State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Haidian District, Beijing, 100875, China.
Institute of Environmental Risk & Damages Assessment, Guangdong Provincial Academy of Environmental Science, Guangzhou, 510045, China.
J Environ Manage. 2019 Sep 15;246:821-831. doi: 10.1016/j.jenvman.2019.06.060. Epub 2019 Jun 20.
Mine tailings ponds that contain heavy metals are sources of potential risk to human security and ecosystem health. China particularly faces challenge of accidental water pollution risk from more than 8869 mine tailings ponds in serve by 2015, some of which are close to residential areas and other important infrastructures within 1 km downstream. To address watershed-scale risk assessment of accidental water pollution from mine tailings ponds, a Bayesian Network-based Risk Dynamic Simulation (BN-RDS) model was proposed to simulate "sources/stressors-receptors-endpoints" risk routes. An accidental water pollution convection-diffusion simulation was coupled to Bayesian Networks to perform the risk dynamic simulation and risk evolution quantification at watershed-scale. This method was applied to the risk assessment of 23 tailings dams in 12 sub-watersheds covering the Guanting Reservoir basin (the major backup drinking water source for Beijing) in Zhangjiakou City, China. The result indicated that ecosystem health and property security were the endpoints at the highest risk in the overall watershed. Spatially, the combined risk distribution map showed the risk was higher in the downstream of the Guanting Reservoir Watershed and in its two tributary basins (the Qingshui River and the Longyang River). This research highlighted a probabilistic approach to accidental water pollution risk assessment of tailings ponds with verifiable and tangible results for risk managers and stakeholders.
矿山尾矿库含有重金属，是对人类安全和生态系统健康造成潜在风险的源头。中国尤其面临着 2015 年之前遗留的 8869 多座矿山尾矿库的突发水污染风险，其中部分尾矿库距离居民区和下游 1 公里内的其他重要基础设施较近。为了对矿山尾矿库突发水污染进行流域尺度的风险评估，提出了基于贝叶斯网络的风险动态模拟（BN-RDS）模型，以模拟“污染源/胁迫源-受体-终点”风险路径。将突发水污染对流-扩散模拟与贝叶斯网络耦合，以进行流域尺度的风险动态模拟和风险演化量化。该方法应用于对中国张家口市官厅水库流域（北京主要的后备饮用水源）12 个小流域内 23 座尾矿坝的风险评估。结果表明，生态系统健康和财产安全是整个流域中风险最高的终点。从空间上看，综合风险分布图谱表明，官厅水库流域及其两个支流（清水河和洋河）的下游风险较高。本研究强调了一种对尾矿库突发水污染风险进行概率评估的方法，为风险管理者和利益相关者提供了可验证和切实的结果。
