Crop Simulation Modelling (CSM) has been the most advanced tool to simulate the average productivity of a cropping system. CSM could predict the growth, development and yield of a crop or cropping system under variable management options, climate and soil environment. For a specific soil and climate, a variable management option was the criterion, which affect the soil-plant environment and varied the yield. Decline or stagnation of yield of rice-wheat rotation has been the major problem in present Indian as well as in Asian Agriculture. Rice-wheat rotation cover nearly 24 million hectare of Indian subcontinent. Except the changes in weather parameters, all the other reasons of yield stagnation are site-specific. In Eastern India, soils are poor in organic matter content with low nutrient reserves and water holding capacity moreover use of recent high yielding varieties need higher rate of inorganic N and irrigation. Limited or no crop residue incorporation along with inappropriate use of inorganic N fertilizers resulted in depletion of soil fertility and ultimately decreasing the yield. Thus a comprehensive study for assessing the effects of management options for sustainability of transplanted rice-wheat system in eastern India was initiated. The study comprised of a three years field experiment along with crop simulation modelling. All data related to soil, crop and weather variables were collected and were used for calibration and validation of CERES-Rice and CERES-Wheat of DSSAT3.5. Solar radiation, maximum and minimum temperature and rainfall were the weather variables which were mainly used to run the model. Seasonal analysis program driver of the DSSAT3.5 suite of model was extensively used to simulate the growth and yield of rice and wheat crops under different crop management options and to evaluate the economic risks associated with different options. While running the seasonal analysis program, 20 years of generated weather data were used as 20 replications to run each combination of management options of rice-wheat crop residues, N application rates and irrigation regimes. The weather generator SIMMETEO was used to generate the future weather scenario and to run the seasonal analysis program. In order to select the best management combination for rice and wheat crops, the analysis was used separately for different treatment combinations and the best combination was selected through biophysical and economical analysis. The box plots (mean, standard deviation, maxima and minima), mean-variance plots and yield-cumulative probability plots were used to compare the results under different treatment combinations. The biophysically tested treatment combinations were also compared by economical analysis and finally through Mean-Gini stochastic dominance analysis, which is an economical analysis method in seasonal analysis program to select the most dominant treatment, was applied to find out the best suitable treatment combination separately for rice and wheat crops. Eight combinations of four crop residue levels (no residue, rice residue, wheat residue and both rice and wheat residues) and two N levels (N100 and N120) were compared for rice and the best treatment combination selected was incorporation of both rice and wheat residues and N at 100 kg ha–1 for rice. Sixteen combinations of two irrigation regimes, four crop residue levels (no residue, rice residue, wheat residue and both rice and wheat residues) and two levels of N (N80 and N100) application rates were compared for maximum economic yield of wheat and the best treatment combination was application comparatively dry irrigation regime with incorporation of both rice and wheat residues and application of N at 80 kg ha–1. The predictions through seasonal analysis clarified that DSSAT3.5 as capable of predicting reliable results and selecting best suitable management options for economic yield of rice-wheat system in subhumid subtropical agroclimatic region of India.