Addressing vulnerability to
climate variability and change
through an assessment of issues
and options
TERI study
Supported by The World Bank
December 2006

Study highlights
• Rationale:
– agriculture an important sector, sensitive to climate,
millions dependent
• Overall goal:
– Identify issues and opportunities that enhance the
coping capacities of communities in dealing
effectively with climatic extremes including droughts
and floods
• Timeframe: started May 2005 (still continuing)

Broad objectives
• Reviewing coping strategies being employed by
communities in India and assessing issues and
opportunities for adaptation
» study focus on drought and flood affected regions
» distinguish between reactive temporary mechanisms and
measures for strengthening the adaptive capacities
» links with developmental aspects will be explored
• Assessing the effectiveness with which coping
measures are being employed and the factors
influencing their implementation
• Identifying/ suggesting measures to enhance
adaptive capacities
» Incremental in nature than those currently being employed
to cope during with such circumstances

Basin selection and mapping
of vulnerability
Preliminary discussions and consultations
Pennar in Andhra Pradesh, Mahanadi in Orissa,
Godavari in Maharashtra

GIS based quantitative analysis for
selection of districts within sites
Quantitative Indicators
Physical vulnerability Social vulnerability Economic &
technological
vulnerability
1) Soil severity 1) Labourer/ 1) Infrastructure
2) Soil cover Cultivator Ratio Development
3) Groundwater 2) Land under 2) Irrigated area
exploitation cultivation 3) Presence of
3) Population agricultural credit
density societies
Principles, Criteria and Indicators Approach to quantitatively assess the vulnerability
aspects

AP Vulnerability
Index
Focus: Chittoor
and Anantapur
1991: Anantapur –
ADILABAD
V IZIA NAG ARAM
very high vul &
SRIK AKULAM
NIZAMABAD
KARIMNAGAR
WA RANGAL VISAKHAPATNAM
Chittoor – high vul
MEDA K
KHAMMA M
EAS T GODAVARI
HYDERABAD
RANGAREDDI
WEST G ODAVARI
NA LGONDA
KRISHNA
2001: Shift to high vul
GUNTUR
MAHBUBNAGA R
in Anantapur
PRAKASAM
KURNOOL
ANANTAPUR
CUDDAPAH
NELLO RE
CHITTOOR

Selection of villages
State Districts Villages
Andhra Chittoor and Katherapalli, Pathpalayam
Pradesh Anantapur Harijanwada,
Chinnapongapalle,
Neramatla, Manesamudram,
and Brahmanapalle
Maharashtra Ahmednagar and Karanji, Malewadi,
Nasik Hiwrebazaar, Karegaon,
Korhate
Orissa Puri and Gada Sampat, Deipur,
Jagatsinghpur Raibaidar, Tarasahi,
Naugaon, Sunadia Kanda

Case study: Andhra Pradesh
• In all 23 districts, 13
declared drought prone
• Three regions: Coastal,
Telangana and
Rayalseema
• FOCUS REGION:
Rayalseema,
• Lies in the Pennar River
Basin
• Comprises districts of
Chittoor, Anantapur,
Kurnool & Cuddapah.
• FOCUS DISTRICTS:
Chittoor &Anantapur
• SURVEYS: 6 villages, 2 per
district

Agro-climatic conditions of the
Pennar
• Rainfed; lies in the rain shadow of W. Ghats,
lowest rainfall among the three regions (650
mm/year).
• Predominantly covered by red and black soil, poor
nutrient quality.
• Chittoor: dry-sub-humid zone, 700-1000 mm/year
average rainfall, red loamy soils, cultivation of
paddy and sugarcane possible.
• Anantapur: scarce rainfall zone, 500-700 mm/yr
average rainfall, red sandy soils, cultivation of
coarse millets, pulses, groundnut
• Chittoor more favourable agro-climatically,
irrigation (31 % as opposed to 12 % in Anantapur)

Defining the baseline
• Focus largely on agricultural dependent
communities and households.
• Unit of investigation: land categories (LC)
• Households chosen based on stratified random
sampling, and classified into four LCs: large (> 4
acres), medium (1-3 acres), small/marginal (< 1
acres) and landless.
• Number of households surveyed: 570
• Concentration of households in the medium (47%)
and landless categories (30%)

Baseline contd….
• Information on incomes of households collected for a
‘normal year’ and an ‘impact (drought) year’.
• Incomes classified as Agricultural (cultivation and
agricultural labour AL) and Non Agricultural (Non
Agricultural Labour NAL, Petty Business, Dairy and
Remittances).
• Agriculture (climate-sensitive) main source of income
(82% in Chittoor, 95% in Anantapur). This means that
vulnerability to climatic stress is congruously high.
• However, differential vulnerabilities exist given
a. geographical location, agro-climatic conditions
b. degree of dependence on agriculture, safety nets,
infrastructural facilities, institutions/social networks etc

Sources of Income
• Average annual NY incomes higher in Chittoor (Rs
32650), than Anantapur (Rs 22300).
• LC 1: 81% of income from cultivation. Second largest
source is NAL (higher incomes obtained, as education
allows for taking up jobs as teachers, doctors, in
government etc). Income diversification (income apart
from agriculture) limited, as reliant on safety nets built
up in a normal year.
• LC 2: little more than half of their income from
cultivation, with the rest divided between AL and NAL.
• LC3 and LC 4: AL is major source of income.
• LC1 and LC 4: extreme cases.

Impacts, Coping and Adaptive
Strategies
• Terms cannot be clubbed into water-tight
compartments, define for each case study. E.g.,
distress sale as an impact or as a coping measure.
• Impacts: drops in agricultural production/productivity,
water scarcity, food intake, consumption expenditure,
drop out of school and health status.
• Coping : short-term/proactive: distress sale, shift in
occupation, temp migration, availing of credit/loan,
changes in cropping pattern
• Adaptive: long-term/reactive/boosts resilience: income
diversification (one main activity, with a cluster of
activities supplementing it).

Impact indicators
• Fall in acreage, water availability and crop
production
– 44 to 100 % (acreage)
– Production only 4 % on comparison with normal
year
– Depth of water 300 to 400 feet
• Health and education, varies across
landholdings
– 12 % reported ill-health and 10 % fall-out on
education
• Sharp decline in incomes
– Highest impact on cultivators (large landholders)
• Monotonic relationship between large
landholdings and proportion of incomes

Impact on Incomes
• A vast drop in total average incomes of 65%
• Drop in incomes decreasing from larger to smaller
land categories
• Drops in income from cultivation are 92 %. All land
owning categories experience similar drops
• Drops in income from dairy activities are 40%
• Labour incomes increases by 46% for households
that fall in the large land category
• Remittance income registers a marginal increase of
3%

World Bank Study – droughts in AP
• Income proxy of well Income Impact Index
Mean income = (Normal+Impact
being. income)/2
Variance =
• Income Impact Index
across land categories Standard deviation = square root
(variance)
and villages Coefficient of Variation = (Standard
deviation/mean)*100
• Coping Variables:
Distinguish b/w ‘reactive 9LOODJHV ,,,
temporary’ & ‘long-term’ /DQG ,,,
&DW
.DWKHUDSDOOL 
measures.   3DWKSDOD\\DP + 
 
&KLQQDSRQJDSDOOH 
• Identifying significant  
1HUDPDWOD 
variables that help   0DQHVDPXGUDP 
households ‘maintain’ 7RWDO 
%UDKPDQDSDOOH 
income levels, i.e., cope.

Income Impact Index
• Quantitative Assessment of vulnerability.
• Assumption: households undertaking ‘income-
smoothening activities’ (coping/adaptive), exhibit
lower deviation in incomes from normal year.
• Values obtained maybe incongruous with
perception (e.g., Brahmanapalle). But, credibility
in facts, since perceptions may be misleading!
• Significant strategies: availing credit/loans
(68%), distress sale (33%, mainly jewellery), and
shift in occupation (28%)

Community responses
• Strategies deployed/developed by
communities
– Change in cropping intensity
– Income diversification
– Distress sale of cattle, land and jewellery
– Credits/ loans
• External factors that aid response to climatic
stress
– Infrastructure development
• Village Neramatla and its dependence on agriculture
• Village Mansamudram and connectivities
– Income diversification
• Proximity to a town/ city; village Katherapalli
– Ability to diversify cropping patterns

Institutional/ non-institutional
factors
• Role of government departments in enhancing
adaptive capacities through implementation of plans
and programmes
• Policies of the government to help communities cope
with current climatic variability and drought and flood
mitigation
• Role of local institutions in strengthening capacities:
SHGs, banks and agricultural credit societies
• Role of community institutions and their strengths
• Role of private sector

Issues for consideration
• Obtained from the simultaneous regression
equation.
• Identifies variables that can lower the III (deviations
between NY and DY incomes), and hence can feed
into policy interventions.
• Significant variables:
• Education(formal/skillsets): increases ability to
diversify.
a. No. of working members in the family (especially
for LC4): more helping hands, brings in more
income.
b. Indebtedness ratio (credit/loan:NY income): higher
the ratio, the lesser the gap, as this amount is used
to tide over the stress period.

Thank you