The relationship between moisture and yield of maize under different water levels using cropsyst model

This thesis study was aimed at determining the effect of different irrigation regimes on maize under subsurface drip irrigation system and the prediction of maize yield using CropSyst plant growth model. Within the scope of this study, a one-year period field experiment was carried out under Çukurova climatic condition. Three irrigation regimes including I100 (full irrigation), I75 (75% of full irrigation), and I50 (50% of full irrigation) was applied in the field study. During the period of the study, maize plant's important growth data were collected and after harvest soil samples was also collected. The yield of maize was estimated by creating different scenarios with CropSyst and the relationship between temperature and moisture was modelled. It was found that the irrigation regimes had no significant effect on soil physical properties, biomass, and the leaf area index (LAI) in the study. On the other hand, I100 and I75 performed better in soil carbon content, some soil chemical properties, cob length and width and yield compared to I50. From the result of the calibration and validation of CropSyst, it was determined that the biomass of maize under subsurface irrigation system can be effectively predicted in all irrigation regimes. According to the result of scenario made when the planting date was altered yields of I75 and I50 were the most affected. Throughout the scenario period at different constant temperature regimes I100, I75 and I50 practice's yield increased up to 35oC, 32oC and 27oC respectively. When the daily mean temperature was raised by 1oC, I75 and I50 treatment's yield decreased with increase in temperature while I100's yield remained relatively the same. In this study, when taken yield componets of maize is taken into consideration, it came into prominence that limited irrigation (I75) which is 25% less use of full irrigation capacity can be adopted. In addition, the adoption of CropSyst in terms of estimating the crop yield is strongly suggested and also the model should be expanded considering different management applications.