AquaCrop modeling for sustainable potato irrigation: trade-offs between yield and crop water productivity

Potato is an important staple food crop for global food security, and its productivity is sensitive to water availability, making precision irrigation management crucial for optimum yield and crop water productivity ( $W{P}_C$ ). The AquaCrop model was calibrated and validated under 50% and 70% field capacity (FC) managed through SoilWatch 10 moisture sensors at depths of 15, 30, and 45 cm. Thereafter, different irrigation scenarios, from 20% to 90% FC, were developed and simulated across 10 years (2014-2024), classified into wet (>312.9 mm), normal (256-312.9 mm), and dry (<256 mm) years based on the total crop growing season rainfall for yield and $W{P}_C$ across two soil types. Trade-off analyses were performed for all scenarios across all years-normal, wet, and dry years-to assess the relationship between yield and $W{P}_C$ , simulating yield effectively with an index of agreement (IA) of 0.999. The results indicated that the simulated yield at harvest closely matched the observed yield (±10%), suggesting significant accuracy of the model. The soil water content (SWC) estimations under both treatments were satisfactory, with the IA and the Nash-Sutcliffe model efficiency coefficient (NSE) both close to 1. Scenario analysis exhibited variations in the yield and $W{P}_C$ for irrigation treatments across soil types. Trade-off analysis showed that irrigation at 40%-60% FC resulted in better yield and $W{P}_C$ , as categorized in the win-win scenarios, across all years and two different soil characteristics. Similarly, the correlation analysis revealed that the mid-tuber to the late-tuber bulk stages were critical for irrigation supplementation, corroborated by the findings of the 40%-70% FC irrigation scenarios. As such, AquaCrop could be a feasible modeling tool to optimize irrigation for potato yield and $W{P}_C$ under climate variability.