In the heart of Switzerland, a decade-long experiment is shedding new light on how pollutants travel through soil, with implications that could reshape how we manage drinking water resources and even impact the energy sector. At the Rietholzbach lysimeter, a unique weighing grassland lysimeter, researchers have been meticulously tracking water movement and pollutant transport, providing a wealth of data that has now been used to validate a novel modeling approach.
The study, led by Robin Schwemmle from the Hydrology Faculty of Environment and Natural Resources at the University of Freiburg, couples process-based hydrologic modeling with StorAge Selection (SAS) functions. This innovative approach allows for a more accurate representation of transport processes and travel times of pollutants in the subsurface.
“Understanding these processes is crucial for effective water resource management,” Schwemmle explains. “By coupling hydrologic models with SAS functions, we can better predict how pollutants move through soil, which is essential for protecting our drinking water supplies.”
The research, published in Water Resources Research, which translates to Water Resources Research, involved conducting modeling experiments at the Rietholzbach lysimeter. The team compared their simulations to measured hydrologic variables and water stable isotope signals over a ten-year period. They also conducted a virtual bromide tracer experiment to further benchmark their models.
One of the key findings was that the advection-dispersion transport model produced the best results, indicating that advective-dispersive transport processes play a dominant role at the Rietholzbach lysimeter. This has significant implications for the energy sector, particularly in areas where water is used for cooling or where there is a risk of groundwater contamination from energy production activities.
The modeling approach developed by Schwemmle and his team provides a powerful tool for testing hypotheses about different transport mechanisms. This could lead to improved process understanding and predictions of transport processes, ultimately enhancing our ability to manage water resources more effectively.
But the potential applications don’t stop at water management. In the energy sector, understanding subsurface transport processes is crucial for managing risks associated with activities like hydraulic fracturing, carbon sequestration, and nuclear waste disposal. By providing a more accurate way to model these processes, this research could help energy companies mitigate environmental risks and ensure the safety of their operations.
Moreover, the open-source nature of the models used in this study means that they can be easily adapted and applied to a wide range of scenarios. This could lead to a more collaborative and innovative approach to water and energy management, with researchers and practitioners sharing their findings and building on each other’s work.
As we face increasing pressures on our water and energy resources, the need for accurate and reliable modeling tools has never been greater. This research represents a significant step forward in our understanding of subsurface transport processes, and it has the potential to shape the future of water and energy management for years to come.