2001) has been employed to simulate the rice yield response to climate change. Compared with other rice simulation models like CERES, DSSAT crop models, ORYZA2000 provides the most consistent rice yield prediction with uncertainties in comparison to the variation of field observation (Li et al. 2015). Similar to other models, a site specific parameterization of crop management practices and rice cultivars of the model will improve confidence in simulation. It can simulate precisely the response of rice yield to climatic variability in various climatic regions equally good or even better than other rice crop models (Zhang and Tao 2013). A significant number of ORYZA2000 model studies under different scenarios on the impacts of climate change on rice production have been well documented in the recent literature (Shen et al. 2011; Lee et al. 2012; Devkota et al. 2013; Wang et al. 2014; Zhang et al. 2015; Sumathi et al. 2015; Kim et
2001) has been employed to simulate the rice yield response to climate change. Compared with other rice simulation models like CERES, DSSAT crop models, ORYZA2000 provides the most consistent rice yield prediction with uncertainties in comparison to the variation of field observation (Li et al. 2015). Similar to other models, a site specific parameterization of crop management practices and rice cultivars of the model will improve confidence in simulation. It can simulate precisely the response of rice yield to climatic variability in various climatic regions equally good or even better than other rice crop models (Zhang and Tao 2013). A significant number of ORYZA2000 model studies under different scenarios on the impacts of climate change on rice production have been well documented in the recent literature (Shen et al. 2011; Lee et al. 2012; Devkota et al. 2013; Wang et al. 2014; Zhang et al. 2015; Sumathi et al. 2015; Kim et