Skip to main content

Advertisement

SpringerLink
Log in

Risk scenario prediction for sudden water pollution accidents based on Bayesian networks

  • Original Article
  • Published:
International Journal of System Assurance Engineering and Management Aims and scope Submit manuscript

Abstract

Predicting and analyzing the future possible scenario of the sudden water pollution accident can help emergency managers to get know the possible future of the accident and make response. In this paper, the Bayesian Network (BN) is extended to support emergency decision for sudden water pollution accidents. Three types of node variables for BN are built according to the characteristics of sudden water pollution accident. Then, the directed acyclic graph (DAG) is constructed to connect the variables. Through Estimating of the conditional probability of BN, the possible scenario of sudden water pollution accident can be formed based DAG and BN. Finally, the Longjiang River cadmium pollution in Guangxi Province is given to illustrate the feasibility and validity of the proposed method. The results show that the BN can give the possible scenario of the sudden pollution accident and can help emergency managers to make detailed alternatives further to minimize the losses.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  • Domingos BP, Pazzani M (2012) On the optimality of the simple baysian classi under zero-one loss. Mach Learn 29:103–130

    Article  MATH  Google Scholar 

  • Duan WL, Chen GH, Qing Y, Chen QG (2011) The situation of hazardous chemical accidents in China between 2000 and 2006. J Hazard Mater 86:1489–1494

    Article  Google Scholar 

  • Farmani R, Henriksen HJ, Savic D (2009) An evolutionary Bayesian belief network methodology for optimum management of groundwater contamination. Environ Model Softw 24:303–310

    Article  Google Scholar 

  • He Q, Peng S, Zhai JJ, Xiao HW (2011) Development and application of a water pollution emergency response system for the Three Gorges Reservoir in the Yangtze River, China. J Environ Sci 23:595–600

    Article  Google Scholar 

  • Li Chunhui, Sun Lian, Jia Junxiang, Cai Yanpeng, Wang Xuan (2016) Risk assessment of water pollution sources based on an integrated k-means clustering and set pair analysis method in the region of Shiyan, China. Sci Tot Environ 557–558:307–316

    Article  Google Scholar 

  • Liu J, Guo L, Jiang JP, Hao LL, Liu RT, Wang P (2015) Evaluation and selection of emergency treatment technology based on dynamic fuzzy GRA method for chemicalcontingency spills. J Hazard Mater 299:306–315

    Article  Google Scholar 

  • Loo SL, Fane AG, Krantz WB, Lim TT (2012) Emergency water supply: a review of potential technologies and selection criteria. Water Res 46:3125–3151

    Article  Google Scholar 

  • Managi S, Kaneko S (2009) Environmental performance and returns to pollution abatement in China. Ecol Econ 68:1643–1651

    Article  Google Scholar 

  • Pendock NE, Sears M (2002) Choosing geological models with Baysian belief networks. S Afr J Sci 98:500–502

    Google Scholar 

  • Peng JF, Song YH, Yuan PS, Xiao H, Han L (2013) An novel identification method of the environmental risk sources for surface water pollution accidents in chemical industrial parks. J Environ Sci 25:1441–1449

    Article  Google Scholar 

  • Pollino CA, Woodberry O, Nicholson A, Korb K, Hart BT (2007) Parameterisation and evaluation of a Bayesian network for use in an ecological risk assessment. Environ Model Softw 22:1140–1152

    Article  Google Scholar 

  • Ratna V, Reddy BB (2006) Impact of water pollution on rural communities: an economic analysis. Ecol Econ 58:520–537

    Article  Google Scholar 

  • Rebelo A, Ferra I, Goncalves I, Marques AM (2014) A risk assessment model for water resources: releases of dangerous and hazardous substances. J Environ Manage 140:51–59

    Article  Google Scholar 

  • Rui YK, Shen DT, Khalid S, Yang ZG, Wang JC (2015) GIS-based emergency response system for sudden water pollution accidents. Phys Chem Earth Parts A/B/C 79–82:115–121

    Article  Google Scholar 

  • Samuels WB, Bahadur R, Ziemniak C (2015) Development and application of the incident command tool for drinking water protection. Water Environ J 29:1–15

    Article  Google Scholar 

  • Shang ZT, Ren J, Qin MR, Xia Y, He L, Chen YW (2010) The relationship between temperature changing and Taihu blue-green algae. Econ J 29(1):55–61 (In Chinese)

    Google Scholar 

  • She L, Liu YS, Wu GB (2011) Water pollution emergency incidents: evolutionary model and emergency management. Resour Environ Yangtze Basin 20:1004–1010 (In Chinese)

    Google Scholar 

  • Shi SG, Cao JC, Feng L, Liang WY, Zhang LQ (2014) Construction of a technique plan repository and evaluation system based on AHP group decision-making foremergency treatment and disposal in chemical pollution accidents. J Hazard Mater 276:200–206

    Article  Google Scholar 

  • Stergios A, Anastasios X (2012) Pollution control with uncertain stock dynamics: when, and how, to be precautious. J Environ Econ Manage 63:304–320

    Article  Google Scholar 

  • Tang CH, Yi YJ, Yang ZF, Cheng X (2014) Water pollution risk simulation andprediction in the main canal of the South-to-North Water Transfer Project. J Hydrol 519:2111–2120

    Article  Google Scholar 

  • The Longjiang River cadmium pollution accident in China (2012) http://news.sina.com.cn/z/longjianghewuran/ (In Chinese)

  • The Longjiang River cadmium pollution accident in China (2012) http://news.sohu.com/s2012/cdpollution/ (In Chinese)

  • Xie JL, Li JX, Wang N, Jiang RG (2013) The sudden water pollution diffusion simulation of the river basin based on multi-agent. J Xi’an Univer Technol 29:13–20

    Google Scholar 

  • Xin K, Yin W, Wang M (2012) Reservoir operation schemes for water pollution accidents in Yangtze River. Water Sci Eng 5:59–66

    Article  Google Scholar 

  • Zhang B, Wang Q, Sun Q, Li S (2009) Spatio-temporal simulation of water quality based on SD-GIS accidential water pollution. Geomatics Inform Sci Wuhan Univer 34:341–348 (In Chinese)

    Google Scholar 

Download references

Acknowledgements

Authors would like to thank the editors and anonymous referees for their valuable comments and suggestions. Their comments helped improve the quality of the paper immensely. The work is supported by the National Social Science Foundation of China (17CXW012).

Author information

Authors and Affiliations

  1. School of Economics, Nanjing University of Posts and Telecommunications, Nanjing, 210023, China

    Tiejun Cheng

  2. Bell Honors School, Nanjing University of Posts and Telecommunications, Nanjing, 210023, China

    Panpan Wang & Qianyi Lu

Authors
  1. Tiejun Cheng
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Panpan Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Qianyi Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Tiejun Cheng.

Appendix

Appendix

See Figs. 8, 9, 10, 11, 12, 13, 14 and 15.

Fig. 8
figure 8

Possible scenario for Longjiang River cadmium pollution accident: Scenario 5

Full size image
Fig. 9
figure 9

Possible scenario for Longjiang River cadmium pollution accident: Scenario 6

Full size image
Fig. 10
figure 10

Possible scenario for Longjiang River cadmium pollution accident: Scenario 7

Full size image
Fig. 11
figure 11

Possible scenario for Longjiang River cadmium pollution accident: Scenario 8

Full size image
Fig. 12
figure 12

Possible scenario for Longjiang River cadmium pollution accident: Scenario 9

Full size image
Fig. 13
figure 13

Possible scenario for Longjiang River cadmium pollution accident: Scenario 10

Full size image
Fig. 14
figure 14

Possible scenario for Longjiang River cadmium pollution accident: Scenario 11

Full size image
Fig. 15
figure 15

Possible scenario for Longjiang River cadmium pollution accident: Scenario 12

Full size image

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cheng, T., Wang, P. & Lu, Q. Risk scenario prediction for sudden water pollution accidents based on Bayesian networks. Int J Syst Assur Eng Manag 9, 1165–1177 (2018). https://doi.org/10.1007/s13198-018-0724-y

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13198-018-0724-y

Keywords

Search

Navigation