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1 Rosegrant, M. W.; Koo, J.; Cenacchi, N.; Ringler, C.; Robertson, R.; Fisher, M.; Cox, C.; Garrett, K.; Perez, N. D.; Sabbagh, P. 2014. Food security in a world of natural resource scarcity: the role of agricultural technologies. Washington, DC, USA: International Food Policy Research Institute (IFPRI). 154p. [doi: https://doi.org/10.2499/9780896298477]
(Location: IWMI HQ Call no: 333.7966 G000 ROS Record No: H046529)
(5.56 MB) (5.56 MB)
(Location: IWMI HQ Call no: e-copy only Record No: H051155)
(0.32 MB) (332 KB)
Climate change and associated extreme weather events directly impact the functioning and sustainability of food systems. The increasingly erratic onset of seasonal rainfall and prolonged heat stress during growing seasons are already causing crop losses. As of late 2021, for example, Madagascar’s three successive seasonal droughts had put 1.35 million people at risk of the world’s first climate-change-induced famine. In the United States, the number of days between billion-dollar weather-related disasters has fallen from more than 80 in the 1980s to just 18 in recent years. Without adequate preparation, these weather hazards disrupt food supply chains by interrupting production and cause problems farther along these chains by raising costs and prices of processing, storage, transport, retail, and consumption and reducing business revenues.
(Location: IWMI HQ Call no: e-copy only Record No: H053058)
(1.12 MB)
A Digital Twin is a virtual representation of an object or system that spans its lifecycle, is updated from real-time data, and uses simulation, machine learning and reasoning to help decision making. The use of Digital Twins to aid decision-makers to make realtime decisions in complex systems is a growing field, with large potential for water system management. The CGIAR Initiative on Digital Innovation is developing a prototype Digital Twin for the Limpopo River Basin in close combination with stakeholders, to enable better management and conservation of this imperilled natural resource upon which millions of people depend. The Digital Twin will provide an attractive and easy-to-use interface for users to intuitively understand large volumes of data and modelling results for timely management decisions, and to simulate the impact of these decisions on the complex river basin ecosystem before they are put into action. This includes an artificial intelligence (AI) tool to interrogate and visualize key actionable data and forecasts. It will be developed in a phased approach according to stakeholder priorities.
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