摘要
针对传统污染溯源难以做到实时性的问题,建立了基于HEC-RAS水动力模块和多链贝叶斯-蒙特卡洛算法的水污染溯源数学模型系统。依据单点非固定源和多点固定源两类突发排放设计案例,对溯源模型的反演精度进行了测试,结果表明,溯源模型能高效反演河道中潜在的单个突发性污染排放,包括排放的位置、水量、起始和终止时刻;溯源模型能够同时识别多个固定点源对应的排放水量及排放起始、结束时刻。该溯源模型可为未来基于在线数据的突发污染溯源提供技术支撑。
A methodological frameworkwas established to realize the all-weather and dynamic supervision of sudden water pollution sources.The proposed model integrates the concepts of a Bayesian-multi Markov chain Monte Carlo method and HEC-RAS hydrodynamic model.The methodological framework was tested using two hypothetical cases of a potential sudden wastewater spill incident and multi-point sources which the location information is known.The study results show that:For the tracking of sudden wastewater discharge,the inverse problem model can effectively estimate source parameters including source location,source flow rate,starting and ending time of discharge.For the dynamic supervision of multiple pollution sources,the inverse problem model can effectively identify the discharge amounts and starting/ending time of multiple pollution sources.The developed inverse model could provide technical solution for dynamic monitoring of sudden water pollution with the support of on-line data in the future.
作者
林夷媛
Lin Yiyuan(Fujian Provincial Key Laboratory of Green Building Technology,Fujian Academy of Building Research Co.Ltd.,Fuzhou 350000,China)
出处
《环境科学与管理》
2025年第7期15-20,共6页
Environmental Science and Management
基金
福建省环保科技计划项目(No.2023R019)
福建省科技厅区域发展项目(No.2021Y3002)。
关键词
污染溯源
反问题
水动力模型
HEC-RAS
贝叶斯算法
pollution source tracking
inverse problem
hydrodynamic model
HEC-RAS
Bayesian algorithm
作者简介
林夷媛(1997-),女,硕士研究生,工程师,主要从事城市水环境综合治理研究工作。
