The Use of Crop Simulation Models as a Tool for Environmental Characterization for Maize and Soybean Crops.

Drought and temperature stress have been reported as important variables that can affect crop yield. However; studies comparing the magnitude, duration and timing of crop stress for different seasons and locations and its impact on field crops have been limited. Process-based crop simulation models can be used to predict growth, development, and yield of crops. These models use local environmental conditions, including weather and soil physical and chemical characteristics, crop management, and genetic information. Previous research has shown that crop simulation models are well suited to determine the impact of weather on growth and development and that they can be a useful tool to assess the long-term impact of climate and associated environmental risks on crop yield. In the present study a set of maize and soybean trials conducted under rainfed conditions through the USA during 2007 and 2008 were analyzed to characterize the conditions related to temperature and drought stress for specific developmental phases. The CSM-CERES-Maize and CSM-CROPGRO-Soybean models were used to simulate maize and soybean growth and development. Model simulations were analyzed with an emphasis on crop water stress for specific periods of the growing season. Two temperature stress indices were estimated using the daily maximum temperature for the “day temperature stress index” and the daily minimum temperature for the “night temperature stress index”. The study showed that in general during 2007 the soybean and corn trials were exposed to higher water stress levels than during 2008 growing season. In addition, the temperature stress in the 2007 growing season was consistently higher than during 2008. However, there was variability for the temperature stress indices and water stress indices across different locations (space) and period of analysis (temporal).