چكيده به لاتين
One of the major problems of the international community is the provision of food for the world's population. It is predicted that in the future, in addition to increasing the world's population, the amount of agricultural production will also be threatened. The impact of climate change on the agricultural sector is one of the major challenges of the future. As the global warming, the concentration of carbon dioxide is rising rapidly. Different scenarios have been predicted for the amount of greenhouse gas emissions in the future, each of which will lead to different results. The two phenomena of global warming and increasing the concentration of carbon dioxide can have an adverse effect on agricultural production. Also, providing the resources needed by the agricultural section will be very important in the future. One possible way to deal with the negative effects of climate change is to use adaptive strategies. Accordingly, by changing the approach and crop management, the effects of climate change can be reduced and more agricultural products are produced.
The SUBSTOR-Potato model, which is one of the DSSAT sub-models, is one of the powerful tools for finding the response of potato crop to the growing conditions. In this model, all the growth processes of the potato crop are considered. Input data of this model include weather data, management practices and genetic parameters of the cultivar. In this study, using GLUE tool and data related to two experiments in Ardabil and Mashhad, the SUBSTOR-Potato model was calibrated and validated, and genetic parameters related to the potato crop of Agria cultivar were obtained. The future climate was then predicted using the LARS-WG. To do this, model was calibrated and validated with using the historical weather data to finding parameters of semi-empirical distribution. Then LARS-WG will be able to simulate artificial weather data for the near, middle and far periods under the RCP4.5 and RCP8.5 scenarios. To generate future data, five models of GCMs were used and by averaging them, multi model ensemble mean (MMEM) was calculated and used to assess the effects of climate change. Finally, in two parts, simulation and optimization, the effect of climate change on potato crop growth was used. In the simulation part, the SUBSTOR-Potato model was simulated for the base line and future periods in two modes without changing the carbon dioxide concentration and by changing the carbon dioxide concentration in the two provinces of Hamedan and Kerman, and their results were compared to each other. In the optimization section, the model has three objectives of maximum crop yield, minimum water consumption and minimum fertilizer consumption and with a series of restrictions. To solve this model, MOPSO algorithm was used. In order to better display the results, the maximum crop yield goal became a constraint, and the problem became a two-objective optimization problem. Finally, the results of solving the optimization model in the form of Pareto fronts were obtained from the optimal answers that there is a trade-off between the amount of water and fertilizer consumption.
According to the results, it is predicted that in the coming years in Hamadan province, potato production will change from -8% to +6%, and in Kerman province this amount will be between -20% to +2%. These values are if the potato plant does not tolerate any nitrogen stress and also enough water reaches the plant. By comparing the Pareto fronts, water and fertilizer consumption are expected to decrease in the future compared to the base line in Hamedan province, but in Kerman province, water and fertilizer consumption is expected to increase in the future compared to the base line. Therefore, it is expected that with the constant amount of water and fertilizer consumption, the amount of production in Hamadan province will increase and in Kerman province will decrease in the future.
