GrowSphere™, developed by a global provider of sustainable irrigation solutions, is a precision irrigation management system focusing on optimized water usage in farming by incorporating real-time data, automation and remote access features. By integrating hydraulic, agronomic and operational data, the system enables farmers to make informed decisions that enhance irrigation efficiency and crop yield. The system collects data from soil moisture sensors, weather stations and hydraulic sensors, channelling this data into a centralized platform which allows for: –Automated irrigation and fertigation tailored to the specific water requirements of each crop type. –Remote control and monitoring via a desktop and mobile interface. –AI-powered decision support for optimizing irrigation schedules. –Notifications and anomaly detection, minimizing water wastage stemming from leaks or inefficiencies.Optimizing irrigation schedules for maximum efficiency AI models can generate irrigation schedules across agricultural fields to provide optimized water usage for crops. The power of AI models in irrigation lies in their ability to adapt to changing environmental conditions by continuously learning from large data sets of historical irrigation events, weather forecasts and soil moisture levels. Processing real-time data from IoT sensors and remote sensing, AI can predict the optimal time and precise irrigation amount depending on local weather conditions and crop growth stages. For instance, AI-driven digital tools developed by ClimateAi can integrate crop types, soil conditions and historical weather data to fine-tune irrigation timing, diminishing water usage without sacrificing yield.26 This predictive ability of AI prevents both under- and over-irrigation, fostering water conservation and crop health. Farm-level irrigation planning based on water-stress assessments Drones and satellites can capture high-resolution images of crops, which are then analysed with machine learning algorithms to enable farmers to target only those areas requiring water. Allocating resources to stressed zones leads to reduced water consumption without negatively impacting yields. Real-time maps showing soil types, topography, crop types and water requirements can be created by GIS platforms, merging data obtained from satellite and drones. Based on analysis of these maps, farmers can divide vast fields into separate irrigation zones, each having different water requirements. When GIS data is fed into precision irrigation systems, location-based decisions regarding where and how much water to apply can be swiftly made by pinpointing certain areas in need, making it easier to apply irrigation more efficiently across different areas. With high-resolution thermal imaging satellites, we can detect crop water stress much earlier than conventional technologies. This allows farmers to optimize irrigation strategies before visual symptoms appear in the field, potentially reducing water usage by up to 30%. Beate Tempel, constellr Digital platform for precision irrigation BOX 1 Source: Netafim.27 Harnessing Digital Technologies for Smarter Water Management in Agriculture 14

Harnessing Digital Technologies for Smarter Water Management in Agriculture 2025