Water-saving potential analysis of spring wheat in Altay based on AquaCrop model

In 2017, the comprehensive irrigation quota of various crops in Altay was 955 mm, and the actual irrigation quota of spring wheat, the main food crop, was approximately 780 mm, which is far higher than the actual water demand of spring wheat. To improve water-use efficiency, the best irrigation quota for spring wheat was determined, and the relationship between crop yield and water consumption was established. The AquaCrop model was used as the research model, and the main parameters of the AquaCrop model were localized in northern Xinjiang. The annual rate and applicability of the AquaCrop model from 2005 to 2014 were evaluated based on standardized water production efficiency (WP*) and reference harvest index (HI₀). After determining the appropriate parameters, the meteorological data from 2015 to 2017 were used for verification. Two sowing dates of spring wheat variety ‘Xinchun 6’ on April 10 and April 20 were set in this study, and irrigation quotas of 400 mm, 350 mm, 300 mm, 250 mm, and 200 mm and irrigation cycles of 7 d and 10 d were set under each sowing date for a total of 20 scenarios. The spring wheat yield in the Altay region of Xinjiang was simulated, and the spring wheat yield and irrigation water use efficiency under different scenarios and influence of the irrigation quota and irrigation times were compared. The optimal irrigation strategy was selected, with high yield and water-use efficiency as the goal. Using the wheat planting area and irrigation quota in 2017 as reference values, the differences in wheat yield and total water-saving amount under different scenarios in 2017 and 2020 were compared to analyze the water-saving potential of wheat. The results are as follow: 1) WP*=18 g∙m⁻² and HI₀=48% were recommended as the yield module parameters in the Altay area. The parameters of the AquaCrop model are divided into two modules: crop growth and yield. The parameters of the crop growth module required field experiments; therefore, the parameters of the yield module were adjusted. WP*=18 g∙m⁻², HI₀=48% and WP*=19 g∙m⁻², HI₀=45% were selected as the yield module parameters, and the yield error ranges were −3.44% to 5.67% and −4.92% to 4.56%, respectively. WP*=18 g∙m⁻² and HI₀=48% had better applicability, and the evaluation indexes: root mean square error (RMSE), relative RMSE (RRMSE), residual coefficient (CRM), Willmott cossitancy (d), and Nash efficincy coefficient (E_NS) were 0.110, 0.023, 0.002, 0.956, and 0.935, respectively. Finally, meteorological data from 2015 to 2017 were used for validation, and the validated yield error results were −0.41%, −3.02%, and 3.34%, respectively, with small simulation errors. 2) Scenario S15 (sowing on April 20, irrigation quota of 300 mm, irrigation cycle of seven days) can be used as the recommended irrigation strategy. Through the simulation of spring wheat yield and calculation of irrigation water-use efficiency under different scenarios, it was found that the postponement of sowing date was beneficial to the accumulation of crop yield because the crop was less exposed to low-temperature stress at that time. The effect of irrigation cycle on spring wheat yield was the opposite under different planting dates and irrigation quotas. The spring wheat yield of S15 was 5.610 t∙hm⁻², and the irrigation water use efficiency was 1.870 kg∙m⁻³. 3) In 2017, scenario S15 saved 2.335×10⁸ m³ of water. Under irrigation quotas (400 mm, 350 mm, 300 mm, 250 mm and 200 mm), 1.849×10⁸ m³, 2.092×10⁸ m³, 2.335×10⁸ m³, 2.579×10⁸ m³, and 2.822×10⁸ m³ were saved in 2017. Under the recommended irrigation strategy, water savings of 2.407×10⁸ m³, 2.431×10⁸ m³, and 2.476×10⁸ m³ can be achieved in the future when the utilization coefficient of irrigation water is 0.570, 0.580 and 0.600, respectively; indicating a huge water-saving potential.