ADVANCES IN SENSOR-BASED AND INTELLIGENT IRRIGATION SCHEDULING: INTEGRATING SOIL, PLANT, AND CLIMATE DATA FOR PRECISION WATER MANAGEMENT

ÇUKUROVA INTERNATIONAL AGRICULTURE AND TOURISM CONGRESS, Adana, Türkiye, 3 - 05 Ekim 2025, cilt.1, ss.26-37, (Tam Metin Bildiri)

Water scarcity and the demand for higher crop productivity have accelerated the evolution of

irrigation scheduling from empirical routines to intelligent, data-driven systems. This review

synthesizes recent progress in sensor-based and automated irrigation scheduling across eleven

key studies. Traditional evapotranspiration (ET) and water-balance models remain

fundamental but are increasingly enhanced by real-time soil and plant sensing technologies.

Capacitance, tensiometric, and dielectric soil-moisture sensors combined with wireless sensor

networks (WSN) and Internet-of-Things (IoT) platforms enable continuous field monitoring

and adaptive irrigation control. Integration of these sensors with model-based or fuzzy-logic

algorithms allows closed-loop regulation that dynamically adjusts irrigation depth and timing

according to crop stage and micro-climate variability. Applications in orchards, vegetable

systems, and arid-region field crops demonstrate water savings of 30-50 % and yield

maintenance or improvement compared with conventional scheduling. Site-specific

calibration and hybrid ET sensor approaches are emphasized as critical for accuracy.

Emerging trends include machine-learning-based decision support, cloud-connected mobile

interfaces, and the convergence of remote sensing (NDVI, UAV imagery) with ground

sensors. Collectively, these advances mark a transition toward autonomous, precise, and

resource-efficient irrigation management, positioning sensor-integrated systems as essential

tools for sustainable agriculture under climate-change pressures.