An integrated view of data for both food and water can drive improved decision-making and sustained solutions in every geography.
Food systems represent 72% of water withdrawals worldwide. Current production and consumption trends are not sustainable, as global food production is projected to increase by 70%, intensifying pressure on already-stressed water resources. Connecting data from food and water systems is essential for scaling sustainable interventions in these interlinked areas. While several frameworks recognize the overlap between datasets, integrating them to create a platform for robust decision-making remains a challenge. This white paper outlines connections between water and food, the impacts of aggregated data, the role of artificial intelligence (AI) and a data stack framework to inform and improve decision making. This approach can also promote collaboration between stakeholders and spur innovation within the interlinked systems.
The successful application of the food-water stack framework requires a diverse set of data sources – captured manually or through technologies such as remote sensing and internet of things (IoT) – and includes macro-level information such as water availability, weather forecasts, salinity levels and land use patterns. The data is assessed in combination with information about the physical infrastructure in a location, and the technology available to create an analysis that can then be distilled and communicated to the relevant stakeholders through tools like AI chatbots. The white paper outlines three cases that illustrate how the stack framework can bring together stakeholders for more sustainable management of water resources. The food-water stack, at scale, offers an opportunity to elevate the role of water as an impact multiplier in food (to the same level as carbon and other emissions). With the challenges in food and water systems only growing more complex, the time to act is now. The stack methodology offers a clear pathway to better decision-making, resilience and sustainability for generations to come. The Global Future Council on Food and Water Security recommends the following actions to implement the stack at country level:
- Intentionally co-create the stack with end users to ensure that the stack applies to different contexts and includes necessary data for sufficiently tailored, scenario-specific applications.
- Design the food-water data stack to respond to local circumstances. While some high-level characteristics of food and water systems are similar across the world, they often possess specific features unique to the country and region. Localization guarantees ownership and commitment to improving implementation over the long term.
- Ensure open access to the stack. Use a coordinating mechanism to host the stack and convene communities of local and global stakeholders on its use, management and governance.
- Harness nature markets and innovative financing to multiply benefits. Various sources of financing can be used to develop and maintain the stack, and, in the long run, collective analysis from the stack can demonstrate the benefits of its use by linking water and food to climate and nature finance.
- Convene a multi-ministerial and multistakeholder coordinating mechanism to coordinate the development of the stack, including key issue areas to focus on.
- Integrate food and water outcomes into national action plans, including climate and social development targets, the national food systems pathways developed from the United Nations (UN) Food Systems Summit, national biodiversity strategies and action plans (NBSAPs), water roadmaps, AI and digital policies, and more.
- Collaborate across industry to drive implementation. Working with private actors and users in the food and water sectors will drive rapid adoption, while facilitating the solution safely into real world scenarios.
- Future-proof for improved resilience and decision-making on new innovation. While developing the stack, account for future decisions in food, including the use of water in alternative proteins or AI.Develop efficient and collective data infrastructures. When incorporating proprietary information, common data-sharing protocols, as well as contours around privacy, access and monetization, need to be developed.
Year of publication | |
Geographic coverage | GlobalSouthern AfricaCosta RicaIndia |
Originally published | 06 Dec 2024 |
Related organisation(s) | WEF - World Economic Forum |
Knowledge service | Metadata | Global Food and Nutrition Security | Sustainable Food Systems | Food systems transformationWater for food security and nutrition |
Digital Europa Thesaurus (DET) | MonitoringDatapolicymakingwater supplywater policy |