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Towards a probabilistic model for estimation of grounding accidents in fluctuating backwater zone of the Three Gorges Reservoir

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  • Jiang, Dan
  • Wu, Bing
  • Cheng, Zhiyou
  • Xue, Jie
  • van Gelder, P.H.A.J.M.

Abstract

The water level fluctuations in the upper reach of dam reservoirs may result in increasing occurrence probabilities of ship grounding accidents, which is especially prominent in the Three Gorges Reservoir. Grounding accidents may not only cause congestion of the traffic but also lead to loss of properties and pollution to the maritime environment. An analytical model incorporating Bayesian Network is proposed to estimate the occurrence likelihood of a ship being grounded in the fluctuating backwater zone. The proposed model comprehensively considers the characteristics of the ship's properties, organizational factors, hydrological conditions and human factors from a systematic perspective. Historical data collected from the Chongqing Maritime Safety Administration, together with incident reports, are used to develop a quantitative model. The developed model in this paper concludes that out of twenty-six factors, the area of the fluctuating backwater zone, the month, and water level are the predominant factors for the occurrence of grounding accidents in the Three Gorges Reservoir. The results can be used by maritime stakeholders to take mitigation measures for grounding accident reduction.

Suggested Citation

  • Jiang, Dan & Wu, Bing & Cheng, Zhiyou & Xue, Jie & van Gelder, P.H.A.J.M., 2021. "Towards a probabilistic model for estimation of grounding accidents in fluctuating backwater zone of the Three Gorges Reservoir," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    • Handle: RePEc:eee:reensy:v:205:y:2021:i:c:s0951832020307390
    DOI: 10.1016/j.ress.2020.107239
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    as
    1. Wang, Likun & Yang, Zaili, 2018. "Bayesian network modelling and analysis of accident severity in waterborne transportation: A case study in China," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 277-289.
    2. Fu, Shanshan & Zhang, Di & Montewka, Jakub & Yan, Xinping & Zio, Enrico, 2016. "Towards a probabilistic model for predicting ship besetting in ice in Arctic waters," Reliability Engineering and System Safety, Elsevier, vol. 155(C), pages 124-136.
    3. Pristrom, Sascha & Yang, Zaili & Wang, Jin & Yan, Xinping, 2016. "A novel flexible model for piracy and robbery assessment of merchant ship operations," Reliability Engineering and System Safety, Elsevier, vol. 155(C), pages 196-211.
    4. Montewka, Jakub & Ehlers, Sören & Goerlandt, Floris & Hinz, Tomasz & Tabri, Kristjan & Kujala, Pentti, 2014. "A framework for risk assessment for maritime transportation systems—A case study for open sea collisions involving RoPax vessels," Reliability Engineering and System Safety, Elsevier, vol. 124(C), pages 142-157.
    5. Chen, Chao & Reniers, Genserik & Khakzad, Nima, 2019. "Integrating safety and security resources to protect chemical industrial parks from man-made domino effects: A dynamic graph approach," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    6. Yang, Yunfeng & Chen, Guohua & Reniers, Genserik, 2020. "Vulnerability assessment of atmospheric storage tanks to floods based on logistic regression," Reliability Engineering and System Safety, Elsevier, vol. 196(C).
    7. Goerlandt, Floris & Montewka, Jakub, 2015. "Maritime transportation risk analysis: Review and analysis in light of some foundational issues," Reliability Engineering and System Safety, Elsevier, vol. 138(C), pages 115-134.
    8. Bye, Rolf J. & Aalberg, Asbjørn L., 2018. "Maritime navigation accidents and risk indicators: An exploratory statistical analysis using AIS data and accident reports," Reliability Engineering and System Safety, Elsevier, vol. 176(C), pages 174-186.
    9. Kujala, P. & Hänninen, M. & Arola, T. & Ylitalo, J., 2009. "Analysis of the marine traffic safety in the Gulf of Finland," Reliability Engineering and System Safety, Elsevier, vol. 94(8), pages 1349-1357.
    10. Yang, Zhisen & Yang, Zaili & Yin, Jingbo, 2018. "Realising advanced risk-based port state control inspection using data-driven Bayesian networks," Transportation Research Part A: Policy and Practice, Elsevier, vol. 110(C), pages 38-56.
    11. Zhang, D. & Yan, X.P. & Yang, Z.L. & Wall, A. & Wang, J., 2013. "Incorporation of formal safety assessment and Bayesian network in navigational risk estimation of the Yangtze River," Reliability Engineering and System Safety, Elsevier, vol. 118(C), pages 93-105.
    12. Marcelo Ramos Martins & Marcos Coelho Maturana, 2010. "Human Error Contribution in Collision and Grounding of Oil Tankers," Risk Analysis, John Wiley & Sons, vol. 30(4), pages 674-698, April.
    13. Yip, Tsz Leung, 2008. "Port traffic risks - A study of accidents in Hong Kong waters," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 44(5), pages 921-931, September.
    Full references (including those not matched with items on IDEAS)

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    6. Ma, Xiaoxue & Deng, Wanyi & Qiao, Weiliang & Lan, He, 2022. "A methodology to quantify the risk propagation of hazardous events for ship grounding accidents based on directed CN," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    7. Liu, Kezhong & Yu, Qing & Yang, Zhisen & Wan, Chengpeng & Yang, Zaili, 2022. "BN-based port state control inspection for Paris MoU: New risk factors and probability training using big data," Reliability Engineering and System Safety, Elsevier, vol. 224(C).
    8. Fan, Cunlong & Montewka, Jakub & Zhang, Di, 2022. "A risk comparison framework for autonomous ships navigation," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    9. Ung, S.T., 2021. "Navigation Risk estimation using a modified Bayesian Network modeling-a case study in Taiwan," Reliability Engineering and System Safety, Elsevier, vol. 213(C).

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