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| Mannum Waterfalls in South Australia Photo Credit: © denisbin Creative Commons 2.0 |
A solution to a tricky groundwater riddle from Australia: Researchers at TU Wien have developed numerical models to simulate the movement of fluids in porous materials.
Things are complicated along the Murray–Darling River in southern Australia. Agricultural irrigation washes salt out of the upper soil layers, and this salt eventually ends up in the river. To prevent the river’s salt concentration from rising too much, part of the salty water is diverted into special basins. Some of these basins are designed to let the salty water evaporate, others to slowly release it in a controlled manner in the underground. That keeps salt temporarily out of the river and allows a better management of the river’s water—but increases the salinity in the ground. How can we calculate how this saltwater spreads underground and what its long-term effects will be?
Such questions are extremely difficult to answer, as several physical effects interact in complex ways. At TU Wien, researchers have now developed an efficient computer model that can run on supercomputers to calculate the spreading of fluids in porous materials—allowing the movement of saltwater in the soils, like in the case of the Murray–Darling River, to be predicted much more accurately. The same approach can also be applied to other problems, such as the dispersion of pollutants in groundwater.
Diffusion and flow
“When different fluids mix, diffusion occurs,” explains Dr. Marco De Paoli from the Institute of Fluid Mechanics and Heat Transfer at TU Wien. “If you place a drop of ink in a glass of water, the ink molecules will gradually spread out, simply because of their random motion.”
At the same time, the behavior of fluids—such as groundwater in the soil—is also affected by other effects: denser fluids tend to sink, while lighter ones rise. This can create flows with a distinct direction, unlike diffusion, which spreads evenly in all directions. The situation becomes even more complicated when the fluid flows through a porous material, such as a sandy soil. The higher the velocity of the fluid through the sand, the more the salt (or the contaminants) carried by the fluid will spread. In addition, this spreading process, defined as ‘dispersion’, is larger in some directions than in others.
Chaotic finger patterns
“All these effects have been known for a long time, but we have now finally managed to incorporate them into a computer model, allowing us to simulate situations like those in southern Australia for the first time with the aid of supercomputers,” says Marco De Paoli. Interesting instabilities emerge: saltwater is denser than freshwater, but the upper soil layers contain more salt—so the denser fluid lies above the lighter one.
“That’s an unstable situation,” De Paoli explains. “If, by chance, a bit of the saltier water starts to sink, gravity amplifies the imbalance. The water begins to flow downward, forming finger-like structures that extend deep into the ground, and further enhance the dispersion of salt.”
Reliable formulas for many applications
Just as small differences in temperature and pressure can produce complex weather patterns, subtle variations in salinity and soil structure can give rise to intricate saltwater flows and patterns underground. With the computer models developed by Marco De Paoli in collaboration with the University of Twente (the Netherlands) and the Gran Sasso Science Institute (Italy), these processes can now be described and understood in detail.
The salt distribution near the Murray–Darling River is just one example where these computational methods can be employed. The same approach can be applied to a wide range of other phenomena—such as pollutant dispersion in groundwater, underground carbon dioxide storage, or convection processes in geothermal reservoirs.
Title: Solute mixing in porous media with dispersion and buoyancy
Authors: Marco De Paoli, Guru Sreevanshu Yerragolam, Roberto Verzicco, and Detlef Lohse
Source/Credit: Technische Universität Wien
Reference Number: phy110425_01
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