Fault displacement can occur due to primary faulting on a main fault intersecting a dam foundation or rim, as well as by secondary faulting. This secondary faulting may be triggered locally by the occurrence of primary faulting on a main fault; its occurrence is conditional on the occurrence of an earthquake on the main fault. A probabilistic approach is most viable for fault displacement hazard analysis. Unlike the case of probabilistic ground motion hazard, which is nonzero even for short return periods due to the occurrence of a broad range of earthquake magnitudes in a wide region around the site, probabilistic fault displacement hazard is zero for return periods less than the recurrence interval of surface faulting earthquakes on the fault. In Australia, these recurrence intervals typically lie in the range of 10,000 to 100,000 years.
Consequently, the fault displacement hazard due to primary faulting may be zero or negligible for return periods shorter than 10,000 or 100,000 years. For longer return periods, the hazard is best evaluated using a risk-based approach, as recommended by ANCOLD (2018); the alternative of using a deterministic approach, which disregards return period, could potentially yield a large fault displacement. The probability of triggered secondary faulting, conditional on the occurrence of a large earthquake on the main fault, is typically one or two orders of magnitude lower than that on the main fault, and so is even more likely to be zero or negligible for return periods shorter than 10,000 to 100,000 years
Sedimentation of reservoirs is acknowledged as a global issue and likely impacts water storage capacity in Australia. This major challenge to our future water supply is a highly complex process with deposition leading to infilling of the reservoir of course sediments in headwaters following major inflows, progressively to finer fractions towards dam walls. Wave action and catchment inflows during drawdown conditions will further transport and redistribute sediments into the main body of the reservoir.
Managing reservoir sedimentation requires an understanding of the sediment types and deposition patterns across the reservoir. Once the location and type of sediment is known, strategies to mitigate the effects on the reservoir can be determined. Methods typically used for determining sedimentation of a reservoir are empirical or modeling techniques that rely on detailed data from inflow events, suspended solids loads and flow rates. In the absence of this data, more direct measurements to quantify the amount of sediment present can be used. Direct measurements are more robust than modelling approaches that utilise rating curves that can result in over estimations of the sediment present. This study combined several measurement techniques to produce high spatial coverage of the reservoir floor. Detailed validation of this approach was undertaken in one representative reservoir prior to adopting this approach across multiple reservoirs.
The importance of building and maintaining safe, resilient tailings dams has become increasingly apparent with the rise in catastrophic failures in recent years. According to the World Mine Tailings Failures (WMTF) data base, 11 major failures have occurred over the past decade, often with devastating impacts to nearby communities in terms of loss of life and impact to the environment. With the occurrence of these types of events only expected to increase in coming years, there has been a corresponding increase in global calls to action to develop monitoring systems to better predict and wherever possible, prevent these failures from occurring.
With up to an estimated 20,000 tailings dams around the world, the development and implementation of a worldwide monitoring protocol is a daunting task, particularly as many of these structures are remote and difficult to access. This is where a technology like InSAR can make an immediate impact. InSAR is a remote sensing technique that uses radar satellite imagery to measure ground movement with up to millimetric precision. Radar systems are active, meaning they collect information from reflections of the radar signal off the ground and therefore do not require the installation of any equipment. As satellite images cover areas that extend thousands of square kilometres, they can provide information not only on the stability of dams, but also entire regions. Global archives already exist due to the Sentinel constellation of satellites, which provide coverage since 2014 over most parts of the world.
In an ideal world, tailings dams are safe and constructed to provide permanent containment of mining by- products. However, experience has shown that they can fail, often with dire consequences, especially if these failures occur without warning. The development of an internationally accepted standard for tailings dam monitoring is imperative to ensure the safety and resiliency of these structures is continuously tracked. This paper explores the role InSAR can play in the development of a global protocol for tailings dam monitoring.
Computational Fluid Dynamics (CFD) is the science of predicting momentum, mass and heat transport, and can aid in design and safety issues for dam resilience in modern settings. Applications of CFD have historically been in the aerospace, automotive and chemical process industries with limited application in the hydraulic engineering field; possibly due to the associated computational intensity that is typically required. However, over the past two decades the cost of computing power has decreased substantially while the processing speed has increased exponentially. These developments have now made the application of CFD in the commercial environment feasible. CFD is particularly valuable in complex flow situations where the outputs required cannot be provided by a traditional hydraulic assessment approach and where there are stakeholder drivers such as service life, insurance cover and safety implications of infrastructure. The need for CFD when these drivers and complex flow situations arise, are demonstrated by means of a case study.
In the case study, CFD was used to investigate the flow patterns and the predicted performance of the outlet pipework from Massingir Dam in Mozambique. Three flow scenarios with appropriate pressure and flow boundary conditions were analysed for the outlet pipework, which included bifurcations for power generation from the main discharge conduits. Specific concerns addressed were, firstly, the possible excessive negative pressure in the region of the offtake for power generation and the potential for cavitation effects and, secondly, unacceptable velocity gradients in the power offtake pipework. Results showed that although some negative pressures were possible in one flow scenario, mitigation measures based on the CFD outputs could be considered and designed before construction.
The implementation of CFD in the above case study displays how risk in design can be reduced to ensure safety issues are addressed effectively.
Satellite remote sensing data can be used to monitor environmental processes and inform disaster risk reduction and hazard early warning. This paper describes the analysis of satellite remote sensing images to investigate the partial wall collapse of a tailings dam at the Cadia gold-copper mine in Australia that occurred on 9th March 2018. Our case study uses freely available remote sensing imagery acquired by the Copernicus Sentinel-1 (radar) and Sentinel-2 (multispectral) satellite constellations to monitor land surface changes in the Cadia mine area before and after the collapse. In this paper we discuss the benefits of utilising both radar and multispectral remote sensing imagery in a holistic approach to remote sensing, which could be used for continuous, near-real time monitoring of risk-related infrastructure such as dams without the need for in-situ measurement equipment.
We applied the Interferometric Synthetic Aperture Radar (InSAR) technique to measure surface displacements and interferometric coherence maps from a stack of Sentinel-1 radar images acquired between 2nd December 2015 and 25th June 2018 at regular 12 day intervals. The time series of surface displacements show a significant increase in the rate of movement of the dam wall in the area that eventually breached in the two months prior to the collapse. This change in movement behaviour was not observed at parts of the dam wall that remained intact. This analysis demonstrates the potential for InSAR monitoring to identify issues in advance of infrastructure failure, which could allow risk mitigation strategies to be implemented by the mine operator. We used interferometric coherence data to observe changes in the dam wall and surrounding areas before and after the collapse. A drop in coherence occurred in the breached section of dam wall, indicating the surface change caused by the collapse. Coherence for unaffected parts of the dam wall remained stable. Sentinel-2 multispectral imagery acquired between 2nd July 2017 and 24th June 2018 show the timing, extent and effects of the collapse as well as the rate of tailings movement.
Many numerical simulations have tried to model the failure-induced displacements of earth structures due to liquefaction. In this paper, the challenges in modelling such as the large displacement and non-immediate failure of earth structures due to liquefaction are discussed. An advanced bounding surface plasticity model is used to simulate the dynamic behaviour of saturated porous media. A series of benchmark welldocumented seismic events are analysed, and the results are compared to the reported laboratory and field observations. These analyses consist of one centrifuge test on liquefiable sand (Model #12 of the VELACS project) and one earthfill dam (Lower San Fernando Dam in California) subjected to seismic loading that leads to liquefaction. The capability of the model to capture the flow failure due to liquefaction is demonstrated and results are compared with other attempts in the literature to capture similar responses.