Simulating maize yield and soil inorganic N dynamics in South Ontario using the DSSAT model

Citation

Yang, J.Y., Yang, X.M., Drury, C.F., Liu, S. 2019. Simulating maize yield and soil inorganic N dynamics in South Ontario using the DSSAT model. Oral presentation In: SSSA International Soils Meeting, Jan. 6-9, 2019, in San Diego, California

Résumé

Nitrogen (N) fertilizer is applied to achieve high maize yield, but excess N can lead to environmental losses, (leaching, denitrification) and insufficient N can result in a reduced yield. The objective of this study was to evaluate the ability of the CSM-CERES-Maize model in the Decision Support Systems for Agro-technology Transfer (DSSAT) v4.7 software to simulate maize (Zea mays L.) grain yield, grain N uptake, soil inorganic N, and soil water storage for five fertilizer N rates (0, 50, 100, 150 and 200 kg N/ha) in Southern Ontario. The second objective was to see if this model could simulate maize yield accurately in 5 counties across Southern Ontario. The measured datasets used for model evaluation were obtained from 2010 to 2012. Statistical evaluation showed a “good” agreement between the simulated and measured grain yields (i.e., nRMSE≤15%), a “moderate” agreement for growing season’s biomass and plant N uptake due to the over-estimation by the model in the middle of the growing season, and a “poor” agreement for soil inorganic N in the 30 cm and soil water storage in the 100 cm depth. The model was applied at 5 counties in Southern Ontario to simulate maize yield (2010-2012). A total of 177 field simulations were made based on soil and daily weather datasets. The simulated average maize dry yield at each county matched well with the measured county yields under the normal years of 2011-2012, while it tended to underestimate the yield in two of the counties under a dry year of 2010. We concluded that the CSM-CERES-Maize model could be used to simulate optimal N rates and grain yields for various soils and weather conditions in maize Southern Ontario.