The importance of agricultural mathematical models development and application, had considerably increased in the last decay, due to the complex possibilities which they offer in simulation of the interactive crop-weather relationship, growth dynamics for different crops and the impact of agriculture management practices for the crop yield productivity and natural environment preservation. Using mathematical models is providing a better understanding of developing processes at ecosystem's level, offering the possibility to simulate alternative scenarios, by changing input parameters like: weather conditions, crop variety, agro-technologies application's options (irrigation, fertilization, pesticides), for the agricultural management strategies analysis.
The large development of computer technology and software, represents an important support system for implementation of mathematical models, enabling complex analysis and storage of input data, efficient simulation of the models, or graphical and tabular interfaces for results' representation.
The capability of mathematical models, used for agricultural ecosystems simulation, to respond correctly to the proposed scenarios' key problems, depends mostly on input data accuracy and specific parameters calibration according to the climate, soil, and crop's phenology of specific locations. Therefore, the application of the modeling systems without a careful adaptation of local input data and parameters would conduct to erroneous output results and specific phenomena interpretations.
The main objective of this study is to propose a methodology for the use of Decision Support System for Agrotechnological Transfer (DSSAT) v.3, (developed by The International Benchmark Sites Network for Agrotechnology Transfer [IBSNAT], at University of Hawaii, 1994) in order to calibrate and validate the CERES-Wheat model included in this complex modeling system, taking into account the impacts of weather variability, varieties' performance and agricultural