Groundwater is a vital water supply for humanity. It supplies 35% of the drinking water in the U.S. and almost half of all drinking water in the world. Unfortunately, over-extraction, industrial contamination, and pollution from agricultural activities have depleted the groundwater resources. To make things worse, traditional methods for groundwater assessments have proven inadequate for accurately monitoring and managing these resources.
A research team led by the San Diego Supercomputer Center (SDSC) at UC San Diego is using data science and AI to develop a more in-depth understanding of groundwater dynamics. This could enable the researchers to lay the foundation for advanced models to assess groundwater resources.
Principal Investigator (PI) Ilya Zaslavsky, director of the SDSC Spatial Information Systems Laboratory, is heading the SDSC team, along with Co-PI Christine Kirkpatrick, director of the SDSC Research Data Services Division, and Co-PI Ashley Atkins, SDSC chief of staff. The SDSC team is joined by researchers from Poland, Ukraine, Lithuania, Latvia, Estonia, and the U.S.
The two-year project, titled Groundwater Resilience Assessment through Integrated Data Exploration for Ukraine (GRANDE-U), is funded jointly by the U.S. National Science Foundation (NSF), Research Council of Lithuania (LMT), Estonian Research Council (ETAG), Latvian Council of Science (LCS), National Science Center of Poland (NCN), U.S. National Academy of Sciences and Office of Naval Research Global (DoD).
Assessing and managing groundwater is particularly challenging in transboundary regions, where aquifers span across political boundaries. The challenges of international coordination coupled with a few technical issues make it difficult for researchers to conduct reliable groundwater assessments.
The uneven sensor networks, disparate data collection methods, and incompatible hydrogeologic descriptions across the transboundary regions make it complex to model groundwater systems and manage the aquifers effectively.
According to Zaslavsky, one of the primary objectives of the research team is to “integrate hydrogeologic models with satellite and ground-based observations and deliver highly detailed and timely predictions of groundwater storage and flows across borders.”
The SDSC GRANDE-U team aims to use the power of AI and data science to overcome the limitations of traditional methods for groundwater observation. One of the new methods being used is remote sensing for groundwater assessment using aerial imagery to gather information about the regions’ subsurface features.
The remote sensing method is even more vital for regions like Ukraine, where there is a sharp rise in demand for aquifers for drinking water, but the population displacement in the eastern parts of the country has made it difficult for researchers to gather critical data to understand groundwater dynamics.
According to Oleksii Shevchenko, chief scientist at the Ukrainian Hydrometeorological Institute in Kyiv and leader of the Ukrainian research team, addressing the groundwater assessment challenges transcends the capabilities of any single nation or discipline. The project’s success is heavily reliant on collaboration and knowledge-sharing across borders.
“Beyond the technical challenges of groundwater hydrology, this project also delves into the economic, social, and political factors affecting groundwater storage and dynamics,” said Co-PI Atkins. “We aim to understand the role that perceptions play in water decision-making and by working with transboundary water resource experts on our international team, we strive to enhance the credibility and reliability of our models.”
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AI and data science could play a key role in unlocking innovative solutions to addressing the threats of groundwater depletion. Researchers around the globe are using these technologies to gain a deeper understanding of groundwater dynamics.
The United States Geological Survey (USGS) has been developing AI models to predict groundwater responses to various stressors, such as climate change. NASA has been working on combining remote sensing and AI techniques for aquifer mapping and its recharge dynamics. AI is also being used in several other projects to save Earth’s precious resources.
The global research efforts demonstrate the potential of AI and data science in sustainable groundwater management. As the demand for groundwater continues to grow, advanced technologies will remain crucial for tackling the pressing challenges of water scarcity and resource management.
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