Accurate prediction of wheat yield under combined saline water irrigation and arid stress: a comprehensive analysis of the FAO-AquaCrop model - Sekhri, Leyla; Razi, Sabah; Merdaci, Samir; Sellem, Fouad; Daibouche, Yacine; Poddubsky, Anton; Kucher, Dmitry E.; Rebouh, Nazih Y.; Fadl, Mohamed E. (Frontiers in Sustainable Food Systems, 2025)
The AquaCrop model was calibrated and validated for durum wheat in the arid region of Biskra, Algeria. using field data from the CAZDA COSIDER farm during the 2022/2023 growing season. The wheat field was irrigated using a center pivot system with saline water at 4.45 dS m−1. Validation was performed with independent yield data from the Technical Institute for the Development of Saharan Agronomy (TIDSA) in Biskra region; to take into consideration the differences in weather conditions, soil, salinity levels and irrigation management. The calibration process involved adjusting only the non-conservative crop parameters. The model accurately simulated canopy cover (RMSE = 3.7%, NRMSE = 5.5%, EF = 0.99, R = 1) and above-ground biomass (RMSE = 1.1 t ha−1, NRMSE = 9.6%, EF = 0.78, R = 0.95), with a slight underestimation of 0.25 t ha−1 in the final above-ground biomass. The model captured the temporal trends in soil water content, but with low quantitative accuracy (RMSE = 40.2 mm, NRMSE = 14.9%, EF = −0.42, R = 0.94). Validation confirmed very good predictive performance for grain yield (R2 = 0.92, RMSE = 0.2 t ha−1, NRMSE = 2.76%, EF = 0.9, d = 0.98). Overall, the results demonstrate that, with rigorous calibration using field measured data, the AquaCrop model can accurately predict durum wheat grain yield and final above-ground biomass under the arid and saline conditions of the studied area. In contrast, the use of default parameters resulted in poor yield prediction performance, underscoring the critical need for site-specific calibration. The locally calibrated AquaCrop model can effectively support water managers and decision-makers in optimizing irrigation scheduling and enhancing durum wheat yields under the challenging saline and arid conditions characteristic of the Biskra region. Serving as a robust decision support tool, the model enables the implementation of improved agricultural practices that ultimately benefit farmers and promote sustainable agriculture in the area.