Agricultural Climate Change Impact General Concerns and Findings from Mali, Kenya, Uganda, and Senegal Tanveer A Butt, Jay Angerer,, Paul Dyke, Man-keun Kim, Robert Kaitho,, and Jerry Stuth Center for Natural Resource Information Technology Texas A&M University College Station, TX SANREM CRSP Accomplishments and Lessons Learned Workshop June 16, 2004 Contact Info: tanveer@tamu.edu; Ph: 979-845-3805
Presentation Outline Concern about climate change Climate Change Impact Assessment Methodology Climate Change Impact Assessment in Mali, Kenya, Uganda, and Senegal
Specific Concerns In Regards to Agriculture Temp Rainfall CO2 Sea Level Extreme Events Plants Crop and forage growth X X X X Crop /forage water need X X X X Soils Soil moisture supply X X X Irrigation demand X X X X Soil fertility X X X X Animals Performance X X X Pasture/ Range Carrying capacity X X X X Irrigation Water Supply Evaporation loss X X Run-off/general supply X X X Non-AG competition X X Other Water borne transport X X X X Port facilities X Pest and diseases X X X Crop insurance X Forest/Brush Fires X Losses owing to floods X X X
Average Yields in Temperate and Tropical Regions (Kg/Hect.) 4500 4000 3500 3000 Kg 2500 2000 Temperate Tropical 1500 1000 500 0 Rice Wheat Maize Sorghum Soybean G-Nuts Crops Source: Rosenzweig & Hillel, pg. 189
Changes in Temperature and Precipitation During 1900-2000 Region Temp. ( o C) Precipt. (%) Central Asia +0.2 to +0.6-10 to +40 South Asia -0.2 to +0.2 +10 to +40 Sub Saharan Africa +0.2 to +0.4-20 to -50 North America -0.2 to +0.4-20 to +50 Source: IPCC
Mali Projected Changes in Temp. and Precipt. 3.0 Hot Dry Quadrant 2.5 CGCM HADCM 2.0 1.5 1.0 0.5 Temperature Deg C 0.0-0.20-0.15-0.10-0.05 0.00 0.05 Precipitation mm
Kenya Changes in precipitation
Climate Change Impact Assessment Price s Risk of Hunger Mali Agriculture Sector Model d Quantity Physical Impacts Changes in crop yield -- EPIC Changes in livestock forage yield on pasture land - Phygrow Changes in animal appetite and weight loss - Nutbal
Changes in Crop Yield (%) Kenya 25 21.3 20 15 10 8.9 5 3.2 0-5 Maize Millet Sorghum Beans Wheat -3.4-10 -8.5
% Change in Maize Yield in Kenya Crop: Maize Technology: Baseline Climate: CGCM1/Base Attribute: % Change in Yield, Climate 1
Changes in Crop Yield (%) Senegal 0 Cotton Maize Rice Cowpeas -5-10 -15-20 -15.7-17.2-16.4-22.0-25
Physical Impacts - Changes in Crop Yield (%) 10 7.63 5 5.34 Mali 2.61 0 Cotton Cowpeas Groundnuts Maize Millet Sorghum -2.57-2.96-5 -6.45-6.61-5.52-4.38-10 HADCM CGCM -8.47-9.39-15 -16.94-20
Changes in Crop Yield (%) Uganda 0-5 -10 Maize -2.2 Cotton Rice -2.3 Sorghum Millet -7.3-15 -14.1-20 -25-24.2-30
Impact on Production, Import, and Prices of Cereals
Changes in Cereal Production (%) 10 5 6.3 0-5 Mali Senegal Kenya Uganda -4.7-10 -15-11.7-14.5-20
Changes in Cereal Import (%) 70 60 60.2 50 40 30 20 10 15.2 13.0 0 0.0 Mali Senegal Kenya Uganda
Changes in Cereal Price Index (Base = 100) 300 274.0 250 200 150 100 136.2 106.7 115.5 50 0 Mali Senegal Kenya Uganda
Economic and Food Security Implications of Climate Change and the Mitigative Adaptations Details for Mali
Adaptations to Climate Change Economic Adaptations Crop mix Market and Trade Agronomic Adaptations Changing planting and harvesting dates Heat resistant varieties Policy Adaptations (later)
Economic Implications - Surplus Measures (Mil. Dollars) 975 875 775 675 575 475 375 275 175 75-25 Loss of 105-122 973 868 850 Total Surplus Mali Gain of 133-177 689 647 Loss of 229-290 515 447 219 157 Loss of 6-9 11 2 5 Consumer Surplus Producer Surplus Foreign Surplus Base HADCM CGCM
Value of Adaptation ($ Million) - Mali 120 Loss = 105 Loss in Mil Dollars 100 80 60 40 20 2 6 15 90 102 98 38 67 36% loss recovered 0 C Change Crop Mix Trade Tech Full Adaptations Considered HADCM Model Projections
Risk of Hunger - With and Without Adaptation Mali Without adaptation Percent of Population 80 70 60 50 40 30 20 10 0 34 69 75 Base HADCM CGCM HADCM CGCM HADCM: Hadley Coupled Model CGCM: Canadian Global Coupled Model With adaptation 42 49
Risk of Hunger in Mali - Regional Implications Base 90 80 77 84 81 Climate Change Adaptation Percent of Population 70 60 50 40 30 20 10 0 65 58 56 45 47 42 33 6 3 Sikasso Tombouctou Gao Bamako Productive Area Dry Areas Urban Area Canadian Model Projections
Price Instability - Millet Prices under Canadian Model Mali 200 180 Base No Adapt. With Adapt. 160 140 CFAs Per Kg. 120 100 80 60 40 20 0 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 Coefficient of Variation: Base: 61 Without Adaptation: 100 With Adpatation: 65 Year
Policy Adaptation - Land Expansion and Technology Adoption Mali Cons. Plus Prod. Surplus (Mil. $) 1000 800 1052 1054 972 905 868 69 600 60 50 CSPS 400 40 ROH 30 42 34 35 22 200 20 10 0 0 Base C Change Expand AdoptTech Exp & Adopt 100 90 80 70 Percent of Population Policy adaptations are super-imposed on economic and technological adaptations considered earlier. The results shown in this graph are under Hadley projections.
General Findings For the Four Countries Generally, unfavorable environmental conditions for agriculture are expected (worsening food security conditions) Increased risk of hunger Increased dependence on food import Weather induced price instability is likely to increase Adaptations to climate change can effectively mitigate the climate change impact (In Mali, the risk of hunger reduced to 22% - even lower than the base level of 34%) Economic adaptations through trade may be realized if markets work well. Investing in heat resistant varieties may a have high pay-off.
Recommendations for Future Research Extreme climatic events Cost of adaptation Implications for regional trade
References Following references were consulted for this presentation Butt, T.A., McCarl, B. A., Dyke, P., Angerer, J. P., and Stuth J.W.: 2003, Economic and Food Security Implications of Climate Change - A Case Study for Mali. Climatic Change (Under submission) http://agecon.tamu.edu/faculty/mccarl/climchg.html Butt, T.A., and McCarl, B. A..: 2003, An Analytical Framework For Making Long -Term Interlinked Economic And Food Security Projections: A Case Study For Mali. (Under submission) http://agecon.tamu.edu/faculty/mccarl/roh.htm Downing, T. E., Olsthoorn, A. J., and Tol, R.S.J.: 1999, Climate Change and Risk. Routledge Pub., London, U.K. Rosenzweig, C., and Hillel, D.: 1998, Climate Change and the Global Harvest: Potential Impacts of the Greenhouse Effect on Agriculture, Oxford University Press, New York. Swaminathan, M.S. and S. K. Sinha (eds.). 1986. Global Aspects of Food Production. Tycooly International. Oxford. Pp. 417-449.
Carbon Sequestered For Different Payments and the Associated Risk of Hunger Preliminary Estimates from CDM Study in Mali 250 90 85 % 80 200 70 Price $ per ton 150 100 60 50 40 30 R O H 50 34 % 20 10 per ton ROH 0 0-1000 0 1000 2000 3000 4000 5000 6000 7000 1,000 Tons of Carbon Afforestation adaptation
Carbon Sequestered For Different Payments, Cereal Imports, and Cotton Area Preliminary Estimates from CDM Study in Mali 250 600 542 Price $ per ton & Cotton Area (Base=100) 200 150 100 50 0 100 100 82 119 171 61 229 42 328 382 20 17-1000 0 1000 2000 3000 4000 5000 6000 7000 13 500 400 300 200 100 0 Imports per ton Cot Area Imports 1,000 Tons of Carbon
Kenyan Current Temperature Feb to June Average (Deg. Cent.)
Kenyan 2030 Temperature Feb to June Average (Deg. Cent.)
Kenyan Current Rainfall Feb to June Total (mm)
Kenyan 2030 Rainfall Feb to June Total (mm)
Risk of Hunger By Weather Across 1985-1996 (Canadian Model) 80 70 Percent of Population 60 50 40 30 20 10 Base Climate Change With Adaptation 0 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 Years under which weather was modeled
Implications for Agriculture for the Countries we Studied Climate is expected to be hotter and drier CO 2 fertilization effect Adaptations can be made to mitigate climate change impact
Historical Temperature Changes (1900-1999) Source: IPCC
Crop Diseases in Temperate and Tropical Regions (Swminanthan and Sinha, 1986) No. of diseases reported Crop Temperate Tropical Rice 54 500-600 Maize 85 125 Citrus 50 248 Tomato 32 278 Beans 52 250-280
Historical Precipitation Changes (1900-1999) Source: IPCC