Digital Twin of the Limpopo Basin advances with new prototype
CGIAR July 5 2024
The idea of creating a complete virtual representation, or Digital Twin, of a natural system opens up future in which decision-makers can easily identify and respond to environmental issues. Advances in remote sensing and cloud computing mean that it is technically feasible, but how can it practically be achieved in the context of the global South?
The Limpopo Watercourse Commission (LIMCOM) Secretariat has been engaging closely with researchers from the International Water Management Institute (IWMI) to develop a Digital Twin that meets their needs, under the CGIAR Initiative on Digital Innovation and the Digital Innovations for a Water Secure Africa (DIWASA) project.
Around 18 million people rely on freshwater in the Limpopo River Basin, which is now threatened by climate variability, overuse and pollution. LIMCOM faces the challenge of overseeing this large and complex system, which covers four hundred thousand square kilometers and four countries: Botswana, Mozambique, South Africa and Zimbabwe. A Digital Twin would radically improve the ability for LIMCOM, riparian governments and other stakeholders to sustainably use and preserve the river basin.
The prototype Digital Twin for the Limpopo River Basin Concept leverages a high-resolution 3D topographical map to integrate near real-time, historical, and forecasted data. The core of the system is a hydrological model, including layers for river discharge, rainfall, water quality, and ecosystem information, providing detailed insights into water availability and risks. The prototype aims to monitor droughts, map reservoirs, irrigated areas and support environmental flows (e-flows) management by monitoring the river ecosystem’s state over time.
“The possibilities for a Digital Twin in river basin water management are extraordinary,” said Chris Dickens, principal researcher at IWMI. “In the present world, water resource managers are faced with complex decisions based on large amounts of sometimes contradictory data interpreted by different models. The Digital Twin has the potential to simplify this, using AI to pull together this complex data so that the manager can make what-if decisions freely and rapidly without having to work through all the models. This has the potential to make water resource management more effective, leading to greater sustainability and increasing water security for all.”
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