5th International Disaster and Risk Conference IDRC 2014 Integrative Risk Management - The role of science, technology & practice 24-28 August 2014 in Davos, Switzerland

1. POTENTIAL OF SATELLITE DATA IN CATASTROPHIC FLOOD
RISK MAPPING AND ASSESSMENT:
CASE STUDIES FROM ASIA AND AFRICA
GIRIRAJ AMARNATH
Contributors: Niranga Alahacoon, Ameer Rajah, Yoshiaki Inada,
Ryosuke Inoue, Pramod Aggarwal, Vladimir Smakhtin
International Water Management Institute (IWMI)
Session: Space Observation, GIS and Risk Mapping
5th International Disaster and Risk Conference IDRC 2014
25 August 2014 - Davos
Water for a food-secure world
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2. OUTLINE
• Synthesis of global flood occurrence and hotspot analysis
• Flood Mapping Products using multi-scale satellite data for risk
Water for a food-secure world
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assessment
– South Asia & South east Asia
– Niger – Benue River Basin
– Gash catchment in Eastern Sudan
• Blending satellite data and RADAR tool for rapid flood damage assessment
in Agriculture: A case study in Sri Lanka

3. Where we are based:
Tashkent
Lahore
New Delhi
Anand
Hyderabad
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Colombo
Pretoria
Ouagadougou
Cairo
Addis Ababa
Kathmandu
Vientiane
Washington, DC
The Hague

4. THE PROBLEM
• Floods – primary natural disasters
• Precipitation intensity and variability is projected
to increase – increasing risks of flooding
globally and in Asia
• Global flood losses in 2011 >$100 Billion
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o Largest global losses:
• Thailand (Jun-Nov) $40-50B
• Australia (Jan-Feb) $20-30B
• Hurricane Irene (Aug) $5-10B
• May rise to over $450B by 2030

5. Mapping Flood Hotspots for Climatic Change

6. CATASTROPHIC FLOODS IN ASIA: 1900-2011
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• Collated from 6 global sources
• >4000 floods globally
• Around 35% - in Asia
Annual Flood Occurrence
< 10 days
< 50 days
> 50days
Flood Duration
Country
Flood
Occurrence
India 237
China P Rep 209
United States 155
Indonesia 142
Philippines 116
Brazil 112
Bangladesh 83
Iran Islam Rep 72
Pakistan 72
Vietnam 67
Source : DFO, SAARC, Sentinel Asia, NDMA etc.

7. IDENTIFYING FLOOD HOTSPOTS
• 100 km grid over the globe;
• numbers of floods in each cell over 1900-2011
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8. CHARACTERISING FLOOD HOTSPOTS
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AGRICULTURE;
PAGE (2005)
POPULATION
CIESIN - 2010
FLOOD EXPOSED
GDP
WB, 2010

9. CHARACHERIZING FLOOD HOTSPOTS
• Globally - 90 grid cells with catastrophic
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flood occurrence ≥ 5;
• 60% of these cells -in Asia
• Estimated total over these hotspots:
– annual economic loss due to floods - $20bn
– 30 million affected people
– 500,000 km2 of affected croplands

10. SUB-CONTINENTAL SCALE FLOOD MAPPING
Examples from SA and SEA – MODIS images
Indus Mekong
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August 18, 2009
August 17, 2010
August 26, 2010
August 24, 2011

11. SUB-CONTINENTAL SCALE FLOOD MAPPING
Examples from SA and SEA – MODIS images
• 8-days maps of inundation extent
• Annual maps of maximum inundation
• Inter-annual variation of regional flooding extent
Flood
Mixed (Crop)
Water bodies
Inter-annual variation (2000 – 2011)
Normal River
2010
2010

12. Flood Duration : Indus Basin, Pakistan
• Duration of annual flood inundation is defined from the start and
end dates of annual flood inundation
• Longer flood duration significantly increase the flood risk damage

13. Spatial Distribution of population growth (1980 – 2000) and
location of the recent floods mapped using RS data
• Sub-continental scale, the dynamics of human settlements ( i.e. population growth between 1980
and 2000) and the location of latest floods in SA using RS data.
• Highlights that most of the recent floods (i.e. period 2000 – 2011) have occurred where the
population has increased more.
• Intensive and unplanned urbanization of flood-prone areas, played a major role in increasing the
potential adverse consequences of floods
Total
Population
Affected
Population
%
Bangladesh 152,518,015 99,412,500 65.18
India 1,210,193,422 131,107,100 10.83
Nepal 26,620,080 323,995 1.22
Pakistan 180,440,000 18,933,730 10.49
Sri Lanka 20,277,597 901,151 4.44
Flooding in SA has affected total
population = 250million

14. Flood Data Web Services !!

15. SOUTH EAST ASIA++ Flood Mapping
August 2011
MODIS Terra Image
MODIS 15 tiles covering SE Asia++
Total Images (2000 – 2011) = 7590
MODIS Flood Maps 2011 completed.
Validation ongoing
Tonle Sap Inundation Map (28th August 2011)

16. Flood Mapping Products (Initial Results)

17. Flood Impact Assessment using RADAR
Rapid Agriculture and Disaster Assessment Routine (RADAR)

18. Basic concept of RADAR – Flood Impact Assessment Tool
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

19. Basic concept of RADAR – Flood Impact Assessment Tool
Damage is function of three variables
Affected area Damage
Z (%)
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Value density
Percentage
Loss
X (Rs/ha)
Flood
Y (ha)
Damage
(Rs)

20. Percentage Loss is expected value loss
when the component is affected by flood event
Percentage Loss based on precipitation intensity
Intensity Moderate Rain Heavy Rain Torrential Rain Flood
Paddy rice 5±2% 30±10% 60±20% 100±10%
Livestock 0% 0±1% 15±1% 35±5%
Farm Asset 0% 5±1% 15±10% 75±10%
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Percentage Loss
Percentage Loss based on inundation intensity
Inundation depth
(m)
0-0.5 0.5-1.0 1.0-1.5 1.5-2.0 2.0-3.0 3.0-
Duration period
(days)
1 - 2 3 - 4 5 - 6 7 - 1 - 2 3 - 4 5 - 6 7 - 1 - 2 3 - 4 5 - 6 7 -
Paddy rice 21% 30% 35% 50% 25% 45% 50% 70% 35% 55% 65% 75% same as 1.0-1.5
Livestock 10% 20% 60% 100%
Farm Asset 15% 25% 30% 65% 70%

21. Flood Inundation Extent using ALOS PALSAR data

22. 1. Input before Flood
Just input affected area from GIS, then
You can immediately estimate the damage
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Data Synthesis
2. Input after Flood
(Affected area)
3. Run the program and damage
will be automatically calculated

23. Results (in Batticaloa District – Sri Lanka)
Estimated Damage
Paddy
Livestock
Farm asset
Comparison with
Direct measurement
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887 mil.Rs
762 mil.Rs
276 mil.Rs
2.43 billion Rs.
1.93 billion Rs.
RADAR Estimate Reported Estimate*
*source: District secretariat – Batticaloa and Disaster Management Centre

24. THANK YOU
“ Let not a single drop of water received from rains go waste into the sea without benefiting
the man and the beast ”
Water for a food-secure world
King Parakramabahu (1153-1186 AD)
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