An initiative to map multiple hazards in the South Asia region to help build resilient farming communities.

1. Mapping multiple climate-related hazards in South Asia
G. Amarnath1
, N. Alahacoon1
, S. Yoshimoto1
, V. Smakhtin2
and P. Aggarwal3
1
International Water Management Institute (IWMI), Colombo, Sri Lanka
2
United Nations University - Institute for Water, Environment and Health (UNU-INWEH), Ontario, Canada
3
CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), New Delhi, India
RESEARCH
PROGRAM ON
Water, Land and
Ecosystems
Using the ranking procedure, we found that most of the divisions in Bangladesh, and some divisions in India, Sri Lanka, Pakistan and Nepal are extreme-risk areas. Some cities are highly affected by
frequent disasters in spite of their high adaptive capacity, because the adaptive capacities of those cities are not sufficient due to high population densities and significant exposure to the hazards.
www.fsm4.susana.org
Risk is understood as the probability that exposure to a climate-related hazard with a given
vulnerability will lead to negative consequences. Disaster risk reduction includes systematic
efforts to analyze and manage the causal factors of disasters through reduced exposure and
vulnerability to hazards, and improved preparedness for disaster events. In South Asia, interest
in multi-risk assessment has increased during the last decade. The main objectives of this study
were to:
Introduction
map areas exposed to five climate-related hazards: floods, droughts, extreme
rainfall, extreme temperature (heat wave) and sea-level rise;
develop a method for estimating the population exposed to individual natural hazards and
their impacts on agriculture; and
assess the overall vulnerability and risk at the country level based on country-wide, urban and
rural population exposure to these hazards.
For more information, contact Giriraj Amarnath (a.giriraj@cgiar.org)
International Water Management Institute (IWMI)
127 Sunil Mawatha, Pelawatte, Battaramulla, Sri Lanka
Mailing address
P. O. Box 2075, Colombo, Sri Lanka
Tel: +94 11 2880000, 2784080; Fax: +94 11 2786854
Email: iwmi@cgiar.org; Website: www.iwmi.org
Dried tank and damaged crops (Sri Lanka), and flood-affected paddy field (Bihar, India).
Method and approach
Results and discussion
World Bosai Forum/International Disaster and Risk Conference 2017 http://www.worldbosaiforum.com/english/overview/
Conclusion
Reference
Flood – Frequency was obtained from
flood inundation maps based on analyses
of 8-day MOD09A1 reflectance
Drought – Vegetation water stress
NDDI was calculated from
MOD09A1 surface reflectance
Extreme rainfall – Events with
intensity greater than 124.4 mm/
day were classified as ‘extreme’
Heat wave – High temperature
anomaly greater than 6 °C was
distinguished from MODIS-based LST
Sea-level rise – Rate of sea-level rise,
coastal morphology, tidal range, etc. were
integrated
Data used
Hazard Dataset Period Spatial Temporal
Flood MODIS – MOD09A1 2001-2013 500 m 8-day
Drought MODIS – MOD09A1 2001-2013 500 m 8-day
Extreme rainfall APHRODITE and TRMM 1951-2013 11 km Daily
Heat wave MODIS – MOD11C2 2001-2013 5,000 m 8-day
Sea-level rise Tidal gauge data 1930-2013 Points Monthly
resolution resolution
Figure 2. Population exposure to multiple climate hazards in
the eastern part of India and Bangladesh.
Figure 1. Indices of the climate-related hazards calculated in this study: (a) floods, (b) droughts, (c) extreme rainfall, (d) extreme temperature (heat wave), and (e) sea-level rise.
(a) (b) (c) (d) (e)
Figure 4. Hazard rank in comparison with adaptive
capacity (Human Development Index [HDI]).
Multi-hazard risk was calculated as a combination of the individual hazard maps and
population/crop maps with weighting and normalization.
Mappingclimatehazards
This assessment of exposure to climate hazards has implications for country-level adaptation to climate change. It could be used to help
inform decisions about financial aid or how to allocate climate adaptation resources within a country. Additionally, the assessment allows
for comparisons to be made between different countries’ exposure to a particular hazard. The model is designed to be flexible, allowing
exposure assessment methods to be applied to a range of outcomes and adaptation measures, such as economic loss, etc. The approach
can be promoted within the Sendai Framework for Disaster Risk Reduction 2015-2030 to member states for building long-term resilience.
Acknowledgements
This research study was funded by the CGIAR Research Program (CRP) on Climate Change, Agriculture and Food Security (CCAFS);
CGIAR Research Program on Water, Land and Ecosystems (WLE); Ministry of Agriculture, Forestry and Fisheries (MAFF), Japan; and the
International Water Management Institute (IWMI). The contribution made by various government agencies in data sharing and providing
valuable feedback is gratefully acknowledged.
Amarnath, G.; Alahacoon, N.; Smakhtin, V.;
Aggarwal, P. 2017. Mapping multiple climate-related
hazards in South Asia. Colombo, Sri Lanka:
International Water Management Institute (IWMI).
41p. (IWMI Research Report 170).
Figure 3. Sub-national evaluation (a) overall climate hazard map, and (b) climate change
vulnerability map.
(a) (b)
Sendai, Japan
November 25-28, 2017