Research on emergency scheduling for sudden water pollution accident in reservoir based on time-space analysis method

Aiping Huang; Fei Dong; Xiaobo Liu; Zhipeng Zhu; Bing Ma; Xiaochen Yang; Jun Ran; Luwei Zhang

doi:10.1117/12.2667943

10 February 2023 Research on emergency scheduling for sudden water pollution accident in reservoir based on time-space analysis method

Aiping Huang, Fei Dong, Xiaobo Liu, Zhipeng Zhu, Bing Ma, Xiaochen Yang, Jun Ran, Luwei Zhang

Author Affiliations +

Proceedings Volume 12552, International Conference on Geographic Information and Remote Sensing Technology (GIRST 2022); 1255202 (2023) https://doi.org/10.1117/12.2667943
Event: International Conference on Geographic Information and Remote Sensing Technology (GIRST 2022), 2022, Kunming, China

Abstract

A sudden water pollution accident poses a serious threat to the safety of water supply from reservoirs. In this paper, we built a model of sudden water pollution accident in the Songbaishan Reservoir, designed a pollutant leakage scenario and a discharge flow scheduling scenario, simulated the rules of influence from pollutant leakage on the water quality in the reservoir, and analyzed the effects of different regulated discharge flows on the water quality in the reservoir. The research results indicated that: (1) The EFDC-based model of sudden water pollution accident in the Songbaishan Reservoir can accurately simulate the evolution process of hydrodynamics and water quality in the Songbaishan Reservoir; (2) What follows the sudden water pollution accident is the pollutant mass, and as the movement distance of the pollutant mass increases, the maximum concentration of the pollutant mass decreases and the exceeding-standard time of each cross section increases; (3) Regulating the discharge flow can reduce the impact of pollutant leakage on the reservoir water quality, and increasing the discharge flow can reduce the exceeding-standard time of the water quality in the cross section of the drinking water supply intake. The research results may provide technical support for emergency treatment of sudden water pollution accidents in the Songbaishan Reservoir.

Citation Download Citation

Aiping Huang, Fei Dong, Xiaobo Liu, Zhipeng Zhu, Bing Ma, Xiaochen Yang, Jun Ran, and Luwei Zhang "Research on emergency scheduling for sudden water pollution accident in reservoir based on time-space analysis method", Proc. SPIE 12552, International Conference on Geographic Information and Remote Sensing Technology (GIRST 2022), 1255202 (10 February 2023); https://doi.org/10.1117/12.2667943

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KEYWORDS

Water quality

Water contamination

Water

Calibration

Data modeling

Pollution

Analytical research

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