Canal delivery and irrigation scheduling optimization based on crop water demand

Abstract Conventionally, canal water is distributed empirically regardless of soil water status at the time in irrigation districts of China, and the mismatch between the timing of water delivery and crop water demand often leads to the reduction in total production and irrigation water efficiency. In the study, an optimization model with minimizing both the difference between the time of water delivery and water demand, and fluctuation of discharge of the main canal as objectives was developefd for a two-stage canal system. The genetic algorithm was used to solve the problem. The irrigation time to meet the water demand in the optimization model was determined using a field water balance model for the command area of secondary canals. The optimization model was applied to the Xixun irrigation district located at Zhangye, Gansu Province, Northwest China. The performance of the model was evaluated by comparing crop water consumption and water productivity (WP) between optimized with conventional scheduling. The results showed that the optimized scheduling could achieve greater total production, less water loss, higher water use efficiency (WUE) and irrigation water productivity (IWP) under both full and reduced capacity conditions. Specifically, the optimized scheduling led to 20% greater total production, 33% less water loss, and more than 20% larger IWP than the conventional scheduling under both conditions. The optimization model could be a valuable tool in improving WP over the command area by adjusting water delivery and irrigation scheduling for irrigation districts.