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Tools for Assessing Vulnerability and Adaptation
IIT Bombay Team
K.Narayanan, D.Parthasarathy, Unmesh Patnaik
BASIC Project India Workshop,
New Delhi, May 2006
Assessment of Vulnerability
• Vulnerability Index
Assessment of Adaptation
• Adaptive Efficiency Tool
BASIC Project India Workshop,
New Delhi, May 2006
Framework 1: Livelihood Vulnerability and
Adaptation
Identifying livelihoods likely to be affected by uncertainty
–
–
Climate related uncertainties: rainfall, temperature, sea level
changes
Uncertainties exacerbated by system inefficiencies (social,
economic, political)
1.
2.
3.
4.
5.
6.
Policies and institutions
Market
Government
Physical infrastructure
Social infrastructure
Demographic factors (population growth, density,
literacy)
BASIC Project India Workshop,
New Delhi, May 2006
Framework 1: contd.
• Who are vulnerable – when and where?
• Who perform these livelihoods? Who is affected by loss / reduction
in livelihoods?
(age, gender, class, race, ethnicity, region)
• What are the factors that enhance / reduce risk? Which factors are
more important in influencing / mediating livelihood impacts?
• What are the existing and potential mechanisms of adaptation?
BASIC Project India Workshop,
New Delhi, May 2006
Framework 2: Physical Vulnerability and
Adaptation
•
Identifying populations likely to be affected by uncertainty (rainfall,
temperature, sea level changes)
• Who are these people? How are they affected?
• What are the factors that enhance / reduce risk?
• Who are vulnerable – when and where?
• Existing and potential mechanisms of adaptation
BASIC Project India Workshop,
New Delhi, May 2006
Threats and risk perception – vulnerability and adaptation
Perception of risk influences adaptation behaviour and hence
vulnerability
Perception of risk dependent on social attitudes, values, social
structure, culture but also,
•Livelihood patterns and structures
•Poverty levels
Perception and response to risk: information integrity issues
BASIC Project India Workshop,
New Delhi, May 2006
Tools for assessing relation between risk perception and
adaptation behaviour
•Correlations and regressions (poverty – threat
response)
•Qualitative, field based empirical validation
BASIC Project India Workshop,
New Delhi, May 2006
Vulnerability Index
 This index takes care of the many factors that are crucial in
determining the overall vulnerability of the people in the area
of concern. These sources of vulnerability are derived from
demographic, climatic, occupational and agricultural factors.
 The idea is to prepare an index to map the vulnerability
among the various coastal districts of the eastern coast of
India and rank the districts in terms of vulnerability.
 The following indicators has been used in the construction of
the Vulnerability Index.
BASIC Project India Workshop,
New Delhi, May 2006
Approaches to Measure Vulnerability
Various methods used to measure vulnerability arising out of
climate change
These can be categorized as follows:
 Conceptual Approaches
 Extended Vulnerability Framework
 Critical Thresholds Framework
 Indicator Lead approaches (Bottom-up approaches and Top
Down approaches)
BASIC Project India Workshop,
New Delhi, May 2006
Assessment of Vulnerability:
 Methods for assessing vulnerability includes
Historical Narratives
Statistical Analysis
GIS and Mapping techniques
Comparative analysis
 The dynamics of vulnerability are captured by relating it to
Climate change
Adaptation to climate change
Impacts of climate change
Natural hazards and responses
Social indicators
BASIC Project India Workshop,
New Delhi, May 2006
Studies pertaining to assessment of vulnerability:
Study
Year
Vulnerability Arising From
Watson et al.
1995
IPCC Indicators
Zeidler
1997
Sea Level Rise
Rosenzweig & Parry / Dehn & Buma
1994 /
1999
Landslide Activities
Blaikie et al.
1994
Human Dimensions (Pressure and release model)
Wisner
1999
Earthquake, Hurricane
Watts and Bohle
1993
Famines
Adger and Kelly
1996,2001
Entitlement approach in terms of access to resources
O’Brien and Liechenko
2002
Climate Change and Access to resources
Smit and Pilifosova; Bohle; Downing
2002
Vulnerability = (Exposure to a stimulus, capacity to
adjust to it)
Ghazala Mansuri and Andrew Healy
2002
Probability of future poverty
Ethan Ligon and Laura Schecter
2002
Loss associated with different sources of uncertainty
Shubham Chaudhuri
2001
Household Vulnerability to poverty
M.A. Chen
1991
Poverty, lack of access to food (entitlements)
W.E. Riebsane, S.A. Changnon Jr. and T.R. Karl
1991
Drought
Gunther Fischer, Mahendra Shah, and Harriz
2002
Agricultural vulnerability
vanValthuizen
BASIC Project India Workshop,
New Delhi, May 2006
Quantifying Vulnerability :
Sensitivity sectors
Coping and Adaptive Capacity sectors
Settlement
Economy
Food
Human Resources
Health
Ecosystems
Environment
Water
Sensitivity Indicators
Coping-Adaptive Capacity Indicators
National Baseline estimates and projections of
Sectoral- Indicators
BASIC Project India Workshop,
New Delhi, May 2006
Source: Moss et.al., (2001)
Sources and Indicators of Vulnerability:
Vulnerability Index
Demographic
Vulnerability
Density of
Population
Literacy Rate
Climatic
Vulnerability
Variance in annual
rainfall
Variance in JuneJuly-August
Rainfall
Frequency of
extreme events
Agricultural
Vulnerability
Occupational
Vulnerability
Production of
Rice
Cropping
Intensity
Area under
Cultivation
Irrigation
Intensity
No. of Cattle
and Livestock
Total Workers
BASIC Project India Workshop,
New Delhi, May 2006
Agricultural
Laboureres
Manufacturing
Labourers
Non Workers
Methodology of Calculation:

The methodology used to calculate the vulnerability
index follows the basic approach developed by (Anand
and Sen, 1994) for the calculation of the human
development index (HDI)
Step 1: Calculate a dimension index of the each of the
indicators for a district (X I) by using the formula
(Actual X I – Minimum X I) / (Maximum X I – Minimum X I)
Step 2: Calculate a average index for each of the four
sources of vulnerability viz. Demographic, Climatic,
Agricultural and Occupational vulnerability. This is done
by taking a simple average of the indicators in each
category.
Average Index i = [Indicator 1 +………. + Indicator J] / J
BASIC Project India Workshop,
New Delhi, May 2006
Methodology of Calculation contd.:
Step 3: Aggregate across all the sources of vulnerability by
the following formula.
n
Vulnerability Index = [ ∑ (Average Index i)α ]1/α/ n
i=1
Where,
J = Number of indicators in each source of vulnerability
n = Number of sources of vulnerability
(in the present case n = α = 4)
•
This computation is repeated for different time periods
1971, 1981 and 1991 in order to see how the
vulnerability profile has changed over the years for the
districts in terms of the indicators used to measure the
vulnerability.
BASIC Project India Workshop,
New Delhi, May 2006
Vulnerability Index: Findings
Districts
Dhenkanal
Nellore
Ganjam
Krishna
Visakhapatnam
Puri
West Godavari
Guntur
East Godavari
Srikakulam
Cuttack
Balasore
Vulnerability
Rank in 1971
(Base)
1
2
3
4
5
6
7
8
9
10
11
12
Vulnerability Vulnerability
Rank in 1981 Rank in 1991
Most
Vulnerable
Least
Vulnerable
BASIC Project India Workshop,
New Delhi, May 2006
1
2
3
5
4
11
7
9
6
8
10
12
1
3
5
6
7
4
8
9
10
11
12
2
Adaptive Efficiency: Conceptualization and
Measurement
• Concept defines how economies and societies work
effectively in a dynamic time frame
• Helps in assessing adaptive efficiency of population
or region to climate change
• Predicts probability distribution of outcomes due to
climate change under different risk scenarios
• Vulnerability of population / region can be captured
through simple proxy variables (poverty,
infrastructure, etc.) or a more comprehensive index
• Permits mapping of climate change scenarios with
vulnerability scenarios over a period of time
BASIC Project India Workshop,
New Delhi, May 2006
Adaptive Efficiency and the Vulnerability
Context
Poverty
Extreme Events
Uncertainty
Persistent
Stochastic
Probability
RISK
VULNERABILITY
BASIC Project India Workshop,
New Delhi, May 2006
Framework for using adaptive efficiency
Climate Change
Risk
Outcomes / Scenarios
Impact
Poverty
Infrastructure
Demography
A d a p t i v e E f f i c i e n c y
Final Impact on Population / Region
Vulnerability Context of Population / Region
BASIC Project India Workshop,
New Delhi, May 2006
Economy
Adaptive efficiency = ƒ (income, infrastructure, literacy, poverty,
institutions, extremes, occupational distribution, risk)
Vulnerability arising
Description of Variables
Expected Relationship
from
Income
Income per capita
Inverse Relationship
Infrastructure
Performance measured in terms of
↑ proxies
composite index of infrastructure
Literacy
Literacy Rate
↓ Vulnerability
Institutions
Institutional support
Occupational
Index of occupational distribution
Distribution
of workforce (composite index)
Risk
risk bearing capacity based on
alternate sources of income support
Poverty
Incidence of poverty
Direct Relationship
Extremes
Number and intensities of extreme ↑ proxies ↑ Vulnerability
events BASIC Project India Workshop,
New Delhi, May 2006
Preliminary Findings (Extreme Events)
• In developing countries like India, climate change could represent
an additional stress on ecological and socioeconomic systems that
are already facing tremendous pressures due to rapid urbanization,
industrialization and economic development
• With regards to India it can be said that the Eastern Coast is more
vulnerable than the Western Coast with respect to the frequency of
occurrence of extreme events like cyclones and depressions with
the districts of Orissa and Andhra Pradesh being the most
vulnerable followed by the districts in Tamilnadu
BASIC Project India Workshop,
New Delhi, May 2006
Puri
Cuttack
Balasore
Srikakulam
Vishakapatnam
East Godavari
Nellore
Ganjam
Krishna
Chengalpattu
Tanjaur
South Arcot
Ramanathpuram
Prakasam
Vizanagaram
Ratnagiri
Thane
Raigad
Guntur
Trichur
West Godavari
Malapuram
Tirunelveli
Kanyakumari
Ernakulam
Idukki
Kottayam
Dakshin
Trivandrum
Palghat
Uttar Kannada
Dhenkanal
Quilon
Kozhikode
Alleppey
Cannore
Frequency
Vulnerability in coastal India
Frequency of severe storms, storms and depressions
90
80
70
60
50
40
30
20
10
0
BASIC Project India Workshop,
New Delhi, May 2006
Districts
Preliminary Findings (Impacts)
• The maximum numbers of extreme events are reported in the
districts Cuttack and 24 – Parganas (1970-1990)
• But if we look at the death toll from the extreme events we find
Tanjaur, Cuttack and Nellore far ahead than the rest of the districts
• The coastal zones of Gujarat, Maharashtra and Karnataka report too
few extreme events (many districts reporting not even one extreme
event) and even the persons affected from these events are quite
low as compared to the states in the eastern coast.
• Therefore in terms of impacts of extreme events also the districts on
the eastern coast of India are more vulnerable than the western
coast
BASIC Project India Workshop,
New Delhi, May 2006
Preliminary Findings (Agricultural
Production)
•
•
•
•
•
•
The coastal zones in India are the major producers of paddy which
is cultivated in both the seasons
The districts on the eastern coast account for the majority of the
paddy production
The districts in Gujarat, Maharashtra and Karnataka perform very
low in production as compared to the eastern district
All the other districts exhibit a positive growth rates for production as
well as yield except for the districts in Gujarat
The average rate of growth of production and yields is more than
2% for all the districts on the eastern coast
Eastern coastal districts are major producers of rice, and adverse
climate change effects (increase in the frequency of occurrence of
extreme events) may have an impact on production and availability
of food grains
BASIC Project India Workshop,
New Delhi, May 2006
Production / Yield (%)
-2
-10
Production
-4
Yield
BASIC Project India Workshop,
New Delhi, May 2006
Midnapore
24-Paraganas
Puri
Ganjam
Cuttack
Nellore
Balasore
Guntur
Krishna
West Godavari
East Godavari
Srikakulam
Visakhapatnam
Uttara Kannara
Dakshina
Tirunelveli
Ramanthapuram
Tanjavur
Chengalpattu
South Arcot
Ratnagiri
Raigad
Thane
Kanyakumari
Amreli
Bharuch
Ahmedabad
Junagadh
Jamnagar
Bhavnagar
Surat
Compounded Rate of Growth of Production and Yield
6
4
2
0
-6
-8
Districts
BASIC Project India Workshop,
New Delhi, May 2006
Preliminary Findings
• The overall production over the years is sharply increasing in all the
districts but with a lot of fluctuations
• The fallings trends in some particular years can be attributed to the
occurrences of extreme events
• This holds true in case of most of the districts in the earlier years
(1970-1980). Whenever there is occurrence of extreme events it is
always followed by decline in agricultural production
• In the later years, that is after the 1980s we find that the occurrence
of a particular event is not always followed by a decline in the
production values
• For example in the districts of West Bengal we see that the decline
in paddy production after the events is around 20-25% less than the
average production till 1982. After that although disasters were
reported the paddy production has not declined as a result of it
BASIC Project India Workshop,
New Delhi, May 2006
Preliminary Findings
•
Similar is the case for the districts in Orissa, Andhra Pradesh and
Tamilnadu
• In most of the cases we see that till the early 80s there is a decline
in paddy production in subsequent time periods due to the
occurrence of extreme events
• This pattern is not reflected in later years especially in the years
after 1985
BASIC Project India Workshop,
New Delhi, May 2006
Conclusions
• Methodologically it is very difficult to separate climate effects from
other factors such as technological change and economic
development, because of the complexities of these systems
• In terms of our results also we see that there is some evidence of
adaptation process in terms of the population as far as agriculture is
concerned
• This is just some preliminary evidence and cannot be generalized as
a final result and more rigorous analysis needs to be done in terms
of other sectors of the economy before generalizing this finding
• In the present study one of the limitations has been that we have
looked only at the agricultural setup. Future research should aim at
studying the dynamics of the social-economic system
BASIC Project India Workshop,
New Delhi, May 2006