Early Warning System for Flood Risk Management

International Program Civil Engineering for Risk Management

An end to end Early Warning System- Lessons
Learned from Recent Floods
S.H.M. Fakhruddin
Team Leader- Hydrology
fakhruddin@rimes.int

08 March 2012

Politecnico di Milano, Dipartimento di Templates Pianificazione
Free Powerpoint Architettura e

Discussion Topics

• An end to end EWS

• About RIMES

• Case Study- Bangladesh Flood

• Lessons Learned from Thailand

Flood 2011

Free Powerpoint Templates

EW System


EW System Structure

Detection Subsystem

Monitoring, detection, data Assessment,
data analysis, prediction

Management Subsystem

Risk Assessment, interpretation,
communication

Response Subsystem

Interpretation, confirmation and
response


Reasons for Warning Failure


Gaps
 Regulatory framework for warning
 Stakeholders involvement and roles
Observation/ monitoring
 Aging and insufficient observation and data communication facilities

Data analysis  Data sharing among agencies

 Numerical prediction capability
Prediction Risk assessment  Skilled human resource
 Capacity to make use of new generation forecasts

Potential impact assessment  Local level potential impact assessment not done

 Language
Warning formulation
 Localized, relevant

Preparation of response options  Institutional mechanism, linkages
 SOPs
 Redundant communication systems
Dissemination to at-risk communities  Reach to special groups
 Public awareness
 Communication of forecast limitations
Emergency response plans
Community response Public education/ awareness  Lack of trainers/ facilitators
Mitigation programs  Resources to respond to warning

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.


Warning Technology Parameters

• Reliability

• Coverage

• Messaging

• Emergency Issues


Decision Support Framework


DSS Development Process


Risk Assessment

Risk Scoping Feedback

Risk
Characterization
• Establish target and
criteria through
consultation with
Risk Evaluation
stakeholders • Estimate for risk
• Identify possible event and receptor:
•Risk event •Likelihood of
•Source of stress exposure to
stressors
Risk Management
•Stress receptors
•Relationship •Consequences •Compare event
between sources of exposure to and total risks with
stress targets and criteria •Evaluate
and receptor
•Develop risk •Assess existing treatment options
profile risk management •Develop strategy
practices against based on option
risk profile

Flood Risk Characterization

flood characteristics
with respect to
onset, peak,
recession and
duration for the
selected major river
stations.


1 Need/ capacity assessments

Assessment of available
2 technology

Capacity building through
3 partnerships
Climate
Institutionalization of end-to-
Forecast
4 end system: pilot
demonstrations, replication
Application
Apply information to enable
Methodology:
5
pro-active decision making
Six step
Monitor and evaluate
6
applicability of information process

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


Focused Intervention

National
institutions

Global
climate End-users
information
providers


About RIMES


RIMES Member States


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

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

Organizational Chart
Council

Secretariat

Director, Program Unit

Tsunami Watch Provision Support to Hydro-Met Services Societal Applications Program Management

Chief Scientist Chief Scientist Team Leader Chief
Tsunami Early Warning Climate Change Climate Risk Management Program Management

Seismologist Chief Scientist Climate Impact ICKM Specialist
Seasonal Forecasting Assessment Team

Oceanographer Finance Officer
Chief Scientist Climate Forecast
Severe Weather Application Team
Seconded Scientists (6) Human Resource and
Administration Officer
Project Teams
Telecommunications Synoptician
Specialist
Hydrologist Team Leader
System Analysts (2) Early Warning

Seconded Scientists (2)
Warning Coordination Earthquake Hazard and
Scientist Risk Assessment Expert
System Analyst
Tsunami Hazard and Risk
Assessment Expert
Decision-support Tool
Development Specialist
GIS and Survey Specialist

Project Teams
Capacity Building
Specialist

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 Free Powerpoint Templates

Case Study- Long Lead Flood
Forecasting for Societal Benefits


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


Institutional Collaboration For Sustainable
End-to-end Flood Forecasts System

Climate (rainfall and discharge)
forecasting technology
RIMES- CFAN

BMD

RIMES Flood forecast RIMES

FFWC Discharge
Agro met
translation translation
Interpretation

DMB, DAE RIMES, Local Partners

Communication RIMES, Local Partners

End users

Discharge Forecast Schemes

(I). Initial Data (II). Statistical (III). (IV). Generation of (V).
Input Rendering Hydrological Probabilistic Q Forecast
Modeling Product

Discharge data • Accounting for
Hydrological uncertainties
Model • Final error
Hydrologic model parameters • Lumped correction
• Generation of
• Distributed
discharge
• Multi-Model forecast PDF
NOAA and NASA
(i.e.CMORPH and GPCP) Discharge • Critical level
satellite precipitation & GTS Forecasting probability
rain gauge data forecast

ECMWF
Operational
ensemble
Downscaling of forecasts
forecast Statistical correction

2007 Flood- Brahmaputra Ensemble Forecasts and
Danger Level Probabilities
7-10 day Ensemble Forecasts 7-10 day Danger Levels

7 day 8 day

7 day 8 day

9 day 10 day

9 day 10 day


Distribution of H combined with DEM -->
probabilities of flood classes

DEM Distribution of H values


Vulnerability & Flood Risk Assessment

• Development of flood risk map which
will include:
– low probability Social Map
– medium probability
– high probability Flood Vulnerable area Map

Flood Risk Map


USER MATRIX on Disasters, Impacts and
Management Plan for Crop, Livestock and Fisheries


DSS

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
…

Recommendations
1. 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

Risk Communication of flood forecasts


Risk Communication for Flood
Forecasts
Mobile phone
Sending SMS to Mobile

Flag
hoisting

Free Powerpoint Templates 32

Community responses to flood
forecasts


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
Average Amount of Saving per Household
– Fisheries = TK. 8,800
( $120) per households Save Fishereis

Save Livestock

• Experiment showed that every Save HH assets
USD 1 invested, a return of USD
Save agriculture
40.85 in benefits over a ten-year
period may be realized (WB). 0 5000 10000 15000 20000 25000 30000 35000
Free Powerpoint Templates Amount (TK.)

Analytical tools which can be used Free Powerpoint Templates interventions for subsequent
to assist in preparing preferred
decision making

Recent Floods- Thailand


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


Precipitation Scenario

table 1. Evaluation of Runoff Volume in Ping, Vang, Yom and Nan River Basin from storm during June to August 2011

Average Rainfall - mm Runoff Volume -Mmillion Cubic meter
STORM/DEPRESSION Duration
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
9,885

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.

Rainfall-Runoff

30 yrs average at Sukhothai observatory（1971‐2000）
Source: Daisuke KOMORI, Impact-T

Chao Phraya River
Basin
• There is no reservoir in Yom river, Sirikit
Bhumibol
and during Aug- Sep Bhumibal and Dam Dam
Sirikit Dam can’t release much
water
• Thus this region frequently
experiences floods in Aug-Sep


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

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.


Lessons Learned &
Recommendations

• Water Saving
Technology: updates
water rule curve
• Integrated Reservoir
modelling for robust
monitoring system


Flash Flood Forecasts


Produce reliable and skillful ensembles for a
wide spectrum of hydrology and water
resources services in Thailand


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! Powerpoint Templates
Free

Lessons Learned &
Recommendations

• 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.


Thank you


Early Warning System for Flood Risk Management

Recommended

Recommended

More Related Content

Recently uploaded

Recently uploaded (20)

Featured

Featured (20)

Early Warning System for Flood Risk Management