The Regional Integrated Multi-Hazard Early Warning System for Africa and Asia
(RIMES)
Ensembles Probabilistic Long Lead Flood
Forecasts For Community Level Applications
S.H.M. Fakhruddin
Team Leader- Hydrology
fakhruddin@rimes.int
www.shmfakhruddin.com
Measuring ‘Real’ Impact
Monday 25th June 2012
UK CDS, Wellcome Trust,
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Free215
Powerpoint
Road, London NW1 2BE
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Discussion Topics
 About RIMES & Key Activities
 End to End EWS
 Case Study on Flood forecasting
and Agriculture Risk Management
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RIMES Member States
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Purpose and objectives
Purpose: Provide early warning services for enhanced preparedness,
response, and mitigation of natural hazards, according to differing
needs and demands of its Member States
Objectives:
 Facilitate establishment and maintenance of core regional observation
and monitoring networks and ensure data availability for early warning
 Provide regional tsunami watch within the framework of UNESCO
Intergovernmental Oceanographic Commission (IOC)
 Support National Meteorological and Hydrological services for
providing localized hydro-meteorological risk information within the
framework of the World Meteorological Organization (WMO)
 Enhance warning response
all levels (national to
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community) within each national early warning framework
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Governance
Council
 Heads of NMHSs/ national scientific and technical agencies generating multihazard early warning information, empowered to make policy decisions, on
behalf of governments, concerning regional early warning arrangements for
enhanced preparedness for, response to, and mitigation of natural hazards
 Chair: Government of India
Secretariat
 Carries out the decisions and tasks assigned by the Council, and provides
support to the Program Unit in managing the regional early warning center
 Government of Maldives (Presidential Task Force led by the H.E. Vice President
of Maldives) serves as Administrative Secretariat; Government of Mongolia
(Ministry of Foreign Affairs) as Program Secretariat
Program Unit
 Responsible for the day-to-day operation and management of the regional early
warning center and the implementation of programs and activities
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 Co-located with the RIMES regional early warning Center
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Organizational Chart
Council
Secretariat
Director, Program Unit
Tsunami Watch Provision
Support to Hydro-Met Services
Chief Scientist
Tsunami Early Warning
Chief Scientist
Climate Change
Team Leader
Climate Risk Management
Chief
Program Management
Seismologist
Chief Scientist
Seasonal Forecasting
Climate Impact
Assessment Team
ICKM Specialist
Chief Scientist
Severe Weather
Climate Forecast
Application Team
Societal Applications
Finance Officer
Oceanographer
Seconded Scientists (6)
Telecommunications
Specialist
Program Management
Synoptician
Hydrologist
System Analysts (2)
Human Resource and
Administration Officer
Project Teams
Team Leader
Early Warning
Seconded Scientists (2)
Warning Coordination
Scientist
Earthquake Hazard and
Risk Assessment Expert
System Analyst
Tsunami Hazard and Risk
Assessment Expert
Decision-support Tool
Development Specialist
GIS and Survey Specialist
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Project Teams
Capacity Building
Specialist
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Key services
1) Tsunami Watch Provision to National Tsunami Warning Centers
 Seismic and sea level monitoring and data exchange
 Provision of earthquake alerts and regional tsunami bulletins
 Tsunami hazard and risk assessment tools for local coastal inundation
forecasting
2) Support to National Meteorological and Hydrological Services
 Customization of climate and weather forecasting models for generation of
more reliable, location-specific severe weather and short- and medium-term
weather forecasts, and seasonal climate outlook, having longer lead times
 Downscaling of global climate models for generating high-resolution climate
change information for national and local level planning
 Development of decision-support tools
 Translation of products of research into operational forecast products and
testing these for local level application
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Key services continued
3) Capacity Building on End-to-End Early Warning

Early warning system audits

Assistance in establishing and maintaining observation and monitoring
stations of regional benefit

Training of scientists (in-country and RIMES secondment program)

Development of decision-support tools

Strengthening national early warning provider and user interface

Application of tailored risk information at different time scales in decisionmaking

Enhancing community responses to early warning
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EW System
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EW System Structure
Detection Subsystem
Monitoring, detection, data Assessment,
data analysis, prediction
Management Subsystem
Risk Assessment, interpretation,
communication
Response Subsystem
Interpretation, confirmation and
response
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Reasons for Warning Failure
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Gaps
 Regulatory framework for warning
 Stakeholders involvement and roles
Observation/ monitoring
 Aging and insufficient observation and data communication facilities
Data analysis
Prediction
 Data sharing among agencies
Risk assessment
Potential impact assessment
Warning formulation
Preparation of response options
Dissemination to at-risk communities
Community response
 Numerical prediction capability
 Skilled human resource
 Capacity to make use of new generation forecasts
 Local level potential impact assessment not done
 Language
 Localized, relevant




Institutional mechanism, linkages
SOPs
Redundant communication systems
Reach to special groups
 Public awareness
 Communication of forecast limitations
Emergency response plans
 Lack of trainers/ facilitators
Public education/ awareness
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Mitigation programs
 Resources to respond to warning
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A Case Study- Bangladesh
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Probabilistic Flood Forecasting
and Applications in Agriculture
• Research Project initiated
since 2000 and completed
in 2007
• GoB requested RIMES to
continue to support
• RIMES provides 10 days
lead time flood forecast
to GoB and build capacity
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Institutional Collaboration For Sustainable
End-to-end Flood Forecasts System
Climate (rainfall and discharge)
forecasting technology
RIMES- CFAN
BMD
RIMES
Agro met
translation
Flood forecast
FFWC
RIMES
Discharge
translation
Interpretation
DMB, DAE
Communication
RIMES, Local Partners
RIMES, Local Partners
End users
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Flood risk management at community level
decisions and forecast lead time requirement
Target groups
Farmers
Household
Fisherman
DMCs
Char households
Decisions
Forecast lead time
requirement
Early harvesting of B.Aman, delayed planting of T.Aman
10 days
Crop systems selection, area of T. Aman and subsequent crops
Seasonal
Selling cattle, goats and poultry (extreme)
Seasonal
Storage of dry food, safe drinking water, food grains, fire wood
10 days
Collecting vegetables, banana
1 week
With draw money from micro-financing institutions
1 week
Protecting fishing nets
1 week
Harvesting fresh water fish from small ponds
10 days
Planning evacuation routs and boats
20 – 25 days
Arrangements for women and children
20 – 25 days
Distribution of water purification tablets
1 week
Storage of dry food,Free
drinking
water, deciding
on temporary
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accommodation
1 week
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Discharge Forecast Schemes
(I). Initial Data
Input
(II). Statistical
Rendering
(III).
Hydrological
Modeling
Discharge data
Hydrologic model parameters
NOAA and NASA
(i.e.CMORPH and GPCP)
satellite precipitation & GTS
rain gauge data
ECMWF
Operational
ensemble
forecast
Hydrological
Model
• Lumped
• Distributed
• Multi-Model
Discharge
Forecasting
(IV). Generation of
Probabilistic Q
(V).
Forecast
Product
• Accounting for
uncertainties
• Final error
correction
• Generation of
discharge
forecast PDF
• Critical level
probability
forecast
Downscaling of forecasts
Statistical correction
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2007 Flood- Brahmaputra Ensemble Forecasts and
Danger Level Probabilities
7-10 day Ensemble Forecasts
7 day
9 day
7-10 day Danger Levels
8 day
7 day
8 day
9 day
10 day
10 day
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2012- Brahmaputra Ensemble Forecasts
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Plumes and probability pies for the first
Brahmaputra flood July 28-August 6, 2007
Model able to meet three
fundamental information needs of
communities at risk
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Distribution of H combined with DEM -->
probabilities of flood classes
DEM
Distribution of H values
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Vulnerability & Flood Risk Assessment
• Development of flood risk map which
will include:
– low probability
– medium probability
– high probability
Social Map
Flood Vulnerable area Map
Flood Risk Map
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Flood Risk Map
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Decision Support System
High flood
J
F
M A M J
J
1
1
T.Aman
T.Aus
2
2
A S
O N D
3
2
3
Jute
3
S.Vegetables
Cattle
5
5
5
5
4
4
4
5
5
5
5
5
5
5
5
…
Community Outcomes
1.
2.
3.
4.
5.
Delayed seedling raising, gapfilling, skipping early fertilizer application
Advance harvest of paddy ( 70-80 % mature)
Early harvest of jute for rotten in water
Pot culture (homestead), Use resistant variety
Food storage, flood shelter, vaccination de-warming
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Decision Support System (DSS)
High flood
J
F
M A M J
J
1
1
T.Aman
T.Aus
2
2
A S
3
2
3
Jute
3
S.Vegetables
Cattle
O N D
5
5
5
5
4
4
4
5
5
5
5
5
5
5
5
…
Recommendations
1.
2.
3.
4.
5.
Delayed seedling raising, gapfilling, skipping early fertilizer application
Advance harvest
Early harvest
Pot culture (homestead), Use resistant variety
Food storage, flood shelter, vaccination de-warming
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USER MATRIX on Disasters, Impacts and
Management Plan for Crop, Livestock and Fisheries
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Decision Tree
Harvest in
early July
No flood
Quality lost (I)
Flood
Crop and input up
to now saved (II)
Harvesting
decision
No flood
Gain 100% yield
and quality (III)
Wait until mid
July
Flood
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Entire cro p and input
upto now lost (IV)
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Risk Communication of flood forecasts
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Risk Communication for Flood
Forecasts
Mobile phone
Sending SMS to Mobile
Flag
hoisting
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Community responses to flood
forecasts
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Economic- Benefits
• In 2008 Flood, Economic
Benefits on average per
household at pilot areas
– Livestock's
= TK. 33,000
($485) per household
– HH assets
= TK. 18,500
( $270) per household
– Agriculture
= TK 12,500
($180) per household
– Fisheries
= TK. 8,800
( $120) per households
Average Amount of Saving per Household
Save Fishereis
Save Livestock
• Experiment showed that every
USD 1 invested, a return of USD
40.85 in benefits over a ten-year
period may be realized (WB).
Save HH assets
Save agriculture
0
5000
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10000 15000 20000 25000 30000 35000
Amount (TK.)
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Expansion of
Areas
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Thank you
S.H.M. Fakhruddin
Team Leader- Hydrology
fakhruddin@rimes.int
www.shmfakhruddin.com
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