School of Resource and Environmental Sciences, Wuhan University, Wuhan, 430079, PR China.
Agricultural and Biological Engineering, Purdue University, West Lafayette, IN, 47907-2093, USA.
J Environ Manage. 2018 Feb 15;208:122-133. doi: 10.1016/j.jenvman.2017.12.006. Epub 2017 Dec 16.
A fast and accurate water quality pollutant risk assessment and early warning system, which has great practical significance for decision making in accident management, is urgently needed for water protection and management. Based on a fast mobile early warning system named MEWSUB, this paper modified its framework to make it generate data more automatically and accurately. By adapting manning formula and particle swarm optimization (PSO) for parameters optimization, the accuracy of water quantity and water quality simulation results has been improved. The modified system was successfully applied in an antimony tailings dam leakage accident that happened in China. The coefficient of determination (R) of the prediction result was higher than 0.9 and relative error (ree) was less than 0.1, which indicated that the accuracy of MEWSUB was high enough for realistic water quality pollutant risk early warning.
快速、准确的水质污染物风险评估和预警系统，对于事故管理中的决策制定具有重要的实际意义，这是水环境保护和管理所急需的。基于一个名为 MEWSUB 的快速移动预警系统，本文对其框架进行了修改，使其能够更自动、更准确地生成数据。通过采用曼宁公式和粒子群优化（PSO）进行参数优化，提高了水量和水质模拟结果的准确性。该改进系统成功应用于中国发生的一次锑尾矿库泄漏事故。预测结果的决定系数（R）高于 0.9，相对误差（ree）小于 0.1，表明 MEWSUB 的准确性足以进行现实水质污染物风险预警。
