2017FACCE MACSUR ReportsRequires access

Evaluation of CERES Wheat and Rice Model for changing Climatic Conditions in Haryana, India

Mamta Rana

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Abstract

The simulation models with its soil-weather-plant atmosphere interacting system are important tools for assessing the crops in changing climate conditions. The CERES-Wheat & Rice vs. 4.6 DSSAT was calibrated and evaluated for one of major producers of wheat and rice state- Haryana, India. The simulation runs were made under irrigated conditions and three fertilizer applications dose of N-P-K to estimate crop yield and other growth parameters along with phenological development of the crop. The genetic coefficients derived by iteratively manipulating the relevant coefficients that characterize the phenological process of wheat and rice crop to best fit match between the simulated and observed anthesis, physiological maturity and final grain yield.The model validated by plotting the simulated and remote sensing derived Leaf Area Index (LAI). LAI product from remote sensing provides the edge of spatial, timely and accurate assessment of crop. For validating the yield and yield components, the error percentage between the observed and simulated data was calculated. The analysis shows that the model can be used to simulate crop yield and yield components for selected wheat and rice cultivar under different management practices. During the validation, the error percentage was less than 10%, indicating the utility of the calibrated model for climate risk assessment in the selected region.

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What this paper is about

The simulation models with its soil-weather-plant atmosphere interacting system are important tools for assessing the crops in changing climate conditions. The CERES-Wheat & Rice vs. 4.6 DSSAT was calibrated and evaluated for one of major producers of wheat and rice state- Haryana, India. The simulation runs were made under irrigated conditions and three fertilizer applications dose of N-P-K to estimate crop yield and other growth parameters along with phenological development of the crop. The genetic coefficients derived by iteratively manipulating the relevant coefficients that characterize the phenological process of wheat and rice crop to best fit match between the simulated and observed anthesis, physiological maturity and final grain yield.The model validated by plotting the simulated and remote sensing derived Leaf Area Index (LAI). LAI product from remote sensing provides the edge of spatial, timely and accurate assessment of crop. For validating the yield and yield components, the error percentage between the observed and simulated data was calculated. The analysis shows that the model can be used to simulate crop yield and yield components for selected wheat and rice cultivar under different management practices. During the validation, the error percentage was less than 10%, indicating the utility of the calibrated model for climate risk assessment in the selected region.

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Available abstract

The simulation models with its soil-weather-plant atmosphere interacting system are important tools for assessing the crops in changing climate conditions. The CERES-Wheat & Rice vs. 4.6 DSSAT was calibrated and evaluated for one of major producers of wheat and rice state- Haryana, India. The simulation runs were made under irrigated conditions and three fertilizer applications dose of N-P-K to estimate crop yield and other growth parameters along with phenological development of the crop. The genetic coefficients derived by iteratively manipulating the relevant coefficients that characterize the phenological process of wheat and rice crop to best fit match between the simulated and observed anthesis, physiological maturity and final grain yield.The model validated by plotting the simulated and remote sensing derived Leaf Area Index (LAI). LAI product from remote sensing provides the edge of spatial, timely and accurate assessment of crop. For validating the yield and yield components, the error percentage between the observed and simulated data was calculated. The analysis shows that the model can be used to simulate crop yield and yield components for selected wheat and rice cultivar under different management practices. During the validation, the error percentage was less than 10%, indicating the utility of the calibrated model for climate risk assessment in the selected region.

Key concepts: DSSAT, Crop simulation model, Phenology, Anthesis, Yield (engineering), Environmental science, Agronomy, Crop

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