Improved climate risk simulations for rice in arid environments.

Area of Science:

• Agricultural Science
• Crop Modeling
• Environmental Science

Background:

• Existing crop growth models like ORYZA2000 often struggle to accurately simulate rice yields in arid regions due to temperature extremes.
• Previous models underestimated cold stress and overestimated heat stress, leading to inaccurate yield predictions.

Purpose of the Study:

• To enhance the ORYZA2000 crop growth model by integrating recent research on temperature effects on rice.
• To improve the accuracy of yield simulations in arid environments and assess its utility for climate change impact analysis.

Main Methods:

• Integrated new research on cardinal temperatures for phenology, leaf growth, flowering, and sterility into ORYZA2000.
• Compared simulated yields with observed yields for rice variety 'IR64' sown monthly in Senegal.
• Modified heat and cold stress subroutines, incorporating transpirational cooling and early morning flowering effects.

Main Results:

• Model accuracy improved significantly, with modeling efficiency (EF) increasing from -0.32 to 0.70 after modifications.
• New subroutines accurately accounted for transpirational cooling and early morning flowering (heat sterility) and minimum temperatures (cold sterility).
• Further improvements to 0.48 were achieved by incorporating new cardinal temperatures for phenology and early leaf growth.

Conclusions:

• The adapted ORYZA2000 model provides a more powerful tool for analyzing climate change impacts on rice cultivation in arid regions.
• The enhanced model aids in optimizing cropping calendars for improved rice production under challenging environmental conditions.