Author(s): Enric Bonet; Maria Teresa Yubero; Lluis Sanmiquel; Marc Bascompta
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Keywords: No Keywords
Abstract: Historically, one of the most common causes of dam failure has been overtopping, primarily in earthfill dam, accounting for approximately 34% in the United States, according to the Association of State Dam Safety Officials. There have been other contributing factors to dam failures throughout history, with a significant issue in masonry dams being water infiltration through the dam body, leading to erosion of the mortar that binds the rocks forming the dam body. As a result, quantifying the flow rate from these leakages is an important parameter to consider and measure in the operation of such dams. In this article, a tool is developed using Artificial Intelligence methodologies, specifically artificial neural networks, for predicting water leakages in a masonry dam. The tool learns from historical data collected from the Santa Fe del Montseny Dam (Barcelona) over the past 10 years (although not all dataset is completed), taking into account factors such as temperature, precipitation, reservoir levels, water levels in observation wells within the dam, as well as water leakage measurements.
Year: 2024