Source identification of accidental water pollution in a tidal river network based on a water environment model and database

CHEN Zhengxia; DING Yi; MAO Xuhui; WANG Zheng; JIA Haifeng

doi:10.16511/j.cnki.qhdxxb.2017.21.034

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Journal of Tsinghua University(Science and Technology) ›› 2017, Vol. 57 ›› Issue (11) : 1170-1178. DOI: 10.16511/j.cnki.qhdxxb.2017.21.034

ENVIRONMENTAL SCIENCE AND ENGINEERING

Source identification of accidental water pollution in a tidal river network based on a water environment model and database

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Abstract

The source of accidental water pollution can be accurately and quickly identified using a water environment model and database. The Foshan section of the Xijiang and Beijiang Rivers was taken as an example to build a EFDC (environmental fluid dynamics code) hydrodynamic and WASP (water quality analysis simulation program) water quality model. The WASP water quality model included the WASP-EUTRO model for normal pollutants and the WASP-TOXI model for toxic pollutants. The EFDC-WASP model sorts information on the pollutant risk source at each automatic monitoring section to establish a toxic and normal pollutant source identification database. A hypothetical scenario having the Shakou monitoring station in the Chancheng district measuringa high Cr⁶⁺ concentration was taken as an example with 3 possible pollutant emission situations identified through a database query. Initial loads for each situation 1-3 were estimated according to a first-order kinetics equation, with the location and load for each situation then calculated by the model. The pollutant source was quickly and accurately identified.

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tidal river network / environmental fluid dynamics code (EFDC) model / water quality analysis simulation program (WASP) model / database / accidental water pollution / source identification

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CHEN Zhengxia, DING Yi, MAO Xuhui, WANG Zheng, JIA Haifeng. Source identification of accidental water pollution in a tidal river network based on a water environment model and database[J]. Journal of Tsinghua University(Science and Technology). 2017, 57(11): 1170-1178 https://doi.org/10.16511/j.cnki.qhdxxb.2017.21.034

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