Abstract

Evaluating the performance of AquaCrop models under the drip irrigation of maize with soil conditioners is of great significance for improving coastal saline–alkali land crop management strategies. This study aimed to evaluate the performance of an AquaCrop model for maize growth simulation under different soil conditions (humic acid (HA) and sodium carboxymethyl cellulose (CMC)) and dosages and different levels of irrigation in the Shandong coastal saline–alkali area, China, and to optimize the amount of irrigation. Three years of experiments were carried out in the growing season of maize (Ludan 510) in 2019, 2020, and 2021. The dosages of HA were 5, 15, 25, and 35 g/m2, the dosages of CMC were 1, 2, 3, and 5 g/m2, and the levels of irrigation from 2019 to 2021 were all 120 mm. The model was calibrated with data from 2019, and the model was verified with data from 2020 to 2021, according to the recommended corn parameters in the AquaCrop model manual. The results showed that the model had a good simulation effect on canopy coverage, with a root-mean-square error (RMSE) of less than 15.2%, and the simulated aboveground biomass and yield were generally low. The simulated value of soil water content was generally high, with some treatments having errors of more than 15.0%. The simulation effect of irrigated maize from 2019 to 2020 was better than maize in 2021. The simulation effect of HA was better than that of CMC, while the simulation effect of a low-gradient modifier was better than that of high-gradient conditioner when compared with CMC. In conclusion, the AquaCrop model could be a viable method for predicting maize development under different soil conditioners in this area. The suitable levels of irrigation under HA and CMC treatments were 47.0–65.9 mm and 61.0–92.4 mm, respectively, according to the principle of high yield and water use efficiency. The results provided a reference for optimizing the drip irrigation of maize under the application of soil conditioners in coastal saline–alkali areas.

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