ifpri- climate change and food security - p s birthal, ncap
DESCRIPTION
The presentation was part of the Food Security in India: the Interactions of Climate Change, Economics, Politics and Trade workshop, organized by IFPRI-CUTS on March 11 in New Delhi, India. The project seeks to explore a model for analyzing food security in India through the interactions of climate change, economics, politics and trade.TRANSCRIPT
Pratap S Birthal
National Centre for Agricultural Economics and Policy Research
New Delhi, India
In the past century,
India warmed by 0.68°C, that is 0.07 °C per decade ; and at an accelerated
rate (0.08 °C) in the past four decades.
India experienced many extreme climatic events such droughts, floods,
cyclones and heat waves. Between 1876 and 2009 India experienced a total
of 40 droughts of which 24 occurred until the mid-1960s, and 16 occurred
between 1965 and 2009. In the latter period, five droughts were of severe
droughts.
Agriculture is more sensitive to climate change, hence will be more
threatened by it than any other activity.
By end of 21st century, with climate change crop yields will lower by 10 to 40%.Given the little scope to increase production through area expansion, this will reducefood supplies, which will threaten food security.
Small farmers and poor consumers will suffer more from climate change because of
heavy dependence on agriculture and lack of financial resources for mitigation and
adaptation
Exposure to climate change: recent trends in temperature and precipitation
Impact of climate change on agricultural productivity (aggregate and crop-wise)
Adaptation strategies: Farm level, community level, Intermediate level institutions
Recent Trends in Climate Variable
All India Humid Semi-arid
temperate
Arid-
semi-arid
tropics
Mean monthly temperature (°C)
Annual 0.30*** 0.22*** 0.30*** 0.34***
Rabi 0.38*** 0.28*** 0.26*** 0.45***
Kharif 0.31*** 0.24*** 0.31*** 0.33***
Total seasonal rainfall (mm)
Annual -17.93 -16.62 -95.94*** 7.11
Rabi 0.57 31.41*** -1.31 -10.31**
Kharif -22.90** -53.14* -94.95*** 11.95
Production
function or
crop
modeling
Scientific controlled experiments. Fail to
realize the behavioral response of
farmers.
Ricardian
approach
Ceteris paribus, the regional differences in land value or
productivity are determined by the differences in their
climatic conditions. Assumptions : land value a reflection
of PV of profits, while it is not because of market
imperfections. Unable to capture adjustment.
Panel data
approachTime is an important dimension of
climate change, vulnerability and
adaptation.
We use fixed
effect panel
data
approach to
estimate
effects of
climate
change on
agricultural
productivity.
Panel data suggests that
individuals, firms, states or
countries are heterogeneous.
In panel data (fixed effect) approach the
geographical fixed effects control for all
local characteristics that may be correlated
with climate, which cannot be captured in
cross section studies
More informative data, more variability, less
collinearity among the variables
long term dataset are better able to capture
the evolution of climatic variables and
the resultant adaptation by farmers
What we have used?
District level data on area and production of 19 crops along with other
variables (GCA, irrigated area) for the period 1969 to 2005 for 200
districts at 1970 base. These crops constitute around 90% of the gross
cropped area in the districts
We estimate total value of output of these crops multiplying their
production with farm harvest prices of the triennium ending 2004-05.
VOP then divided by the total area under these crops to obtain the gross
revenue per hectare or agricultural productivity
Rainfall and temperature were extracted from 1 x 1 degree high resolution
daily gridded data for the period of 1969–2005
Two main growing seasons, viz. kharif and rabi . We specify growing
period mean values of temperature and total rainfall in our model
Subscript i and t denotes district and time.
Variable description
Y = Gross returns per hectare
KT = Average kharif temperature (June to September)
RT = Average rabi temperature (October to February)
KR = Total kharif rainfall (June to September)
RR = Total rabi rainfall (October to February)
IR = Area irrigated (%)
D = District dummies
T = Time dummies (from 1969 to 2005)
•Reduces excessive variation or noise
•Regression coefficients are estimated in
proportionate terms and are easily
interpreted as per cent change
log-linear
form
•Non-linear effects of
temperature and rainfall
Quadratic and
interaction
terms
• irrigation and its interactions with
weather variables
• Time dummies for technological
adaptations……
Accounting
for adaptive
response
The model is estimated for all India as well as three homogeneous
agro-climatic zones, viz. humid, semi-arid temperate, and arid and
semi-arid tropics.
Some
observations
from panel
regressions
Excess rainfall in kharif as well as rabi is
damaging
Interactions of rainfall and temperature have a
statistically significant impact on agricultural
productivity
Irrigation mitigates harmful impacts of higher
temperatures as well as low rainfall
Estimated results
All India Humid Semi-arid temperate Arid-Semi-arid tropics
Without
irrigation
With
irrigation
Without
irrigation
With
irrigation
Without
irrigation
With
irrigation
Without
irrigation
With
irrigation
RT -0.0395 -0.0313 -0.0370 -0.0311 -0.02178 -0.0194 -0.0368 -0.0276
KT -0.0545** -0.0452** 0.0159 0.0156 0.0138 0.0116 -0.0883** -0.0749**
RR 0.00019** 0.00025** -0.00003 -0.00001 0.00015 0.00017** 0.00043** 0.00048**
KR 0.00018** 0.00018** 0.00009** 0.00009** 0.00005** 0.00006** 0.00025** 0.00024**
Estimated marginal effects:
Temperature Rainfall
Wheat -0.0577** 0.0002182**
Chickpea -0.0642** 0.0000813
Barley -0.0054 0.0004244**
Rape- Mustard 0.0101 -0.0000676
Climate impact by crop: Marginal effect : All India
Rice -0.0910** 0.000266**
Sorghum -0.0592** 0.0001096**
Groundnut -0.0704** 0.0002022**
Cotton -0.0188 0.000091**
Pigeon pea -0.1112** 0.0002432**
Months 2010-39 2040-69 2070-99
Temp
(degrees) A1F1 B1 A1F1 B1 A1F1 B1
DJF 1.17 1.11 3.16 1.97 5.44 2.93
JJA 0.54 0.55 1.71 0.88 3.14 1.56
SON 0.78 0.83 2.41 1.49 4.19 2.17
Rainfall
(%)
DJF -3 4 0 0 -16 -6
JJA 5 7 13 11 26 15
SON 1 3 8 6 26 10
Scenario All India Humid Semi-arid temperate Semi-arid tropics
Without
irrigation
With
irrigation
Without
irrigation
With
irrigation
Without
irrigation
With
irrigation
Without
irrigation
With
irrigation
2010-39
A1F1 -6.07 -4.76 -2.11 -1.57 -1.19 -1.03 -7.58 -6.01
B1 -5.69 -4.33 -1.85 -1.31 -1.04 -0.86 -7.07 -5.49
2040-69
A1F1 -18.26 -14.31 -5.96 -4.41 -3.15 -2.73 -22.98 -18.21
B1 -9.90 -7.61 -3.62 -2.67 -2.09 -1.76 -12.15 -9.46
2070-99
A1F1 -32.10 -25.11 -9.55 -6.90 -5.08 -4.37 -40.87 -32.43
B1 -16.27 -12.67 -5.06 -3.66 -2.79 -2.38 -20.57 -16.25
Projected Impacts
A1F1 B1Chickpea -30.9 -16.4
Wheat -27.7 -14.7Rice -22.5 -10.7Groundnut -17.5 -8.3Sorghum -16.1 -7.8Pigeon pea -14.2 -6.5Cotton -3.9 -1.8Barley -2.3 -1.3Rapeseed-mustard 4.8 0.5
Projected impacts by crop to
2080-2099
In other words, a year will be a drought year if temperature goes
above its long term average and rainfall goes below its long term
average
The deviations are standardized by district-specific SD, and DI
(severity) is expressed as the product of the standardized
deviations.
This specification: lays relatively more stress on larger deviations,
both in rainfall and temperature.
The index is estimated for kharif season and for rice growing
districts
Advantages of the index: (1) based on both the degree of dryness
and hotness; (2) contains local weather information (3) provides
severity of drought for each district
Drought index: degree of hotness and dryness
Distribution of districts by DI (lower
truncation at DI 0.1)
1969-1987 1988-2005
1969-
2005
Severity
% of total
events
% of total
area
affected
% of
total
events
% of
total
area
affected
% of
total
events
% of
total
area
affected
Low
(0.1<DI<0.5) 50.2 48.8 61.2 62.1 55.8 55.5
Medium
(0.5<DI<1.5) 27.9 28.8 30.7 27.9 29.3 28.3
High
(DI>1.5) 21.9 22.5 8.1 10.0 14.9 16.1
Total 100 100 100 100 100 100
Incidence of drought and its severity
0
10
20
30
40
50
60
70
80
196
9
197
0
197
1
197
2
197
3
197
4
197
5
197
6
197
7
197
8
197
9
198
0
198
1
198
2
198
3
198
4
198
5
198
6
198
7
198
8
198
9
199
0
199
1
199
2
199
3
199
4
199
5
199
6
199
7
199
8
199
9
200
0
200
1
200
2
200
3
200
4
200
5
per
cen
t
Low Medium High
Distribution of droughts by severity
Drought and rice productionLow
intensity
Medium
intensity
High
intensity
Period (1969-1987)Average yield (Kg/ha) 1303 1145 984
Yield loss (Kg/ha) -57.8 -113.5 -234.0
Per cent loss -4.4 -9.9 -23.8
Period (1988-2005)Average yield (Kg/ha) 1801 1633 1627
Yield loss (Kg/ha) -8.9 -93.2 -143.3
Per cent loss -0.5 -5.7 -8.8
Climate impacts will largely be driven by rise in temperature.
Frequency of extreme climatic events has increased
Arid and semi-arid tropics will be more impacted by climate
change
Irrigation is important to minimize harmful impacts of climate
change
Agriculture is becoming resilient to droughts because of
emphasis of R&D on breeding for drought-tolerance,
improvements in management of water resources diversification
Layers of resiliency
Farm levelCrop and varietal adjustment – drought tolerant and
extensive root crop
Crop management practices - changes in inputs, timings,
tillage
Intercropping and mixed cropping
Irrigation practices,
Crop rotation, crop choice, crop and Income
diversification
Crop harvesting and processing
Agro forestry – Agri-silvi-horti-pastoral system
Social Group action - social networks, information
dissemination, migration
SHGs, community projects, coping strategies,
Local water management techniques, in-house
conflict resolution,
TechnologicalMicro-irrigation, conservation agriculture, in-
situ, ex-situ, water harvesting, flood mitigation,
land drainage, Phonemics and other frontier
technologies
Institutional and policyGovernment policy and program (NAPCC,
DPAP, DDP, IWMP, PDS, MNREGA)
Agro and weather advisory – Information
access
Evidence based policy
Strengthening governance structure
Adaptation to climate
change to improve
food security
Rice: Sahbhagi Dhan, drought-tolerant and Swarna-Sub 1,
submergence tolerant varieties
Wheat: To adjust to the rising temperature heat-tolerant wheat
varieties like DBW 14, DBW 16, Raj 3765, Lok 1 and GW 322 etc.
Chickpea e.g. JG11, that are tolerant to heat being promoted in the rainfed
areas.
Returns to investment : 5-10 per cent higher crop yield and an internal rate
of return of 29-167 per cent on investment in drought-tolerance rice
research
Benefits of drought-tolerant wheat and maize (Kostandini, 2008) and
groundnut (Birthal et al., 2012) has brought out that adoption of drought-
tolerant varieties can reduce production risks by 30-50%.
Risk benefits :drought-tolerant groundnut :yield advantage of 23 %;
Reduction in yield variability by 30 %. Benefits due to (i) yield improvement
(65%) and (ii) reduction in variance (35%).
Irrigation can reduce harmful effect of climate change on agricultural
productivity by 20-25 per cent
In India about half of the cropped area receives irrigation, mostly through flooding,
implying considerable loss of water. Irrigation efficiency of surface water resources
:35 to 40 per cent, for ground water, it is about 65-75 per cent.
Drip irrigation technology in horticultural crops can save water by 12-84 per cent,
reduce energy consumption by 29-45 per cent and improve crop yields by 7-98
per cent
Area under micro-irrigation has not exceeded 4 million hectares, as
against the potential of 42 million hectares (Palanisami et al.,
2011).
The 12th Five-Year Plan targets bringing 10.1 million hectares under
micro-irrigation
Laser land levelling; Zero tillage; SRI; Directed Seeding are other options to
improve water use efficiency.
Hydrogel:, a water-absorbing hydrogel has been developed, which when
applied to the soil, imbibes available water, retains it over a period and
releases it for use by plants when they need. This technology has been
evolved specifically to suit the hot tropical and semi-tropical climates. Only
a small quantity of gel (2.5-3.75kg/ha)
The gel has the ability to co-exist with fertilizers, notably urea, is free of
any toxin and can last at least for one full crop season. Additionally, this
product has been found to improve physical health of soil by loosening the
compact soil to enhance crop yields.
In farmers’ fields, the gel has been found to improve seed germination and
reduce requirement of fertilizers and an improvement in crop yields by
about 20 per cent.
Agriculture is likely to become knowledge-intensive. Farmers willdemand varied types of information to take rational decisions inrespect of choice of crops, inputs and technologies to adapt toclimate change.
Net returns/ha
Number of sources Sub-
marginal(0.5ha)
Marginal (0.5-1.0ha)
Small (1.0-2.0ha)
Medium (2.0-4.0ha)
Large (>4.0ha)
All
Non user 10482 9024 8393 7765 6158 7959One source 9871 9957 8547 9709 6982 8826Two sources 12679 10599 9928 9256 8063 9580
Three or more sources 14561 12398 10307 9785 9623 10209
Any source 11024 10146 9078 9569 7784 8994
• Only about 40 per cent of the farm households in India have access to agricultural information mostly from fellow farmers and input dealers.
• One lakh+ Extension workers, more than 600KVKs, Kisan call centres; mobile telephony
Total expenditure (Rs billion) at current prices
As % of total budget
As% of GDP
2006-07 701.7 12.1 1.72007-08 911.8 12.9 1.9
2008-09 1387.2 15.4 2.62009-10 1569.4 15.4 2.7
Poverty alleviation,
livelihood and food
security
74.27%
Health improvement
and prevention of
diseases
7.59%
Land development,
drought proofinh,
irrigation and flood
control
7.40%
Agriculture and
allied sectors
7.50%
Risk financing
1.42%
Forest, biodiversity
and wildlife
conservation
0.75%
Water resources
0.69%
Disater
management
0.27%
Coastal,
marine and
ocean
management
0.11%
A farmer will adapt when the cost of adaptation is less than the
benefit of avoiding impact of climate change. It is thus important to
understand the cost-benefit aspect of implementing any adaptation
measure. If the cost of adaptation outweighs the benefits then such
a measure would not be viable.
There are not many studies that look at this aspect.
Usually, the literature ends a study by suggesting a
menu of measures without relevant cost-benefit
estimates of the same.
It may not be possible to itemize and monetize all the possible
current and future costs and benefits in the present context.
However, it will still provide as a guiding tool to have some
measures such as averted loss of crops production, cost of
implementing a new irrigation system, etc.
Thank You...