Digital Intelligence for Water-Smart Agriculture: AI, Simulation, and Decision Systems in Irrigation Management

Agricultural water management is increasingly shaped by digital tools that support irrigation scheduling, water allocation, and resource planning. Research across settings such as Hebei, Saudi Arabia, and China’s drip-irrigated wheat–maize systems spans artificial intelligence, feasibility simulation, electronic farmland archives, digital twins, and multi-objective optimization. These approaches address decisions faced by farmers, irrigation districts, and water managers, but evidence remains dispersed across technical, agronomic, economic, and policy disciplines. Important questions include how reliably tools improve water-use decisions, whether they can be implemented at scale, and which technical, economic, and institutional conditions support adoption. Bringing this work together can clarify how digital approaches contribute to water-smart food production.This Research Topic aims to consolidate evidence on how digital tools support irrigation and water-management decisions in food production. It will examine their design, validation, practical and commercial feasibility, and implications for water-use efficiency and food security, while identifying the conditions that help move promising approaches from simulation and research settings into practice.To gather further insights into digital support for irrigation and water management in agriculture, we welcome contributions that clearly connect their methods and findings to water-use decisions. Studies of digital agriculture without a defined water-management focus are outside the scope. Themes include, but are not limited to:Artificial intelligence and decision-support systems for irrigation scheduling and water allocationDevelopment, validation, and application of digital twins for irrigation and water-resource managementSimulation and multi-objective optimization of agricultural water use and water-energy-food trade-offsDigital mapping, farmland records, and data systems that support irrigation and water-allocation decisionsEconomic and commercial feasibility of digital irrigation services, including green-energy integrationAdoption, governance, and institutional conditions for digital water-management tools in irrigationEffects of digitally supported irrigation on water-use efficiency and food security in water-stressed regionsField-based, simulated, and hybrid evaluations of digital tools in water-smart food production Topic editors: Yaosheng Wang Source: https://www.frontiersin.org/research-topics/86767/digital-intelligence-for-water-smart-agriculture-ai-simulation-and-decision-systems-in-irrigation-management