Evaluation of a Remotely Operated Semi-Autonomous Monitoring System for a Tailings Dam at a Mine Site in Central Arizona

On average, 3 out of 3,500 tailings storage facilities (TSF) experience failure per year, which is approximately 10 times higher than regular water retention dams. These failures have led to severe environmental damages, loss of life, and substantial financial loss and motivated the development of the next generation monitoring systems for tailing dams. Such systems provide reliable, real-time monitoring information to operators to allow for early detection of potentially hazardous conditions and enable accurate failure predictions. The purpose of this work is to evaluate a remotely operable, semi-autonomous tailings dam monitoring system, which was developed by the University of Arizona in 2016 and deployed at a mining facility in central Arizona. This system uses conventional monitoring methods in unique ways that provide the capability to retrieve historical data and real-time configuration to assess the dam's intrinsic conditions. Our study was aimed to determine if this system can provide an advantage in TSF dam monitoring over conventional approaches and provide a new tool to improve the assessment of dam condition. We evaluated the monitoring system based on its effectiveness in detecting intrinsic changes in the dam structure, its reliability of operation, and its efficiency in collecting data. For this study, we evaluated four years of data from October 2016 to September 2020. The data consisted of a combination of intrinsic and extrinsic sensors installed for evaluating the tailings dam stability by measuring phreatic surface levels, soil temperature, toe drain discharge, and changes in electric resistivity. Our evaluation shows that the system effectively detected changes in the intrinsic dam conditions and functioned reliably for most of the evaluation period. As part of our evaluation, we also present lessons learned from the current operation and provide recommendations for future deployments