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.
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.
The use of datasets from satellites to aid the monitoring of dams has been possible for many years. Within the last five years there has been a rapid development in the type and accuracy of the data available, led by an influx of new satellites and improved access to these datasets. This paper gives an overview of the different types of satellite datasets and satellite infrastructure relevant to dam safety that are currently available, explains the complex processes of converting raw satellite data into useable information and summarises the advantages and disadvantages of each data type along with indications of the level of accuracy and cost. The information presented by the authors is based on experience gained undertaking a 3 year, £4 m, UK-government-funded research project to investigate and combine many types of space data to improve the monitoring of dams.
The study reported here evaluated the outcomes of the New York Master Forest Owner Program by measuring both internal volunteer impacts as well as volunteer impacts on woodland owners visited through the program. Internal impacts allowed volunteers to manage their own properties better, promote forest stewardship in their community, and take on increased leadership roles. External impacts resulted in increased information-seeking and goal-setting behaviors as well as on the ground management activities. The results from the surveys demonstrate that local peer-to-peer programs can positively influence woodland owners in their communities as well empower the volunteers themselves.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.