ACROPOLIS: A graphical user interface for classification of risk for off-stream reservoirs using machine learning

Potential risk identification due to off-stream reservoir failure typically requires the use of two-dimensional hydraulic models, which demands considerable effort in terms of expertise, time and financial resources. Unfortunately, not all reservoir owners have access to these resources, and the pro...

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Published in:SoftwareX 2024-05, Vol.26, p.101657, Article 101657
Main Authors: Silva-Cancino, Nathalia, Salazar, Fernando, Bladé, Ernest
Format: Article
Language:English
Subjects:
Dam break
Machine learning
Off-stream reservoir
Potential risk
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description Potential risk identification due to off-stream reservoir failure typically requires the use of two-dimensional hydraulic models, which demands considerable effort in terms of expertise, time and financial resources. Unfortunately, not all reservoir owners have access to these resources, and the process of assessing hazard classifications for administrations can be burdensome. ACROPOLIS was developed to address this challenge, employing a Machine Learning model to provide a preliminary risk classification according to Spanish regulations for off-stream reservoirs without the necessity of building a hydraulic model. This approach has been integrated into a user-friendly interface, simplifying the process for users.
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subjects Dam break
Machine learning
Off-stream reservoir
Potential risk
title ACROPOLIS: A graphical user interface for classification of risk for off-stream reservoirs using machine learning
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