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An end to end Early Warning System- Lessons
Learned from Recent Floods
S.H.M. Fakhruddin
Team Leader- Hydrology
08 March 2012
International Program Civil Engineering for Risk Management
Politecnico di Milano, Dipartimento di Architettura e Pianificazione
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Discussion Topics
• An end to end EWS
• About RIMES
• Case Study- Bangladesh Flood
• Lessons Learned from Thailand
Flood 2011
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EW System Structure
Detection Subsystem
Management Subsystem
Response Subsystem
Monitoring, detection, data Assessment,
data analysis, prediction
Risk Assessment, interpretation,
communication
Interpretation, confirmation and
response
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Gaps
Dissemination to at-risk communities
Observation/ monitoring
Warning formulation
Community response
Data analysis
Prediction Risk assessment
Emergency response plans
Public education/ awareness
Mitigation programs
Potential impact assessment
Preparation of response options
Aging and insufficient observation and data communication facilities
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
Data sharing among agencies
Public awareness
Communication of forecast limitations
Lack of trainers/ facilitators
Resources to respond to warning
Regulatory framework for warning
Stakeholders involvement and roles
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Factors to Consider in choosing a Warning
Communication Technology
• Targeting populations-at-risk, communication for warning must take into account
– Who are the recipients
– Where they are located
– What they are doing
– Time of day.
– Season (e.g., peak tourist season)
– what they rely upon to receive local news and information
– what special needs they may have, and
– how well they understand and accept the warning in order to take action.
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Warning Technology Parameters
• Reliability
• Coverage
• Messaging
• Emergency Issues
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Risk Assessment
Risk Scoping
Risk
Characterization
Risk Evaluation
Risk Management
Feedback
• Establish target and
criteria through
consultation with
stakeholders
• Identify possible
•Risk event
•Source of stress
•Stress receptors
•Relationship
between sources
and receptor
• Estimate for risk
event and receptor:
•Likelihood of
exposure to
stressors
•Consequences
of exposure to
stress
•Develop risk
profile
•Compare event
and total risks with
targets and criteria
•Assess existing
risk management
practices against
risk profile
•Evaluate
treatment options
•Develop strategy
based on option
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Flood Risk Characterization
flood characteristics
with respect to
onset, peak,
recession and
duration for the
selected major river
stations.
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Need/ capacity assessments1
2
3
4
5
6
Assessment of available
technology
Capacity building through
partnerships
Institutionalization of end-to-
end system: pilot
demonstrations, replication
Apply information to enable
pro-active decision making
Monitor and evaluate
applicability of information
Climate
Forecast
Application
Methodology:
Six step
process
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End-to-end climate information
generation and application system
Providing climate outlook
Interpreting global climate
outlook into local outlook
Translating local climate outlook
into impact scenarios
Communication of response
options/ feedback
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Focused Intervention
Global
climate
information
providers
National
institutions
End-users
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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 capacities at all levels (national to
community) within each national early warning framework
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Governance
Council
Heads of NMHSs/ national scientific and technical agencies generating multi-
hazard 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
Co-located with the RIMES regional early warning Center
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Organizational Chart
Chief Scientist
Tsunami Early Warning
Warning Coordination
Scientist
Seismologist
Oceanographer
Telecommunications
Specialist
System Analysts (2)
Decision-support Tool
Development Specialist
Seconded Scientists (6)
Team Leader
Early Warning
Tsunami Hazard and Risk
Assessment Expert
Team Leader
Climate Risk Management
Earthquake Hazard and
Risk Assessment Expert
Project Teams
Climate Impact
Assessment Team
GIS and Survey Specialist
Secretariat
Council
Director, Program Unit
Program ManagementTsunami Watch Provision Support to Hydro-Met Services Societal Applications
Capacity Building
Specialist
Chief
Program Management
Finance Officer
Human Resource and
Administration Officer
ICKM Specialist
Climate Forecast
Application Team
Project Teams
Chief Scientist
Climate Change
Chief Scientist
Seasonal Forecasting
Chief Scientist
Severe Weather
Synoptician
Hydrologist
System Analyst
Seconded Scientists (2)
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RIMES- Facilities for Water Hazard Risk
Management
• Long lead Probabilistic flood forecasting and
community level application
• River Basin Outlook for the Region
• Drought early warning system
• Decision Support System for IWRM
• Ensemble Forecast Verification System
• Urban Flood Modelling
• Infrastructure Management using Flood
forecasting
• Climate Change and Hydrological impacts
• Storm surge modelling
• Water Quality & Ground water
• Early Warning Audits
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Case Study- Long Lead Flood
Forecasting for Societal Benefits
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Long Lead Flood Forecasting and
Applications
• 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
BMD
Climate (rainfall and discharge) forecasting technology
RIMES- CFAN
Agro met
translation
FFWC Discharge
translation
RIMES
DMB, DAE
Interpretation
Communication
End users
RIMES, Local Partners
RIMES, Local Partners
Flood forecastRIMES
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Discharge Forecast Schemes
ECMWF
Operational
ensemble
forecast
NOAA and NASA
(i.e.CMORPH and GPCP)
satellite precipitation & GTS
rain gauge data
Hydrologic model parameters
Discharge data
Downscaling of forecasts
Statistical correction
Hydrological
Model
• Lumped
• Distributed
• Multi-Model
Discharge
Forecasting
• Accounting for
uncertainties
• Final error
correction
• Generation of
discharge
forecast PDF
• Critical level
probability
forecast
(I). Initial Data
Input
(II). Statistical
Rendering
(III).
Hydrological
Modeling
(IV). Generation of
Probabilistic Q
(V).
Forecast
Product
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2007 Flood- Brahmaputra Ensemble Forecasts and
Danger Level Probabilities
7-10 day Ensemble Forecasts 7-10 day Danger Levels
7 day 8 day
9 day 10 day
7 day 8 day
9 day 10 day
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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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USER MATRIX on Disasters, Impacts and
Management Plan for Crop, Livestock and Fisheries
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High flood J F M A M J J A S O N D
T.Aman 1 1 3
T.Aus 2 2 2 3
Jute 3
S.Vegetables 4 4 4
Cattle 5 5 5 5 5 5 5 5 5 5 5 5
…
DSS
Recommendations1. Delayed seedling raising, gapfilling, skipping early fertilizer application
2. Advance harvest
3. Early harvest
4. Pot culture (homestead), Use resistant variety
5. Food storage, flood shelter, vaccination de-warming
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Sending SMS to Mobile
Risk Communication for Flood
Forecasts
Mobile phone
Flag
hoisting
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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
• Experiment showed that every
USD 1 invested, a return of USD
40.85 in benefits over a ten-year
period may be realized (WB).
Average Amount of Saving per Household
0 5000 10000 15000 20000 25000 30000 35000
Save agriculture
Save HH assets
Save Livestock
Save Fishereis
Amount (TK.)
Free Powerpoint TemplatesAnalytical tools which can be used to assist in preparing preferred interventions for subsequent
decision making
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Thailand Flood 2011
• There were 5 typhoons in 2011 that
affected Thailand-– HAIM, NOCK‐ 21-25 June
– TEN- 26-31 July
– NESAT- 24-30 Sep
– HAITANG 25-27 Sep
– NALGAE- 27 Sep-05 Oct
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Precipitation Scenario
Ping Wang Yom Nan Ping Wang Yom Nan
Haima 24 - 26/06/2011 64.5 56.5 90.7 234 890 245 870 3,270
Nokten 30 - 31/07/2011 97.1 117.7 126.2 46.9 1,000 370 900 1,100
Depression 18 - 20/08/2011 37.6 24 45 56.2 260 65 325 590
2,150 680 2,095 4,960
Average Rainfall - mm Runoff Volume -Mmillion Cubic meterSTORM/DEPRESSION Duration
9,885
table 1. Evaluation of Runoff Volume in Ping, Vang, Yom and Nan River Basin from storm during June to August 2011
The rainfall amount since 1
Jan to 31 Oct 2011 was
1822.4 millimeters, about 28
% above normal and only
Oct rainfall was 201.8
millimeters, 10 % above
normal.
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Rainfall-Runoff
30 yrs average at Sukhothai observatory(1971‐2000)Source: Daisuke KOMORI, Impact-T
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Chao Phraya River
Basin
• There is no reservoir in Yom river,
and during Aug- Sep Bhumibal and
Sirikit Dam can’t release much
water
• Thus this region frequently
experiences floods in Aug-Sep
Bhumibol
Dam
Sirikit
Dam
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Lessons Learned &
Recommendations
• RIMES 1-15 days forecasts model
well captured North Western
Pacific storm reaching Thailand.
Similar model integrating reservoir
component could provide a well
decision support system for water
management authorities.
• Authority should stop seeing floods
as ad-hoc disasters in need of
short-term relief, but as serious
threats to both economic and
social development
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Lessons Learned &
Recommendations
• A decision Support system
for Integrated Water
Resources Management
should be developed
providing priority on water
supply, Reducing flood
damages, hydropower
generation, Securing
navigation, environment
etc.
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Lessons Learned &
Recommendations
• Water Saving
Technology: updates
water rule curve
• Integrated Reservoir
modelling for robust
monitoring system
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Produce reliable and skillful ensembles for a
wide spectrum of hydrology and water
resources services in Thailand
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Lessons Learned &
Recommendations
• Floods shouldn’t be look as ad-
hoc disasters in need of short-
term relief, but as serious threats
to both economic and social
development
• Improved data acquisition from
upstream dams regarding flood
water release decisions and flood
inundation and impacts scenarios
(modelling)
• Improve coordination of inter-
Governmental institutions.
• Disaster Diplomacy!
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• No matter how state-of-the-art they are,
engineering solutions do not last forever.
They become obsolete as the environment
and living conditions change.
• Capacity building of communities on newly
generated forecasts products,
interpretation and response to flood
disaster.
Lessons Learned &
Recommendations