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Vulnerability and Adaptation in Agriculture: the Thai’s Experiences

Vulnerability and Adaptation in Agriculture: the Thai’s Experiences. The study Approach Results Lessons learned and Potential improvement Implication. Approach. Controlled climate. GHG 1% climate. Crop growth models. Yields (controlled climate). Yields (GHG 1% climate).

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Vulnerability and Adaptation in Agriculture: the Thai’s Experiences

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  1. Vulnerability and Adaptation in Agriculture: the Thai’s Experiences • The study • Approach • Results • Lessons learned and Potential improvement • Implication

  2. Approach Controlled climate GHG 1% climate Crop growth models Yields (controlled climate) Yields (GHG 1% climate) Difference in yields

  3. Climate Scenarios Using the simulation of the GCMs Transient (CO2 increases 1% per year) Various GCMs CCCMA ECHAM CSIRO HADLEY

  4. From Global to Local • Direct Interpolation • Use 30 years monthly average to reduce short term climate variation • 1990s(1960-89) • 2020s(2010-2039) • 2050s (2040-2069) • 2080s(2070-2099) • Develop daily climate scenarios for specific locations

  5. Crops: Models and Areas • Crop models • CERES MAIZE, CERES RICE • Crops and areas • Fragrant Rice in two provinces • Maize in two provinces

  6. Scenarios • Four climate inputs from different GCMs • Two crops x two areas • With and without fertilizer • With and without C effects on crop • Four intervals ( 1990s, 2020s, 2050s and 2080s)

  7. Some Results

  8. Maize, Nakhonsawan, no fertilizer

  9. Maize, Nakhonrachasima, no fertilizer

  10. Rice, Roi-et, no fertilizer

  11. Rice, Surin, no fertilizer

  12. Major observations • Results from different GCMs vary quite a lot • Yields tend to drop overtime • Yields of maize are not much different between the two provinces, the reverse is true for rice • There are some positive carbon effects on yield

  13. Lessons learned • High uncertainty of climate models • Crop models need to be improved • Impacts could vary substantially between areas • Vulnerability analysis is not sufficient to be used for adaptation study • Local climate data are limited

  14. How to improve • Reduce uncertainty of climate models • develop regional or sub-regional models • improve downscaling methods • Improve crop growth models • Cover the areas and crops adequately • Develop other approaches

  15. Implications • Research and development on vulnerability is urgently needed • Soft technology transfer • Indigenous capacity building • Sub-regional network is important to facilitate the technology development and capacity building • A need for strong participation in international research and development on vulnerability • Existing mechanisms make vulnerability and adaptation relatively much behind others

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