Smart Irrigation Scheduling Improves Water Productivity and Crop Yield under Water-Limited Conditions: Precision Water Management, Predictive Analytics, Climate-Smart Adaptation, and Yield Stability
Year: 2026
Type: article
Abstract: Growing competition for freshwater, increasing evapotranspiration, irregular rainfall and recurrent drought are trans-forming irrigation scheduling from a routine farm operation into a central component of climate-resilient crop produc-tion. Smart irrigation scheduling integrates soil, plant, weather and crop information to determine when irrigation should be applied, how much water should be supplied and where water is most needed. This review synthesizesthe physiological, agronomic and technological basis through which smart irrigation scheduling improves waterproductivity and sustains crop yield under water-limited conditions. Conventional calendar-based irrigation frequently fails to account for spatial and temporal variability in soil moisture, atmospheric demand and crop developmental sen-sitivity, resulting in over-irrigation, deep percolation, nutrient loss or avoidable water stress. In contrast, soil-moisture sensors, evapotranspiration-based scheduling, canopy-temperature measurements, remote sensing, Internet of Thingsplatforms, decision-support systems, artificial intelligence and machine-learning models allow irrigation to responddynamically to actual crop and environmental conditions. Smart scheduling improves productivity principally bymaintaining root-zone water within physiologically acceptable limits, reducing non-beneficial water losses, protectingflowering and reproductive development, improving nutrient uptake and coordinating controlled water deficits withcrop tolerance. Its effectiveness, however, depends strongly on crop type, genotype, phenological stage, root-zone characteristics, irrigation method, sensor calibration, weather variability and economic feasibility. The plant micro-biome, stress-responsive genetic traits, hormonal regulation and soil biological properties add further complexity because they influence root water acquisition and crop tolerance to intermittent soil drying. Evidence from smarthorticulture and precision-agriculture studies increasingly supports integration of IoT sensors, artificial intelligence,crop models and climate forecasts into adaptive irrigation systems. Future irrigation management should move fromfixed water application toward predictive, closed-loop and plant-responsive scheduling capable of distinguishingbeneficial water conservation from yield-threatening stress. Such integration offers a practical pathway for increasingcrop water productivity, stabilizing yield and conserving scarce freshwater under increasingly water-limited productionenvironments.
Source: Public Health - Open Journal
DOI: 10.17140/phoj-11-704
Language: English
Subfield: Soil Science
Domain: Life Sciences
Open Access status: diamond
OpenAlex ID: W7217281115
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