1. Dynamism of Agricultural Risk Drs. D. R. Reddy, Amor Ines, Sheshagiri Rao

2. Overview I.Decision Making Under Uncertainty Risk Aversion and Optimization Example of optimizing maize production in Kenya II.Analyzing climate risks and risk management approaches at community/village level Example 1: Srirangapura Village, Mahabubnagar Example 2: groundnut in Anantapur III.Using climate information to manage crop mixes: examples from Mahabubnagar

3. Decision Making Under Uncertainty Amor Ines

4. Managing The Full Range of Variability FOREFITED OPPORTUNITY CRISIS HARDSHIP

5. Ex-Ante Impacts: Risk Aversion

10. Risk Aversion

14. Optimization Poorly-behaved response surfaces Computationally- intensive Robust methods: –Simulated annealing –Genetic algorithms Compromise: grid search

15. Value for maize management, Kenya Decisions that are optimal on average are usually far from optimal. Skillful forecasts can inform management that is closer to optimal for given weather conditions. 1995 (dry) 1994 (wet) average weather yield income optimal N

16. d c f e b a

17. CLIMATE RISK- SEMI ARID VILLAGE AT MEHABUBNAGAR CROP (Specific) - RAINFED MAIZE, RAINFED Bt.COTTON LIVESTOCK (Specific) -SHEEP RISK MGT AT –FAMILY LEVEL – LIVELIHOOD PERSPECTIVE –COMMUNITY LEVEL –GOVERNMENT AND BANK VARIABILITY OF RISK –AT FARM SCALE – IN TIME AND SPACE LIVELIHOOD OPTIONS –COMBINATION OF ENTERPRISES

18. Analyzing climate risks and risk management approaches at community/village level Sheshagiri Rao

19. CROP YIELD SCENERIO at study village CROPNORMA L YIELD kg/ha GOOD YEILD kg/ha YEARSPOOR YEILD kg/ha YEARSBEST YEILD kg/ha MaizeRed 3,750 Black- 5,000 Red 5,000 Black- 7,500 2000,19 98, 2007 Red 1,250 Black- 2,500 2001,20 02, 2003, 1997 15,000 (Black) Bt. Cotton 17502500200750020083000

20. Decision onClimate & other information (minimum) Lead time Add ition al cost Additional benefit (correct choice ) Penalty (Wrong choice ) Choice of crop- maize or cotton? Seasonal total. Long dry spell timing Before sowing Non e 30-60% higher yield Lose benefit Best sowing window in – June 1 wk to Aug 1 wk Distribution of wet/dry spells, Crop simulation runs Before sowing Non e 20-80 % higher yield Lose benefit / can not sow the crop Moisture stress management for the crop Dry spell at silk formation stage (60-70 das) 7-10 days ahead Irrig ation 30-60% higher yield Cost Aphids management Wet spells in Vegetative growth, silk formation 7-10 days ahead Plan t prot ectio n 10-30% higher yield Cost

21. Decision onClimate & other information (minimum) Lead time Additio nal cost Additiona l benefit (correct choice ) Penalty (Wrong choice ) Timing and number of top dressing Wet spells in Vegetative growth, silk formation 2-3 weeks ahead None10-30% higher yield Inefficient use, loss of benefit Management of water logging, Downy mildew and wilt in Black soils Long wet spells in Vegetative growth, silk formation 4-7 days ahead Drainag e, Plant protecti on, 20-40% higher yield Cost / Loss of benefit Nutrient management in Low temp. Low Minimum temp. during veg. silk formation 4-7 days ahead Zn foliar spray 10 % higher yield Cost/ loss of benefit

22. Decision onClimate & other information (minimum) Lead time Addition al cost Additional benefit (for correct choice ) Penalty (for Wrong choice ) Best sowing window in – May 4 th wk to June 4 th wk Distribution of wet/dry spells, Crop simulation runs Befor e sowin g None20-80 % higher yield Lose benefit / can not sow the crop Moisture stress management for the crop Dry spell at boll formation stage (90- 120 das) 7-10 days ahead Irrigation30-60% higher yield Cost / loss of benefit Thrips management- vector for Leaf curl/ cotton necrosis Dry spells at Veg. & boll form stage 7-10 days ahead Plant protectio n 10-40% higher yield Cost / loss of benefit Mealy bug and Mirid bug (affects bolls) management Not clear7-10 days ahead Plant protectio n 10-40% higher yield Cost / loss of benefit Cotton

23. Decision onClimate & other information (minimum) Lead time Addition al cost Additional benefit (for correct choice ) Penalty (for Wrong choice ) Aphids management Wet spells in Vegetative growth, boll formation 7-10 days ahead Plant protectio n 10-40% higher yield Cost/ Loose benefit Timing and number of top dressing Wet spells in Vegetative growth, boll formation 2-3 weeks ahead None10-30% higher yield Inefficient use, loss of benefit Management of water logging, and wilt in Black soils Long wet spells in Vegetative growth, boll formation 4-7 days ahead Drainage Plant protectio n, 20-40% higher yield Cost / Loose benefit Nutrient management in Low temp. Low Minimum temp. during veg. boll formation 4-7 days ahead Zn, B, Mg foliar spray 10 % higher yield Cost/ loss of benefit Cotton

24. Decision onClimate & other information (minimum) Lead time Addition al cost Additional benefit (for correct choice ) Penalty (for Wrong choice ) Mango Hopper management during flowering Temperature in January and February 7-10 days Cost of sprays 10-40%Cost/ loss of benefit Anthracnose Management at new flush Humidity7-10 days Cost of sprays 10-20%Cost/ loss of benefit Manage increase Vegetative growth at flowering Wet spells in October November 10-20 days Spray of flowering promoter s 20-60%Cost/ loss of benefit Effect of hail storms Timing of hail storms 3-7 days None- (Early harvest?) 10-40%Loss by early harvest Manage impact of High temperature Timing and intensity of the event 3-7 days (Irrigatio n ?) 10-80%Cost / loss of benefit Mango

25. Decision onClimate & other information (minimum) Lead time Addition al cost Additional benefit (for correct choice ) Penalty (for Wrong choice ) Scheduling and number of de- wormings (2 parasite species ) Humidity, Wet spells. Fecal egg count (Sept- Oct) ??, Faciola Snail as vector 10-30 days Reduce costs by 2-6 times 30 -200 Rs per animal Loss of benefit/ Morbidity of animal Manage ET (Enterotoxaemia), fodder management Timing and intensity of first drenching 7-15 days None (Preventi ve? ) Reduce 5- 40% loss Loss of benefit/ Morbidity of animal Manage Blue tongue- Diptera Vector population dynamics Rainfall, Temperature in November, December 7-15 days None (Preventi ve? ) Govt. prepared ness Reduce 5- 70% loss of lambs Loss of benefit/ Morbidity of animal Sheep – One of the highest district level Population in the nation (AP has the highest amongst states)

26. Decision onClimate & other information (minimum) Lead time Addition al cost Additional benefit (for correct choice ) Penalty (for Wrong choice ) Fodder growth in spatial spread of their migration route Total rainfall, Late season rains 2-3 weeks None20-300 Rs per animal Loss of benefit/ additional loss Availability of Weeds as fodder in crop lands Late season intense wet spells 2-3 weeks None20-300 Rs per animal Loss of benefit/ additional loss Sheep

27. CROP -TOTAL CLIMATE RISK COMPONENT From end to end- Land preparation, crop sowing –TO Harvest and post harvest operations Consider both –Direct impact- by moisture stress, water logging and on Crop physiology –Indirect impact – by triggering rapid increase of pests, diseases and vector populations that are already endemic. In any particular year a particular combination of such ‘adverse events’ would occur It is possible to construct simple models for such climate impact by using –Existing literature –Expert knowledge of farmers, field researchers

28. NOTE All further slides refer to Rainfed groundnut at Anantpur These are illustrative of methodology similar questions (to the ones mentioned here) were asked by farmers in the study village.

29. Plot level = Profit / loss is rain+ many others 05 =43 cm, 06=32cm, 07=52cm, 08=57cm

30. At plot level- Yield variation and rain- relationship is much weaker than EXPECTED 05 =43 cm, 06=32cm, 07=52cm, 08=57cm

31. Cost of Cultivation Anantpur District average groundnut yield- (1975- 1995) - Avg rain-47 cm

32. TOTAL CLIMATE RISK FOR GROUNDNUT CROP

33. Simple model for Rainfed Groundnut At Anantpur- an example

34. Climate – Direct impact

35. Climate- indirect impact

36. Validation of Model Prediction and Field data

37. 6 villages in Anantpur region Located in 3 separate Mandals, distributed in an area of about 4000 sq km Data from Marginal and small farmers, Vulnerable sections to climate risk Sample of 20-40% of the total families in the community Family wise data collection from 2005 to 2008

38. Community level Livelihood options at 3 villages of Anantpur

40. Family wise Annual income distribution- 6 villages

41. Family wise Cattle population in 6 villages.

42. Family wise sheep and Goat income- 6 villages

43. How much credit?

44. Reasons for first debt ? – crop (during bad year), bore wells, sheep are the big reasons

45. Debt trap (3 rd Default) - Reasons

46. Govt. programs as a safety net

47. CPRs as the safety net

48. Highest number of animals not with the largest of farms

49. Mid size farms have the largest credit

50. Using climate information to manage crop mixes Dr. Reddy

51. Timely onsetLate onset Black soilRed soilBlack soilRed soil CottonMaize** Castor Maize*Redgram Sunflowe r Green gram Castor Onset of sowing rains and crop choice * Long duration maize ** Short duration maize

52. Agronomic options during dry spell Red soils Maize Reduced dose top dressing of N application Supplemental irrigation (Tolerates 8-10 days dtress) Protect crop from sucking pests Black soil Cotton Reduced dose of top dressing of N application Supplemental irrigation Maize Supplemental irrigation (Tolerates 15 -20 days Under severe drought conditions maize can be removed and chickpea can be taken-up of in black soil as rabi crop

53. Distribution of sunflower seed in Kurnool district during month of July 2002 in A.P Implications of rain forecasts Policy decision

54. Simulated Potential Maize Yields Andhra Pradesh

55. Maize: “Rainfall distribution from 55 days after sowing to maturity is important”

56. Higher yielding crops with rainfall of < 600 escaped swdef < 0.75, support for local agronomist’s rainfall distribution explanation Water stress (post flag leaf emergence) explained most but not all of the low yields

57. Maize crop calendar 29 (16-22Jul) 28 (9-15Jul) 27 (2-8Jul) 26 (25-01Jul) 25 (18-24June) FebJanDecNovOctSepAugJulJunSowing week EstCD TA+SL G.fil Mat. EstCD TA+SL G.fil Mat. EstCD TA+SL G.fil Mat. EstCD TA+SL G.fil Mat. EstCD TA+SL G.fil Mat. Porbability of occurrence two and three consecutive dry spells

58. Cotton crop calendar 29 (16-22Jul) 28 (9-15Jul) 27 (2-8Jul) 26 (25-01Jul) 25 (18-24June) FebJanDecNovOctSepAugJulJunSowing week EstCDFl&BDMaturity EstCDFl&BDMaturity EstCDFl&BDMaturity EstCDFl&BDMaturity EstCDFl&BDMaturity 0.00 0.20 0.40 0.60 0.80 1.00 1.20 1921232527293133353739414345474951 Std. week Probability 2nd week3rd week Porbability of occurrence two and three consecutive dry spells