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BASIC Project India Workshop, New Delhi, May 2006 Tools for Assessing Vulnerability and Adaptation IIT Bombay Team K.Narayanan, D.Parthasarathy, Unmesh.

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Presentation on theme: "BASIC Project India Workshop, New Delhi, May 2006 Tools for Assessing Vulnerability and Adaptation IIT Bombay Team K.Narayanan, D.Parthasarathy, Unmesh."— Presentation transcript:

1 BASIC Project India Workshop, New Delhi, May 2006 Tools for Assessing Vulnerability and Adaptation IIT Bombay Team K.Narayanan, D.Parthasarathy, Unmesh Patnaik

2 BASIC Project India Workshop, New Delhi, May 2006 Assessment of Vulnerability Vulnerability Index Assessment of Adaptation Adaptive Efficiency Tool

3 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.Policies and institutions 2.Market 3.Government 4.Physical infrastructure 5.Social infrastructure 6.Demographic factors (population growth, density, literacy)

4 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?

5 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

6 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

7 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

8 BASIC Project India Workshop, New Delhi, May 2006 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. Vulnerability Index

9 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)

10 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

11 BASIC Project India Workshop, New Delhi, May 2006 Studies pertaining to assessment of vulnerability: StudyYearVulnerability Arising From Watson et al.1995IPCC Indicators Zeidler1997Sea Level Rise Rosenzweig & Parry / Dehn & Buma1994 / 1999 Landslide Activities Blaikie et al.1994Human Dimensions (Pressure and release model) Wisner1999Earthquake, Hurricane Watts and Bohle1993Famines Adger and Kelly 1996,2001 Entitlement approach in terms of access to resources OBrien and Liechenko2002Climate Change and Access to resources Smit and Pilifosova; Bohle; Downing2002 Vulnerability = (Exposure to a stimulus, capacity to adjust to it) Ghazala Mansuri and Andrew Healy2002Probability of future poverty Ethan Ligon and Laura Schecter2002Loss associated with different sources of uncertainty Shubham Chaudhuri2001Household Vulnerability to poverty M.A. Chen1991Poverty, lack of access to food (entitlements) W.E. Riebsane, S.A. Changnon Jr. and T.R. Karl1991Drought Gunther Fischer, Mahendra Shah, and Harriz vanValthuizen 2002Agricultural vulnerability

12 BASIC Project India Workshop, New Delhi, May 2006 Quantifying Vulnerability : Settlement Food Health Ecosystems Water Sensitivity sectorsCoping and Adaptive Capacity sectors Economy Human Resources Environment Sensitivity Indicators Coping-Adaptive Capacity Indicators Source: Moss et.al., (2001) National Baseline estimates and projections of Sectoral- Indicators

13 BASIC Project India Workshop, New Delhi, May 2006 Sources and Indicators of Vulnerability: Vulnerability Index Demographic Vulnerability Climatic Vulnerability Occupational Vulnerability Density of Population Literacy Rate Variance in annual rainfall Variance in June- July-August Rainfall Frequency of extreme events Agricultural Vulnerability Production of Rice Cropping Intensity Area under Cultivation Irrigation Intensity No. of Cattle and Livestock Total Workers Agricultural Laboureres Manufacturing Labourers Non Workers

14 BASIC Project India Workshop, New Delhi, May 2006 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

15 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.

16 BASIC Project India Workshop, New Delhi, May 2006 Vulnerability Index: Findings

17 BASIC Project India Workshop, New Delhi, May 2006 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

18 BASIC Project India Workshop, New Delhi, May 2006 Adaptive Efficiency and the Vulnerability Context RISK VULNERABILITY Uncertainty Extreme Events Probability Poverty StochasticPersistent

19 BASIC Project India Workshop, New Delhi, May 2006 Framework for using adaptive efficiency Climate ChangeRisk Outcomes / Scenarios Final Impact on Population / Region Impact PovertyInfrastructureDemographyEconomy Vulnerability Context of Population / Region A d a p t i v e E f f i c i e n c y

20 BASIC Project India Workshop, New Delhi, May 2006 Adaptive efficiency = ƒ (income, infrastructure, literacy, poverty, institutions, extremes, occupational distribution, risk)

21 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

22 BASIC Project India Workshop, New Delhi, May 2006

23 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

24 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

25 BASIC Project India Workshop, New Delhi, May 2006

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27 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

28 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

29 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


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