Volume 44 Issue 1
Feb.  2026
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ZHAO Zunrong, HAN Ya, WU Bing, XU Xueqian. Navigation Status Control of Cargo Ships in the Three Gorges Dam-Gezhouba Dam Cascade Navigation Hubs[J]. Journal of Transport Information and Safety, 2026, 44(1): 113-126. doi: 10.3963/j.jssn.1674-4861.2026.01.010
Citation: ZHAO Zunrong, HAN Ya, WU Bing, XU Xueqian. Navigation Status Control of Cargo Ships in the Three Gorges Dam-Gezhouba Dam Cascade Navigation Hubs[J]. Journal of Transport Information and Safety, 2026, 44(1): 113-126. doi: 10.3963/j.jssn.1674-4861.2026.01.010

Navigation Status Control of Cargo Ships in the Three Gorges Dam-Gezhouba Dam Cascade Navigation Hubs

doi: 10.3963/j.jssn.1674-4861.2026.01.010
  • Received Date: 2025-09-07
    Available Online: 2026-08-28
  • This study addresses the high navigation risk of cargo ships caused by the drastic flood-season flow changes between the Three Gorges and Gezhouba navigation hubs. A navigation state control model for cargo ships based on a Bayesian network is developed to identify ships that fail to meet navigation conditions and to evaluate their permissible navigation probability. The model structure is designed according to the waterway's navigation characteristics and includes three modules: environmental conditions, flow mutation, and traffic complexity. An influencing factor system couples ship attributes with channel flow variations. The flow mutation module evaluates mutation grades using flow peak, variation amplitude, and transition grade to represent flood-season flow changes.The traffic complexity module considers separate upstream and downstream navigation, using a five-hour analysis window, and graded indexes of ship quantity and spacing to characterize channel traffic state. Node conditional probability tables are determined using the Flood Season Navigation Flow Standard, survey results, and IF-THEN rules to address difficulty in directly obtaining model parameters. The Bayesian network calculates permissible navigation probabilities, forming a navigation state control framework for navigation access. Verification with five actual ship samples, multiple noncompliant samples, and sixty dam-passing records shows that all five actual ship samples have permissible navigation probabilities above 80%, consistent with observed operations. Noncompliant samples have non-navigation probabilities of 88%~95%, identifying high-risk conditions. Sixty dam-passing records show permissible navigation probabilities of 82%~88%, averaging 85%, consistent with operational records. Sensitivity analysis identifies flow conditions and ship power as the main factors influencing cargo ship navigation state control.

     

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