IFPRI- Climate Change and Food Security - P S Birthal, NCAP

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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.

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IFPRI- Climate Change and Food Security - P S Birthal, NCAP

  1. 1.  Pratap S Birthal  National Centre for Agricultural Economics and Policy Research  New Delhi, India
  2. 2.  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 reduce food 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
  3. 3.  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
  4. 4. Recent Trends in Climate Variable
  5. 5. 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
  6. 6. 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 approach Time is an important dimension of climate change, vulnerability and adaptation.
  7. 7. 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?
  8. 8. 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
  9. 9. 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)
  10. 10. •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
  11. 11. 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
  12. 12. 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:
  13. 13. 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**
  14. 14. 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
  15. 15. 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
  16. 16. A1F1 B1 Chickpea -30.9 -16.4 Wheat -27.7 -14.7 Rice -22.5 -10.7 Groundnut -17.5 -8.3 Sorghum -16.1 -7.8 Pigeon pea -14.2 -6.5 Cotton -3.9 -1.8 Barley -2.3 -1.3 Rapeseed- mustard 4.8 0.5 Projected impacts by crop to 2080-2099
  17. 17. 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
  18. 18. Distribution of districts by DI (lower truncation at DI 0.1)
  19. 19. 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
  20. 20. 0 10 20 30 40 50 60 70 80 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 percent Low Medium High Distribution of droughts by severity
  21. 21. Drought and rice production Low 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
  22. 22. 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
  23. 23. Layers of resiliency Farm level Crop 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, Technological Micro-irrigation, conservation agriculture, in- situ, ex-situ, water harvesting, flood mitigation, land drainage, Phonemics and other frontier technologies Institutional and policy Government 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
  24. 24. 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%).
  25. 25. 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
  26. 26. 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.
  27. 27.  Agriculture is likely to become knowledge-intensive. Farmers will demand varied types of information to take rational decisions in respect of choice of crops, inputs and technologies to adapt to climate change. Net returns/ha Number of sources Sub- marginal (0.5ha) Marginal (0.5-1.0ha) Small (1.0- 2.0ha) Mediu m (2.0- 4.0ha) Large (>4.0 ha) All Non user 10482 9024 8393 7765 6158 7959 One source 9871 9957 8547 9709 6982 8826 Two 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
  28. 28. Total expenditure (Rs billion) at current prices As % of total budget As% of GDP 2006-07 701.7 12.1 1.7 2007-08 911.8 12.9 1.9 2008-09 1387.2 15.4 2.6 2009-10 1569.4 15.4 2.7
  29. 29. 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%
  30. 30. 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.
  31. 31. Thank You...

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