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      A copula based representation for tailings dam failures

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          Abstract

          In this article, we model the dependence between dam factor and D max, where dam factor is an indicator of risk of a tailings dam failure, which involves the height H of the tailings dam, the volume of material housed by the tailings dam V T and the volume dispensed by the tailings dam, V F , when the dam breaks. And, D max is the maximum distance traveled by the material released by the tailings dam, after the collapse. With the dependence found via copula models and Bayesian estimation, given a range of dam factor, we estimate the probability of the released material to exceed a certain threshold. Since the dam factor involves the released volume V F (unknown before the dam break), we present a naive way to estimate it using V T and H. In this way, it is possible to estimate the dam factor of a tailings dam and with such a value to identify the probability of the tailings dam to show a D max that exceeds a certain threshold.

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          Most cited references 8

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          A characterization of gumbel's family of extreme value distributions

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            Floods from tailings dam failures.

            This paper compiles the available information on historic tailings dam failures with the purpose to establish simple correlations between tailings ponds geometric parameters (e.g., dam height, tailings volume) and the hydraulic characteristics of floods resulting from released tailings. Following the collapse of a mining waste dam, only a part of tailings and polluted water stored at the dam is released, and this outflow volume is difficult to estimate prior the incident. In this study, tailings' volume stored at the time of failure was shown to have a good correlation (r2=0.86) with the tailings outflow volume, and the volume of spilled tailings was correlated with its run-out distance (r2=0.57). An envelope curve was drawn encompassing the majority of data points indicating the potential maximum downstream distance affected by a tailings' spill. The application of the described regression equations for prediction purposes needs to be treated with caution and with support of on-site measurement and observations. However, they may provide a universal baseline approximation on tailing outflow characteristics (even if detailed dam information is unavailable), which is of a great importance for risk analysis purposes.
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              Fonctions de répartition à n dimensions et leurs marges

               A. Sklar,  A. Sklar,  Sklar (1959)
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                Author and article information

                Journal
                fopen
                https://www.4open-sciences.org
                4open
                4open
                EDP Sciences
                2557-0250
                25 September 2020
                25 September 2020
                2020
                : 3
                : ( publisher-idID: fopen/2020/01 )
                Affiliations
                [1 ] School of Technology, University of Campinas, , Paschoal Marmo 1888, 13484-332 Limeira, S.P., Brazil,
                [2 ] Department of Statistics, University of Campinas, , Sergio Buarque de Holanda 651, 13083-859 Campinas, S.P., Brazil,
                Author notes
                [* ]Corresponding author: rafael.moraes@ 123456gmx.de
                Article
                fopen200007
                10.1051/fopen/2020011
                © L.M. Canno Ferreira Fais, et al., Published by EDP Sciences, 2020

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                Page count
                Figures: 3, Tables: 10, Equations: 73, References: 11, Pages: 10
                Product
                Self URI (journal page): https://www.4open-sciences.org/
                Categories
                Research Article
                Mathematics - Applied Mathematics
                Custom metadata
                4open 2020, 3, 12
                2020
                2020
                2020
                yes

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