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- H41V-1495: Identifying Research Gaps in Hydrology Using Large Language Models and Knowledge Graphs
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Board 1495‚ Hall EFG (Poster Hall)NOLA CC
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Abel Andres Ramirez Molina, The University of Alabama (First Author, Presenting Author)
Saide Zand, The University of Alabama
Jiaqi Gong, University of Alabama
Scientific knowledge about water—such as how rivers flood, how droughts affect regions, or how water quality changes over time—is spread across thousands of research papers and reports. This makes it difficult for people who manage water systems to find and use the information they need. In this project, we created a new digital tool that helps organize and search through this large body of research. The tool connects two technologies: one that organizes information into a network of related ideas, and another that can answer questions in everyday language. Together, these technologies help users explore past research more easily and get clear, useful answers. We applied this system to a real-world case in Texas, focusing on the Galveston Bay area, which is vulnerable to storms, flooding, and other water challenges. Using 153 scientific papers, we built a smart database that can answer questions about past research and highlight areas that need more attention. Early results show that the tool gives more relevant and accurate answers than standard methods. This approach can help water researchers, planners, and decision-makers find the information they need faster, leading to better choices about how we manage and protect water resources.
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