14:45 〜 15:00
[ACG39-05] Estimation of wheat production by process-based model MATCRO-Wheat
キーワード: process-based model、climate change、future prediction
Crop production has been significantly influenced by climate change (Schindeler et al. 2001). In recent years, there is a concern that crop yield might decline due to rising temperatures and extreme weather events caused by global warming. Under the risk that rapid population growth could cause food shortages in near future, therefore, many crop models have been developed to assess future impacts of climate change. For wheat, which is one of main crops, high temperature inhibits vernalization related to wheat growth and would cause yield loss. On the other hand, high CO2 concentration increases the efficiency of the photosynthesis and would lead to high yield. Other climate changes such as precipitation and radiation would also affect wheat yields. Key climate variables which have significant influence on yields are different among regions. Hence it is important to identify them for climate change adaptation. However, there have been few global studies on this topic, although a lot of global studies only showing climate change impacts.
This study aims to assess climate change impacts on wheat production in the future and geographically identify key climate variables, by using process-based wheat growth model MATCRO-Wheat, recently developed.
To the goal, MATCRO-Wheat was run under current and future values for each climate variables at global scale with the spatial resolution of 0.5 degree x 0.5 degree and with the simulation period from 2015 to 2100. In the presentation, the preliminary results on key climate variables will be presented.
This study aims to assess climate change impacts on wheat production in the future and geographically identify key climate variables, by using process-based wheat growth model MATCRO-Wheat, recently developed.
To the goal, MATCRO-Wheat was run under current and future values for each climate variables at global scale with the spatial resolution of 0.5 degree x 0.5 degree and with the simulation period from 2015 to 2100. In the presentation, the preliminary results on key climate variables will be presented.