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Scaling up climate smart agriculture via the Climate Smart Village Approach for Telangana State

  1. CCAFS- ICRISAT Scaling up climate smart agriculture in Telangana state Shalander Kumar, K DakshinaMurthy, Murali Gumma, S Nedumaran, Anthony Whitbread, ICRISAT Arun Khatri, CCAFS Partners from EPTRI, PJTSAU, ANGRAU Dept. of Agriculture/others, Telangana
  2. Major hindrances/constraints in scaling up climate smart agriculture in Telangana state  Lack of information on climatic stresses/hot spots at disaggregate (mandal level) • Which area to target for what CSAPs and priority  Lack of awareness and integration of stakeholders perspective in identifying CSA practices for different sub-regions • No mechanism to integrate stakeholders perspective in prioritization of CSAPs  SAPs impacts consider incremental yields but not income, market, even soil types  Lack of information on region/district wise & CSA practice specific potential benefits and investment requirements • High instability in incremental returns across years e.i good / drought years (esp. NRM based CSA options)  Poor access to farm machinery and reliable climate information (SCF)  Hindrances due to compartmentalization/ lack of convergence among deptts  Severe gaps in capacities of farmers, extension staff, bankers as well as input dealers on CSA Poor Targeting, lack of capacity at different levels & low adoption of CSAPs
  3.  Climate Risk mapping to identify and prioritize mandals vulnerable to climate stresses (Prioritization of areas- Targeting)  Review the success stories of climate smart villages from different stakeholders and identify best practices that are relevant to target districts/mandals (Inventory of CSA practices/ technical coefficients)  Participatory prioritization of location specific climate smart agricultural practices (districts/region specific CSAPs)  Participatory identification of barriers and incentives, and convergence opportunities for promoting CSA (Targeting on incentives, harmonization of governance)  Ex-ante impact analysis of potential adoption of selected CSA practices in different districts of Telangana state (potential benefits for better targeting)  Assessment of investment and infrastructure need to support CSA in TS (identifying gaps)  Stakeholders consultations and sharing prioritization outcomes (realistic & ownership)  Integrating climate risk analysis, CSAPs prioritization, Ex-ante analysis and seasonal climate forecasts help develop district specific scaling up strategy Approach to develop a strategy for scaling up climate smart agriculture in Telangana state: Framework & information for decision support Aim is to provide tools and information wrt above to help policy makers and development actors take informed decisions to scale up CSA
  4. i. Mandal wise climate risk analysis– understanding current climate risk and identifying the factors that render some mandals more vulnerable than others to climate Mandal wise climate exposure index for baseline climate Mandal wise climate exposure index with major crop type and command areas (2015-16)
  5. Climate risk analysis helps prioritizing and better targeting of different districts / Mandals to address different climate stresses There are areas having high risk of droughts, have concentration of cotton and maize Need for location specific diversification of cropping systems/cultivars/enhancing water access for most attractive crops in vulnerable areas
  6. ii. Participatory prioritization of climate smart agriculture (CSA) practices Participants representing all TS districts and other NARS & project partners, PJTSAU, EPTRI, NABARD
  7. i. Climate smartness index based on potential contribution of each CSA option to productivity, climate risk reduction (resilience), mitigation (emission & sequestration) and Resource sustainability; ii. Index for ‘Ease of adoption’ was estimated based on the technical feasibility of the CSA option; cost of technology; inclusivity (smallholder, gender) and synergy with state plans/development programs. Workshop participants arrived at a weight for each criterion & score for each CSA practice against each criterion. I/ J = C1w1+………………+cn wn I = ∑ ci wi J = ∑ cj wj Multi criteria analysis (MCA) prioritization of CSAPs
  8. Participatory prioritization of CSA practice in Telangana
  9. Southern zone of Telangana
  10. Central zone of Telangana
  11. 0 1 2 3 4 5 19. Integrated Pest Management 18. Grading of local cows 17. AWD/SRI in Rice 16. Shelter for animal 15. Conservation of fodder resource… 14. Drought tolerant cultivars 13. Integrated Nutrient Management 12. Mechanization-small scale 11. Cotton + Pigeonpea/Soybean 10. Seed bank - Soybean/Pigeonpea 9. Rainwater Harvesting-… 8. Micro Irrigation 7. Crop Insurance 6. Paddy crop residue managemnet… 5. CLIC- Climate Information Service 4. Agro-Horti/IFS 3. Contingent Crop Planning 2. In-situ moisture conservation -… 1. Rainwater Harvesting- Farm… Finance/Capital 0 1 2 3 4 5 Machinery Incentives needed to promote CSA
  12. Incentives needed to promote CSA 0 1 2 3 Capacity Building 0 1 2 3 Market Linking 0 1 2 3 Infrastructure
  13. 1. Broad bed and furrow (BBF) for moisture conservation and drainage 2. Ridge and furrow for in-situ water conservation 3. Residue incorporation (paddy and cotton) in high potential districts 4. Farm pond for critical/supplemental irrigation in relatively high value crops 5. Provision of seasonal and mid-season climate forecast based cropping systems options iii. Ex-ante impact analysis of potential adoption of selected CSA practices in different districts of Telangana state  Considered actual area and yields of major crops and rainfall level for 5 years from 2010-11 top 2014-15 to estimate net additional returns due to potential adoption of CSA practice per ha and at district level  The coefficient of yield increment due to CSA practices are considered based on the empirical studies and results of various on-farm research in different locations in TS/SAT. We selected five high priority CSA practices for ex-ante impact assessment:
  14. Assumptions Ridge and furrow system:  50% of rainfed area under cotton, maize, pigeon pea, groundnut, sorghum, green gram Farm pond:  5% of rainfed land holdings <2 ha  20-25 % of rainfed land holdings >2 ha Residue incorporation:  Crops: cotton  50% of rainfed area Broad bed & furrow (BB&F):  All black soil area under cotton and Soybean Machinery & implements: Rotavator (rainfed), Happy seeder (irrigated), BBF maker, ridge maker  70% at village level- Machine used for 15 days (individual/custom hiring)  30% at cluster of villages/mandal level- Machine used for 30 days (FPOs/business models) Capacity development (cost):  Training program and demonstration/field school at village level consecutively at least for 2 years
  15. Technical coefficients- Rate of yield increments in different crops due to different CSA interventions CSA practices Rainfall Situation Sorgh um Maiz e Green gram Redgra m Groun dnut Cotton Soyab ean Paddy Mango Mosa mbi Sapot a Tomat o Ridges and Furrows Drought 15 20 18 18 18 15 Mild Drought 8 10 9 9 9 8 Normal 4 5 4 4 5 4 Excess 8 10 9 4 9 8 Broad Bed Furrow Drought 22 28 Mild Drought 12 15 Normal 5 5 Excess 12 15 Farm Pond Drought 20 20 25 37 24 25 42 Mild Drought 10 10 15 25 15 15 21 Normal 10 10 10 15 15 15 10 Excess 5 5 5 10 10 5 10 Crop Residue incorporation Impact assessed in terms of value of nutrient added to the soil Based on various published sources
  16. 16 Potential Additional Net Returns due to Broad Bed and Furrow in cotton & soybean (INR/year, Current Prices) Black soil area suitable for BBF Soybean Cotton Drought 22% Mild Drought 12% Normal 5% Excess 12%
  17. AgMIP Sentinel Sites 17 High instability in the additional annual net returns from BBF depending on the rainfall and price For example: Cotton Seasonal climate forecast could prevent additional costs during normal years- reducing the investment risk -2000 0 2000 4000 6000 8000 10000 12000 14000 2010-11 2011-12 2012-13 2013-14 2014-15 Adilabad Nizamabad Karimnagar Medak Rangareddy Mahabubnagar Nalgonda Warangal Khammam
  18. AgMIP Sentinel Sites 18 District Infrastruct ure/imple ments (Million Rs) Capacity Developme nt (Million Rs) Total Additional Net Returns*/ year (Million Rs) Adilabad 97 4 205 Nizamabad 6 3 132 Karimnagar 57 4 40 Medak 34 3 106 Rangareddy 16 3 27 Mahabubnagar 63 5 32 Nalgonda 80 4 14 Warangal 54 4 19 Khammam 47 3 2 Initial Investment Needs and Potential Total Additional Net Returns by adopting BB&F in cotton & soybean (INR, Current Prices) Additional Operational Cost per hectare - Rs. 2000 * varies depending on the amount of rainfall and price
  19. AgMIP Sentinel Sites 19 Broad bed and Furrow: Major concerns Concerns Options Lack of awareness on potential benefits and technical skills Trainings and demonstrations/farm field schools at village level at least for 2-3 consecutive years This is not in the agenda of extension staff Extension staff also lack awareness and skills Poor access to BBF makers Promote BBF makers through custom hiring centers or individual entrepreneurs Individual tractor farmers has low interest to buy as it has utility for few days in a year. Targeting Need to target most promising crops cotton and soybean in black soil regions Need to consider net additional economic returns
  20. AgMIP Sentinel Sites 20 Major crops under soils other than black, suitable for ridge and furrow systems (targeting rainfed areas)
  21. AgMIP Sentinel Sites 21 District Average Additional Net Returns/ha Total Additional Net Returns (Million Rs) Adilabad 1751 214 Nizamabad 2603 14 Karimnagar 2101 153 Medak 3082 87 Rangareddy 1307 4 Mahabubnagar 1549 119 Nalgonda 2157 268 Warangal 2221 140 Khammam 1725 128 Potential Additional Net Returns due to Ridge and Furrow in Cotton in TS (INR/year, Current Prices) Drought 15% Mild Drought 8% Normal 4% Excess 8%
  22. AgMIP Sentinel Sites 22 High instability in the annual net additional returns from ridge & furrow system depending on the rainfall and prices (INR, Current Prices) Seasonal climate forecast could prevent additional costs during normal years- reducing the investment risk -2000 0 2000 4000 6000 8000 10000 2010-11 2011-12 2012-13 2013-14 2014-15 Cotton Adilabad Nizamabad Karimnagar Medak Rangareddy Mahabubnagar Nalgonda Warangal Khammam -5000 0 5000 10000 15000 2010-11 2011-12 2012-13 2013-14 2014-15 Maize Adilabad Nizamabad Karimnagar Medak Rangareddy Mahabubnagar Nalgonda Warangal Khammam
  23. 23 Similar estimates for other crops (Ridge and furrow) Pigeon pea Green gram Sorghum Maize
  24. AgMIP Sentinel Sites 24 District Infrastructure / implement (Million Rs) Capacity Developmen t (Million Rs) Total Addl Net Returns*/ year (Million Rs) Adilabad 74 4 236 Nizamabad 9 3 133 Karimnagar 38 4 208 Medak 26 3 326 Rangareddy 12 3 48 Mahabubnagar 48 5 265 Nalgonda 62 4 313 Warangal 31 4 228 Khammam 35 3 154 Initial Investment Needs and Potential Total Additional Net Returns by adopting Ridge and Furrow in Major Crops (INR, Current Prices) Additional Operational Cost per hectare - Rs. 1500 * varies depending on the amount of rainfall and price
  25. AgMIP Sentinel Sites 25 Ridge and Furrow: Major concerns Concerns Options Lack of awareness on potential benefits and technical skills Trainings and demonstrations/farm field schools at village level at least for 2-3 consecutive years This is not in the agenda of extension staff Extension staff also lack awareness and skills Poor access to ridgers Power drawn as well as bullock drawn ridgers through custom hiring centers or individual entrepreneurs Though there is poor access to power drawn ridgers, buck drawn machines are hardly available Targeting Need to target most promising crops and regions Need to consider economic returns, not only productivity.
  26. AgMIP Sentinel Sites 26 Potential Additional Net Returns due to Crop Residue Incorporation in Cotton in TS (INR/year, Current Prices) Additional Operational Cost per hectare - Rs. 3500 Benefits estimated as value of nutrient added into soil District Infrastructure (Million Rs) Capacity Development (Million Rs) Total Additional Net Returns (Million Rs) Adilabad 425 4 795 Nizamabad 25 3 47 Karimnagar 215 4 401 Medak 150 3 273 Rangareddy 70 3 126 Mahabubnagar 272 5 495 Nalgonda 356 4 643 Warangal 180 4 333 Khammam 199 3 369
  27. AgMIP Sentinel Sites 27 Residue incorporation (Rotavator): Major concerns Concerns Options Lack of awareness on potential benefits and technical skills Trainings and demonstrations/farm field schools at village level at least for 2-3 consecutive years • This is not in the agenda of extension staff • Extension staff also lack awareness and skills • Farmers are not able to visualize the benefits in the form of adding nutrients to soil (support!!) Poor access to machine Promote rotvator & happy seeder through custom hiring centers or individual entrepreneurs • Individual tractor farmers has low interest to buy as it has utility for few days • Local skills building for repair and maintenance is also critical Targeting Targeting most promising crops cotton and soybean and black soil regions • Need to consider net additional economic returns
  28. 28 Potential No of Farm Ponds (000) & area (000 ha) under suitable crops for supplemental irrigation in TS (5% of <2ha and 20-25% of >2 ha land holdings) Particulars Adilabad Nizamaba d Karimnag ar Medak Rangaredd y Mahabu bnagar Nalgonda Waranga l Khamma m Potential No of Farm Ponds 42 15 22 31 18 58 34 22 23 Potential area of suitable crops for supplemental irrigation, 000 ha Potential Total area: Cotton, Groundnut, maize, mango, Mosambi, Vegetable/tomato 84 30 44 62 37 116 67 45 45 Farm ponds Crops Adilabad Nizamabad Karimnagar Medak Rangareddy Mahabub nagar Nalgonda Warangal Khammam Cotton 2736 3391 3250 3549 1839 2121 2474 3998 3988 Groundnut 4149 6337 3817 3097 4803 4602 3295 4902 4060 Maize 1960 4143 3464 2307 1740 1396 1227 3315 3829 Mango 15019 23859 28672 27246 20746 24327 40706 26535 25393 Batavia 18601 22164 18601 22164 18601 18601 22164 18601 18601 Tomato/vegeta ble 17600 15800 17600 19100 14300 14300 19100 17600 17600 Potential Additional Net Returns due to Farm Pond in Major Crops in TS (INR/ha)
  29. AgMIP Sentinel Sites 29 Instability in additional Net Returns due to Farm Pond across years (INR/ha, Current Prices) 0 1000 2000 3000 4000 5000 6000 7000 8000 9000 2010-11 2011-12 2012-13 2013-14 2014-15 Cotton Adilabad Nizamabad Karimnagar Medak Rangareddy Mahabubnagar Nalgonda Warangal Khammam -1000 0 1000 2000 3000 4000 5000 6000 7000 2010-11 2011-12 2012-13 2013-14 2014-15 Maize Adilabad Nizamabad Karimnagar Medak Rangareddy Mahabubnagar Nalgonda Warangal Khammam 0 10000 20000 30000 40000 50000 60000 70000 2010-11 2011-12 2012-13 2013-14 2014-15 Mango Adilabad Nizamabad Karimnagar Medak Rangareddy Mahabubnagar Nalgonda Warangal Khammam Despite the instability average returns are attractive for suitable crops
  30. AgMIP Sentinel Sites 30 Proposed used of harvested water for different crops (%) District Cotton 2.0 Groundnut 2.0 Maize 2.0 Mango 2.0 (Mosambi) 2.0 Cotton 1.6 + Tomato 0.4 Adilabad 50 0 10 10 0 30 Nizamabad 20 0 50 5 0 25 Karimnagar 25 10 20 10 5 30 Medak 20 0 40 10 0 30 Rangareddy 20 8 25 10 2 35 Mahabubnagar 25 10 30 10 5 20 Nalgonda 40 10 0 10 20 20 Warangal 25 15 25 10 0 25 Khammam 45 5 20 30 0 0
  31. AgMIP Sentinel Sites 31 Potential Total Additional Net Returns due to Farm Pond in Major Crops in TS (INR/ha, Current Prices)
  32. AgMIP Sentinel Sites 32 District Infrastructure with Drip System (Million Rs) Infrastructure with Sprinkler System (Million Rs) Capacity Development (Million Rs) Total Additional Net Returns (Million Rs) Adilabad 7439 6419 4 387 Nizamabad 2647 2284 3 171 Karimnagar 3869 3339 4 326 Medak 5480 4729 3 436 Rangareddy 3235 2791 3 220 Mahabubnagar 10303 8890 5 428 Nalgonda 5947 5131 4 678 Warangal 3952 3410 4 262 Khammam 4006 3456 3 460 Initial Investment Needs and Potential Total Additional Net Returns through Major Crops due to Farm Pond in TS (INR, Current Prices)
  33. Farm Ponds: Concerns to address MNREGS Smaller size- 10x10x3 • In farmers perception not useful • No lifting device • No training on efficient & economic use of water NHM (Major program) Size is appropriate 20mx20mx3m • Farmers with drip has preference • Available mostly for horticulture crops, not for other crops • Number of slots available not as per the potential There has to be a common platform to access farm pond support based on farmers preference for crops and size The farm pond support has to be a customized package (pond, water lifting device, MIS) based on farmers preference and resources Capacity building of farmers and extension staff
  34. Climate information- Seasonal and short & medium term forecast Farmers to some extent have access and faith on the short and medium term forecasts But the seasonal forecasts Poor access Reliability Inability to understand to make their use in decision making Need to build capacity on scientists and extension system on delivering crop management options based on credible downscaled SCFs (RARS & KVKs could play an important role) Excel based tools or an app could be developed to prioritize cropping options based on probabilistic SCFs Need to have understanding/ MOU with IITM for timely availability of mandal level SCFs
  35. Remote sensing based Tank water resource monitoring systems created for enabling efficient allocations using relative depth of water tanks through ‘topo sheets’ accessible from the Geological survey of India Monitoring of common minor irrigation tanks
  36. Based on prioritization and ex-ante analysis, we undertake these activities:  District specific gaps on targeting of CSAPs and infrastructure  Validation of results with farmers and field level extension functionaries  Stakeholders workshop with senior government functionaries, NARS & private sector  Working paper Where we have reached  Climate Risk mapping for mandal specific prioritization  Inventory of CSA practices and associated technical coefficients  Participatory prioritization of location specific CSA practices (MCA)  Participatory identification of barriers and incentives for promoting CSA  Shared climate risk analysis and prioritization outputs with state govt and NABARD  Ex-ante impact analysis on potential benefits for better targeting of CSA practices  Assessment of investment and infrastructure need (identifying gaps) Steps completed Next steps
  37. Thank you!
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