The contradiction between crop water requirements and water supplies in Guanzhong Plain of Northwest China restricts the production of local winter wheat. The optimization of irrigation strategies considering multiple-objectives is of great significance to alleviate water crisis and sustainability of winter wheat production. This paper considered three typical hydrological years (dry year, normal year, and wet year), and a simulation optimization model coupling AquaCrop and NSGA-III was developed using Python language. The multi-objective optimization problem considered four objectives: (1) maximize crop yield (Y), (2) minimize irrigation water (IW), (3) maximize irrigation water productivity (IWP), and (4) maximize water use efficiency (WUE). The TOPSIS-Entropy method was then adopted for decision-making based on the Pareto fronts which were generated by multi-objective optimization, thus facilitating the optimization of the irrigation strategies. The results show that AquaCrop model could accurately simulate the growth process of winter wheat in the study area, the relative error is acceptable. The R2 of canopy cover (CC) is 0.75 and 0.61, and above ground biomass production (B) is 0.94 and 0.93, respectively. In the Pareto fronts, the difference between the maximum and minimum yield of winter wheat is 9.48 %, reflecting the diversity of multi-objective optimization results. According to the analysis results of this paper, the performance of different irrigation scenarios in each typical year varies greatly. The performance of the optimization in dry years is significantly better than that in normal years and wet years. The optimization of irrigation strategies and comparison of different scenarios play a positive role in improving the local water use efficiency, the winter wheat yield, as well as the sustainable development level of water resources.
Keywords: ACOSP; Irrigation strategy; NSGA-III; TOPSIS-Entropy method; Winter wheat.
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