Identification and Assessment of Critical Waterways in Water Network Areas from a Community Detection Perspective

Inland water transport, a critical component of integrated transportation systems, relies on the unobstructed status of critical waterways to ensure network efficiency. Firstly, a weighted topological network was constructed based on waterway class and length. The Leiden algorithm was then employed to divide the inland waterway network into communities, with community bridges identified as critical waterways. Finally, attack simulation experiments were conducted to verify the methodology. Results revealed that the Jiangsu inland waterway network exhibits a distinct community structure, and the regional division is closely aligned with the actual river system. The rapid performance degradation under community bridge attacks confirmed the validity of the critical waterway identification method. Furthermore, a recommended method for waterway class assignment was explored in the inland waterway weighting network. The innovative identification and assessment of critical waterways from the perspective of community detection breaks through the limitations of traditional methods that rely on betweenness centrality and waterway class. Vessel traffic flow across different waterway classes was analyzed using the Automatic Identification System (AIS) data, enabling tailored management strategies for critical waterways. This research provides theoretical support for an in-depth understanding of the structure and function of the inland waterway network, guiding policymaking and promoting the efficiency and security of inland water transport.