A user-friendly decision support tool for irrigation scheduling in smallholder olive orchards

Water scarcity and climate variability threaten Mediterranean agriculture, particularly for smallholder growers who often lack the knowledge to use advanced irrigation technologies. This study presents the development and validation of a user-friendly decision support tool (DST) designed to optimise irrigation scheduling through a simplified, sensor-based balance model, the Soil-Atmosphere Adjusted Model (SAAM). The tool delivers weekly irrigation recommendations via a mobile application. The SAAM algorithm adjusts irrigation volumes based on weekly variations in reference evapotranspiration (ET 0 ) and relative soil water status (RWS) from capacitive soil moisture sensors. Field trials were conducted during 2022 and 2023 in a commercial olive orchard in eastern Spain with a dual objective: ( i ) to empirically define crop-specific physiological thresholds for RWS, and ( ii ) to validate the performance of the DST under real farming conditions. The drought cycles implemented enabled the identification of optimal RWS boundaries (RWS LL = 0.63, RWS UL = 0.73) based on stem water potential (Ψ stem ) and stomatal conductance ( g s ) responses. In parallel, the SAAM demonstrated its capacity to reduce irrigation volumes by 11 % (11.9 mm) compared to a conventional technician-guided strategy (99.4 mm and 111.3 mm, respectively), while maintaining Ψ stem and g s within non-limiting physiological ranges. No significant differences were observed in olive or oil yields between treatments, resulting in improved irrigation water productivity under the DST approach. The modular DST architecture ensured robust, automated data acquisition, quality control, and real-time output via a user-friendly interface. These findings highlight the DST framework as a solution to promote smart irrigation and water use efficiency. • A user-friendly soil sensor-based DST was developed and validated in olive orchards. • Empirical calibration defined optimal olive RWS thresholds between 0.63 and 0.73. • SAAM reduced irrigation by 11 % without affecting plant water status or yield. • The HANDYWATER-DST ensures automated data flow, quality control, and mobile access.