Tailings dams’ classification based on risk using data from SIGBM

Authors

  • Claudinei Oliveira Cruz
  • Henrique Nogueira Soares
  • Hernani Mota de Lima

DOI:

https://doi.org/10.54033/cadpedv21n3-164

Keywords:

Tailings Dam Failure, Tailings Dam Safety, Risk Classification, Risk Mitigation, Vulnerability

Abstract

The Brumadinho and Mariana tailings dam failures in Brazil tragically highlighted the critical need for robust risk management in the mining sector. Tailings dams, by their very nature, pose significant risks to downstream communities and the environment in the event of failure. To mitigate these risks, a comprehensive risk classification system is essential. This abstract emphasizes the real-world impact of dam failures and strengthens the importance of risk classification. Risk analysis plays a central role in identifying, quantifying, and ultimately mitigating the potential consequences of tailings dam failure. The classification process considers various factors that influence dam stability and safety, including dam geometry and construction methods — the design and construction techniques employed significantly impact a dam's stability; tailings characteristics — the physical and chemical properties of the stored tailings can influence factors like liquefaction potential; operating conditions — factors like the rate of tailings deposition and the presence of seismic activity need evaluation; drainage system effectiveness — a well-functioning drainage system is crucial for managing pore pressures within the dam. By analyzing these elements, risk classification aims to categorize tailings dams into distinct risk levels, typically ranging from low to very high. This categorization allows for targeted risk mitigation strategies to be implemented based on the specific vulnerabilities of each dam. This paper proposes a methodology for risk classification of tailings dams utilizing data from the Brazilian National Mining Agency's (ANM) Integrated Mining Dam Management System (SIGBM). The study focuses on 203 dams situated in Minas Gerais, a Brazilian state with a history of dam failures. Data was extracted from SIGBM in February 2023. This research not only presents a general risk classification for the assessed dams but also delves deeper, offering a quantitative measure of vulnerability, risk potential, and potential consequences of a failure event for each individual dam.

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Published

2024-03-25

How to Cite

Cruz , C. O., Soares, H. N., & Lima , H. M. de. (2024). Tailings dams’ classification based on risk using data from SIGBM. Caderno Pedagógico, 21(3), e3359. https://doi.org/10.54033/cadpedv21n3-164

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Section

Articles