Analysis of water-saving potential of summer maize in Ta'e Basin based on AquaCrop model
Based on the AquaCrop model,combined with the measured data of summer maize in the Ta'e Ba-sin in 2021-2022,the conservative parameters of the model and the standard water productivity(WP*)and the reference harvest index(HI0)of the yield module were calibrated and verified.Through the setup of a three-factor crossover test of initial irrigation time,irrigation quota,and irrigation cycle,the yield of summer maize was simula-ted,and the degree to which its yield and crop water use efficiency were affected by irrigation quota and initial irri-gation time was analyzed.The optimal irrigation scheme was selected under the premise that both yield and crop wa-ter use efficiency were higher values.Taking the actual summer maize sown area as a reference value,the summer maize yield and total water-saving under different irrigation schemes in 2022 and the next four years were simulated and predicted,and the water-saving potential of summer maize in Ta'e Basin was analyzed accordingly.The results showed that:(1)The parameter rates of the main parameters of the crop growth module,the soil water stress pa-rameters and the yield module parameters WP*and HI0 of the AquaCrop model were determined,and the final pa-rameters of the yield module were selected as WP=35 g·m-2 and HI0=43％,and the relative error values of the yield simulations were 1.26％in 2021 and 1.07％in 2022,respectively.(2)Combined with the model simulation,the recommended optimal irrigation scheme is as follows:the starting irrigation time is May 20;the irrigation quota is 470 mm;the irrigation period is 7 days;the irrigation period is 11 times;the crop water-use efficiency is 2.005 kg·m-3,and the yield is 9.423 t·hm-2.(3)Taking 2022 as the current level year,the water saving can be real-ized in the current level year and future level years(2022-2025)under the optimal irrigation scheme,and the wa-ter saving amounts are 2.1338×105,2.1826×105,2.1992×105 m3 and 2.2306×105 m3,respectively.
万方数据
维普
