Harnessing Digital Technologies for Smarter Water Management in Agriculture 2025

Nonetheless, combining various data sources remains difficult, requiring both technical know-how and stakeholder collaboration. This underscores the importance of open-data platforms and collaboration across sectors to guarantee that farmers, policy-makers and investors can access practical insights. Establishing supportive governance frameworks and policy enablers, such as regulatory incentives for data-sharing, is critical to foster the adoption and influence of open-data platforms in agriculture. Hybrid modelling methods, in which AI improves physics-based hydrological models, can assist in forecasting water supply, optimizing irrigation timelines and bolstering drought resilience. Through investment in digital infrastructure that enhances data interoperability, agriculture can shift from reactive water management to proactive, data-driven decision-making that brings advantages to both individual farmers and broader water basins. Table 3 outlines key implementation approaches to build a robust data infrastructure in agriculture. Strategies for robust data infrastructure in agriculture TABLE 3 Implementation approach Practical strategies and benefits Standardized data frameworks Establish common data formats and protocols to facilitate seamless integration and communication between multiple digital agriculture platforms, enhancing interoperability and usability. Infrastructure for data-sharing Develop data infrastructure that enables integration and sharing of data from various data owners, while complying with a set of binding governance conditions. Decentralized data storage Leverage blockchain or distributed cloud storage to secure agricultural data against loss or damage, ensuring consistent data availability in rural regions with unreliable connectivity. Public-private data partnerships Create open-data initiatives, fostered by supportive policies, that combine farmer- generated insights with satellite imagery, enabling more accurate agricultural forecasting, resource allocation and proactive decision-making. Through investment in digital infrastructure that enhances data interoperability, agriculture can shift from reactive to proactive water management. Data interoperability through agriculture data spaces BOX 4 The shift towards digital agriculture relies on accessible data, seamless integration and effective governance so that farmers and agribusinesses can make informed choices regarding water utilization, crop health and irrigation management. The fragmentation of data platforms leads farmers to operate with multiple, non-integrated systems. To tackle this issue, various initiatives are creating shared digital environments – called “agriculture data spaces” – where farmers, agribusinesses, policy-makers and researchers can securely exchange data, while retaining control over how their data is used. These frameworks, which are endorsed by a broader initiative of the European Commission37 to promote common European data spaces in crucial sectors, seek to: –Standardize agricultural data formats for smooth integration across various platforms. –Enable farmers to have data sovereignty, ensuring they retain authority over their data. –Improve collaboration between agriculture and other sectors, such as manufacturing, energy and logistics. –Promote trust and transparency via blockchain-driven data-sharing agreements. Agriculture data spaces enhance data access and interoperability, which streamlines precision irrigation, soil moisture tracking and predictive water utilization analytics, thereby making smart agriculture more efficient, scalable and accessible. Initiatives such as GEOGLAM (Group on Earth Observations Global Agricultural Monitoring) Crop Monitor38 provide open, timely and science- driven classification schemes on crop conditions by leveraging Earth observation data to provide unified, interoperable and farmer-accessible data systems. Similarly, GODAN (Global Open Data for Agriculture and Nutrition)39 promotes open sharing of agricultural and nutritional data to enhance informed decision-making across the value chain. Harnessing Digital Technologies for Smarter Water Management in Agriculture 23