Sustainable development of cropping pattern based on optimal irrigation scheduling in real time (Case study: Shoushtar plain)

On-time information and real time decision-making are effective factors in the process of water management in the farm. Therefore, in the present study, a real-time decision support system has been developed for the irrigation scheme of Mian-Ab irrigation network in Shoushtar plain with 24 sub-sets of cropping pattern and results are compared with existing pattern. To increase the accuracy of modeling, including soil water balance, crop production and root growth, a one-day time step is considered by replacing real-time data. For this purpose, the Particle Swarm Optimization Algorithm (PSOA) is used to maximize the net benefit of a growing season. The results showed that the optimal economic efficiency of water was obtained for tomato by 92500 IRR/m3. Its yield production also has increased more than 3000 kg/ha in an optimal strategy with a 35 percent reduction in water consumption. Furthermore, critical periods of crop water requirement was between the maximum canopy cover and the start of senescence. Crops like wheat, barley, and rapeseed which their conopy coverage decrease after senescence stage, are more compatible with deficit irrigation.