Optimization of Irrigation Water Use Efficiency in Onion under Subsurface Drip Irrigation

Abstract

The increasing scarcity of water resources and the need for efficient irrigation practices have necessitated advanced strategies to optimize water use efficiency in high-value vegetable crops. This study focuses on the optimization of irrigation water use efficiency in onion cultivated under subsurface drip irrigation systems to enhance productivity and resource conservation. The proposed methodology involves field experiments conducted under varying irrigation levels and scheduling regimes, combined with data-driven analytical approaches. Key parameters such as soil moisture distribution, evapotranspiration rates, bulb yield, and water use efficiency are monitored using soil sensors and standard agronomic measurements. The collected data are preprocessed through cleaning, normalization, and statistical validation to ensure accuracy and consistency. Advanced modeling techniques, including regression analysis, Random Forest, and Artificial Neural Networks, are employed to evaluate the relationship between irrigation input and crop performance. Experimental results demonstrate that subsurface drip irrigation significantly reduces water losses due to evaporation and deep percolation, resulting in improved water use efficiency compared to conventional irrigation methods. Optimal irrigation levels are identified that maximize yield while minimizing water consumption. Additionally, uniform moisture distribution in the root zone enhances bulb development and overall crop health. The findings highlight the effectiveness of integrating efficient irrigation technologies with intelligent analysis for precision agriculture applications. The study concludes that optimizing irrigation water use efficiency through subsurface drip systems provides a scalable, sustainable, and resource-efficient solution for improving onion productivity under water-limited conditions.