Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.
International Center for Agricultural Research in
the Dry Areas - ICARDA
IFPRI, Rome,
26 May, 2015
Global Futures and Stra...
Country-level bio-economic modeling of improved
agricultural practices on wheat-based agricultural
systems of the dry area...
• Yet, some countries current wheat production brings
declining soil productivity (less organic matter),
erosion, etc.;
• ...
Country-level bio-economic modeling of
improved technologies on wheat-based
agricultural systems of the dry areas
Crop mod...
Wheat technologies
1) Conventional tillage: Normal practice  includes removal of
residues by tillage operations (two befo...
Biophysical data collection for crop
simulation
- All these technologies tested with management practices: 1)
Sowing time ...
Key messages
 All technologies
provide benefit over
conventional tillage
except No-till at Tel
Hadya with no N
applicatio...
Planting time
Early Late
Fertilizer rates (kg N/ha) Fertilizer rates (kg N/ha)
0 30 60 0 30 60
Tel Hadya
Zero-tillage -19....
IMPACT modeling
Scenarios (Tel Hadya):
Assumptions:
Socioeconomic: SSP3 (or “Fragmentation’’),  economic growth is assume...
Improved technologies
Technical adoption:
P1: First period of 5 years: Some difference in wheat yield is observed
between ...
2025 2030 2039
Average
Yield T/ha
% change
compared
to CC
scenario
Average
Yield T/ha
% change
compared
to CC
scenario
Ave...
Tot
Supply
(000 mt)
% change
compared
to CC
scenario
Tot
Supply
(000 mt)
% change
compared
to CC
scenario
Tot
Supply
(000 ...
Net trade
balance
(000 mt)
% change
compared
to CC
scenario
Net trade
balance
(000 mt)
% change
compared
to CC
scenario
Ne...
Initial implications:
• Genetic improvement of wheat should be carefully
undertaken and adapted to different countries of ...
Mean change in grain yield (%)
without CO2 (carbon
fertilization) response
Mean change in grain yield
considering CO2 resp...
Steps ahead
1. Country level bio-economic modelling of conservation
agriculture practices on wheat-based agricultural syst...
Thank you
Collaborators/Partners
- NCARE, Jordan (Amal Al-Khatib, Siham Allouzi)
- INRAT, Tunisia (Mohammad Annabi)
Upcoming SlideShare
Loading in …5
×

9 icarda-26-may-2014

346 views

Published on

The Global Futures and Strategic Foresight (GFSF) team met in Rome from May 25-28, 2015 to review progress towards current work plans, discuss model improvements and technical parameters, and consider possible contributions by the GFSF program to the CRP Phase II planning process. All 15 CGIAR Centers were represented at the meeting.

Published in: Government & Nonprofit
  • Be the first to comment

  • Be the first to like this

9 icarda-26-may-2014

  1. 1. International Center for Agricultural Research in the Dry Areas - ICARDA IFPRI, Rome, 26 May, 2015 Global Futures and Strategic Foresight Extended Team Meeting Hotel Abitart, Rome, 25 – 28 May 2015 Aden Aw-Hassan Roberto Telleria Prakash Dixit Aymen Frija
  2. 2. Country-level bio-economic modeling of improved agricultural practices on wheat-based agricultural systems of the dry areas Justification • Key crop for food security (some MENA countries highest wheat consumption per capita); • Last 50 years  Decline per-capita wheat production; • MENA largest wheat importer in the world; • Governments are determined to increase wheat production; • Wheat  Anyways dominate rainfall production in MENA; • Crop employs most people than any other crop in MENA;
  3. 3. • Yet, some countries current wheat production brings declining soil productivity (less organic matter), erosion, etc.; • Future climate change can further lower wheat production? • Promising technologies (including CA) in other arid regions (e.g. arid parts of Australia); • Technologies  capacity to enhance and sustain yield, increase farmer income, protection against land degradation, environmental services (carbon sequestration), mitigation of climate change. • Public investment in technologies is convenient?
  4. 4. Country-level bio-economic modeling of improved technologies on wheat-based agricultural systems of the dry areas Crop model (APSIM) Policy making IMPACT model
  5. 5. Wheat technologies 1) Conventional tillage: Normal practice  includes removal of residues by tillage operations (two before sowing). Traditional wheat variety. 2) Zero-tillage: Complete residue retention without any tillage operation (grain harvested and the entire residue left in the field). Improved wheat variety Sham 3; 3) Mulching: Complete residue retention and 6,000 kg/ha wheat residue mulch added at sowing. Sham 3 wheat variety; 4) Raised bed: 15% increase in water holding capacity of 0-0.45 layer and 25% residue removal at harvest. Sham 3 wheat variety.
  6. 6. Biophysical data collection for crop simulation - All these technologies tested with management practices: 1) Sowing time (two beginning of October and November); and 2) Fertilizer application (N). - 50 year daily weather data (maximum and minimum temperatures, solar radiation and rainfall)  generated using Long Ashton Research Station Weather Generator (LARS-WG)-version 5.5. Two wheat growing areas: Tel Hadya and Breda; - Crop simulations  Agricultural Production Systems Simulator - APSIM (v. 7.5)  Capable of simulating crop yields for different environments and soil types;
  7. 7. Key messages  All technologies provide benefit over conventional tillage except No-till at Tel Hadya with no N application  Benefits are more pronounced with higher rates of N application  Mulching seems to produce best results  Yield effects of No- till, Mulching and Raised-based depend on the location
  8. 8. Planting time Early Late Fertilizer rates (kg N/ha) Fertilizer rates (kg N/ha) 0 30 60 0 30 60 Tel Hadya Zero-tillage -19.6 -2.6 24.7 -13.0 11.3 49.8 Mulching 20.3 17.8 38.8 3.1 31.9 65.3 Raised-bed -4.6 5.9 28.3 5.3 26.4 51.0 Breda Zero-tillage 33.9 120.2 188.2 88.0 151.4 213.6 Mulching 90.4 163.7 225.4 131.5 187.5 258.7 Raised-bed 53.3 114.4 166.8 62.8 118.6 114.8 Percentage change in wheat yield in relation to different planting time, fertilizer rates and cropping technologies in Tel Hadya and Breda sites in Northern Syria.
  9. 9. IMPACT modeling Scenarios (Tel Hadya): Assumptions: Socioeconomic: SSP3 (or “Fragmentation’’),  economic growth is assumed to be much slower as a combination of multiple causes: slow technological progress, low education levels, lack of international cooperation. Climate: Climate dataset chosen  GFDL (rcp8p5 - representative concentration pathway). Adoption: Each TP  35% of cultivated areas following a logistic function of scale 6 and median the year 2028. Timeframe: 2015-2040 (25 years). Name Technolog y simulated Fertilizers dose (Kg N/ha) Planting date % change in yield compared to conventional wheat TP1 Zero-Till 30 Late planting 11.3 TP2 Mulching 30 Early planting 17.8 TP3 Mulching 30 Late planting 31.9 TP4 Raised bed 30 Early planting 5.9 TP5 Raised bed 30 Late planting 26.4
  10. 10. Improved technologies Technical adoption: P1: First period of 5 years: Some difference in wheat yield is observed between conventional and improved technologies. P2: Second period of 7 years: Yield gap between conventional and improved technologies becomes more evident. P3: Third period of 13 years: Yield difference between enhanced technologies and conventional farming is relatively stable. Time Yields under enhanced technologies Yields under conventional wheat farming Yields P1 P2 P3
  11. 11. 2025 2030 2039 Average Yield T/ha % change compared to CC scenario Average Yield T/ha % change compared to CC scenario Average Yield T/ha % change compared to CC scenario No CC, no TP Irrigated 5.94 2.45 6.29 3.20 6.77 4.29 Rainfed 1.51 3.44 1.58 4.54 1.65 6.45 CC, no TP (baseline) Irrigated 5.79 -- 6.10 -- 6.50 -- Rainfed 1.46 -- 1.51 -- 1.55 -- TP1 Irrigated 5.82 0.38 6.17 1.26 6.75 3.91 Rainfed 1.47 0.38 1.53 1.25 1.61 3.90 TP2 Irrigated 5.83 0.61 6.22 2.03 6.91 6.38 Rainfed 1.47 0.61 1.55 2.01 1.65 6.36 TP3 Irrigated 5.86 1.11 6.33 3.74 7.28 12.15 Rainfed 1.48 1.10 1.57 3.71 1.73 12.09 TP4 Irrigated 5.81 0.20 6.14 0.64 6.62 1.95 Rainfed 1.47 0.19 1.52 0.63 1.58 1.94 TP5 Irrigated 5.85 0.92 6.28 3.07 7.13 9.85 Rainfed 1.48 0.91 1.56 3.05 1.70 9.80 Results Impact of different TPs on the average wheat yield in Syria (% of change against baseline scenario: climate change without any technology adoption)
  12. 12. Tot Supply (000 mt) % change compared to CC scenario Tot Supply (000 mt) % change compared to CC scenario Tot Supply (000 mt) % change compared to CC scenario No CC 6194.78 3.16 6624.67 4.15 7185.7 5.81 GFDL 6004.88 0 6360.67 0 6790.88 0 TP1 6027.82 0.38 6440.81 1.26 7055.89 3.9 TP2 6041.44 0.61 6489.31 2.02 7222.96 6.36 TP3 6071.17 1.1 6597.69 3.73 7613.31 12.11 TP4 6016.54 0.19 6401.16 0.64 6922.97 1.95 TP5 6059.67 0.91 6555.29 3.06 7457.59 9.82 2025 2030 2039 Impact of different TPs on the total wheat supply in Syria (% of change against baseline scenario: climate change without any technology adoption)
  13. 13. Net trade balance (000 mt) % change compared to CC scenario Net trade balance (000 mt) % change compared to CC scenario Net trade balance (000 mt) % change compared to CC scenario GFDL -124.02 0 -425 0 -1133.6 0 TP1 -101.14 -22.63 -345.07 -23.16 -869.39 -30.39 TP2 -87.55 -41.65 -296.71 -43.23 -702.82 -61.29 TP3 -57.91 -114.18 -188.63 -125.3 -313.66 -261.4 TP4 -112.39 -10.35 -384.62 -10.5 -1001.9 -13.14 TP5 -69.37 -78.77 -230.91 -84.05 -468.91 -141.75 2025 2030 2039 Effect of different TPs on the long term trade balance of wheat in Syria Note: Negative percent value indicates reduction in trade balance deficit.
  14. 14. Initial implications: • Genetic improvement of wheat should be carefully undertaken and adapted to different countries of the region; • Investments in high yield varieties seem to be profitable; • Adapted improved packages should be developed by the research organizations.
  15. 15. Mean change in grain yield (%) without CO2 (carbon fertilization) response Mean change in grain yield considering CO2 response (%) Year RCP4.5 RCP8.5 RCP4.5 RCP8.5 2025 -2.45 -2.20 1.50 2.65 2035 -4.25 -3.85 3.80 7.00 2045 -5.35 -8.50 6.75 7.75 2055 -8.05 -11.20 7.00 11.15 2065 -9.15 -16.35 8.29 11.20 2075 -10.20 -22.25 8.40 8.45 2085 -13.40 -25.80 4.35 8.55 2095 -14.10 -30.50 4.05 5.10 Mean change in wheat yield (%) taking 2015 as base (i.e., decade of 2010-2020) based on RCP4.5 and RCP8.5 climate change scenarios in Jordan  APSIM was used for Analysis  Results based on two soil types: Heavy clay at Maru and clay loam at Mushaqar  Water holding capacity of Maru soil = 194 mm and, Mushaqar soil =117 mm for a depth of 1.5 m KEY MESSAGES • Impact of ONLY temperature and rainfall due to CC is negative on wheat yield; • Elevated CO2 in atmosphere improved yield due to increased photosynthesis; • OVERALL: There is no negative impact of climate change rather small gains in yield. Will future climate change be favorable for wheat production in Jordan? A decadal analysis
  16. 16. Steps ahead 1. Country level bio-economic modelling of conservation agriculture practices on wheat-based agricultural systems in Jordan/Tunisia (In collaboration with ministries of agriculture of Tunisia and Jordan): • Improved food security from groundwater, conjunctive use, and better management of water storage capacities: Application in selected dry areas (in collaboration with IWMI) • Workshop on 16-17 June in Amman-Jordan; 2. Adaptation of different wheat crops varieties to the climate change in the MENA region: a comparative analysis (in collaboration with CIMMYT).
  17. 17. Thank you
  18. 18. Collaborators/Partners - NCARE, Jordan (Amal Al-Khatib, Siham Allouzi) - INRAT, Tunisia (Mohammad Annabi)

×