A Comprehensive Global Database of Tailings Flows

Tailings are finely ground waste rock produced as a by-product of standard mining projects as well as some industrial and power plant operations. Tailings are conventionally impounded behind a dam that is raised perpetually insofar as operations continue, thus amassing large volumes of materials (sometimes including supernatant pond water) in the process. The failures of some tailings impoundments have triggered downstream mass movements that have caused human, economic and environmental impacts, thus inviting considerable public attention and scrutiny. Developing a detailed inventory of these “tailings flows” facilitates a better understanding of the magnitude-frequency statistics, preconditioning and trigger variables, breach-outflow processes and downstream runout behaviour. Upon screening over 350 historical waste impoundment failure incidents in pre-existing secondary datasets, we have developed a comprehensive global database of 63 tailings flows from 1928-2020 while following strict case selection criteria with the support of satellite imagery, digital elevation models (DEMs) and source literature. Using a novel runout zonation method, the satellite images and DEMs were analyzed on geographic information systems (GIS) platforms to independently estimate runout distances, inundation areas and travel path angles of tailings flows. Depending on data availability or quality, we also summarized the background information, impoundment conditions and geotechnical indices to provide site-specific context to case histories. The collated data is aimed to (i) broaden the scholarly understanding of tailings breach-runout behaviour, (ii) provide comprehensive documentation while assessing the limitations of data availability and/or quality in the public domain and (iii) establish a consistent framework for reporting various properties of tailings dam failures and tailings flows. Lastly, we note that the data should be treated with prudence. Tailings impoundments are highly variable depending on the locality, and site-specific conditions exert strong controls on post-breach behaviour. As such, it is recommended that our database be used purely as a basis for screening-level assessments, case analog comparisons and academic research. For site-specific prediction studies undertaken by practitioners, targeted field observations, laboratory investigations and numerical models are essential.

尾矿（tailings）指常规采矿项目及部分工业、电厂运营过程中产生的细磨废石类副产物。传统尾矿堆存多依托尾矿坝（tailings dam），且随运营推进持续加高坝体，在此过程中会堆积大量物料（有时还包含尾矿库上清池水）。部分尾矿库（tailings impoundment）溃坝引发的下游大规模岩土运动，已造成人员伤亡、经济损失与环境破坏，因此受到公众的广泛关注与审视。
对这类“尾矿流（tailings flow）”开展详细编目，有助于更好地理解其规模-频率统计特征、前置诱发条件与触发变量、溃决溢流过程以及下游运动运移行为。研究团队在现有二次数据集中共筛选出350余起历史废堆场溃坝事故，随后依托卫星影像、数字高程模型（DEMs）与原始文献，遵循严格的案例遴选标准，构建了1928年至2020年间共计63起尾矿流事件的全球综合数据库。
研究团队采用新型运移分区方法，在地理信息系统（GIS）平台上对卫星影像与DEM数据进行分析，以此独立估算尾矿流的运动距离、淹没范围与运动路径角度。根据数据可得性与质量情况，团队同时汇总了各案例的背景信息、堆存库体条件与岩土力学指标，为案例研究提供场地专属的背景信息。
本汇编数据集的目标在于：（1）深化学界对尾矿坝溃决-运移行为的认知；（2）在评估公开领域数据可得性与质量局限性的同时，提供全面的案例记录；（3）构建一套统一的报告框架，用于规范描述尾矿坝溃坝与尾矿流的各类特征参数。
最后需要说明的是，使用本数据集时应保持审慎。尾矿库的特性因地域差异显著，场地专属条件对溃后运动行为具有极强的控制作用。因此，本数据库仅可作为初筛级评估、案例类比对比与学术研究的基础。对于工程人员开展的场地专属预测研究，针对性的现场观测、实验室试验与数值模拟模型是必不可少的。