The development of a crop production strategy through the use of a crop model represents a crucial method for the assurance of a stable agricultural yield and the subsequent enhancement thereof. There are currently no studies evaluating the suitability of the AquaCrop model for the drip irrigation of Gossypium barbadense in Southern Xinjiang, which is the primary planting region for Gossypium barbadense in China. In order to investigate the performance of the AquaCrop model in simulating the growth of cotton under mulched drip irrigation, the model was locally calibrated and validated according to different irrigation thresholds during a key growth period of two years. The results of the simulation for total soil water (TSW), crop evapotranspiration (ET_c), canopy coverage (CC), aboveground biomass (Bio), and seed cotton yield demonstrated a high degree of correlation with the observed data, with a root mean square error (RMSE) of <11.58%. The Bio and yield simulations demonstrated a high degree of concordance with the corresponding measured values, with root mean square error (RMSE) values of 1.23 t ha⁻¹ and 0.15 t ha⁻¹, respectively. However, the predicted yield declined in the verification year, though the prediction error remained below 15%. Furthermore, the estimated evapotranspiration (ET_c) value demonstrated a slight degree of overestimation. Generally, the middle and late stages of cotton growth led to an overestimation of the TSW content. However, the prediction error was less than 13.99%. Through the calculation of each performance index of the AquaCrop model, it is found that they are in the acceptable range. In conclusion, the AquaCrop model can be employed as a viable tool for predicting the water response of cotton to drip irrigation under mulched film in Southern Xinjiang. Based on 64 years of historical meteorological data, three years were selected as scenarios for simulation. Principal component analysis (PCA) showed that, in a local wet year in Southern Xinjiang, the irrigation quota was 520 mm, and the irrigation cycle was 6 days/time. In normal years, the irrigation quota was 520 mm, with an irrigation cycle of 6 days/time. In dry years, the irrigation quota was 595 mm, with an irrigation cycle of 10 days/time. This allowed for higher seed cotton yields and irrigation water productivity, as well as the maximization of cotton yields and net revenue in the arid oasis area of Southern Xinjiang.

Accurate prediction of orchard evapotranspiration (ET) can optimize orchard water management. Based on the jujube (Zizyphus jujuba), ET was continuously measured from 2016 to 2019 using a large weighing lysimeter; the actual jujube ET was compared with the ET simulated with the Priestley–Taylor (P–T), Dual Crop Coefficient (Dual Kc), and Shuttleworth–Wallace (S–W) models, to verify the accuracy of the three models. The results showed that, from 2016 to 2019, the whole growth period of jujube ET was 532–592 mm and the crop coefficient was 0.85–0.93. The basal crop coefficients of the calibrated Dual Kc model were 0.4, 1.0, and 0.5 at the initial, middle, and ending growth stages, respectively. The overall simulation error of the Dual Kc model was low, and simulations were stable during the four years of the study. However, because of rough estimation the water stress coefficient (K_s) simulation accuracy will be reduced in the case of serious water shortage. The simulation error of the S–W model was greater than the simulation error of the Dual K_c model, and the simulations were unstable and vulnerable to interannual changes. The simulation error of the traditional P–T model was large. When the parameter “α” solution method was improved, the simulation accuracy was significantly improved, and the P–T model’s simulation accuracy was only slightly lower than that of the Dual Kc model. However, the model was easily affected by changes in net radiation and air temperature. Therefore, the Dual Kc model is recommended for estimating the ET of young jujube trees in arid areas.