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

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

Decision Making Under Uncertainty Amor Ines

Managing The Full Range of Variability FOREFITED OPPORTUNITY CRISIS HARDSHIP

Ex-Ante Impacts: Risk Aversion

Risk Aversion

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

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 (dry) 1994 (wet) average weather yield income optimal N

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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

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

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, ,19 98, 2007 Red 1,250 Black- 2, ,20 02, 2003, ,000 (Black) Bt. Cotton

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 % 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

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

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 ( 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

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

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 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

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 days Reduce costs by 2-6 times 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)

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 None Rs per animal Loss of benefit/ additional loss Availability of Weeds as fodder in crop lands Late season intense wet spells 2-3 weeks None Rs per animal Loss of benefit/ additional loss Sheep

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

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.

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

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

Cost of Cultivation Anantpur District average groundnut yield- ( ) - Avg rain-47 cm

TOTAL CLIMATE RISK FOR GROUNDNUT CROP

Simple model for Rainfed Groundnut At Anantpur- an example

Climate – Direct impact

Climate- indirect impact

Validation of Model Prediction and Field data

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

Community level Livelihood options at 3 villages of Anantpur

Family wise Annual income distribution- 6 villages

Family wise Cattle population in 6 villages.

Family wise sheep and Goat income- 6 villages

How much credit?

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

Debt trap (3 rd Default) - Reasons

Govt. programs as a safety net

CPRs as the safety net

Highest number of animals not with the largest of farms

Mid size farms have the largest credit

Using climate information to manage crop mixes Dr. Reddy

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

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 days Under severe drought conditions maize can be removed and chickpea can be taken-up of in black soil as rabi crop

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

Simulated Potential Maize Yields Andhra Pradesh

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

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

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

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 Std. week Probability 2nd week3rd week Porbability of occurrence two and three consecutive dry spells