1.
Flood Evaluation, Livelihood Implications
and Adaptation Measures in Sri Lanka
Giriraj Amarnath, Yoshiaki Inada, Surajit Ghosh, Niranga Alahacoon, Umer Yakob,
Harada Kota, Ryosuke Inoue, Brindha Karthikeyan, Joseph Price, Mohammed Aheeyar,
Sanjiv De Silva, Herath Manthrithilake, Vladimir Smakhtin
International Water Management Institute (IWMI), Sri Lanka
National Workshop on “Use of Space Based Information for Disaster
Management”
Colombo, Sri Lanka, 17 November, 2014

2.
• The frequency of flood disasters in Sri Lanka is rising. Hypotheses for this phenomenon
are numerous:
increased climatic variability, the expansion of human settlement in flood
plains, and land cover and land use changes together are believed to be
increasing human exposure and sensitivity to flood impacts.
• The persistence of loss in face of increased knowledge about the dynamics, drivers,
and outcomes of hazards may well signal a significant lack of sustainability in social-environmental
relations, as well as a need to reconsider the underlying principles of
flood management.
Background
Need for a better knowledge on the scale of flooding at various scales that
includes flood extent, flood depth to assess agriculture loss and population
exposure and integration of science-based inputs in flood management to
develop the best possible flood-risk solutions.

3.
Problem and solutions
Issues
Scale of
Challenge
Evidence on current risks
and opportunities
• Who & what is affected
• Scale of consequences
Adaptation
context
Current
adaptation
actions
• Adaptive capacity
• Key relevant policies
• Assessment of actions across
decision makers
• Lack of solutions across institutions
Barriers of
adaptation
Case for
intervention
Published evidence/new
analysis/stakeholders inputs
• Barriers of action:
• Policy
• Behavioral
• Governance
• Adaptive management solutions
• Recommendations
1
2
3
Published evidence/new
analysis/stakeholders inputs
Three Stages of approach for appropriate adaptation

4.
Research framework
Flood Risk
Assessment
Flood
Evaluation,
Livelihood
Implications and
Adaptation
Measures
Developing
Flood
scenarios for
Risk
Reduction
Flood Loss
Estimates
Integration of Sciences, local
perception to understand
Livelihood changes, managing
flood risks
Institutional
Analysis and
Adaptation
Strategies
Flood frequency analysis,
Inundation modeling at basin
scale and provide scenarios
for flood protection measures
Blending RS data and
socioeconomic and land use to
spatially quantify agriculture
impact from flooding
Mapping Historical to Current
Flood Extent using MODIS and
SAR Satellite images

5.
Remote sensing-based flood-risk mapping: Sri Lanka
• Remote sensing approach was employed to estimate flood frequency and extent.
• Agricultural impact from floods is being studied.
• Potential of flood-risk mapping and piloting agricultural insurance products using EO data and
models are the future areas of research in Sri Lanka

6.
Flood Inundation Extent using ALOS PALSAR data

7.
Extent of flooding during the
years 2006–2011 derived from
ALOS PALSAR data (left) and
cropland extent (right) in Sri
Lanka
• Fine-scale flood-risk products mapped using
satellite datasets from 2000 to 2011.
• Province-wise flood statistics and agricultural
impacts are being analyzed.
• Knowledge generated here can be used by the
Disaster Management Centre and the Irrigation
Department for mitigation, preparedness and
index-based crop insurance
Eastern Province (Trincomalee)
Agricultural flooding in Polonnaruwa

8.
Flood Inundation Modeling and Flood Protection measures
Basin features
– Location- Ampara and Batticaloa Districts
Eastern Province
– Catchment area - 1,280 km2
– Three tributaries: Rabukkan Oya, Gallodai
Aru and Maha Oya
– Uni-modeal Rainfall distribution: main rainy
season NE monsoon
– Jan. to Mar. (SW monsoon season)- severe
shortage of water resulting in cultivation
restrictions
– NE monsoon season-flood problem resulting
in loss of life and agricultural production
– Exiting structure (e.g.Rugam Tank) is
not sufficient to reduce flood water
– Need for multi-purpose river basin
development

9.
Flood Inundation Modeling and Flood Protection measures
with counter measure, the flood risk in the
downstream part (Paddy area) is drastically
reduced
Without counter measures (with existing
Tank)-the downstream are highly
impacted from flooding

10.
Flood Risk Maps
Densely populated areas near the
downstream of basin are under the
risk of flooding
Major land use type that fallen
under the flood risk is paddy area
(RED COLOR)- and the most
productive areas to be lost!

11.
Recommendation and Messages
• Integrated flood risk management
that reduces flood risk while
increasing its positive impact is
needed
– Socio-economic aspects
• Building multi-objective reservoir that
reduces flood impact during wet
season and used stored water for
irrigation purpose during dry season
• Proper Dam operation and application
of basin scale forecasting system
– Ecosystem Management aspect
• Re-establishing wetlands in the
downstream of the basin area
• Re-forestation in the upstream areas

12.
Agriculture Loss Estimates from Flooding - RADAR
Water for a food-secure world
www.iwmi.org
Measure an event intensity
Event
Event Intensity
Percentage Loss
Damage
Flood depth, period
Precipitation
Model Base or Remote Sensing
Knowledge Base
Translate from intensity to loss
Data Base
Calculate the damage from
component values

13.
Damage is function of three variables
Affected area Damage
Z (%)
Water for a food-secure world
www.iwmi.org
Basic concept of RADAR
Value density
Percentage
Loss
X (Rs/ha)
Flood
Y (ha)
Damage
(Rs)

14.
Damage Calculation Process
Yield
Price
Value
Density
Water for a food-secure world
www.iwmi.org
Percentage Loss
Damage by
Component
Paddy
Precipitation
Farm Asset
Residence Area
Farm Asset Value
per Farmer
Farmer Ratio
Number of
houses
Livestock
Price
Number
Habitat Area
Flood
event
Crop
Calendar
Exposed
Ratio
Damage by
District
Total Damage
Flood depth,
period
Input (constant)
Input (after flood)
Output
Affected Area

15.
Land Use Map (Survey Dpt.) Flood Map ( Feb 2011 Flood)
Water for a food-secure world
www.iwmi.org
Affected Area
Paddy
Inundated Area
Water Body
Affected area by land use will
be obtained

16.
1. Input before Flood
Just input affected area from GIS, then
You can immediately estimate the damage
Water for a food-secure world
www.iwmi.org
Data Synthesis
2. Input after Flood
(Affected area)
3. Run the program and damage
will be automatically calculated

17.
Estimated Damage
Comparison with
Direct measurement
Water for a food-secure world
www.iwmi.org
Results (in Batticaloa)
Paddy
Livestock
Farm asset
676 mil.Rs
762 mil.Rs
257 mil.Rs
2.34 billion Rs.
1.70 billion Rs.
RADAR Estimate Reported Estimate*
*source: District secretariat – Batticaloa and Disaster Management Centre

18.
Integration of science and policy
• Science-based information (flood mapping, flood risk modeling and
RADAR) can be shared among institutions
• Streamlined into national institutional framework to improve capacity
for better decision-making (requires coordination mechanisms)
• Outcomes:
• Guide suitable planning and investments
• Preparedness
• Early warning
• Emergency response
• Tangible products which demonstrate why one avenue of public
spending may be appropriate
• Justify and rationalise public policy (Poussin et al, 2012)

19.
‘Living with floods’
• Floods inevitable - softer adaptation strategies can be
more productive than heavy structural measures
• Concept – focus on political-economic, cultural and
historical dimensions of disaster
• Above factors can determine risk perception (subjective)
• Flood accepted as norm of land-use, rather than ‘hazard’
• Livelihood strategies - diversification & distribute/plan
farming activities accordingly
• Local perspectives can be incorporated into policy to
address needs & flexible solutions

20.
Application to Batticaloa District
• Concept is applicable to Batticaloa – susceptible to flood
disasters and strong dependence on agriculture (paddy)
• Fieldwork currently being carried out to understand
institutional structure and identify livelihood adaptation
strategies:
• Questionnaires, surveys & interviews
• Two villages of different inundation levels
Source: http://sangam.org/2011/02/images/FloodsBatticaloaJan20112.jpg.

21.
Case study expectations
• Social scientific data:
• Qualitatively evaluate risks posed by floods - understand and improve
methods of coping on local-scale
• Highlight coordination mechanisms and identify gaps
• Consider best practices in flood management
• Reveal opportunities for institutionalizing scientific tools developed by IWMI