Selection of Simulation Locations Twelve Agro-Ecological Zones (AEZs) of Bangladesh were selected among the major rice growing areas in different regions of Bangladesh to predict development phases of two boro varieties BR3 and BR14 for the years 2008, 2030, 2050 and 2070. For this study, Rajshahi (AEZ-11), Bogra (AEZ-25) and Dinajpur (AEZ-27) were selected from northwestern region; Mymensingh (AEZ-9) and Tangail (AEZ-15) were selected from central region; Jessore (AEZ-14) and Satkhira (AEZ-13) from southwestern region; Barisal (AEZ-18) and Madaripur (AEZ-12) from southern region; Chandpur (AEZ-19) and Comilla (AEZ-19) from southeastern region; and Sylhet (AEZ-20) from eastern region. 2.2 Crop Model DSSAT modeling system is an advanced physiologically-based rice crop growth simulation model and has been widely applied to understanding the relationship between rice yield, development phases and its environment (Basak 2009). The model estimates rice yield of irrigated and non-irrigated rice, determines duration of growth stages, dry matter production and partitioning, root system dynamics, effect of soil water and soil nitrogen contents on photosynthesis, carbon balance and water balance. Ritchie et al. (1987) and Hoogenboom et al. (2003) have provided a detailed description of the model. In the present study, the Introductory Crop Simulation (ICSim) of DSSAT modeling system was used for all simulations for predicting development phases of the selected two varieties rice. 2.3 Selection of Rice Variety In predicting crop growth (development phases), DSSAT model takes into effect of weather, crop management, genetics, and soil water, C and N. The model uses a detailed set of crop specific genetic coefficients, which allows the model to respond to diverse weather and management conditions. Therefore, in order to get reliable results from model simulations, it is necessary to have the appropriate genetic coefficients for the selected cultivars (Basak 2009). The two boro rice varieties BR3 and BR14 were selected in the present study because genetic coefficients for these varieties are available in the DSSAT modeling system. Although these varieties are not widely used at present time, the effects of climate change and variability on these varieties provide insights into possible impact of climate change on development phases of boro rice in the future. 2.4 Soil and Crop Management Input The model requires a quite detailed set of input data on soil and hydrologic characteristics (i.e., pedological and hydrological data), and crop management. Soil characteristics include soil texture, number of layers in soil profile, soil layer depth, pH of soil for each depth, clay, silt and sand contents, organic matter, cation exchange capacity, etc were used as a input data for this model (Basak 2009). Required data on soil and hydrologic characteristics for the selected locations (districts) were collected from Bangladesh Rice Research Institute (BRRI, The model required crop management data (i.e., agronomic data) which are planting date, planting density, row spacing, planting depth, irrigation amount and frequency, fertilizer application dates and amounts. The major crop management input data used in all model simulations in the current study are given in Table 3; these represent typical practices (BRRI, 2006 and Rashid, 2008) in Bangladesh. Using these inputs, the average (of 12 locations) yields of BR3 and BR14 for the year 2008, estimated by the model, were about 5500 kg ha-1 and 4050 kg ha-1, respectively (Basak et al. 2009); these values are close to the reported yields of these varieties (BRRI 2006). These crop management inputs were subsequently used in all model simulations under the predicted weather scenarios for the years 2008, 2030, 2050 and 2070. It should be noted that the DSSAT model does not count the water required for preparation of land before transplanting (which usually varies from 200 to 300 mm, depending on soil and weather condition). 2.5 Weather data A regional climate model named Providing Regional Climate for Impacts Studies (PRECIS) was used to generate daily weather data needed for running the DSSAT model. The special report on emission scenarios (SRES) A2 of ECHAM4 has been used as PRECIS input. In this study PRECIS runs with 50-km horizontal resolution for the present climate (2008) using baseline lateral boundary conditions (LBCs). The model domain was selected 65–103°E and 6–35°N to cover Bangladesh and its surrounding areas. In the next step, PRECIS run was completed for the year 2030, 2050 and 2070 using ECHAM 4 SRES A2 as the model input. The PRECIS outputs that were used in the DSSAT model include daily maximum temperature (Tmax), daily minimum temperature (Tmin), daily incoming solar radiation (Srad), and daily rainfall.