4.3 Conclusions
49
4.3 Conclusions
Given the nature of tailings dams, their construction time and expected service life
and closure, the effects of today’s risk mitigation programs will only slowly become
visible because the world portfolio will contain mitigated and unmitigated (legacy)
dams. During that period the industry credibility and SLO will remain vulnerable
(Oboni and Oboni 2014a, b; Oboni et al. 2013). It will be very difficult to evaluate progress as factors such as climate change, seismicity (again, not necessarily
“Black Swans”), increase in population and environmental awareness (consequence
side of the risk equation) will further complicate the situation. Thus public outcry
and hostility toward the mining industry, fuelled by the diffusion of information
and communication technology will likely increase unless transparent, rational, and
defensible approaches to dam portfolio risk prioritization are swiftly implemented.
The model presented has been shown to “construct” the first estimate of the probability of failure of a dam which is consistent with factual historical world-data. As
such it constitutes the first support to any prioritization effort on a portfolio of dams
or a first attempt for a single dam. The causality of various factors entering in the
e-IDC process and other elements in the dam’s service life can then be individually discussed/negotiated among experts and stakeholders with a sensitivity analysis
allowing for better communication and enhancing transparency.
It has been shown with a practical example where and how e-IDC process mitigative actions can be most beneficial, if properly implemented. The potential effects
of CCF have been described. This methodical approach makes it possible to determine in an economical, orderly, efficient way the relative a priori probabilities of
failure of dams, based on archival data, expressed in ranges to include uncertainties.
It is possible to use this approach for one dam or for a portfolio of dams. Later on
in this book (Chap. 14 and Part III) we will discuss more detailed approaches that
require more data, but are still sustainable if portfolio prioritization is required with
a “normal” level of data availability. Companies, governments, regulatory agencies
dealing with large portfolios of dams need to be able to prioritize risks in order to
develop credible and efficient risk reduction programs (Bellringer 2016).
References
Azam S, Li Q (2010) Tailings Dam Failures: A Review of the Last One Hundred Years, Waste Geo
Technics
Bellringer C (2016) An Audit of Compliance and Enforcement of the Mining Sector, Auditor
General for the Province of British Columbia
Bowker LN, Chambers DM (2015) The risk, public liability, & economics of Tailings Storage
Facility failures, the Earthwork Action, 1–56
Caldwell J, Oboni F, Oboni C (2015) Tailings Facility Failures in 2014 and an Update on Failure
Statistics, Tailings and Mine Waste 2015, Vancouver, Canada, October 25–28 2015. https://open.
library.ubc.ca/media/download/pdf/59368/1.0320843/5
49
4.3 Conclusions
Given the nature of tailings dams, their construction time and expected service life
and closure, the effects of today’s risk mitigation programs will only slowly become
visible because the world portfolio will contain mitigated and unmitigated (legacy)
dams. During that period the industry credibility and SLO will remain vulnerable
(Oboni and Oboni 2014a, b; Oboni et al. 2013). It will be very difficult to evaluate progress as factors such as climate change, seismicity (again, not necessarily
“Black Swans”), increase in population and environmental awareness (consequence
side of the risk equation) will further complicate the situation. Thus public outcry
and hostility toward the mining industry, fuelled by the diffusion of information
and communication technology will likely increase unless transparent, rational, and
defensible approaches to dam portfolio risk prioritization are swiftly implemented.
The model presented has been shown to “construct” the first estimate of the probability of failure of a dam which is consistent with factual historical world-data. As
such it constitutes the first support to any prioritization effort on a portfolio of dams
or a first attempt for a single dam. The causality of various factors entering in the
e-IDC process and other elements in the dam’s service life can then be individually discussed/negotiated among experts and stakeholders with a sensitivity analysis
allowing for better communication and enhancing transparency.
It has been shown with a practical example where and how e-IDC process mitigative actions can be most beneficial, if properly implemented. The potential effects
of CCF have been described. This methodical approach makes it possible to determine in an economical, orderly, efficient way the relative a priori probabilities of
failure of dams, based on archival data, expressed in ranges to include uncertainties.
It is possible to use this approach for one dam or for a portfolio of dams. Later on
in this book (Chap. 14 and Part III) we will discuss more detailed approaches that
require more data, but are still sustainable if portfolio prioritization is required with
a “normal” level of data availability. Companies, governments, regulatory agencies
dealing with large portfolios of dams need to be able to prioritize risks in order to
develop credible and efficient risk reduction programs (Bellringer 2016).
References
Azam S, Li Q (2010) Tailings Dam Failures: A Review of the Last One Hundred Years, Waste Geo
Technics
Bellringer C (2016) An Audit of Compliance and Enforcement of the Mining Sector, Auditor
General for the Province of British Columbia
Bowker LN, Chambers DM (2015) The risk, public liability, & economics of Tailings Storage
Facility failures, the Earthwork Action, 1–56
Caldwell J, Oboni F, Oboni C (2015) Tailings Facility Failures in 2014 and an Update on Failure
Statistics, Tailings and Mine Waste 2015, Vancouver, Canada, October 25–28 2015. https://open.
library.ubc.ca/media/download/pdf/59368/1.0320843/5