ACQUAOUNT-Farm: an IoT-based real-time platform for optimizing daily irrigation under water-scarcity

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Abstract
Efficient water management is increasingly more critical in modern agriculture due to unsustainable depletion of water resources, intensified by climate change and growing competition among sectors. Digital technologies such as the Internet of Things (IoT) offer new opportunities to optimize water use by enabling precise, real-time assessment of water requirements to withhold sustained crop productivity. This study presents ACQUAOUNT-Farm, a real-time platform, designed to assist farmers in daily irrigation planning. The tool integrates on-site IoT sensors (soil moisture, water flow and weather) with a user-friendly interface to monitor soil moisture dynamics and provide flexible irrigation scheduling. ACQUAOUNT-Farm requires a minimal set of easily accessible inputs, making it suitable for non-expert users. The model updates daily, it reconstructs hourly soil moisture and irrigation needs up to one week ahead and it generates an irrigation calendar based on crop-specific water stress thresholds, offering recommendations for an early, late, and limited irrigation application. The model was tested in four farms in southern Tunisia for citrus and potato crops during two growing seasons (2024-2025). Comparison between simulated and observed soil moisture showed good agreement (R² > 0.76), confirming the model’s ability to forecast soil moisture dynamics. When compared with farmers’ irrigation practices, ACQUAOUNT-Farm indicated potential water savings of around 60% for one citrus field and 70–80% for autumn potato, while spring potato showed limited savings due to high seasonal water demand. In one citrus field, the model recommended 40% more water to reach optimal productivity, reflecting the farmer’s deficit irrigation strategy, already implemented in the field. Overall, ACQUAOUNT-Farm demonstrates strong potential to enhance irrigation efficiency and reduce water withdrawals.

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