Priyanka Ashok Garsole, Shantini Bokil, Vijendra Kumar, Arunabh Pandey, Niraj S. Topare

A review of artificial intelligence methods for predicting gravity dam seepage, challenges and way-out

  • Management, Monitoring, Policy and Law
  • Pollution
  • Water Science and Technology
  • Ecology
  • Civil and Structural Engineering
  • Environmental Engineering
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Abstract Seepage is the phenomenon of water infiltrating through a gravity dam's foundation, causing erosion and weakening the dam's construction over time. If not properly managed, this can eventually lead to the dam's catastrophic failure, posing a significant danger to public safety and the environment. As a result, precise seepage prediction in gravity dams is essential for ensuring their safety and stability. This review paper looks at the use of artificial intelligence (AI) techniques for predicting seepage in gravity dams, as well as the challenges and possible solutions. The paper identifies and suggests potential solutions to the challenges connected with using AI for seepage prediction, such as data quality and model interpretability. The paper also covers future research paths, such as the creation of advanced machine learning algorithms and the improvement of data collection and processing. Overall, this review gives insight on the current state of the art in using AI to predict gravity dam seepage and recommends methods to improve the accuracy and reliability of such models.

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