Optimizing the allocation of irrigation water for multiple crops based on the crop water allocation priority

There is an urgent need to ensure regional food security and increase irrigation water productivity in response to water shortages in arid and semi-arid regions. Previous studies of the optimal allocation of irrigation water did not consider simultaneously optimizing across multiple crops or at different growth stages. This paper describes the development of an irrigation water optimization model that uses a crop water allocation priority (CWAP) model. The CWAP value was determined by quantifying the changes in three indicators: yield, economic benefits, and irrigation water productivity. Maximum yield, maximum economic benefits, and minimum irrigation shortage (at the critical crop and growth stage) were used as the objective functions of a non-linear multi-objective optimization model. The largest irrigation district in the northern arid area of China, Hetao Irrigation District (HID), was chosen to prototype this model. The optimization results, using CWAP, showed that yield, economic benefits, irrigation water productivity, and water productivity could be increased, respectively, by up to 13.38%, 13.40%, 2.30%, and 6.29%, for most crops when compared with optimization results without CWAP. Comparison of the optimized net irrigation quantities with the actual net irrigation quantities showed that optimization reduced water usage by up to 60.77% for wheat, 51.24% for corn, and 63.59% for sunflower. Blue water utilization under optimal irrigation conditions decreased by 1.12% for wheat, 2.91% for corn, and 9.91% for sunflower, compared with those in actual irrigation scenario. This method of optimizing irrigation water allocation in arid areas using CWAP provides decision-makers with accurate water-saving irrigation protocols that will reduce demand for water resources and promote sustainable agriculture.