Optimizing Irrigation Management of Sweet Corn Using AquaCrop Model: Analysis of Deficit Irrigation Scenarios and Transplanting Age Effects

Background and Objectives:
Sweet corn is a vital crop in global agriculture, contributing significantly to food security and farmers' livelihoods. In arid and semi-arid regions, where water resources are limited, optimizing irrigation management is crucial for sustainable agricultural production. Advanced technologies, such as crop simulation models, play a pivotal role in understanding crop responses to water stress and improving water use efficiency. The AquaCrop model, developed by the Food and Agriculture Organization (FAO), is a widely recognized tool for simulating crop yield under various irrigation conditions. This study aimed to evaluate the performance of the AquaCrop model in simulating sweet corn yield under different irrigation levels and transplanting ages in the semi-arid and cold climate of Khorasan Razavi Province, Iran. Additionally, the study sought to analyze various deficit irrigation scenarios to identify the most effective strategy for water management in sweet corn cultivation.
Methodology:
The research was conducted as a field experiment at the Torogh Research Station in Mashhad during two growing seasons (spring and summer). The experiment was designed as a split-plot arrangement within a randomized complete block design with four replications. The main plots consisted of three irrigation levels: 75%, 100%, and 125% of the full crop water requirement. The subplots included two transplanting ages: 20 and 30 days. Data on crop cover, ear yield, and biomass were collected throughout the growing season. The AquaCrop model was calibrated and validated using meteorological data, soil properties, irrigation management, and crop characteristics. Key statistical indices, including normalized root mean square error (NRMSE), coefficient of determination (R²), Willmott’s index of agreement (d), coefficient of residual mass (CRM), and mean error (ME), were used to evaluate the model's accuracy. Various deficit irrigation scenarios, such as 10% to 40% water reduction and irrigation cutoff at different growth stages, were simulated to assess their impact on crop performance.
Findings:
The results demonstrated that the AquaCrop model had acceptable accuracy in simulating ear yield and biomass under full irrigation conditions (100% and 125% of water requirement), with NRMSE values below 20%. However, under severe water deficit conditions (75% of water requirement), the model tended to overestimate ear yield and underestimate biomass, highlighting the need for further improvement in simulating extreme water stress. Analysis of deficit irrigation scenarios revealed that a 20% reduction in irrigation (80% of full water requirement) during the growing season did not significantly affect yield and could be recommended as an optimal strategy for water resource management.
Furthermore, the study found that sweet corn grown in loamy soil achieved the highest yield, while clay soil resulted in the lowest yield, emphasizing the importance of soil texture in crop performance. Twenty-day-old transplants generally outperformed 30-day-old transplants in terms of yield, but under water deficit conditions, 30-day-old transplants also demonstrated acceptable performance, suggesting their suitability for water-limited environments. The model's ability to simulate crop growth and yield under varying conditions was further validated by the strong correlation between observed and simulated data, as indicated by high R² values and low RMSE.
The simulation results using the AquaCrop model indicated that transplanting maize cultivation in Khorasan Razavi Province has a relatively high production potential, with the highest yields observed in Kashmar and Sarakhs counties and the lowest yields in Fariman and Quchan counties.
Conclusion:
This study underscores the effectiveness of the AquaCrop model as a reliable tool for simulating sweet corn yield under different irrigation levels and transplanting ages. The findings suggest that a 20% reduction in irrigation can be implemented without significantly compromising yield, offering a practical solution for water resource management in semi-arid regions. However, the model's limitations in simulating severe water stress conditions indicate the need for further refinement, particularly in capturing the complex interactions between water deficit and crop physiological responses.
The results also highlight the importance of soil texture and transplanting age in optimizing sweet corn production. Loamy soils and 20-day-old transplants were found to be the most favorable conditions for achieving high yields, although 30-day-old transplants showed resilience under water deficit conditions. These insights can guide farmers and water resource managers in adopting sustainable irrigation practices to enhance crop productivity in water-scarce environments.
For future research, it is recommended to investigate the effects of additional environmental factors, such as soil moisture dynamics, solar radiation, and agronomic management practices, on sweet corn performance. Moreover, expanding the AquaCrop model's capabilities to simulate non-water stresses, such as salinity and high temperature, would further enhance its applicability in diverse agricultural systems. By integrating these improvements, the AquaCrop model can serve as an even more powerful tool for optimizing irrigation management and ensuring food security in the face of climate change and water scarcity.
The findings of this study suggest that the warmer regions of Khorasan Razavi Province have a higher potential for transplanting maize production. Additionally, the spatial distribution of cob yield and biomass across the province revealed that climatic differences significantly influence crop performance.

Keywords: Biomass, Crop yield potential, Moisture stress, Semi-arid climate, Transplanting, Water resource management.