Artificial Intelligence and Data Sciences for Precision Agriculture, Pages 257-273 , 01/01/2026
Irrigation Management Through Smart Water Solutions
Abstract
Smart irrigation systems, integrating sensors, IoT, and AI, address global water scarcity affecting 2.4 × 10<sup>9</sup> people and support food security for a projected 9.7 × 10<sup>9</sup> population by 2050. Achieving 80–95% water use efficiency compared to 40–70% for traditional methods, these systems reduce water waste by 20–50%, enhance crop yields by 10–20%, and cut energy use by 10–20%. This chapter explores the need for smart irrigation amid rising agricultural water demands, detailing core technologies like soil moisture sensors (±2–5% accuracy), automated drip systems, and predictive analytics. Implementation strategies, case studies from California vineyards and Kenyan smallholder farms, and adoption challenges, including high costs (USD 1200–3500/ha) and rural connectivity issues, are analyzed. Benefits include reduced runoff (50–60%) and lower carbon emissions (5–7% of agriculture’s 1.2 × 10<sup>10</sup> kg CO₂e/year). Future trends highlight affordable sensors (USD 20–50 by 2030), solar integration, and satellite imagery, with scalability to 30% of 3.0 × 10<sup>8</sup> ha irrigated land, saving 1.2 × 10<sup>11</sup> m<sup>3</sup> water annually. Practical steps and policy incentives are proposed to ensure sustainable agriculture, fostering a water-secure future.
Document Type
Book Chapter
Source Type
Book
ISBN
[9783032127693, 9783032127709]
ISSN
Keywords
AI-driven irrigationIoT integrationSmart irrigationSustainable agricultureWater efficiency