In this paper, we propose a semi-parametric estimation strategy of the volume of the material released by a tailings dam, after a rupture of the dam. This allows us to determine the risk of a tailings dam. The method is based on Bayesian modeling of the copula between the volume of the contained material and the volume of the released material found in 35 cases of tailings dams’ruptures, reported around the world during the last 55 years, see [1]. For the modeling of the marginal distributions of the volumes, several nonparametric perspectives of estimation are considered. This combination of techniques makes it possible to improve the estimation process of the released volume postulated in [2].
REFERENCES
1.
P. Concha
Larrauri
and U.
Lall
, Tailings dams failures: updated statistical model for discharge volume and runout
. Environments
5
(2
), 28
(2018
)2.
L.M.C.F.
Fais
, V.A.
González-López
, D. S.
Rodrigues
and R. Rodrigues
de Moraes
, A Copula Based Representation for Tailings Dam Failures
. 4open (forthcoming)
.3.
M.
Rico
, G.
Benito
and A.
Diez-Herrero
, Floods from tailings dam failures
. Journal of Hazardous Materials
154
(1-3
), 79
–87
(2008
)4.
M.
Sklar
, Fonctions de repartition à n dimensions et leurs marges
. Publ. inst. statist. univ. Paris
, 8
, 229
–231
(1959
)5.
A.
Gramacki
, Nonparametric kernel density estimation and its computational aspects
Berlin
: Springer International Publishing
, (2017
)6.
J.
Fan
and I.
Gijbels
Local polynomial modelling and its applications: monographs on statistics and applied probability 66
(Vol. 66
) CRC Press
, (1996
)
This content is only available via PDF.
© 2022 Author(s).
2022
Author(s)
You do not currently have access to this content.