The failures of tailings dams, used to store waste from mining operations, pose a significant risk to the health of people and the environment, especially in many low income countries where the extractive industry makes a significant contribution to the nation's wealth. Recently the rate of failure of tailings dams has increased. The demand for raw materials and increases in intense rainfall as a result of climate change will exacerbate this issue in the future. The monitoring of tailings dams is essential to reduce their probability of failure. Virtually all the recent tailings dams failures were preventable. However, there is generally a lack of transparency and accountability for these structures by mining companies. In the past 10 years an increase in the global coverage and accuracy of Earth Observation (EO) based information has made it technically possible to use EO-based data to remotely monitor critical aspects of tailings dams, such as their deformation and the leakage of pollutants. This paper describes the development of an EO-based service, being piloted in Peru, which would allow tailings dams to be monitored cost effectively, and also help to forecast any potentially risk inducing behaviour from tailings dams several weeks in advance. Many regulatory bodies in low income countries do not have the resources to adequately monitor mining operations. A low cost EO-based system could improve the transparency and safety of tailings dams, allowing timely preventative interventions to be made where the probability of failure is found to be high.

This paper presents the development and application of a dam breach model, EMBREA-MUD, which is suitable for tailings dams. One of the common failure modes for these structures is breaching due to overtopping, which together with the flow of liquefied tailings, is simulated by the proposed model. The model simultaneously computes the outflow of water and tailings from a tailings storage facility and the corresponding growth of the breach opening. Tailings outflows are represented by a separate non-Newtonian viscous layer, which together with a water layer, represent the two fluid components of the model. The third component represents dam material that can be eroded by the shear forces exerted by either water or mud. The water layer also exerts dynamic and erosional forces and can transport solids eroded from either the mud or dam layer. The model was verified against laboratory cases as well as two field cases reported in the literature, the failures of the Mount Polley tailings dam in Canada in 2015 and the Merriespruit dam in South Africa in 1994. The model results agreed well with the recorded narrative of the events, although in the latter case, careful calibration of one of the model parameters was necessary to obtain a good match.

This paper presents a new framework of critical success factors (CSF) that is being developed to aid approval of ecological enhancements and green engineering options in cities, historic conservation areas, estuaries and at the coast. This is intended to support asset managers, engineers, conservation and biodiversity teams, decision-makers, and other end-users. The CSF framework is outlined and demonstrated by assessing the engineering performance and ecosystem services benefits of ecological enhancements used in specific operational scale case studies. Where data availability permits, the costs and benefits of different greening approaches compared to 'business as usual' are assessed. Three coastal and estuarine case studies are presented to demonstrate how the framework can be applied to compare traditional engineering solutions to green-grey options. Results show that simple, inexpensive ecological enhancement and green engineering solutions can deliver more multifunctional benefits than business as usual solutions for similar or reduced costs. They also demonstrate that the CSF framework will be a powerful tool that can aid practitioners in evaluating green engineering solutions compared with business as usual.

During the past decade, there have been a number of catastrophic tailings dam failures. Affordable monitoring systems, as well as methods to assess the risk posed to communities living downstream of these structures, are needed. In recent years the availability and accuracy of remote sensing information has increased, whilst its cost has decreased.. This paper provides an overview of DAMSAT, a web-based system that brings together Earth Observation and other data to help governments and mining companies monitor tailing dams, and estimate the downstream risks they pose. The methods developed are being piloted in Peru at a number of tailings dams, with the overall goal of improving the decision making process and sharing of information with respect to managing these structures. Engagement with Peruvian stakeholders has shown that DAMSAT provides tools that can help government authorities both reduce the risks and increase the sustainability of mining.

Abstract.Resilience of critical infrastructure (CI) to extreme weather events, such as heavy rainfall, high temperatures and winter storms, is one of the most demanding challenges for governments and society. Recent experiences have highlighted the economic and societal reliance on a dependable and resilient infrastructure, and the far-reaching impacts that outages or malfunctions can have. Growing scientific evidence indicates that more severe and frequent extreme weather events are likely. The EU-funded INTACT project addresses these CI challenges and attempts to bring together cutting-edge knowledge and experience from across Europe to inform the development of best practice approaches in planning, crisis response and recovery capabilities. The project considers the options for mitigating the extreme weather impacts. A key component of the INTACT project is the development of a risk management structure to support decision-making in the case studies. This structure forms part of the overall INTACT Wiki: the main output of the project. It comprises a risk 'framework' that sets out how information and guidance can be accessed by CI owners and operators. Within this there is a step-wise risk assessment process based on best practice from the IEC. The risk framework and process presents: structures for models and data requirements for decision making; identifies tools and methods that support decision making; supports analysis of measures to protect CI through simulation; and indicates gaps in modelling and data availability. This paper outlines the components of the risk framework and process, and illustrates its use in a case study dealing with electricity supply and winter storms.