Forecasting Water Savings in Greenhouse Vegetable Farms with Precision Irrigation Controllers

Abstract

The escalating global demand for freshwater resources, coupled with the rapid expansion of controlled environment agriculture, necessitates the development and validation of advanced agricultural water management strategies. This paper presents a comprehensive experimental analysis aimed at predicting water savings achieved through the deployment of precision irrigation controllers in greenhouse vegetable farming. By integrating real time soil moisture monitoring, microclimate data, and automated decision support systems, precision irrigation offers a pathway to significantly reduce agricultural water consumption without compromising crop yield or quality. The experimental framework compares traditional timer based irrigation practices with dynamic, sensor driven irrigation control over a full growing season for greenhouse tomatoes. Utilizing high frequency data acquisition and rigorous comparative analysis, this study evaluates the volumetric water applied, the corresponding crop physiological responses, and the overarching water use efficiency. The findings demonstrate a substantial reduction in total water usage in the precision irrigation cohorts, highlighting the critical role of localized environmental data in optimizing irrigation schedules. Furthermore, the analysis provides empirical predictive models that can assist growers and policymakers in estimating potential water savings when transitioning to automated precision agriculture technologies. Ultimately, this research contributes to the broader objective of sustainable agricultural intensification in resource constrained environments.