| Global warming resulting from increasing greenhouse gas emissions is a threat to global food production. A rise in temperatures along with a shift in precipitation regimes is expected to decrease production in the future. However, farm management, such as the choice of crop cultivar, planting decisions, and irrigation can help farmers to alleviate some of the potential crop yield losses from climate change. In order to estimate the role of climate and agricultural management practices on yield, a new global crop model, PEGASUS 1.0 (Predicting Ecosystem Goods And Services Using Scenarios) has been developed for maize, soybean, and spring wheat. This thesis presents the methods used to develop the model, and its evaluation against present-day data, along with a model sensitivity experiment to a global warming of 2°C. Overall, results for present-day simulations are reasonable. Simulated planting and harvesting dates occur within the range of observations for more than 62% of total crop harvested areas, for each of the three crops. A comparison between simulated and observed crop yields indicates a weighted coefficient of determination, with the weighting based on crop harvested area, of 0.81 for maize, 0.63 for soybean, and 0.45 for spring wheat. The model simulates that an increase in temperature will result in a global decrease in crop yields. Nevertheless, adapting planting dates and cultivar choices to changes in temperature can avoid 60{78% of yield losses globally. Overall, the model results suggest that agricultural production in the richest countries, mostly located in the northern high latitudes, could benefit from increase in temperature, while the agriculture in the poorest countries in the tropics are likely to suffer the most. |
