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Identifying new data needs and sources Linking DRR and Adaption: Disaster Inventories Data on impacts and vulnerability. Global Assessment Report Team GAR United Nations International Strategy for Disaster Reduction UNISDR. HYOGO FRAMEWORK FOR ACTION. - PowerPoint PPT PresentationTRANSCRIPT
Geneva, February 2-4, 2011
Global Assessment Report Team GARUnited Nations International Strategy for Disaster Reduction UNISDR
Identifying new data needs and sources
Linking DRR and Adaption: Disaster Inventories Data on impacts and vulnerability
Geneva, February 2-4, 2011
In January 2005, 168 Governments adopted a 10-year plan to make the world safer from natural hazards at the World Conference on Disaster Reduction, held in Kobe, Hyogo, Japan.
Its goal is to substantially reduce disaster losses in lives, and in the social, economic, and environmental assets of communities and countries.
The Hyogo Framework offers guiding principles summarized in 5 priorities for action
HYOGO FRAMEWORK FOR ACTION
Geneva, February 2-4, 2011
Ensure that disaster risk reduction is a national and a local priority with a strong institutional basis for implementation.
Identify, assess and monitor disaster risks and enhance early warning.
Use knowledge, innovation and education to build a culture of safety and resilience at all levels.
Reduce the underlying risk factors.Strengthen disaster preparedness for effective response at all
levels.
HFA 5 PRIORITIES FOR ACTION
Geneva, February 2-4, 2011
Develop, update periodically and widely disseminate risk maps and related information to decision-makers, the general public and communities at risk
Develop systems of indicators of disaster risk and vulnerability at national and sub-national scales
Record, analyse, summarize and disseminate statistical information on disaster occurrence, impacts and losses, on a regular bases through international, regional, national and local mechanisms.
HYOGO FRAMEWORK FOR ACTION A2
Geneva, February 2-4, 2011
GEO/GEOSS goals GEOSS will yield a broad range of societal benefits, notably: Reducing loss of life and property from natural and human-induced
disastersUnderstanding environmental factors affecting human health and
well-beingImproving the management of energy resourcesUnderstanding, assessing, predicting, mitigating, and adapting to
climate variability and changeImproving water resource management through better understanding
of the water cycleImproving weather information, forecasting and warningAND OTHERS....
Geneva, February 2-4, 2011
Current data for monitoring disaster risk
• Hyogo Framework for Action implementation Monitoring of levels of risk to disasters Monitoring levels of losses Progress in measures to reduce risk Global Assessment Report (Biennial)
• Special Report of IPCC (SREX) First IPCC review of what constitutes effective measures to reduce
risk to extreme events
Geneva, February 2-4, 2011
Typical contents of a Disaster database
The actual screen for data capture.
Customizable by users.
Standard Effects (killed, injured, affected, etc.)
Extension (Sectorial detail information)
• Simple, low technology• Non expensive• High impact, ROI
Geneva, February 2-4, 2011
What are National Disaster Inventories?
•Disaster Inventories record and analyse the occurrence and effects of natural disasters
• Disaggregated information is provided in tabular and graphical form (maps and charts)
• Richer than global data: Events of all scales, more indicators, closer (local) level of observation
Geneva, February 2-4, 2011
Temporal Analysis (Trends): distribution of losses over time Behaviour of disaster losses is key in understanding trends and essential for monitoring the effectiveness of DRR
Number of reports of floods and people killed by epidemics in Orissa, India 11 years, showing a high correlation between floods and epidemics.
Ovals show non-related epidemic events.
Seasonal distribution of floods in Mexico
Geneva, February 2-4, 2011
Spatial Analysis (patterns): distribution of losses over space
The Municipalities located over the Andes mountain area are the most prone to landslide disasters
Spatial distribution of landslides in Colombia
Geneva, February 2-4, 2011
The hybrid loss exceedance curve, Colombia
Usage of Disaster loss data in Risk Assessments.
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Typical analytical loss exceedance curve, Colombia
Geneva, February 2-4, 2011
Spatial distribution of Surge reports, PERU
Temporal distribution of Surge reports, PERU
Damage to housing sector – due to Surge , PERU
Mortality due to Surge , PERU
Impact and extent of (possibly) Climate Change related events
Geneva, February 2-4, 2011
Mortality due to extreme precipitation events
Impact and extent of (possibly) Climate Change related events
Frequency of extreme precipitation-related events , 8 South American countries
Geneva, February 2-4, 2011
Usage of Historical Loss Data in DRRM
• Modeling probable maximum losses up to a return
period of approximately 30 – 50 years.
• Provide historical vulnerability indexes/functions
• Allow monitoring of DRR measures
• Historical data can help validating Risk
Assessments
• Provide a dynamic vision of risk evolution over
time
• Provide evidence-based support to decision
makers
• Generate proxy indicators of Risk (for hard-to-model risks or when no
data is available)
…
• Climate Change Adaptation?
Geneva, February 2-4, 2011
UN sponsored Disaster InventoriesAsia/Pacific
Sri Lanka, Indonesia, Iran, Maldives, Nepal, India (Tamil Nadu, Orissa, Andra Pradesh, Uttranchal, Delhi), Jordan, Syria, Vietnam, Laos*, Vanuatu*, Solomon*, SOPAC, East Timor, Philippines
LAC
Mexico, Costa Rica, El Salvador, Panama, Colombia, Ecuador, Peru, Bolivia, Venezuela, Argentina, Chile, Paraguay, Panama, Guatemala, Jamaica, Trinidad & Tobago, Guyana, Antigua
Africa
Egypt, Morocco, Yemen, Mozambique, Mali, Djibouti *
Many other countries (USA, Australia, etc.) have independently build datasets. A total of about 60 datasets identified.
Geneva, February 2-4, 2011
Potential Usage of Historical Loss Data in CC
• Provide measures of historical/current impact ?
• Historical data to be input layer for Impact
Assessments
• Permit finer grain impact analysis (compared to global
datasets)
• Validate hypothesis of realized change?
• Allow monitoring of Climate Change impact ?o Frequency
o Severity
o Location
•Other?
Geneva, February 2-4, 2011
Global Assessment Report on Disaster Risk GAR
United Nations International Strategy for Disaster Reduction UN-ISDR www.unisdr.org
IEH International Environment House7-9 Chemin de Balextert, 4th floor
Julio Serje [email protected] John Harding [email protected] Justin Ginnetti [email protected]