刘晓东, 王珏, LIUXiaodong, WANGJue. 地表水污染源识别方法研究进展[J]. 水科学进展, 2020, 31(2): 302-311. DOI: 10.14042/j.cnki.32.1309.2020.02.016
引用本文: 刘晓东, 王珏, LIUXiaodong, WANGJue. 地表水污染源识别方法研究进展[J]. 水科学进展, 2020, 31(2): 302-311. DOI: 10.14042/j.cnki.32.1309.2020.02.016
Advances in methods for identifying surface water pollution sources[J]. Advances in Water Science, 2020, 31(2): 302-311. DOI: 10.14042/j.cnki.32.1309.2020.02.016
Citation: Advances in methods for identifying surface water pollution sources[J]. Advances in Water Science, 2020, 31(2): 302-311. DOI: 10.14042/j.cnki.32.1309.2020.02.016

地表水污染源识别方法研究进展

Advances in methods for identifying surface water pollution sources

  • 摘要: 地表水污染源的准确识别对于突发水污染事件中制定补救策略、确定责任方具有重要的指导意义。从污染源识别的基本问题出发, 综述了地表水污染源识别的两类方法, 一类是数学模拟法, 包括直接求解法和间接求解法, 直接求解法又包括解析法和正则化方法, 间接求解法又包括模拟优化法、概率统计法及耦合算法; 另一类是足迹分析法。在此基础上, 系统地讨论了污染源识别的不确定性, 包括污染源信息、观测数据、地表水模型、水动力条件、污染物性质5个方面。并指出地表水污染源识别的不确定性和时效性是制约其应用价值的关键因素, 需要在方法耦合、识别效率提高、不确定性分析及污染物性质等方面做进一步的研究。

     

    Abstract: The accurate identification of surface water pollution sources is very important for formulating remedial schemes and determining the parties responsible for sudden water pollution incidents. According to the basic principles and theories of pollution source identification, an overview of the existing methods is presented in this study, including mathematical simulation and footprint analysis methods. The mathematical simulation methods comprise direct solution methods (analytical and regularization-based methods) and indirect solution methods (simulation optimization methods, probability-based statistical methods, and coupling algorithms). The uncertainty of pollution source identification is discussed in terms of the pollution source information, observational data, surface water model, hydrodynamic conditions, and pollutant properties. The uncertainty and timeliness of surface water pollution source identification are the key factors that affect the valid application of these methods, and thus further research is needed in areas such as method coupling, improving the identification efficiency, uncertainty analysis, and determining the pollutant properties.

     

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