Imagine having to navigate through a cave system that is pitch black, with the threat of an impending flood moving at a slow pace. While this scenario may be somewhat familiar to those within the field of hydrogeology who have had to deal with the pollution of groundwater across various locations within the world during the past few decades, it is also one of the reasons for which the introduction of digital twins of aquifers was necessary.
Before the advent of digital twins of aquifers, scientists would have to use physical samples of the soils to determine the movement of the chemicals within the groundwater, as well as perform hand tests of the wells to see how the groundwater moved. Now, however, with the use of sensors that are connected to the internet of things (IoT) that use artificial intelligence (AI) algorithms and physics engines – similar to those used in video games today – scientists can create a 3D model of the underground area. For Groundwater Remediation, contact https://soilfix.co.uk/services/groundwater-remediation
These models, of course, can receive data directly from the sensors that are placed into the aquifer. Unlike the months that are required to receive results from laboratory tests of the aquifer, with the use of digital twins of aquifers, scientists can observe how the pollutants move within the aquifer in real time. Also, using machine learning algorithms based upon physics engines that power video games today, scientists can predict how the pollutants will behave over the coming months.
Based upon these digital twin models, scientists can use autonomous systems that can accurately target the areas into which the pollutants have spread. As a result, the length of time that is required to clean up polluted aquifers has been reduced from decades to merely a few months.