure to Flood Events using DFO database

Climate, Environmental Health Action Plan and Information System (CEHAPIS)WHO/EURO Project 2008-2010 co-funded by EC DG Sanco

OBJECTIVE:Development of tools to monitor and assess environmental health related to climate change through the application of the EH information system methods in particular indicators

Current Estimation of Human Exposure to Flood Events

LimitationsNot all years recorded and some not reliable

Database needs cross validation checked (errors detected)

Estimates based on approximate flooded areas (overestimation)

What if we use satellite footprints instead?

What if we use satellite footprints instead?

Country Glide#a Disaster subtypeb PPEsf PPEws Deathsb MRsf MRws

Algeria 2008-000178 (incomplete) Flash Flood 98 846 120 893 93 9.41 7.69

Kenya Not available General Flood 33 201 22 894 730 17 5.12 0.01

IndiaBangladesh

Not available General Flood 16 831 500 133 154 900

59 0.04 0.001

Australia FL-2008-000014-AUS General Flood 53 512 Not available 0 0 NA

Zimbabwe FL-2008-000004-ZWE General Flood 1 962 106 1 927 270 24 0.12 0.12

Table 1 Comparison of footprint-based and watershed-based approaches to estimate people potentially exposed to floods and mortality rates

Four databases were used to produce these estimates (DFO, GPWv3, EM-DAT, HYDRO1k)a Information retrieved in DFO databaseb Additional information obtained from EM-DAT database. See http:\\www.emdat.be for definition.PPE indicates people potentially exposed to each flood using one of the following methods, SF satellitefootprints, WS watersheds; MR mortality rate, is the proportion of PPE that died due to flooding, expressedper 10,000 inhabitants

Limitations

Few footprints freely accessible (only 5 in DFO used in this study)

No full coverage (eg. some do footprints SERTIT )

GLIDE number not widely used (matching has to be done manually)

Flash floods difficult to capture (rapid onset)

Footprint variability depending on when the satellite is activated after the flood event

Challenges

Many initiatives starting to collect these footprints, UNOSTAT, ITHACA, SERTIT but..

Systematic collection, coordination efforts and a centralized repository should be achieved

Improve the definition and quality of other operational variables collected by EM-DAT such as injuries, homeless or displaced populations

Generalization( or not?) of the use of the GLIDE number

Satellite-based automatic fast production of flooded areas (JRC) – improve resolution