Tailings dams: Assessing the long-term erosional stability of valley fill designs.

Tailings is a generic term for waste material from the extraction and processing of minerals and frequently contain mineral and chemical residues. They are usually highly erodible and transportable via fluvial processes. Tailings are commonly stored in 'tailings dams' and such dams are a feature of many mine sites. As they impound water and sediment, tailings dams can be at risk from both catastrophic and gradual failure, especially if unmanaged. A fundamental question for their management is, can tailings dams ever be walk-away structures? Catastrophic failure occurs when there is a large scale rapid structural failure of the dam wall suddenly releasing large volumes of water and sediment. However, over time, there will the increased risk of gradual failure by the slow infilling of the dam and the erosion of the dam wall. Failure can occur where water overtops the dam wall and then incises through the wall due to a loss of freeboard in the dam, a situation which is more likely in legacy tailings dams where they have been filled, vegetated and abandoned. Here, firstly, a computer based landscape evolution model (CAESAR-Lisflood) is employed to assess a hypothetical tailings dam failure by erosion. Secondly, using an idealised example, it is demonstrated that given average climate conditions a dam can be sufficiently robust to last centuries. Thirdly, and longer term it is demonstrated that the tailings can be contained if (a) maintenance is conducted to increase the dam wall height over time or (b) a more robust dam wall is constructed to manage extreme events. However, erosion and infill will continue to reduce the integrity of any structure over time. Therefore, it is highly likely that tailings dams will require continued monitoring and maintenance. The method outlined provides a new tool for assessing any tailings facility for its erosional stability.

Modelling river history and evolution.

Over the last few decades, a suite of numerical models has been developed for studying river history and evolution that is almost as diverse as the subject of river history itself. A distinction can be made between landscape evolution models (LEMs), alluvial architecture models, meander models, cellular models and computational fluid dynamics models. Although these models share some similarities, there also are notable differences between them, which make them more or less suitable for simulating particular aspects of river history and evolution. LEMs embrace entire drainage basins at the price of detail; alluvial architecture models simulate sedimentary facies but oversimplify flow characteristics; and computational fluid dynamics models have to assume a fixed channel form. While all these models have helped us to predict erosion and depositional processes as well as fluvial landscape evolution, some areas of prediction are likely to remain limited and short-term owing to the often nonlinear response of fluvial systems. Nevertheless, progress in model algorithms, computing and field data capture will lead to greater integration between these approaches and thus the ability to interpret river history more comprehensively.

Nonlinear contrast imaging with an array-based micro-ultrasound system.

The main goal of this study was to determine the optimal strategy for a real-time nonlinear contrast mode for small-animal imaging at high frequencies, on a new array-based micro-ultrasound system. Previously reported contrast imaging at frequencies above 15 MHz has primarily relied on subtraction schemes involving B-mode image data. These approaches provide insufficient contrast to tissue ratios under many imaging conditions. In this work, pulse inversion, amplitude modulation and combinations of these were systematically investigated for the detection of nonlinear fundamental and subharmonic signal components to maximize contrast-to-tissue ratio (CTR) in the 18-24 MHz range. From in vitro and in vivo measurements, nonlinear fundamental detection with amplitude modulation provided optimal results, allowing an improvement in CTR of 13 dB compared with fundamental imaging. Based on this detection scheme, in vivo parametric images of murine kidneys were generated using sequences of nonlinear contrast images after intravenous bolus injections of microbubble suspensions. Initial parametric images of peak enhancement (PE), wash-in rate (WiR) and rise time (RT) are presented. The parametric images are indicative of blood perfusion kinetics, which, in the context of preclinical imaging with small animals, are anticipated to provide valuable insights into the progression of human disease models, where blood perfusion plays a critical role in either the diagnosis or treatment of the disease.

Modelling approaches for coastal simulation based on cellular automata: the need and potential.

The paper summarizes the theoretical and practical needs for cellular automata (CA)-type models in coastal simulation, and describes early steps in the development of a CA-based model for estuarine sedimentation. It describes the key approaches and formulae used for tidal, wave and sediment processes in a prototype integrated cellular model for coastal simulation designed to simulate estuary sedimentary responses during the tidal cycle in the short-term and climate driven changes in sea-level in the long-term. Results of simple model testing for both one-dimensional and two-dimensional models, and a preliminary parameterization for the Blackwater Estuary, UK, are shown. These reveal a good degree of success in using a CA-type model for water and sediment transport as a function of water level and wave height, but tidal current vectors are not effectively simulated in the approach used. The research confirms that a CA-type model for the estuarine sediment system is feasible, with a real prospect for coupling to existing catchment and nearshore beach/cliff models to produce integrated coastal simulators of sediment response to climate, sea-level change and human actions.