Calculation Method for the Early Warning Index of Sudden Water Pollution Based on the Linear Variation Assumption of the Substance Concentration in the River Network

Dayong Li (), Zengchuan Dong, Chuanhai Wang, Jintao Liu and Hongyi Yao
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Dayong Li: Hohai University
Zengchuan Dong: Hohai University
Chuanhai Wang: Hohai University
Jintao Liu: Hohai University
Hongyi Yao: Hohai University

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2020, vol. 34, issue 9, No 12, 2835 pages

Abstract: Abstract Based on the linear variation assumption of the substance concentration, a water quality model is reconstructed, and an early warning model coupled with the river network hydrodynamics and water quality for conventional pollutants and conservative substances is further developed. This paper proposes a new method for calculating the early warning of conventional sudden water pollution accidents, and numerical tests under accidental scenarios are carried out to verify the feasibility of the method. Finally, the influencing factors of the early warning index calculation are analysed, the diffusion errors under two assumptions are compared, and the following conclusions are obtained: (a) the spatial differences in the calculation results of the early warning indexes are mainly caused by the transport path and speed of the accidental pollutants in the river network and the background concentration of the accidental pollutants at sensitive receptors; (b) The numerical diffusion error and the attenuation effect during the transport process of the substance brought by the linear variation assumption is smaller than those of the sufficient mixing assumption; and (c) the linear variation assumption is favourable for prolonging the response time to control the impact from the accident, shortening the duration of the accident impact and decreasing the maximum standard-exceeding multiple of the water quality.

Keywords: Conventional sudden water pollution; Early warning index; Water quality concentration; Numerical simulation; Sensitive receptor (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s11269-020-02584-7

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