Abstract
AbstractNumerical models are used for detailed and site-specific tailings dam breach analyses (TDBAs) to estimate the downstream inundation and deposition resulting from a potential breach at a tailings dam. The results of TDBAs are key inputs into risk assessments, consequence classification, and emergency planning. This paper describes the research and development of a database of 12 tailings dam breach events with a specific focus on observations that are needed for numerical modelling, in conjunction with an assessment of existing dam breach conventions to improve consistency in reporting. The characteristics relevant to modelling include outflow volumes, breach processes, breach geometries, and runout observations local to the downstream area. This study and the new database shed light on the diversity of outflow materials, facility arrangements, breach processes, and downstream environments that affect the breach development and tailings runout. Familiarity with case studies is a crucial element of expert judgement for forward-analysis TDBAs, which this database supports. The database can also be used to define model inputs for back-analysis of additional tailings dam breach events, and simultaneously provides calibration or validation constraints with the runout observations. Continued review and critical assessments are needed to reduce uncertainties and to enhance case history data availability and quality in this database.
Funder
National Science and Engineering Research Council of Canada
GeoscienceBC
University of British Columbia Graduate School
Publisher
Springer Science and Business Media LLC
Subject
Geotechnical Engineering and Engineering Geology,Water Science and Technology
Reference92 articles.
1. Aaron JB, Stark TD, Baghdady AK (2018) Closure to “Oso, Washington, landslide of March 22, 2014: dynamic analysis” by Jordan Aaron, Oldrich Hungr, Timothy D. Stark, and Ahmed K. Baghdady. J Geotech Geoenviron 144(9):2014–2017. https://doi.org/10.1061/(ASCE)GT.1943-5606.0001934
2. Aaron JB, McDougall S, Kowalski J, Mitchell A, Nolde N (2022) Probabilistic prediction of rock avalanche runout using a numerical model. Landslides 19:2853–2869. https://doi.org/10.1007/s10346-022-01939-y
3. Adria DAM (2022) Compilation and critical assessment of observations from a selection of historical tailings dam breach events for numerical breach and runout modelling. MASc thesis, Univ British Columbia. https://doi.org/10.14288/1.0421782
4. Adria DAM, Ghahramani N, Rana NM, Martin V, McDougall S, Evans SG, Take WA (2023) A database of tailings dam breach and runout observations. Borealis Can Dataverse Reposit. https://doi.org/10.5683/SP2/NXMXTI
5. ANM (Agência Nacional de Mineração) [National Mining Agency of Brazil] (2022) Directive no. 95, 7 Feb. 2022 https://anmlegis.datalegis.inf.br/action/UrlPublicasAction.php?acao=abrirAtoPublicoandnum_ato=00000095andsgl_tipo=RESandsgl_orgao=ANM/MMEandvlr_ano=2022andseq_ato=000andcod_modulo=405andcod_menu=6783. Accessed 26 Jun 2023 (in Portuguese)
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