addressing vulnerability to climate variability & change through an assessment of issues &...
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Addressing Vulnerability To Climate Variability & Change Through An Assessment Of Issues & OptionsTRANSCRIPT
Addressing vulnerability toclimate variability and change
through an assessment of issuesand options
TERI studySupported 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 thecoping capacities of communities in dealingeffectively with climatic extremes including droughtsand floods
• Timeframe: started May 2005 (still continuing)
Broad objectives• Reviewing coping strategies being employed by
communities in India and assessing issues andopportunities 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 copingmeasures are being employed and the factorsinfluencing their implementation
• Identifying/ suggesting measures to enhanceadaptive capacities
» Incremental in nature than those currently being employedto cope during with such circumstances
Preliminary discussions and consultationsPennar in Andhra Pradesh, Mahanadi in Orissa,Godavari in Maharashtra
Basin selection and mappingof vulnerability
GIS based quantitative analysis forselection of districts within sites
1) InfrastructureDevelopment
2) Irrigated area3) Presence of
agricultural creditsocieties
1) Labourer/Cultivator Ratio
2) Land undercultivation
3) Populationdensity
1) Soil severity2) Soil cover3) Groundwater
exploitation
Economic &technologicalvulnerability
Social vulnerabilityPhysical vulnerability
Quantitative Indicators
Principles, Criteria and Indicators Approach to quantitatively assess the vulnerabilityaspects
AP VulnerabilityIndex
Focus: Chittoorand Anantapur1991: Anantapur –very high vul &Chittoor – high vul2001: Shift to high vulin AnantapurKURNOOL
ADILABAD
KHAMMAM
ANANTAPUR
PRAKASAM
CHITTOOR
NELLORECUDDAPAH
MEDAK
GUNTUR
NALGONDA
MAHBUBNAGAR
WARANGAL
KRISHNA
KARIMNAGAR
VISAKHAPATNAM
NIZAMABAD
EAST GODAVARI
RANGAREDDI
SRIKAKULAM
WEST GODAVARI
VIZIANAGARAM
HYDERABAD
Selection of villages
Gada Sampat, Deipur,Raibaidar, Tarasahi,Naugaon, Sunadia Kanda
Puri andJagatsinghpur
Orissa
Karanji, Malewadi,Hiwrebazaar, Karegaon,Korhate
Ahmednagar andNasik
Maharashtra
Katherapalli, PathpalayamHarijanwada,Chinnapongapalle,Neramatla, Manesamudram,and Brahmanapalle
Chittoor andAnantapur
AndhraPradesh
VillagesDistrictsState
Case study: Andhra Pradesh• In all 23 districts, 13
declared drought prone• Three regions: Coastal,
Telangana andRayalseema
• FOCUS REGION:Rayalseema,
• Lies in the Pennar RiverBasin
• Comprises districts ofChittoor, Anantapur,Kurnool & Cuddapah.
• FOCUS DISTRICTS:Chittoor &Anantapur
• SURVEYS: 6 villages, 2 perdistrict
Agro-climatic conditions of thePennar
• Rainfed; lies in the rain shadow of W. Ghats,lowest rainfall among the three regions (650mm/year).
• Predominantly covered by red and black soil, poornutrient quality.
• Chittoor: dry-sub-humid zone, 700-1000 mm/yearaverage rainfall, red loamy soils, cultivation ofpaddy and sugarcane possible.
• Anantapur: scarce rainfall zone, 500-700 mm/yraverage rainfall, red sandy soils, cultivation ofcoarse millets, pulses, groundnut
• Chittoor more favourable agro-climatically,irrigation (31 % as opposed to 12 % in Anantapur)
Defining the baseline
• Focus largely on agricultural dependentcommunities and households.
• Unit of investigation: land categories (LC)• Households chosen based on stratified random
sampling, and classified into four LCs: large (> 4acres), medium (1-3 acres), small/marginal (< 1acres) 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 (NonAgricultural Labour NAL, Petty Business, Dairy andRemittances).
• Agriculture (climate-sensitive) main source of income(82% in Chittoor, 95% in Anantapur). This means thatvulnerability to climatic stress is congruously high.
• However, differential vulnerabilities exist givena.geographical location, agro-climatic conditionsb.degree of dependence on agriculture, safety nets,
infrastructural facilities, institutions/social networks etc
Sources of Income
• Average annual NY incomes higher in Chittoor (Rs32650), than Anantapur (Rs 22300).
• LC 1: 81% of income from cultivation. Second largestsource is NAL (higher incomes obtained, as educationallows for taking up jobs as teachers, doctors, ingovernment etc). Income diversification (income apartfrom agriculture) limited, as reliant on safety nets builtup in a normal year.
• LC 2: little more than half of their income fromcultivation, 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 AdaptiveStrategies
• Terms cannot be clubbed into water-tightcompartments, 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 inoccupation, temp migration, availing of credit/loan,changes in cropping pattern
• Adaptive: long-term/reactive/boosts resilience: incomediversification (one main activity, with a cluster ofactivities 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 acrosslandholdings– 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 wellbeing.
• Income Impact Indexacross land categoriesand villages
• Coping Variables:Distinguish b/w ‘reactivetemporary’ & ‘long-term’measures.
• Identifying significantvariables that helphouseholds ‘maintain’income levels, i.e., cope.
Income Impact IndexMean income = (Normal+Impactincome)/2Variance =
Standard deviation = square root(variance)Coefficient of Variation = (Standarddeviation/mean)*100
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Income Impact Index
• Quantitative Assessment of vulnerability.• Assumption: households undertaking ‘income-
smoothening activities’ (coping/adaptive), exhibitlower deviation in incomes from normal year.
• Values obtained maybe incongruous withperception (e.g., Brahmanapalle). But, credibilityin facts, since perceptions may be misleading!
• Significant strategies: availing credit/loans(68%), distress sale (33%, mainly jewellery), andshift 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 climaticstress– 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-institutionalfactors
• Role of government departments in enhancingadaptive capacities through implementation of plansand programmes
• Policies of the government to help communities copewith current climatic variability and drought and floodmitigation
• 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 regressionequation.
• Identifies variables that can lower the III (deviationsbetween NY and DY incomes), and hence can feedinto 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 moreincome.
b. Indebtedness ratio (credit/loan:NY income): higherthe ratio, the lesser the gap, as this amount is usedto tide over the stress period.
Thank you