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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
• 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.
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
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
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
Flood Inundation Extent using ALOS PALSAR data
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
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
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
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!
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
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
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)
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
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
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
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
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)
‘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
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.
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

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Flood Evaluation, Livelihood Implications and Adaptation Measures in Sri Lanka

  • 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

Notas do Editor

  1. Mahaweli, Kalu Ganga, Maha Oya are seasonally flooded
  2. (Eakin and Appendini, 2008)