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Climate change impacts and Adaptation strategies to build the Resilience and farm household income of rainfed farming systems in SAT India.: AERA 2018 Dakshina etal

  1. Climate change impacts and Adaptation strategies to build the Resilience and farm household income of rainfed farming systems in SAT India S Nedumarana, Kadiyala M.D.Ma, Roberto Valdiviab, Sonali McDermidc, Srigiri Srinivas Reddyd, Jyosthnaa Pa, Geethalakshmi Ve and Anthony Whitbreada a International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, Hyderabad, India b Oregon State University, USA c New York University, USA d Social Outlook Consulting, Hyderabad e College of Agriculture, Tamil Nadu Agricultural University, Madurai, Tamil Nadu Special session on “Resilience in Dryland Agri-food systems to achieve SDG targets for India” 26th Annual Conference of Agriculture Economics Research Association (India) NDRI, Karnal, Haryana | 15-17 November 2018
  2. Study regions in south Asia and major farming systems Regional Integrated assessment: case study – Kurnool, AP, India • Characteristics of the regions • Key results: Climate, crop and economic assessment • Co-design and Development of RAPs with stakeholders Summary and key messages Overview
  3. South Asia: Study regions and major farming systems Pakistan: Punjab FS: Irrigated wheat-cotton India: Karnal FS: Irrigated rice-wheat; livestock India: Meerut FS: Irrigated rice-wheat; livestock India: Kurnool FS: Rainfed crop-livestock ‘Fallow-chickpea’ India: Trichy FS: Rainfed maize and/or irrigated rice systems
  4. Rainfed agriculture plays an important role in the livelihoods of rural households in SAT regions Occupies about 55 % (86 M ha) of net sown area and produce 40% of total food grain Highly vulnerable to the adverse impacts of climate variability Minimizing the risk and uncertainty is needed to sustainably increase the food production Increasing rainfed system productivity and climate resilience Introduction
  5. Methodology - Structural Approach Shahnila et al., 2016 Physiological Agronomic Crop Simulation models (process based) Economic models (IAT, TOAMD) Climate Stresses GCMs Technology adoption Yields, farm income, cash flows
  6. Core Questions Source: http://www.agmip.org/
  7. Region: Kurnool District, Andhra Pradesh, India Farming system: Rainfed crop-livestock FS 80% cropped area under RF Low rainfall zone (Avg. RF 760mm) dominated by black cotton soil (vertisols) facing labor scarcity Major crops: Chickpea, Rice, Sorghum, Groundnut cropping pattern: Fallow - Chickpea Characteristic of the study region Andhra Pradesh 0 50 100 150 200 250 300 199019911992199319941995199619971998199920002001200220032004200520062007200820092010 Croppedarea Kurnool Anantapur Prakasam YSR. Kadapa Medak Mahbubnagar Nizamabad in‘000ha
  8. Data Source SPIA HH survey data collected in 2011-12 crop season A representative sample of 1080 HHs from 90 villages of 7 districts in AP Kurnool districts – 351 sample HHs 156 HHs with detailed input/output plot level data 117 chickpea farms 46 sorghum farms 30 rice farms Andhra Pradesh, India Farm location in Kurnool district
  9. Stratification of HHs in Kurnool District Kurnool annual precipitation (mm) and chickpea crop distribution 1. Low rainfall with low potential region 2. Medium rainfall with high potential region
  10. Variables Units Obs Mean Std. Dev. Min Max Household size Numbers 42 5.1 1.6 2.0 9.0 Total own land Ha 42 4.6 3.4 0.0 15.2 Total operated land Ha 42 6.1 3.2 1.6 15.2 Total livestock Unit Numbers 42 1.7 3.2 0.0 20.0 chickpea area Ha 42 3.6 2.1 0.8 8.4 chickpea yield Kg/ha 42 258.5 89.8 149.5 500.0 chickpea price Rs/kg 42 35.1 4.0 28.5 40.0 chickpea TVC Rs/ha 42 17754.0 4644.0 9525.0 31008.3 Legumes and Oilseeds area Ha 42 0.5 1.3 0.0 6.4 Legumes and Oilseeds TVC Rs 42 8786.0 25661.8 0.0 140330.0 Legumes and oilseeds NR Rs 42 10901.7 31413.8 0.0 174000.0 other crops area Ha 42 1.9 2.3 0.0 9.6 other crops TVC Rs 42 41290.7 51118.1 0.0 209725.0 Other crops NR Rs 42 69009.6 109105.3 0.0 515400.0 Livestock income Rs 42 13454.8 17347.2 0.0 60000.0 Non-agrl income Rs 42 66109.5 49873.9 4000.0 216000.0 Variables Units Obs Mean Std. Dev. Min Max Household size Numbers 69 5.3 2.1 2.0 11.0 Total own land Ha 69 5.4 4.0 0.4 16.6 Total operated land Ha 69 6.7 4.8 0.4 23.5 Total livestock Unit Numbers 69 2.0 2.5 0.0 14.1 chickpea area Ha 69 4.6 3.8 0.4 20.2 chickpea yield Kg/ha 69 1407.6 454.3 625.0 2573.1 chickpea price Rs/kg 69 38.5 6.2 25.0 50.0 chickpea TVC Rs/ha 69 27281.6 5263.6 11460.8 37419.3 Legumes and Oilseeds area Ha 69 0.4 1.0 0.0 5.6 Legumes and Oilseeds TVC Rs 69 9454.5 20776.3 0.0 108550.0 Legumes and oilseeds NR Rs 69 25887.9 68584.1 0.0 347090.0 other crops area Ha 69 1.7 1.9 0.0 9.6 other crops TVC Rs 69 69687.6 87155.6 0.0 400090.0 Other crops NR Rs 69 180926.0 248315.4 0.0 1046490.0 Livestock income Rs 69 127671.7 186803.4 0.0 880570.0 Non-agrl income Rs 69 130213.5 191499.6 0.0 883740.8 Strata1:Low Rainfall Region 05 101520 100 200 300 400 500 Chickpea Yield (Kg/ha) Strata1_current climate Distribution of Chickpea yield (kg/ha) 05 101520 NumberofHHs 0 100000 200000 300000 400000 Chickpea Net Returns (Rs/farm) Strata1_current climate Distribution of Chickpea Net Returns (Rs/farm) Strata2:High Rainfall Region 05 1015 NumberofHHs 500 1000 1500 2000 2500 Chickpea Yield (Kg/ha) Strata2_current climate Distribution of Chickpea yield (kg/ha) 0 10203040 NumberofHHs 0 200000 400000 600000 Chickpea Net Returns (Rs/farm) Strata2_current climate Distribution of Chickpea Net Returns (Rs/farm)
  11. Sensitivity of current production systems to climate change CLIMATE 2050s • Temperature could increase up to 0.5 to 3°C • Rainfall could increase by 6.4% to 37.8% Climate scenario Low rainfall Medium and High rainfall Mean CV (%) Mean CV (%) Cool/wet 1.33 22.45 1.12 11.02 cool/dry 1.05 9.92 0.92 8.51 middle 0.83 6.49 0.69 6.66 hot/wet 0.95 9.27 0.76 6.12 hot/dry 0.88 8.25 0.74 6.86 Simulated Average relative chickpea yields in different climate scenarios • Hot-dry scenario: chickpea yields are projected to decrease due to heat and water stress • Cool/wet and cool/dry: projected to have a positive impact on chickpea yields
  12. Aggregate farm household vulnerability, net economic impacts, percent change in farm net returns, per-capita income and poverty rate GCM Strata Vulnerability (%) Net economic impact (%) % change of current system in climate change Net farm Returns Per-capita income Poverty rate Hot-dry Low rainfall 68.2 -15.1 -20.5 -13.5 19.3 High and medium rainfall 67.6 -19.0 -25.0 -20.9 8.5 Aggregate farms 67.8 -18.1 -24.0 -18.2 14.7 cool-wet Low rainfall 34.5 13.8 18.8 12.4 -15.9 High and medium rainfall 47.2 2.8 3.9 3.2 -4.0 Aggregate farms 42.4 5.4 7.3 6.6 -10.9 • 68% farms are vulnerable in hot-dry scenario and 42% farms are vulnerable in cool-wet scenario • Hot-dry scenario: 13% reduction in per-capita income, increase the poverty rate by 19% in low rainfall region • Cold-wet scenario: 12% increase in per-capita income, decrease the poverty rate by 16% in low rainfall region
  13. Components Key Drivers Strata1: Low Rainfall region Starta2: High rainfall region Biophysical  Short duration chickpea cultivar  2 critical irrigation during the vegetative and maturity stage of the crops  Recommended level of fertilizer use (20 kg N)  High yielding chickpea cultivar with higher water use efficient traits (NBeG-3)  Recommended level of fertilizer use (20 kg N) Socio- economic  Reduced fertilizer cost (The average fertilizer cost for chickpea in Kurnool is Rs. 4675/ha, which is 19% of the TVC. we reduce the fertilizer cost to Rs. 1558/ha for each survey farms  Mechanical harvesting of chickpea  Cultivation of new crop (foxtail millet) in the kharif season instead of keeping the land follow before cultivating chickpea. We assumed 50% of chickpea area will be cultivated by foxtail millet by the farmers  Reduced fertilizer cost (The average fertilizer cost of chickpea in Kurnool is Rs. 4675/ha, which is 19% of the TVC. we reduce the fertilizer cost to Rs. 1558/ha for each survey farms  Mechanical harvesting of chickpea  Cultivation of new crop (foxtail millet) in the kharif season instead of keeping the land follow before cultivating chickpea. We assumed 50% of chickpea area will be cultivated by foxtail millet by the farmers ‘Climate smart’ Adaptation Package Meeting with Stakeholders for Adaptation
  14. Strata 1: Low rainfall Strata 2: High rainfall Base Adapted Base Adapted Chickpea cropped area (ha) 4.0 4.0 5.2 5.2 chickpea Production (kg/farm) 3009 6392 7159 9025 chickpea TVC (Rs/farm) 71616 48590 143669 103403 Chickpea Net Returns (Rs/farm) 34638 175882 158457 253300 Foxtail millet area* (ha) 2.0 2.6 Foxtail millet production (Kg/farm) 2758 3654 Foxtail millet TVC (Rs/farm) 21757 28829 Foxtail millet Net Returns (Rs/farm) 22374 29647 Parameters of base and adapted system Note: * 50% of the chickpea area will be cultivated with foxtail millet in the kharif season Strata 1: Low rainfall(n=42 HHs) Strata 2: High rainfall (n=69 HHs) Crop model Base Adapted* % change Base Adapted % change DSSAT 744.9 1194.2 60.3 1347.0 1664.6 23.5 Simulated chickpea yields (Kg/ha) in current and adapted production system in different strata Note: * Adapted system – New cultivars with recommended fertilizer and irrigation
  15. Strata Adoption rate (%) Net Return per farm (Rs) Per capita Income (Rs) Poverty (%) Without adaptation With adaptation Without adaptation With adaptation Without adaptation With adaptation Low rainfall 85.5 162206 322231 48842 83075 30.9 15.6 High and medium rainfall 75.7 286551.8 456872 74510 111762 22.8 14.1 Aggregate farms 79.5 236882.0 380438 61676 92865 26.8 16.4 Adoption rate of new production system, net returns per farm, per capita income and poverty rate under base and adapted system • The predicted adoption rate of climate smart adaptation strategies would increase farm household income in both strata 1 and 2 (doubled in low rainfall regions) • Increase in per capita income of the households substantially reduce poverty rate (- 55%) of low rainfall region
  16. Developed regional (Andhra Pradesh) RAPs Developed national (India) RAPs Parameterized the Future farming systems using Global Models projections (yield, prices, etc.) Developed future adaptation strategies Assessed the farm vulnerability and potential of adaptation strategies in future world Shared the results with stakeholders Future Farming system and its adaptation Co-designed and co-developed with national and regional level stakeholders
  17. Representative Agriculture Pathways (RAPs), Andhra Pradesh, India RAP 4: Inclusive pathway towards 'Swarna' Andhra Pradesh (Green) • successfully implementing National Mission on sustainable agriculture coupled with reform in key sectors such as energy, land and water • The primary sector mission of the State has the holistic approach including economic and ecological objectives to enhance the productivity and incomes of the farm households • Promote the adoption of resource efficient technologies and practices for production and post-harvest handling • Inclusive growth enabled by the improved access to financial services for large number of smallholder farmers through SHGs as well as other collective action based models such as FPOs and cooperatives • In general the state Government investment on public health, education, skill development and rural infrastructure will slow population growth rate and improve household welfare RAP5: Unsustainable pathway towards 'Dead End' Andhra Pradesh (Grey) • Increased population growth, growing demand for food and fuel coupled with lower research and development investment from the state government in developing resource efficient and high yielding technologies will lead to over exploitation of land and water resources • Low adoption of productivity enhancing technologies due to limited access to financial services • Slow and ineffective reforms process in energy, water and land lease leading to highly inequitable distribution of resources • Inadequate infrastructure and low skill levels in rural areas lead to high post harvest loses and lower opportunities in non- farm employment • Low-investment on health and education in rural areas will lead to migration of unskilled labor to urban areas increasing poverty and nutrition insecurity
  18. RAPs Key variables Direction Magnitude Farm size Increase 10% Household size Decrease 30% Off-farm income Increase 60% Herd size Decrease 10% Access to formal credit Increase 30% Minimum Support Price (MSP) Disappear 100% Electricity subsidy Decrease 70% - slow disappear Fertilizer subsidy Decrease 40% Micro irrigation subsidy coverage Increase 50% Fertilizer price Increase 25% Irrigation efficiency Increase 40% Mechanization Increase 30% Crop Yields Increase 20-25% New cultivars(improved) Increase 50% Chickpea sorghum Rice Milk Scenario Price Yield Price Yield Price Yield Price Yield Without climate change 1.21 2.25 1.39 1.65 1.10 1.21 1.21 3.04 With climate change 1.37 1.63 1.35 1.23 India Price and Yield trends from Global Economic model (IMPACT) RAPs Key variables Direction Magnitude Farm size Decrease 20% Household size Increase 10% Off-farm income Decrease 10% Herd size Increase 20% Access to formal credit Increase 15% Minimum Support Price (MSP) Increase 10% Electricity subsidy Decrease 15% Fertilizer subsidy No Change No Change Micro irrigation subsidy coverage Decrease 10% Fertilizer price Increase 30% Irrigation efficiency Decrease 20% Mechanization Increase 10% Crop Yields Increase 5%-10% New cultivars(improved) Increase 10% Chickpea sorghum Rice Milk Scenario Price Yield Price Yield Price Yield Price Yield Without climate change 1.52 2.23 1.53 1.56 1.46 1.20 1.12 2.92 With climate change 1.79 1.82 1.97 1.14 India Price and Yield trends from Global Economic model (IMPACT) Key Drivers of RAP4 and RAP5 RAP4: Green Road RAP5: Grey Road
  19. Vulnerability of future farm households to climate change in 2050 by strata • 47% negatively impacted by CC • High rainfall region is more vulnerable than Low rainfall region • 43% negatively impacted by CC • Low rainfall region is highly vulnerable to Hot-Dry climate High prices in RAP5 – offsets climate change impacts on yield
  20. Change in poverty rate with adaptation in 2050 by strata •65% benefit from adaptation packages •Poverty reduction is high with adaptation for Low rainfall region •58% benefit from adaptation packages •Poverty reduction is low with adaptation
  21. Climate • All climate models predict a future with higher (warmer) temperature in the Kurnool district • By 2050s the temperature could increase from 0.5 to 3°C • Future rainfall could increase by 6% to 40% Impacts • Cool-wet and cool-dry climate scenarios have a positive impact on chickpea yield • Hot-dry and hot-wet climate scenarios have a negative impact on chickpea yield • 62% of farms could be vulnerable to the impacts of climate change • Per capita income decreases by 12% in the hot-dry climate scenario • 47% negatively impacted by climate change in sustainable pathway (Green road) • 43% negatively impacted by climate change in unsustainable pathway (Grey road) Adaptations • An adaptation package including a new chickpea cultivar with drought tolerant traits, sustainable water management, improved fertilizer application, and increased mechanization and new crop could benefit more than 70% of farms • 65% benefited from adaptations in sustainable pathway (Green road) • 58% benefited from adaptation in unsustainable pathway (Grey road) Key Messages to stakeholders
  22. Thank You
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