New 'digital twin' Earth technology could help predict water-based natural disasters before they strikeThe water cycle looks simple in theory—...
Published on by Water Network Research, Official research team of The Water Network
The water cycle looks simple in theory—but human impacts, climate change, and complicated geography mean that in practice, floods and droughts remain hard to predict. To model water on Earth, you need incredibly high-resolution data across an immense expanse, and you need modeling sophisticated enough to account for everything from snowcaps on mountains to soil moisture in valleys. Now, scientists have made a tremendous step forward by building the most detailed models created to date.
"Simulating the Earth at high resolution is very complex, and so basically the idea is to first focus on a specific target," said Dr. Luca Brocca of the National Research Council of Italy, lead author of the article published in Frontiers in Science. "That's the idea behind what we have developed—digital twin case studies for the terrestrial water cycle in the Mediterranean Basin. Our goal is to create a system that allows non-experts, including decision-makers and citizens, to run interactive simulations."
A test environment for the planet
In engineering, a digital twin is a virtual model of a physical object which can be tested to destruction without doing real damage. A digital twin of the Earth, constantly updated with new data, would allow us to simulate best and worst-case scenarios, assess risks, and track the development of dangerous conditions before they occur. Such information is vital for sustainable development and protecting vulnerable populations.
To build their digital twin models, Brocca and his colleagues harnessed extraordinary volumes of satellite data, combining new Earth observation data that measures soil moisture, precipitation, evaporation, river discharge, and snow depth. This newly available data, crucial to the development of the models, includes measurements taken much more frequently across space and time: as often as once a kilometer and once an hour.
Attached link
https://phys.org/news/2024-03-digital-twin-earth-technology-based.htmlTaxonomy
- Digital Twins