One lesson we all probably remember from primary school is the water cycle. Even if you don’t remember exactly what you learned, you probably have memories of a video or diagram that was so colorful and creative that it made the day a little more fun. For some of us (myself included), it’s honestly hard to forget. Even in the adult world, it feels neat and easy to think about the three components of the water cycle that, as the pun is intended, rinse and repeat: evaporation, condensation, and precipitation.
Our planet could not survive without water, a substance that makes up 71% of the entire world’s surface, while the oceans account for about 97% of this figure. That said, however, the process can become quite complicated when you add in the ever-changing climate, driven by human activities such as burning coal, as well as other daily impacts that we as a society face. As a weather forecaster, I know the challenges we face when it comes to predicting water-based natural disasters, including floods, landslides and droughts.
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But to ensure that scientists can make the most accurate predictions and better understand how this cycle works, we need to obtain and assess models that contain as much high-resolution data as possible. This data should also ideally cover every inch of the planet, from the highest mountain peaks to the water deep in the ground.
And thanks to funding from the European Space Agency, scientists are building just that: a digital twin of Earth, and all its beautiful water, that can be inspected.
“Simulating the Earth at high resolution is very complex, so the idea is actually to focus on a specific target first,” says Luca Brocca of Italy’s National Research Council. said in a statement. “That is the idea behind what we have developed: digital double case studies for the terrestrial water cycle in the Mediterranean. Our goal is to create a system that allows non-experts, including decision makers and citizens, to run interactive simulations.”
Brocca, the lead author of an in-depth paper on the research, worked with colleagues to create the digital twin. By having this model, scientists can consistently input new data to simulate the best and worst case scenarios of natural disasters in different environments on our planet. For example, by simulating a landslide, the associated risks and conditions associated with it can be monitored as if they were happening in real time. This could further help prepare for potentially destructive events in the future, based on what is learned during each test.
How are these models made?
It took a lot of work for scientists to collect as much satellite data as possible, collected through a large number of Earth observations. They then combined measurements of soil moisture, precipitation, snow depth, evaporation and river discharges, taken at specific time intervals, to paint a clear picture of the dynamics of the variables across the planet. The model’s high-resolution data can then be used as an interactive tool for scientists.
“This project is a perfect example of the synergy between advanced satellite missions and the scientific community,” said Brocca. “Collaborations like these, coupled with investments in computing infrastructure, will be critical to managing the effects of climate change and other human impacts.”
As with any type of model, it takes practice to strive for perfection. But you have to start somewhere.
Brocca and colleagues first used the digital twin to model the Po River valley in northern Italy and other parts of the Mediterranean; they have future plans to create similar models across Europe before collaborating with scientists from other continents. The main goal of this project is to help predict where floods and landslides may occur and to learn how we can better manage our water resources.
“We have to start from something we know very well,” Brocca said. “The Po River valley is very complex – we have the Alps, we have snow, which is difficult to simulate, especially on irregular and complex terrain such as mountains. Then there is the valley with all the human activities – industry, irrigation. Then we have We have a river and extreme events – floods, drought. And then we moved to the Mediterranean, which is a good place to study extreme events, both due to too much and too little water.”
While the team’s modeling focuses on a larger-scale region, there are also plans to look at more localized studies. But for now, scientists remain focused on the biggest, most persistent challenges in their mechanism. For example, the complex algorithms they have developed will need to be adjusted as significant amounts of data continue to be added; There is also a need for more ground observations, they say, to continue verifying the satellite data they use.
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In a similar vein, to combat any uncertainties that may arise from using satellite data, Brocca hopes to incorporate artificial intelligence into his program to iron out some of the kinks. In a sense, the AI would act as an extra pair of eyes, if it can indeed be trained properly. As we have seen with the use of AI in weather models, such as those related to wildfire forecastsThe benefits of such collaboration include minimizing errors that can sometimes occur due to changes in atmospheric conditions while images are being captured. Implementing AI can also save time, allowing human engineers to focus on other areas of concern.
“The collective efforts of scientists, space agencies and decision makers promise a future where Digital Twin Earths for hydrology provide valuable insights for sustainable water management and disaster resilience,” said Brocca.
The study was published March 5 in the journal Frontiers in science.