early warning system for flood risk management

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An end to end Early Warning System- Lessons

Learned from Recent Floods

S.H.M. Fakhruddin

Team Leader- Hydrology

[email protected]

08 March 2012

International Program Civil Engineering for Risk Management

Politecnico di Milano, Dipartimento di Architettura e Pianificazione

http://www.powerpointstyles.com/

mailto:[email protected]


Discussion Topics

• An end to end EWS

• About RIMES

• Case Study- Bangladesh Flood

• Lessons Learned from Thailand

Flood 2011



EW System



EW System Structure

Detection Subsystem

Management Subsystem

Response Subsystem

Monitoring, detection, data Assessment,

data analysis, prediction

Risk Assessment, interpretation,

communication

Interpretation, confirmation and

response



Reasons for Warning Failure



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



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

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



Flood Risk Characterization

flood characteristics

with respect to

onset, peak,

recession and

duration for the

selected major river

stations.



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



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

Global

climate

information

providers

National

institutions

End-users



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

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)



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



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

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



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



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



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

– medium probability

– high probability

Social Map

Flood Vulnerable area Map

Flood Risk Map



USER MATRIX on Disasters, Impacts and

Management Plan for Crop, Livestock and Fisheries



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



Risk Communication of flood forecasts


Free Powerpoint Templates 32

Sending SMS to Mobile

Risk Communication for Flood

Forecasts

Mobile phone

Flag

hoisting



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

– 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



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

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.



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,

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



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!



• 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



Thank you


early warning system for flood risk management

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