Risk Probability Assessment of Sudden Water Pollution in the Plain River Network Based on Random Discharge from Multiple Risk Sources

Dayong Li (), Zengchuan Dong, Liyao Shi, Jintao Liu, Zhenye Zhu and Wei Xu
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Dayong Li: Hohai University
Zengchuan Dong: Hohai University
Liyao Shi: Hohai University
Jintao Liu: Hohai University
Zhenye Zhu: Hohai University
Wei Xu: Hohai University

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2019, vol. 33, issue 12, No 1, 4065 pages

Abstract: Abstract Starting from the time variance and uncertainty of accidental discharge, this paper describes the probability of the occurrence of the “normal-accident” alternate state for a risk source using the Markov state transfer model, simulates the behaviour of pollutants in rivers using the hydrodynamic and water quality models for non-conservative substances, and tracks the transport path of pollutants in rivers using the water quality model for conservative substances. The above models are coupled with the Sequential Monte Carlo algorithm, and the risk probability analysis model for sudden water pollution in the plain river network is established and applied to the Yixing river network. The results show that (a) the risk probability of exceeding ammonia nitrogen standard (PES of ammonia nitrogen) is lower in the upper reaches and higher in the middle and lower reaches; (b) dynamic changes in pollutant concentration lead to different changes in the PES of ammonia nitrogen in each reach; (c) the differences in the simulated PES values between the sudden scheme and the stable scheme (NPES of ammonia nitrogen) in the upper and middle reaches show a patchy distribution of high and low values, which are related to the risk source location, the water movement direction and the concentration change in the reach after accepting pollutant loads from the risk sources; (d) the NPES of ammonia nitrogen in the lower reaches results from the coupling effect caused by accidental discharges from multiple risk sources; and (e) the different effects of the lower boundary hydrological conditions on the upstream water inflow lead to the different coupling effect on the water quality probability of sections in the downstream area.

Keywords: Plain river network; Sudden water pollution; Sequential Monte Carlo algorithm; Risk probability assessment; Numerical simulation (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s11269-019-02366-w

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