InSAR, Tailings dam failure, Consolidation settlement separation, Failure risk assessment, Surface displacement monitoring, Physical geography, GB3-5030, Environmental sciences, GE1-350

Ground surface displacements monitored by interferometric synthetic aperture radar (InSAR) techniques are a useful indicator for revealing precursors and assessing risks of tailings dam failures. However, the long-term and large-magnitude consolidation settlements, which impose low risks on dam collapses, usually dominate InSAR displacement observations. The phenomenon would cause misleading in failure precursors and false alarms in dam failure risks. To circumvent this, we proposed a new framework for assessing tailings dam failure risks from InSAR displacements. In which, a novel Weibull-based algorithm was firstly developed to statistically identify and robustly separate long-term consolidation settlement components from InSAR displacements. The dam failure risks were then statistically assessed based on the remaining InSAR observations after consolidation settlement separation using a comprehensive standardized deformation index (CSDI) model. Six tailings storage facilities (TSFs) worldwide were selected to be tested using the proposed model. The results suggest that the new framework can effectively reduce the false alarms of dam failure risks (about 48% in this study) due to consolidation settlements. In addition, the identified regions with high failure risks are more reliable than that by traditional algorithms without consolidation settlement separation. The new framework offers a robust tool to assess dam failure risks of large-scale (e.g., global) TSFs, thus scientifically guiding the control of catastrophic tailings dam failures.