Fast and optimal decision for emergency control of sudden water pollution accidents in long distance water diversion projects

Author:

Qiao Yu12,Lei Xiaohui1,Long Yan3,Li Jiahong14,Yang Yilin4,Tian Yu1,Li Youming5,Yao Ye4,Chang Wenjuan6

Affiliation:

1. State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing, 100038, China

2. Construction and Administration Bureau of South-to-North Water Division Middle Route Project, Beijing 100038, China

3. School of Water Conservancy and Hydroelectric Power, Hebei University of Engineering, Handan, Hebei Province 056002, China

4. State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300072, China

5. Bgi Engineering Consultants Ltd, Beijing, 100038, China

6. China Three Gorges University, Yichang, Hubei, 443002, China

Abstract

Abstract Long distance water diversion projects transfer clean water to cities for industrial, agricultural and domestic use; there is a great risk of sudden water pollution accidents. Without a fast and optimal decision for emergency control in response to sudden water pollution accidents, dispatchers or decision-makers will not be prepared to respond to the accidents during the process of an emergency spill. To address this gap, a framework for fast and optimal decision support in emergency control is reported in this paper. The proposed fast and optimal decision system covers four stages. In this study, the analytical hierarchy process integrated with grey fixed weight clustering was used to determine the gate closing mode. The emergency control strategy in ice cover formation period is presented. A case study was examined in the demonstrative project conducted in the Middle Route of the South-to-North Water Diversion Project in China. The relative errors of the arrival time of the peak concentration and the peak concentration in monitoring points between the actual monitoring values and the formula calculation values are less than 18%.

Funder

National Natural Science Foundation of China

Publisher

IWA Publishing

Subject

Water Science and Technology

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